diff --git a/CHANGELOG.md b/CHANGELOG.md index 08523a0..e3b3db4 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,16 @@ ## Changelog +### v1.4.7 (October 1, 2025) +- add custom LLM based learner +- add Falcon-H and Mistral-Small custom AutoLLMs. +- Add custom LLm documentations. +- Minor bug fix and improvements in documentation and code. + +### v1.4.6 (September 22, 2025) +- add type annotation to metrics +- add minor fix to retriever taxonomy discovery +- add count metrics in evaluation. + ### v1.4.5 (September 16, 2025) - add batch retriever feature to `AutoRetrieverLearner` diff --git a/CITATION.cff b/CITATION.cff index 46cf53c..1a7bbe0 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -31,5 +31,5 @@ keywords: - Large Language Models - Text-to-ontology license: MIT -version: 1.4.5 +version: 1.4.7 date-released: '2025' diff --git a/docs/source/learners/llm.rst b/docs/source/learners/llm.rst index 46edb59..6128ce6 100644 --- a/docs/source/learners/llm.rst +++ b/docs/source/learners/llm.rst @@ -135,5 +135,155 @@ The OntoLearner package also offers a streamlined ``LearnerPipeline`` class that # Print all returned outputs (include predictions) print(outputs) + +Custom AutoLLM +----------------- + +OntoLearner provides a default ``AutoLLM`` wrapper for handling popular model families (Mistral, Llama, Qwen, etc.) through HuggingFace or external providers. However, in some cases you may want to integrate a model family that is not natively supported (e.g., Falcon, DeepSeek, or a proprietary LLM). + +For this, you can extend the ``AutoLLM`` class and implement the required +``load`` and ``generate`` methods. Basic requirements are: + +1. Inherit from ``AutoLLM`` +2. Implement ``load(model_id)``, if your loging model is different (as an example `mistralai/Mistral-Small-3.2-24B-Instruct-2506 `_ uses different type of loading) +3. Implement ``generate(inputs, max_new_tokens)`` to encodes prompts, performs generation, decodes outputs, and maps them to labels. + + +.. tab:: Falcon-H + + The following example shows how to build a Falcon integration: + + :: + + from ontolearner import AutoLLM + from typing import List + import torch + + class FalconLLM(AutoLLM): + + def generate(self, inputs: List[str], max_new_tokens: int = 50) -> List[str]: + encoded_inputs = self.tokenizer( + inputs, + return_tensors="pt", + padding=True, + truncation=True + ).to(self.model.device) + + input_ids = encoded_inputs["input_ids"] + input_length = input_ids.shape[1] + + outputs = self.model.generate( + input_ids, + max_new_tokens=max_new_tokens, + pad_token_id=self.tokenizer.eos_token_id + ) + + generated_tokens = outputs[:, input_length:] + decoded_outputs = [ + self.tokenizer.decode(g, skip_special_tokens=True).strip() + for g in generated_tokens + ] + + return self.label_mapper.predict(decoded_outputs) + +.. tab:: Mistral-Small + + For Mistral, you can integrate the official ``mistral-common`` tokenizer and chat completion interface: + + :: + + from ontolearner import AutoLLM + from typing import List + import torch + + class MistralLLM(AutoLLM): + + def load(self, model_id: str) -> None: + from mistral_common.tokens.tokenizers.mistral import MistralTokenizer + from mistral_common.models.modeling_mistral import Mistral3ForConditionalGeneration + + self.tokenizer = MistralTokenizer.from_hf_hub(model_id) + + device_map = "cpu" if self.device == "cpu" else "balanced" + self.model = Mistral3ForConditionalGeneration.from_pretrained( + model_id, + device_map=device_map, + torch_dtype=torch.bfloat16, + token=self.token + ) + + if not hasattr(self.tokenizer, "pad_token_id") or self.tokenizer.pad_token_id is None: + self.tokenizer.pad_token_id = self.model.generation_config.eos_token_id + + self.label_mapper.fit() + + def generate(self, inputs: List[str], max_new_tokens: int = 50) -> List[str]: + from mistral_common.protocol.instruct.messages import ChatCompletionRequest + + tokenized_list = [] + for prompt in inputs: + messages = [{"role": "user", "content": [{"type": "text", "text": prompt}]}] + tokenized = self.tokenizer.encode_chat_completion(ChatCompletionRequest(messages=messages)) + tokenized_list.append(tokenized.tokens) + + # Pad inputs and create attention masks + max_len = max(len(tokens) for tokens in tokenized_list) + input_ids, attention_masks = [], [] + for tokens in tokenized_list: + pad_length = max_len - len(tokens) + input_ids.append(tokens + [self.tokenizer.pad_token_id] * pad_length) + attention_masks.append([1] * len(tokens) + [0] * pad_length) + + input_ids = torch.tensor(input_ids).to(self.model.device) + attention_masks = torch.tensor(attention_masks).to(self.model.device) + + outputs = self.model.generate( + input_ids=input_ids, + attention_mask=attention_masks, + eos_token_id=self.model.generation_config.eos_token_id, + pad_token_id=self.tokenizer.pad_token_id, + max_new_tokens=max_new_tokens, + ) + + decoded_outputs = [] + for i, tokens in enumerate(outputs): + output_text = self.tokenizer.decode(tokens[len(tokenized_list[i]):]) + decoded_outputs.append(output_text) + + return self.label_mapper.predict(decoded_outputs) + + +Once your custom class is defined, you can pass it into ``AutoLLMLearner``: + +.. code-block:: python + + from ontolearner import AutoLLMLearner, LabelMapper, StandardizedPrompting + + falcon_learner = AutoLLMLearner( + prompting=StandardizedPrompting, + label_mapper=LabelMapper(), + llm=FalconLLM, # 👈 plug in custom Falcon + token="...", + device="cuda" + ) + + falcon_learner.llm.load(model_id="tiiuae/Falcon-H1-1.5B-Deep-Instruct") + + # Train and evaluate + falcon_learner.fit(train_data, task="term-typing") + predictions = falcon_learner.predict(test_data, task="term-typing") + + print(predictions) + +The following models are specialized within the OntoLearner: + +- To use `mistralai/Mistral-Small-3.2-24B-Instruct-2506 `_ you can use ``MistralLLM`` instead of ``AutoLLM``. +- To use `Falcon-H` series of LLMs (e.g. `tiiuae/Falcon-H1-1.5B-Deep-Instruct `_ you can ``FalconLLM`` instead of ``AutoLLM``. + +.. note:: + + You can implement as many custom AutoLLM classes as needed (e.g., for proprietary APIs, local models, or new HF releases). As long as they subclass ``AutoLLM`` and implement ``load`` + ``generate``, they will work seamlessly with ``AutoLLMLearner``. + + .. hint:: See `Learning Tasks `_ for possible tasks within Learners. diff --git a/metadata/ontolearner-metadata.rdf b/metadata/ontolearner-metadata.rdf index 6642d7e..6fde85d 100644 --- a/metadata/ontolearner-metadata.rdf +++ b/metadata/ontolearner-metadata.rdf @@ -5,526 +5,119 @@ This Dublin Core metadata collection describes ontologies benchmarked in OntoLearner. It includes information such as title, creator, format, license, and version. OntoLearner Team MIT License - 1.4.5 + 1.4.7 - - AIISO - Academic Institution Internal Structure Ontology (AIISO) - The Academic Institution Internal Structure Ontology (AIISO) provides classes and properties to describe the internal organizational structure of an academic institution. AIISO is designed to work in partnership with Participation (http://purl.org/vocab/participation/schema), FOAF (http://xmlns.com/foaf/0.1/) and aiiso-roles (http://purl.org/vocab/aiiso-roles/schema) to describe the roles that people play within an institution. - Open University - RDF - 2008-05-14 - Creative Commons 4.0 - https://vocab.org/aiiso/ - Scholarly Knowledge - Academic Institution - 1.0 - - - OntoCAPE - Ontology of Computer-Aided Process Engineering (OntoCAPE) - OntoCAPE is a large-scale ontology for the domain of Computer Aided Process Engineering (CAPE). Represented in a formal, machine-interpretable ontology language, OntoCAPE captures consensual knowledge of the process engineering domain in a generic way such that it can be reused and shared by groups of people and across software systems. On the basis of OntoCAPE, novel software support for various engineering activities can be developed; possible applications include the systematic management and retrieval of simulation models and design documents, electronic procurement of plant equipment, mathematical modeling, as well as the integration of design data from distributed sources. - RWTH Aachen University - OWL - GNU General Public License. - https://www.avt.rwth-aachen.de/cms/avt/forschung/sonstiges/software/~ipts/ontocape/?lidx=1 - Materials Science and Engineering - Manufacturing - 2.0 - - - BFO - Basic Formal Ontology (BFO) - The Basic Formal Ontology (BFO) is a small, upper-level ontology that describes the basic types of entities in the world and how they relate to each other. - University at Buffalo - OWL - 2020 - Creative Commons 4.0 - https://github.com/BFO-ontology/BFO-2020/ - Upper Ontology - Basic - 2.0 - - - ENM - Environmental Noise Measurement Ontology (ENM) - The eNanoMapper project (https://www.enanomapper.net/), NanoCommons project (https://www.nanocommons.eu/) and ACEnano project (http://acenano-project.eu/) are creating a pan-European computational infrastructure for toxicological data management for ENMs, based on semantic web standards and ontologies. This ontology is an application ontology targeting the full domain of nanomaterial safety assessment. It re-uses several other ontologies including the NPO, CHEMINF, ChEBI, and ENVO. - eNanoMapper Consortium - OWL - 2025-02-17 - Creative Commons 3.0 - https://terminology.tib.eu/ts/ontologies/ENM - Medicine - Material Science and Engineering - 10.0 - - - CiTO - Citation Typing Ontology (CiTO) - The Citation Typing Ontology (CiTO) is an ontology that enables characterization of the nature or type of citations, both factually and rhetorically. - Silvio Peroni, David Shotton - OWL - 2018-02-16 - Creative Commons 4.0 - https://github.com/SPAROntologies/cito/tree/master/docs/current - Scholarly Knowledge - Scholarly Communication - 2.8.1 - - - SIOC - Semantically-Interlinked Online Communities (SIOC) - The SIOC (Semantically-Interlinked Online Communities) Ontology is an ontology for describing the information in online communities. This includes sites that support online discussions, blogging, file sharing, photo sharing, social networking, etc. - Data Science Institute, NUI Galway - RDF - 2018/02/28 - Creative Commons 3.0 - http://rdfs.org/sioc/spec/ - Social Sciences - Social Networks - 1.36 - - - PeriodicTable - Periodic Table of the Elements Ontology (PeriodicTable) - PeriodicTable.owl is a representation of the Periodic Table of the Elements in the OWL Web Ontology Language. It provides reference data to support Semantic Web applications in chemistry and related disciplines. - Michael Cook - OWL - 2004/02/05 - https://www.daml.org/2003/01/periodictable/ - Materials Science and Engineering - Periodic Table of Elements - 1.10 - - - MechanicalTesting - Mechanical Testing Ontology (MechanicalTesting) - A domain ontology for mechanical testing based on EMMO. - Fraunhofer IWM - OWL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/domain-mechanical-testing - Materials Science and Engineering - Mechanical Testing - 1.0.0 - - - DSIM - Dislocation Simulation and Model Ontology (DSIM) - Dislocation simulation and model ontology (DSIM) is an ontology developed to model various concepts and relationships in the discrete dislocation dynamics domain and microscopy techniques used in the dislocation domain. The various concepts are the numerical representation of dislocation applied in the dislocation dynamic simulation and the pictorial concept of pixel applied in representing dislocation in the experimental image, eg., TEM image, SEM image, and FIM image. - Ahmad Zainul Ihsan - OWL - 17.08.2023 - Creative Commons Attribution 3.0 Unported (CC BY 3.0) - https://github.com/OCDO/DSIM - Materials Science and Engineering - Materials Science - 1.0 - - - EMMO - The Elementary Multiperspective Material Ontology (EMMO) - The Elementary Multiperspective Material Ontology (EMMO) is the result of a multidisciplinary effort within the EMMC, aimed at the development of a standard representational ontology framework based on current materials modelling and characterization knowledge. Instead of starting from general upper level concepts, as done by other ontologies, the EMMO development started from the very bottom level, using the actual picture of the physical world coming from applied sciences, and in particular from physics and material sciences. - European Materials Modelling Council (EMMC) - OWL - 2024-03 - Creative Commons 4.0 - https://emmo-repo.github.io/ - Materials Science and Engineering - Materials Modelling - 1.0.0-rc3 - - - NFDIcore - National Research Data Infrastructure Ontology (NFDIcore) - The National Research Data Infrastructure (NFDI) initiative has led to the formation of various consortia, each focused on developing a research data infrastructure tailored to its specific domain. To ensure interoperability across these consortia, the NFDIcore ontology has been developed as a mid-level ontology for representing metadata related to NFDI resources, including individuals, organizations, projects, data portals, and more. - Jörg Waitelonis, Oleksandra Bruns, Tabea Tietz, Etienne Posthumus, Hossein Beygi Nasrabadi, Harald Sack - OWL - 2025-02-07 - Creative Commons 1.0 - https://ise-fizkarlsruhe.github.io/nfdicore/ - Scholarly Knowledge - Research Data Infrastructure - 3.0.0 - - - PATO - Phenotype and Trait Ontology (PATO) - An ontology of phenotypic qualities (properties, attributes or characteristics). + + IAO + Information Artifact Ontology (IAO) + The Information Artifact Ontology (IAO) is an ontology of information entities, originally driven by work by the OBI digital entity and realizable information entity branch. OWL - 2025-02-01 + 2022-11-07 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/PATO - Biology and Life Sciences - Biology - 1.2 - - - GeoNames - GeoNames Ontology (GeoNames) - The Geonames ontologies provides elements of description for geographical features, in particular those defined in the geonames.org database. - Bernard Vatant - RDF - 2022-01-30 - Creative Commons 3.0 - https://www.geonames.org/ontology - Geography - Geographic Knowledge - 3.3 - - - ENVO - Environment Ontology (ENVO) - ENVO is an expressive, community ontology which helps humans, machines, and semantic web applications understand environmental entities of all kinds, from microscopic to intergalactic scales. As a FAIR-compliant resource, it promotes interoperability through the concise, controlled description of all things environmental. - Pier Luigi Buttigieg (https://orcid.org/0000-0002-4366-3088) - OWL - 2024-07-01 - Creative Commons 1.0 - https://obofoundry.org/ontology/envo.html - Ecology and Environment - Environment, Ecosystems, Habitats - 2024-07-01 - - - BIBFRAME - Bibliographic Framework Ontology (BIBFRAME) - The Bibframe vocabulary consists of RDF classes and properties used for the description of items cataloged principally by libraries, but may also be used to describe items cataloged by museums and archives. Classes include the three core classes - Work, Instance, and Item - in addition to many more classes to support description. Properties describe characteristics of the resource being described as well as relationships among resources. For example: one Work might be a "translation of" another Work; an Instance may be an "instance of" a particular Bibframe Work. Other properties describe attributes of Works and Instances. For example: the Bibframe property "subject" expresses an important attribute of a Work (what the Work is about), and the property "extent" (e.g. number of pages) expresses an attribute of an Instance. - United States, Library of Congress - RDF - 2022-10-03 - Creative Commons 1.0 - https://id.loc.gov/ontologies/bflc.html - Education - Library, Museums, Archives - 2.5.0 - - - PODO - Point Defects Ontology (PODO) - PODO focuses on the description of point defects in crystalline materials. - https://orcid.org/0000-0001-7564-7990 - OWL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/OCDO/podo - Materials Science and Engineering - Materials Science - 1.0.0 + https://terminology.tib.eu/ts/ontologies/IAO + General Knowledge + Information, Data, Knowledge - - PMDco - The Platform MaterialDigital core ontology (PMDco) - The PMD Core Ontology (PMDco) is a comprehensive framework for representing knowledge that encompasses fundamental concepts from the domains of materials science and engineering (MSE). The PMDco has been designed as a mid-level ontology to establish a connection between specific MSE application ontologies and the domain neutral concepts found in established top-level ontologies. The primary goal of the PMDco is to promote interoperability between diverse domains. - Jannis Grundmann + + PreMOn + Pre-Modern Ontology (PreMOn) + The PreMOn Ontology is an extension of lemon (W3C Ontology Lexicon Community Group, 2015) for representing predicate models and their mappings. The Core Module of the PreMOn Ontology defines the main abstractions for modelling semantic classes with their semantic roles, mappings between different predicate models, and annotations. + Francesco Corcoglioniti, Marco Rospocher <https://dkm.fbk.eu/rospocher> OWL - 2025-03-20 - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/materialdigital/core-ontology?tab=readme-ov-file - Materials Science and Engineering - Materials Science - 3.0.0-alpha1 - - - Metadata4Ing - Metadata for Intelligent Engineering (Metadata4Ing) - The ontology Metadata4Ing provides a framework for the semantic description of research data and of the whole data generation process, embracing the object of investigation, all sample and data manipulation methods and tools, the data files themselves, and the roles of persons and institutions. The structure and application of the ontology are based on the principles of modularity and inheritance. - Metadata4Ing Workgroup - TTL - 2025-03-10 + 2018-02-15 Creative Commons 4.0 - https://git.rwth-aachen.de/nfdi4ing/metadata4ing/metadata4ing + https://premon.fbk.eu/ontology/core# Scholarly Knowledge - Materials Science - 1.3.1 - - - ONTORULE - Ontology for the Steel Domain (ONTORULE) - This deliverable consists of the ontology developed in ONTORULE for the steel industry use case. It is presented as an attachment to this document as an html document which was generated by SpecGen from the OWL file. The original OWL file is also included. This document describes the different concepts and attributes included in the ontology. For a better understanding of the decisions taken at the time of representing the knowledge in the ontology, the reader is encouraged to also read the document D5.4. - Diego Daz - TTL - 2010-05-31 - N/A - https://raw.githubusercontent.com/ISE-FIZKarlsruhe/mseo.github.io/master/Ontology_files/ONTORULEsteel.ttl - Materials Science and Engineering - Materials Science - - - NPO - NanoParticle Ontology (NPO) - NanoParticle Ontology (NPO) is developed within the framework of the Basic Formal Ontology (BFO), and implemented in the Ontology Web Language (OWL) using well-defined ontology design principles. The NPO was developed to represent knowledge underlying the preparation, chemical composition, and characterization of nanomaterials involved in cancer research. Public releases of the NPO are available through BioPortal website, maintained by the National Center for Biomedical Ontology. Mechanisms for editorial and governance processes are being developed for the maintenance, review, and growth of the NPO. - Dennis G. Thomas - OWL - 2013-05-31 - BSD-3-Clause license - https://github.com/sobolevnrm/npo?tab=readme-ov-file - Biology and Life Sciences - Materials Science - 2013-05-31 - - - MAT - Material Properties Ontology (MAT) - The Material Properties Ontology aims to provide the vocabulary to describe the building components, materials, and their corresponding properties, relevant within the construction industry. More specifically, the building elements and properties covered in this ontology support applications focused on the design of building renovation projects. - María Poveda-Villalón, Serge Chávez-Feria - RDF - Creative Commons 4.0 - https://bimerr.iot.linkeddata.es/def/material-properties/ - Materials Science and Engineering - Materials Properties - 0.0.8 + Linguistics + 2018a - - BBCWildlife - BBC Wildlife Ontology (BBCWildlife) - A simple vocabulary for describing biological species and related taxa. The vocabulary defines terms for describing the names and ranking of taxa, as well as providing support for describing their habitats, conservation status, and behavioural characteristics, etc. - https://www.ldodds.com#me, http://tomscott.name/ + + BBCCoreConcepts + BBC Core Concepts Ontology (BBCCoreConcepts) + The generic BBC ontology for people, places, events, organisations, themes which represent things that make sense across the BBC. This model is meant to be generic enough, and allow clients (domain experts) link their own concepts e.g., athletes or politicians using rdfs:sublClassOf the particular concept. + jeremy.tarling@bbc.co.uk, tom.hodgkinson@bbc.co.uk TTL - 2013/12/18 + 2019-11-21 Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/wildlife-ontology + https://www.bbc.co.uk/ontologies/core-concepts-ontology News and Media - Wildlife - 1.1 - - - PRotein - Protein Ontology (PRO) - The PRotein Ontology (PRO) formally defines taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. - RDF - 08:08:2024 - Creative Commons 4.0 - http://purl.obolibrary.org/obo/pr.owl - Medicine - Protein - 1.2 - - - GFO - General Formal Ontology (GFO) - The General Formal Ontology is a top-level ontology for conceptual modeling, which is being constantly further developed by Onto-Med. It includes elaborations of categories like objects, processes, time and space, properties, relations, roles, functions, facts, and situations. Moreover, we are working on an integration with the notion of levels of reality in order to more appropriately capture entities in the material, mental, and social areas. - OWL - 2024-11-18 - Creative Commons 4.0 - https://onto-med.github.io/GFO/release/2024-11-18/index-en.html - Upper Ontology - - - OIECharacterisation - Open Innovation Environment Characterisation (OIECharacterisation) - EMMO-compliant, domain-level OIE ontology tackling the areas of characterization methods. - Daniele Toti, Gerhard Goldbeck, Pierluigi Del Nostro - TTL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/OIE-Ontologies/ - Materials Science and Engineering - Materials - - - FRAPO - Funding, Research Administration and Projects Ontology (FRAPO) - The Funding, Research Administration and Projects Ontology (FRAPO) is an ontology for describing the administrative information of research projects, e.g., grant applications, funding bodies, project partners, etc. - David Shotton - RDF - Creative Commons 4.0 - http://www.sparontologies.net/ontologies/frapo - Scholarly Knowledge - Administration - - - CHEMINF - Chemical Information Ontology (CHEMINF) - The chemical information ontology (cheminf) describes information entities about chemical entities. It provides qualitative and quantitative attributes to richly describe chemicals. Includes terms for the descriptors commonly used in cheminformatics software applications and the algorithms which generate them. - Egon Willighagen, Nina Jeliazkova, Ola Spjuth, Valery Tkachenko - OWL - Creative Commons 1.0 - https://terminology.tib.eu/ts/ontologies/CHEMINF - Chemistry - 2.1.0 - - - MGED - MGED Ontology (MGED) - An ontology for microarray experiments in support of MAGE v.1. Concepts, definitions, terms, and resources for standardized description of a microarray experiment in support of MAGE v.1. The MGED ontology is divided into the MGED Core ontology which is intended to be stable and in synch with MAGE v.1; and the MGED Extended ontology which adds further associations and classes not found in MAGE v.1 - Chris Stoeckert, Helen Parkinson, Trish Whetzel, Paul Spellman, Catherine A. Ball, Joseph White, John Matese, Liju Fan, Gilberto Fragoso, Mervi Heiskanen, Susanna Sansone, Helen Causton, Laurence Game, Chris Taylor - OWL - Feb. 9, 2007 - Creative Commons 4.0 - https://mged.sourceforge.net/ontologies/MGEDontology.php/ - Biology and Life Sciences - Domain Ontology - 1.3.1.1 - - - CSO - Computer Science Ontology (CSO) - The Computer Science Ontology (CSO) is a large-scale ontology of research areas in computer science. It provides a comprehensive vocabulary of research topics in computing, organized in a hierarchical structure. This class processes the Computer Science Ontology (CSO) with custom hooks for: - Topic-based class detection - superTopicOf relationships - contributesTo relationships - Knowledge Media Institute, Open University - OWL - Creative Commons 4.0 - https://cso.kmi.open.ac.uk/home - Scholarly Knowledge - Computer Science - 3.4 + Core Concepts + 1.30 - - AMOntology - Additive Manufacturing Ontology (AMOntology) - The AM ontology has been developed following two major milestones. The ontology developed within the first milestone includes AMProcessOntology, ModelOntology and AMOntology files. AMProcessOntology contains the set of entities used to capture knowledge about additive manufacturing processes. ModelOntology contains the set of entities used to capture knowledge about modeling concepts that represent (possibly) multi-physics multi-scale processes. AMOntology uses AMProcessOntology and ModelOntology files to describe entities that capture knowledge about characteristics of computational models for AM processes. - Iassou Souroko, Ali Riza Durmaz + + BBCCreativeWork + BBC Creative Work Ontology (BBCCreativeWork) + This ontology defines the terms required to describe the creative works produced by the BBC and their associated metadata. This ontology powers reading and writing creative works in the triplestore using tags associated with them (about) their more specific types (BlogPost, NewsItem, Programme) and audiences (audience). + LinkedData@bbc.co.uk TTL - 2023-05-10 - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/iassouroko/AMontology - Materials Science and Engineering - Manufacturing - 1.0 - - - ICON - Icon Ontology (ICON) - The ICON ontology deals with high granularity art interpretation. It was developed by conceptualizing Panofsky's theory of levels of interpretation, therefore artworks can be described according to Pre-iconographical, Iconographical and Iconological information. - Knowledge Media Institute - OWL - April 26th, 2024 - Creative Commons 4.0 - https://w3id.org/icon/ontology/ - Arts and Humanities - Art History, Cultural Heritage - 2.1.0 - - - DoCO - Document Components Ontology (DoCO) - DoCO, the Document Components Ontology, is an OWL 2 DL ontology that provides a general-purpose structured vocabulary of document elements. DoCO has been designed as a general unifying ontological framework for describing different aspects related to the content of scientific and other scholarly texts. Its primary goal has been to improve the interoperability and shareability of academic documents (and related services) when multiple formats are actually used for their storage. - David Shotton and Silvio Peroni - RDF - 2015-07-03 + 2012-12-01 Creative Commons 4.0 - http://www.sparontologies.net/ontologies/doco - Education - document components - 1.3 + https://www.bbc.co.uk/ontologies/creative-work-ontology + News and Media + Creative Work + 1.19 - - AFO - Allotrope Foundation Ontology (AFO) - The AFO is an ontology suite that provides a standard vocabulary and semantic model for the representation of laboratory analytical processes. The AFO suite is aligned at the upper layer to the Basic Formal Ontology (BFO). The core domains modeled include, Equipment, Material, Process, and Results. This artifact contains all triples of Allotrope Foundation Merged Without QUDT Ontology Suite (REC/2023/12) together with triples inferred with HermiT. - Allotrope Foundation + + BBCStoryline + BBC Storyline Ontology (BBCStoryline) + The News Storyline Ontology is a generic model for describing and organising the stories news organisations tell. The ontology is intended to be flexible to support any given news or media publisher's approach to handling news stories. At the heart of the ontology, is the concept of Storyline. As a nuance of the English language the word 'story' has multiple meanings. In news organisations, a story can be an individual piece of content, such as an article or news report. It can also be the editorial view on events occurring in the world. + http://uk.linkedin.com/in/paulwilton, http://www.bbc.co.uk/blogs/internet/authors/Jeremy_Tarling, http://uk.linkedin.com/in/jarredmcginnis TTL - 2024-06-28 - CC BY 4.0 - https://terminology.tib.eu/ts/ontologies/AFO - Chemistry - Laboratory Analytical Processes - 2024-06 - - - MassSpectrometry - Mass Spectrometry Ontology (MassSpectrometry) - A structured controlled vocabulary for the annotation of experiments concerned with proteomics mass spectrometry. - Andreas Bertsch - OWL - 12:02:2025 - Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/MS - Chemistry - Mass Spectrometry, Proteomics - - - OBI - Ontology for Biomedical Investigations (OBI) - The Ontology for Biomedical Investigations (OBI) helps you communicate clearly about scientific investigations by defining more than 2500 terms for assays, devices, objectives, and more. - OWL - 2025-01-09 + 2013-05-01 Creative Commons 4.0 - https://github.com/obi-ontology/obi/tree/master - Medicine - Biomedical Investigations - - - OEO - The Open Energy Ontology (OEO) - The Open Energy Ontology (OEO) is a domain ontology of the energy system analysis context. It is developed as part of the Open Energy Family. The OEO is published on GitHub under an open source license. The language used is the Manchester OWL Syntax, which was chosen because it is user-friendly for editing and viewing differences of edited files. The OEO is constantly being extended. The first version of the OEO has been released on June 11th 2020. A Steering Committee (OEO-SC) was created to accompany the development, increase awareness of the ontology and include it in current projects. - OWL - 03/2025 - Creative Commons Attribution 1.0 Generic (CC BY 1.0) - https://github.com/OpenEnergyPlatform/ontology?tab=readme-ov-file - Ecology and Environment - Energy - 2.7.0 + https://iptc.org/thirdparty/bbc-ontologies/storyline.html + News and Media + Storyline + 0.3 - - RO - Relation Ontology (RO) - The Relations Ontology (RO) is a collection of OWL relations (ObjectProperties) intended for use across a wide variety of biological ontologies. + + REX + Physico-chemical process ontology (REX) + REX is an ontology of physico-chemical processes, i.e. physico-chemical changes occurring in course of time. REX includes both microscopic processes (involving molecular entities or subatomic particles) and macroscopic processes. Some biochemical processes from Gene Ontology (GO Biological process) can be described as instances of REX. + University of Warsaw OWL - 2024-04-24 - CC0 - http://purl.obolibrary.org/obo/ro.owl - General Knowledge - Relations - 2024-04-24 - - - AGROVOC - AGROVOC Multilingual Thesaurus (AGROVOC) - AGROVOC is a relevant Linked Open Data set about agriculture available for public use and facilitates access and visibility of data across domains and languages. It offers a structured collection of agricultural concepts, terms, definitions and relationships which are used to unambiguously identify resources, allowing standardized indexing processes and making searches more efficient. - Food and Agriculture Organization of the United Nations - RDF - August 12, 2024 - Creative Commons 4.0 - https://agroportal.lirmm.fr/ontologies/AGROVOC - Agriculture - Agricultural Knowledge - 2024-04 + 2025-03-11 + Creative Commons 4.0 + https://terminology.tib.eu/ts/ontologies/REX + Chemistry + 1.0 - - BBCSport - BBC Sport Ontology (BBCSport) - The Sport Ontology is a simple lightweight ontology for publishing data about competitive sports events. The terms in this ontology allow data to be published about: The structure of sports tournaments as a series of eventsThe competing of agents in a competitionThe type of discipline a event involvesThe award associated with the competition and how received it...etc Whilst it originates in a specific BBC use case, the Sport Ontology should be applicable to a wide range of competitive sporting events data publishing use cases. Care has been taken to try and ensure interoperability with more general ontologies in use. In particular, it draws heavily upon the events ontology. - https://uk.linkedin.com/pub/jem-rayfield/27/b19/757, https://uk.linkedin.com/in/paulwilton, https://www.blockslabpillar.com, https://www.linkedin.com/in/tfgrahame, https://uk.linkedin.com/pub/stuart-williams/8/684/351, https://uk.linkedin.com/in/brianwmcbride + + OIECharacterisation + Open Innovation Environment Characterisation (OIECharacterisation) + EMMO-compliant, domain-level OIE ontology tackling the areas of characterization methods. + Daniele Toti, Gerhard Goldbeck, Pierluigi Del Nostro TTL - Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/sport-ontology - News and Media - Sport - 3.2 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/emmo-repo/OIE-Ontologies/ + Materials Science and Engineering + Materials - - ChordOntology - Chord Ontology (ChordOntology) - The Chord Ontology is an ontology for describing chords in musical pieces. - Yves Raimond, Samer Abdallah, Centre for Digital Music, Queen Mary, University of London + + DoCO + Document Components Ontology (DoCO) + DoCO, the Document Components Ontology, is an OWL 2 DL ontology that provides a general-purpose structured vocabulary of document elements. DoCO has been designed as a general unifying ontological framework for describing different aspects related to the content of scientific and other scholarly texts. Its primary goal has been to improve the interoperability and shareability of academic documents (and related services) when multiple formats are actually used for their storage. + David Shotton and Silvio Peroni RDF - 2007-10-25 - Creative Commons 3.0 - https://github.com/motools/chordontology - Arts and Humanities - Musical Works - 1.0 - - - EFO - Experimental Factor Ontology (EFO) - The Experimental Factor Ontology (EFO) provides a systematic description of many experimental variables available in EBI databases, and for projects such as the GWAS catalog. It combines parts of several biological ontologies, such as UBERON anatomy, ChEBI chemical compounds, and Cell Ontology. The scope of EFO is to support the annotation, analysis and visualization of data handled by many groups at the EBI and as the core ontology for Open Targets. EFO is developed by the EMBL-EBI Samples, Phenotypes and Ontologies Team (SPOT). - OWL - 2025-02-17 - Apache 2.0 - https://www.ebi.ac.uk/efo - Biology and Life Sciences - Biology - 3.75.0 + 2015-07-03 + Creative Commons 4.0 + http://www.sparontologies.net/ontologies/doco + Education + document components + 1.3 - - GO - Gene Ontology (GO) - The Gene Ontology (GO) Provides structured controlled vocabularies for the annotation of gene products with respect to their molecular function, cellular component, and biological role. + + SPWorkflow + SMART Protocols Ontology: Workflow Module (SP-Workflow) + SP-Workflow module represents: i) the executable elements of a protocol; ii) the experimental actions and material entities that participates in instructions (sample/specimen, organisms, reagents, instruments); and iii) the order of execution of the instructions. + http://oxgiraldo.wordpress.com OWL - 2024-11-03 - Creative Commons 4.0 - https://geneontology.org/docs/download-ontology/ - Biology and Life Sciences - Molecular Biology, Genetics + 2013-07-01 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/SMARTProtocols/SMART-Protocols + Scholarly Knowledge + Workflows + 4.0 SchemaOrg @@ -539,167 +132,77 @@ Web Development 28.1 - - LPBFO - Laser Powder Bed Fusion Ontology (LPBFO) - The LPBF Ontology can be used to describe the additive manufacturing of a component via Laser Powder Bed Fusion (LPBF) / Selective Laser Melting (SLM). The ontology builds on BFO2.0 and BWMD_mid and has been developed to be used in conjunction with the digital workflows provided by Fraunhofer IWM. If possible, the terminology within this ontology was used as provided by ISO/ASTM 52900:2015. Recently, classes relevant for Life Cycle Analysis (LCA) were added that enable sustainability assessment. - Fraunhofer IWM - OWL - 2022-09-20 - Creative Commons 4.0 - https://matportal.org/ontologies/LPBFO - Materials Science and Engineering - Materials Science - 1.1.9 - - - QUDT - Quantities, Units, Dimensions and Data Types (QUDT) - QUDT is an advocate for the development and implementation of standards to quantify data expressed in RDF and JSON. - NASA Ames Research Center - TTL - March 1, 2022 - Creative Commons 4.0 - https://qudt.org/ - Units and Measurements - Physics - 2.1 - - - AgrO - Agronomy Ontology (AgrO) - An ontology is a formal representation of a disciplinary domain, representing a semantic standard that can be employed to annotate data where key concepts are defined, as well as the relationships that exist between those concepts (Gruber, 2009). Ontologies provide a common language for different kinds of data to be easily interpretable and interoperable allowing easier aggregation and analysis. The Agronomy Ontology (AgrO) provides terms from the agronomy domain that are semantically organized and can facilitate the collection, storage and use of agronomic data, enabling easy interpretation and reuse of the data by humans and machines alike. To fully understand the implications of varying practices within cropping systems and derive insights, it is often necessary to pull together information from data in different disciplinary domains. For example, data on field management, soil, weather and crop phenotypes may need to be aggregated to assess performance of particular crop under different management interventions. However, agronomic data are often collected, described, and stored in inconsistent ways, impeding data comparison, mining, interpretation reuse. The use of standards for metadata and data annotation play a key role in addressing these challenges. While the CG Core Metadata Schema provides a metadata standard to describe agricultural datasets, the Agronomy Ontology enables the description of agronomic data variables using standard terms. - The Crop Ontology Consortium - RDF - 2022-11-02 - Creative Commons 4.0 - https://agroportal.lirmm.fr/ontologies/AGRO?p=summary - Agriculture - Agronomy - 1.0 - - - PRIMA - PRovenance Information in MAterials science (PRIMA) - An ontology that captures the provenance information in the materials science domain. - Ahmad Zainul Ihsan, Mehrdad Jalali, Rossella Aversa + + MSEO + Materials Science and Engineering Ontology (MSEO) + MSEO utilizes the IOF Ontology stack giving materials scientists and engineers the ability to represent their experiments and resulting data. The goal is to create machine and human readable sematic data which can be easily digested by other science domains. It is a product of the joint venture Materials Open Lab Project between the Bundesanstalt für Materialforschung und -prüfung (BAM) and the Fraunhofer Group MATERIALS and uses the BWMD ontology created by Fraunhofer IWM as a starting point. + Thomas Hanke, Fraunhofer IWM TTL - 2024-01-29 - Creative Commons Attribution 3.0 Unported (CC BY 3.0) - https://materials-data-science-and-informatics.github.io/MDMC-NEP-top-level-ontology/PRIMA/complete/ver_2_0/index.html + MIT License + https://github.com/Mat-O-Lab/MSEO Materials Science and Engineering Materials Science - 2.0 - - BBCPolitics - BBC Politics News Ontology (BBCPolitics) - The Politics Ontology describes the concepts that occur in BBC politics news. - https://www.r4isstatic.com/ + + AFO + Allotrope Foundation Ontology (AFO) + The AFO is an ontology suite that provides a standard vocabulary and semantic model for the representation of laboratory analytical processes. The AFO suite is aligned at the upper layer to the Basic Formal Ontology (BFO). The core domains modeled include, Equipment, Material, Process, and Results. This artifact contains all triples of Allotrope Foundation Merged Without QUDT Ontology Suite (REC/2023/12) together with triples inferred with HermiT. + Allotrope Foundation TTL - 2014-01-06 - Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/politics-ontology - News and Media - Politics - 0.9 + 2024-06-28 + CC BY 4.0 + https://terminology.tib.eu/ts/ontologies/AFO + Chemistry + Laboratory Analytical Processes + 2024-06 - - NanoMine - NanoMine Ontology (NanoMine) - Polymer Nanocomposites based ontology which enable researchers to develop and test broad-reaching hypotheses about how inter-relationships between different materials processing methods and composition result in specific changes in material properties. - TTL - APACHE 2.0 - https://github.com/tetherless-world/nanomine-ontology - Materials Science and Engineering + + NPO + NanoParticle Ontology (NPO) + NanoParticle Ontology (NPO) is developed within the framework of the Basic Formal Ontology (BFO), and implemented in the Ontology Web Language (OWL) using well-defined ontology design principles. The NPO was developed to represent knowledge underlying the preparation, chemical composition, and characterization of nanomaterials involved in cancer research. Public releases of the NPO are available through BioPortal website, maintained by the National Center for Biomedical Ontology. Mechanisms for editorial and governance processes are being developed for the maintenance, review, and growth of the NPO. + Dennis G. Thomas + OWL + 2013-05-31 + BSD-3-Clause license + https://github.com/sobolevnrm/npo?tab=readme-ov-file + Biology and Life Sciences Materials Science + 2013-05-31 - - DBO - Digital Buildings Ontology (DBO) - The Digital Buildings ontology (DBO) is used by Google to represent structured information about buildings and building-installed equipment. - Google + + IOF + Industrial Ontology Foundry (IOF) + The IOF Core Ontology contains notions found to be common across multiple manufacturing domains. This file is an RDF implementation of these notions. The ontology utilizes the Basic Formal Ontology or BFO as a top-level ontology but also borrows terms from various domain-independent or mid-level ontologies. The purpose of the ontology is to serve as a foundation for ensuring consistency and interoperability across various domain-specific reference ontologies the IOF publishes. + IOF Core Working Group RDF - 02/23/2023 - Apache 2.0 - https://github.com/google/digitalbuildings?tab=readme-ov-file + 2020 + MIT + https://oagi.org/pages/Released-Ontologies Industry - Building Information - 0.0.1 - - - BBCCoreConcepts - BBC Core Concepts Ontology (BBCCoreConcepts) - The generic BBC ontology for people, places, events, organisations, themes which represent things that make sense across the BBC. This model is meant to be generic enough, and allow clients (domain experts) link their own concepts e.g., athletes or politicians using rdfs:sublClassOf the particular concept. - jeremy.tarling@bbc.co.uk, tom.hodgkinson@bbc.co.uk - TTL - 2019-11-21 - Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/core-concepts-ontology - News and Media - Core Concepts - 1.30 + Manufacturing + 1.0 - - MMO - Materials Mechanics Ontology (MMO) - The materials mechanics ontology is an application-level ontology that was created for supporting named entity recognition tasks for materials fatigue domain. The ontology covers some fairly general MSE concepts that could prospectively be merged into PMDco or other upper materials ontologies such as descriptions of crystallographic defects and microstructural entities. Furthermore, concepts related to the materials fatigue subdomain are also heavily incorporated. - Akhil Thomas, Ali Riza Durmaz + + Wine + Wine Ontology (Wine) + A project to define an RDF style ontology for wines and the wine-industry RDF - 2024-01-30 - Creative Commons 4.0 - https://iwm-micro-mechanics-public.pages.fraunhofer.de/ontologies/materials-mechanics-ontology/index-en.html - Materials Science and Engineering - Scholarly Knowledge - 1.0.1 - - - MatWerk - NFDI MatWerk Ontology (MatWerk) - NFDI-MatWerk aims to establish a digital infrastructure for Materials Science and Engineering (MSE), fostering improved data sharing and collaboration. This repository provides comprehensive documentation for NFDI MatWerk Ontology (MWO) v3.0, a foundational framework designed to structure research data and enhance interoperability within the MSE community. To ensure compliance with top-level ontology standards, MWO v3.0 is aligned with the Basic Formal Ontology (BFO) and incorporates the modular approach of the NFDIcore mid-level ontology, enriching metadata through standardized classes and properties. The MWO addresses key aspects of MSE research data, including the NFDI-MatWerk community structure, covering task areas, infrastructure use cases, projects, researchers, and organizations. It also describes essential NFDI resources, such as software, workflows, ontologies, publications, datasets, metadata schemas, instruments, facilities, and educational materials. Additionally, MWO represents NFDI-MatWerk services, academic events, courses, and international collaborations. As the foundation for the MSE Knowledge Graph, MWO facilitates efficient data integration and retrieval, promoting collaboration and knowledge representation across MSE domains. This digital transformation enhances data discoverability, reusability, and accelerates scientific exchange, innovation, and discoveries by optimizing research data management and accessibility. - Hossein Beygi Nasrabadi, Jörg Waitelonis, Ebrahim Norouzi, Kostiantyn Hubaiev, Harald Sack - TTL - 2025-03-01 - Creative Commons 1.0 - https://github.com/ISE-FIZKarlsruhe/mwo?tab=readme-ov-file - Materials Science and Engineering - Research Data, Interoperability - 3.0.0 - - - SEPIO - Scientific Evidence and Provenance Information Ontology (SEPIO) - The SEPIO ontology is in its early stages of development, undergoing iterative refinement as new requirements emerge and alignment with existing standards is explored. The SEPIO core file imports two files which can be resolved at the URLs below: IAO ontology-metadata import: https://raw.githubusercontent.com/monarch-initiative/SEPIO-ontology/master/src/ontology/imports/ontology-metadata.owl bfo mireot: https://raw.githubusercontent.com/monarch-initiative/SEPIO-ontology/master/src/ontology/mireots/bfo-mireot.owl - OWL - 2015-02-23 - Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/SEPIO - Scholarly Knowledge - Scientific Evidence - - - UMBEL - Upper Mapping and Binding Exchange Layer Vocabulary (UMBEL) - UMBEL is the Upper Mapping and Binding Exchange Layer, designed to help content interoperate on the Web. UMBEL provides two valuable functions: First, it is a broad, general reference structure of 34,000 concepts, which provides a scaffolding to link and interoperate other datasets and domain vocabularies. Second, it is a base vocabulary for the construction of other concept-based domain ontologies, also designed for interoperation. - n3 - May 10, 2016 - https://github.com/structureddynamics/UMBEL/tree/master/Ontology - General Knowledge - Web Development - 1.50 + https://github.com/UCDavisLibrary/wine-ontology + Food and Beverage + Wine - - DataCite - DataCite Ontology (DataCite) - The DataCite Ontology (DataCite) is an ontology that enables the metadata properties of the DataCite Metadata Schema Specification (i.e., a list of metadata properties for the accurate and consistent identification of a resource for citation and retrieval purposes) to be described in RDF. - David Shotton, Silvio Peroni + + Framester + Framester Ontology (Framester) + Framester is a a frame-based ontological resource acting as a hub between linguistic resources such as FrameNet, WordNet, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, and leveraging this wealth of links to create an interoperable predicate space formalized according to frame semantics and semiotics. Framester uses WordNet and FrameNet at its core, expands it to other resources transitively, and represents them in a formal version of frame semantics. + Aldo Gangemi RDF - 15/09/2022 + 19-04-2016 Creative Commons 4.0 - https://schema.datacite.org/ + http://150.146.207.114/lode/extract?url=http://ontologydesignpatterns.org/ont/framester/framester.owl Scholarly Knowledge - Metadata - 3.1 + Linguistics + 1.0 VOAF @@ -714,30 +217,53 @@ Social Network 2.3 - - REX - Physico-chemical process ontology (REX) - REX is an ontology of physico-chemical processes, i.e. physico-chemical changes occurring in course of time. REX includes both microscopic processes (involving molecular entities or subatomic particles) and macroscopic processes. Some biochemical processes from Gene Ontology (GO Biological process) can be described as instances of REX. - University of Warsaw + + PKO + Provenance Knowledge Ontology (PKO) + Procedural Knowledge (PK) is knowing how to perform some tasks, as opposed to descriptive/declarative knowledge, which is knowing what in terms of facts and notions. In industry, PK refers in general to structured processes to be followed, and can be related to both production (e.g., procedure on the production line in a plant) and services (e.g., procedure for troubleshooting during customer support); to specific technical expertise (e.g., procedure to set up a specific machine) and general regulations and best practices (e.g., safety procedures, activities to minimise environmental impact). + Mario Scrocca (Cefriel), Valentina Carriero (Cefriel) + RDF + 2025-03-01 + Creative Commons 4.0 + https://github.com/perks-project/pk-ontology/tree/master + Industry + Provenance + 1.0.0 + + + SUMO + Suggested Upper Merged Ontology (SUMO) + The Suggested Upper Merged Ontology (SUMO) and its domain ontologies form the largest formal public ontology in existence today. They are being used for research and applications in search, linguistics and reasoning. SUMO is the only formal ontology that has been mapped to all of the WordNet lexicon. OWL - 2025-03-11 + 2025-02-17 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/REX - Chemistry + https://www.ontologyportal.org/ + Upper Ontology 1.0 - - SPWorkflow - SMART Protocols Ontology: Workflow Module (SP-Workflow) - SP-Workflow module represents: i) the executable elements of a protocol; ii) the experimental actions and material entities that participates in instructions (sample/specimen, organisms, reagents, instruments); and iii) the order of execution of the instructions. - http://oxgiraldo.wordpress.com - OWL - 2013-07-01 - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/SMARTProtocols/SMART-Protocols + + PRotein + Protein Ontology (PRO) + The PRotein Ontology (PRO) formally defines taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. + RDF + 08:08:2024 + Creative Commons 4.0 + http://purl.obolibrary.org/obo/pr.owl + Medicine + Protein + 1.2 + + + WiLD + Workflows in Linked Data (WiLD) + Ontology to describe Workflows in Linked Data. + Tobias Käfer + TTL + 2020-06-10 + DBpedia License + https://databus.dbpedia.org/ontologies/purl.org/wild--vocab/2020.06.10-210552 Scholarly Knowledge - Workflows - 4.0 + Materials Science OIEManufacturing @@ -750,31 +276,204 @@ Materials Science and Engineering Materials - - BBCCreativeWork - BBC Creative Work Ontology (BBCCreativeWork) - This ontology defines the terms required to describe the creative works produced by the BBC and their associated metadata. This ontology powers reading and writing creative works in the triplestore using tags associated with them (about) their more specific types (BlogPost, NewsItem, Programme) and audiences (audience). - LinkedData@bbc.co.uk + + QUDT + Quantities, Units, Dimensions and Data Types (QUDT) + QUDT is an advocate for the development and implementation of standards to quantify data expressed in RDF and JSON. + NASA Ames Research Center TTL - 2012-12-01 + March 1, 2022 Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/creative-work-ontology - News and Media - Creative Work - 1.19 + https://qudt.org/ + Units and Measurements + Physics + 2.1 + + + Juso + Juso Ontology (Juso) + Juso Ontology is a Web vocabulary for describing geographical addresses and features. + James G. Kim, LiST Inc. + TTL + 2015-11-10 + Creative Commons 4.0 + https://rdfs.co/juso/0.1.1/html + Geography + geographical knowledge + 0.1.1 + + + ENM + Environmental Noise Measurement Ontology (ENM) + The eNanoMapper project (https://www.enanomapper.net/), NanoCommons project (https://www.nanocommons.eu/) and ACEnano project (http://acenano-project.eu/) are creating a pan-European computational infrastructure for toxicological data management for ENMs, based on semantic web standards and ontologies. This ontology is an application ontology targeting the full domain of nanomaterial safety assessment. It re-uses several other ontologies including the NPO, CHEMINF, ChEBI, and ENVO. + eNanoMapper Consortium + OWL + 2025-02-17 + Creative Commons 3.0 + https://terminology.tib.eu/ts/ontologies/ENM + Medicine + Material Science and Engineering + 10.0 + + + PTO + Product Types Ontology (PTO) + The Product Types Ontology is designed to be used in combination with GoodRelations, a standard vocabulary for the commercial aspects of offers. + Martin Hepp + RDF + 2025-02-21 + Creative Commons 3.0 + http://www.productontology.org/ + Industry + 1.0 + + + CIFCore + Crystallographic Information Framework Core Dictionary (CIFCore) + (1) to explain the historical development of CIF dictionaries to define in a machine-actionable manner the contents of data files covering various aspects of crystallography and related structural sciences; (2) to demonstrate some of the more complex types of information that can be handled with this approach. + TTL + May 24, 2023 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/emmo-repo/CIF-ontology?tab=readme-ov-file + Materials Science and Engineering + Materials Science + 0.1.0 + + + MDO + Materials Design Ontology (MDO) + MDO is an ontology for materials design field, representing the domain knowledge specifically related to solid-state physics and computational materials science. + Materials Design Division, National Institute for Materials Science (NIMS) + OWL + 2022-08-02 + Creative Commons 4.0 + https://github.com/LiUSemWeb/Materials-Design-Ontology/tree/master/ + Materials Science and Engineering + Materials Design + 1.1 + + + OntoKin + Chemical Kinetics Ontology (OntoKin) + OntoKin is an ontology developed for representing chemical kinetic reaction mechanisms. + IEEE + OWL + 08 February 2022 + Creative Commons 4.0 + https://www.ontologyportal.org/ + Chemistry + 1.0 + + + Atomistic + Atomistic Ontology (Atomistic) + An EMMO-based domain ontology for atomistic and electronic modelling. + Francesca L. Bleken, Jesper Friis + TTL + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/emmo-repo/domain-atomistic + Materials Science and Engineering + Materials Science + 0.0.2 + + + PSIMOD + Protein Modifications Ontology (PSIMOD) + PSI-MOD is an ontology developed by the Proteomics Standards Initiative (PSI) that describes protein chemical modifications, logically linked by an is_a relationship in such a way as to form a direct acyclic graph (DAG). The PSI-MOD ontology has more than 45 top-level nodes, and provides alternative hierarchical paths for classifying protein modifications either by the molecular structure of the modification, or by the amino acid residue that is modified. + OWL + 2022-06-13 + Creative Commons Attribution 4.0 + https://github.com/HUPO-PSI/psi-mod-CV + Chemistry + Protein Modifications + 1.031.6 + + + ChordOntology + Chord Ontology (ChordOntology) + The Chord Ontology is an ontology for describing chords in musical pieces. + Yves Raimond, Samer Abdallah, Centre for Digital Music, Queen Mary, University of London + RDF + 2007-10-25 + Creative Commons 3.0 + https://github.com/motools/chordontology + Arts and Humanities + Musical Works + 1.0 + + + GeoNames + GeoNames Ontology (GeoNames) + The Geonames ontologies provides elements of description for geographical features, in particular those defined in the geonames.org database. + Bernard Vatant + RDF + 2022-01-30 + Creative Commons 3.0 + https://www.geonames.org/ontology + Geography + Geographic Knowledge + 3.3 + + + LPBFO + Laser Powder Bed Fusion Ontology (LPBFO) + The LPBF Ontology can be used to describe the additive manufacturing of a component via Laser Powder Bed Fusion (LPBF) / Selective Laser Melting (SLM). The ontology builds on BFO2.0 and BWMD_mid and has been developed to be used in conjunction with the digital workflows provided by Fraunhofer IWM. If possible, the terminology within this ontology was used as provided by ISO/ASTM 52900:2015. Recently, classes relevant for Life Cycle Analysis (LCA) were added that enable sustainability assessment. + Fraunhofer IWM + OWL + 2022-09-20 + Creative Commons 4.0 + https://matportal.org/ontologies/LPBFO + Materials Science and Engineering + Materials Science + 1.1.9 + + + PPlan + Ontology for Provenance and Plans (P-Plan) + The Ontology for Provenance and Plans (P-Plan) is an extension of the PROV-O ontology [PROV-O] created to represent the plans that guided the execution of scientific processes. P-Plan describes how the plans are composed and their correspondence to provenance records that describe the execution itself. + http://www.isi.edu/~gil/ + OWL + 2014-03-12 + Creative Commons 4.0 + https://vocab.linkeddata.es/p-plan/index.html + Scholarly Knowledge + 1.3 + + + PROV + PROV Ontology (PROV-O) + The PROV Ontology (PROV-O) expresses the PROV Data Model [PROV-DM] using the OWL2 Web Ontology Language (OWL2) [OWL2-OVERVIEW]. It provides a set of classes, properties, and restrictions that can be used to represent and interchange provenance information generated in different systems and under different contexts. It can also be specialized to create new classes and properties to model provenance information for different applications and domains. The PROV Document Overview describes the overall state of PROV, and should be read before other PROV documents. + OWL + 2013-04-30 + W3C Software License + https://terminology.tib.eu/ts/ontologies/PROV + General Knowledge + General + 2013-04-30 - - VIBSO - Vibrational Spectroscopy Ontology (VIBSO) - The Vibration Spectroscopy Ontology defines technical terms with which research data produced in vibrational spectroscopy experiments can be semantically enriched, made machine readable and FAIR. - VIBSO Workgroup + + QUDV + Quantities, Units, Dimensions and Values (QUDV) + The SysML QUDV (Quantities, Units, Dimensions and Values) modelLibrary is specified in a UML/SysML class/block diagram. In order to generalize its potential usage and alignment with other standardization efforts concerning quantities and units, it is of interest to verify that the QUDV model can also be represented in the form of an ontology using a formal ontology definition language. + SysML OWL - 2024-09-23 - Creative Commons Attribution 4.0 - https://terminology.tib.eu/ts/ontologies/vibso - Chemistry - Spectroscopy - 2024-09-23 + 2009-10-30 + Apache License 2.0 + https://www.omgwiki.org/OMGSysML/doku.php?id=sysml-qudv:qudv_owl + Units and Measurements + 2009-10-30 + + + DBpedia + DBpedia Ontology (DBpedia) + The DBpedia ontology is generated from the manually created specifications in the DBpedia Mappings Wiki. Each release of this ontology corresponds to a new release of the DBpedia dataset, which contains instance data extracted from various language versions of Wikipedia. The DBpedia ontology has evolved into a crowd-sourced effort, resulting in a shallow cross-domain ontology. + DBpedia Maintainers and Contributors + OWL + 2008-11-17 + Creative Commons 3.0 + https://wiki.dbpedia.org/ + General Knowledge + Knowledge Graph BBCCMS @@ -789,270 +488,341 @@ Content Management Systems 3.7 - - FSO - Flow Systems Ontology (FSO) - The Flow Systems Ontology (FSO) is an ontology for describing interconnected systems with material or energy flow connections, and their components. - Ali Kücükavci, Mads Holten Rasmussen, Ville Kukkonen + + MatOnto + Material Ontology (MatOnto) + The Material Ontology (MatOnto) is based on the upper level ontology, the BFO. + OWL + https://github.com/EngyNasr/MSE-Benchmark/blob/main/testCases/secondTestCase/MatOnto.owl + Materials Science and Engineering + Scholarly Knowledge + + + CopyrightOnto + Copyright Ontology (CopyrightOnto) + The Copyright Ontology tries to formalise the copyright domain as a way to facilitate automated (or computer-supported) copyright management through the whole content value chain, as it is shaped by copyright law. Therefore, it does not focus just on the last step, end-users permissions to consume content, like many rights languages and ontologies do. + Rhizomik TTL - 2020-08-06 + 2019-09 Creative Commons 4.0 - https://github.com/alikucukavci/FSO/ - Materials Science and Engineering - Materials Science - 0.1.0 + https://rhizomik.net/ontologies/copyrightonto/ + Law + Legal Knowledge - - SAREF - Smart Applications REFerence ontology (SAREF) - The Smart Applications REFerence (SAREF) suite of ontologies forms a shared model of consensus intended to enable semantic interoperability between solutions from different providers and among various activity sectors in the Internet of Things (IoT), thus contributing to the development of data spaces. SAREF is published as a set of open standards produced by ETSI Technical Committee Smart Machine-to-Machine communications (SmartM2M). - ETSI Technical Committee Smart Machine-to-Machine communications (SmartM2M) - RDF - 2020-12-31 - https://saref.etsi.org/core/v3.2.1/ - Web and Internet - interoperability - 3.2.1 + + AS2 + Activity Streams 2.0 Ontology (AS2) + The Activity Streams 2.0 ontology is a vocabulary for describing social activities and actions. It is based on the Activity Streams 2.0 specification and provides a set of classes and properties for describing activities on the web. + TTL + 23 May 2017 + W3C Document License + https://github.com/w3c/activitystreams?tab=License-1-ov-file#readme + Social Sciences + Social + 2.0 - - MatVoc - Materials Vocabulary (MatVoc) - The official ontology produced in the context of the STREAM project. - Tatyana Sheveleva, Javad Chamanara - RDF - 2022-12-12 - MIT License - https://stream-project.github.io/#overv + + ASMO + Atomistic Simulation Methods Ontology (ASMO) + ASMO is an ontology that aims to define the concepts needed to describe commonly used atomic scale simulation methods, i.e. density functional theory, molecular dynamics, Monte Carlo methods, etc. ASMO uses the Provenance Ontology (PROV-O) to describe the simulation process. + https://orcid.org/0000-0001-7564-7990 + OWL + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/OCDO/asmo?tab=readme-ov-file#atomistic-simulation-methods-ontology-asmo Materials Science and Engineering Materials Science 1.0.0 - - FoodOn - Food Ontology (FoodON) - FoodOn, the food ontology, contains vocabulary for naming food materials and their anatomical and taxonomic origins, from raw harvested food to processed food products, for humans and domesticated animals. It provides a neutral and ontology-driven standard for government agencies, industry, nonprofits and consumers to name and reference food products and their components throughout the food supply chain. - OWL - 2025-01-16 - Creative Commons 4.0 - http://purl.obolibrary.org/obo/foodon.owl - Agriculture - Diet, Metabolomics, and Nutrition - - - DUO - Data Use Ontology (DUO) - DUO is an ontology which represent data use conditions. - OWL - 2025-02-17 + + DataCite + DataCite Ontology (DataCite) + The DataCite Ontology (DataCite) is an ontology that enables the metadata properties of the DataCite Metadata Schema Specification (i.e., a list of metadata properties for the accurate and consistent identification of a resource for citation and retrieval purposes) to be described in RDF. + David Shotton, Silvio Peroni + RDF + 15/09/2022 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/DUO/ + https://schema.datacite.org/ Scholarly Knowledge - 1.0 + Metadata + 3.1 - - PPlan - Ontology for Provenance and Plans (P-Plan) - The Ontology for Provenance and Plans (P-Plan) is an extension of the PROV-O ontology [PROV-O] created to represent the plans that guided the execution of scientific processes. P-Plan describes how the plans are composed and their correspondence to provenance records that describe the execution itself. - http://www.isi.edu/~gil/ + + ENVO + Environment Ontology (ENVO) + ENVO is an expressive, community ontology which helps humans, machines, and semantic web applications understand environmental entities of all kinds, from microscopic to intergalactic scales. As a FAIR-compliant resource, it promotes interoperability through the concise, controlled description of all things environmental. + Pier Luigi Buttigieg (https://orcid.org/0000-0002-4366-3088) OWL - 2014-03-12 + 2024-07-01 + Creative Commons 1.0 + https://obofoundry.org/ontology/envo.html + Ecology and Environment + Environment, Ecosystems, Habitats + 2024-07-01 + + + Hydra + Hydra Ontology (Hydra) + Hydra is a lightweight vocabulary to create hypermedia-driven Web APIs. By specifying a number of concepts commonly used in Web APIs it enables the creation of generic API clients. + Hydra W3C Community Group + JSONLD + 13 July 2021 Creative Commons 4.0 - https://vocab.linkeddata.es/p-plan/index.html - Scholarly Knowledge - 1.3 + https://www.hydra-cg.com/spec/latest/core/#references + Web and Internet + Web Development - - BBCFood - BBC Food Ontology (BBCFood) - The Food Ontology is a simple lightweight ontology for publishing data about recipes, including the foods they are made from and the foods they create as well as the diets, menus, seasons, courses and occasions they may be suitable for. Whilst it originates in a specific BBC use case, the Food Ontology should be applicable to a wide range of recipe data publishing across the web. + + GTS + Geologic Timescale model (GTS) + This is an RDF/OWL representation of the GeoSciML Geologic Timescale model, which has been adapted from the model described in Cox, S.J.D, & Richard, S.M. (2005) A formal model for the geologic timescale and GSSP, compatible with geospatial information transfer standards, Geosphere, Geological Society of America. + Simon J D Cox (simon.cox@csiro.au) of CSIRO TTL - 2014/03/18 - Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/food-ontology - News and Media - Food and Beverage - 0.1 + 2020-05-31 + Creative Commons 1.0 + https://raw.githack.com/CGI-IUGS/timescale-ont/master/html/gts.html + Geography + geospatial Information, Geology + 1.0 - - FRBRoo - Functional Requirements for Bibliographic Records - object-oriented (FRBRoo) - The FRBRoo (Functional Requirements for Bibliographic Records - object-oriented) initiative is a joint effort of the CIDOC Conceptual Reference Model and Functional Requirements for Bibliographic Records international working groups to establish a formal ontology intended to capture and represent the underlying semantics of bibliographic information and to facilitate the integration, mediation, and interchange of bibliographic and museum information. + + TimelineOntology + Timeline Ontology (TimelineOntology) + The Timeline Ontology is centered around the notion of timeline, seen here as a way to identify a temporal backbone. A timeline may support a signal, a video, a score, a work, etc. + Christopher Sutton, Yves Raimond, Matthias Mauch RDF - November 2015 + 25th October 2007 + Creative Commons 1.0 + https://github.com/motools/timelineontology + Arts and Humanities + Music Theory + 1.0 + + + NCIt + NCI Thesaurus (NCIt) + NCI Thesaurus (NCIt) is a reference terminology that includes broad coverage of the cancer domain, including cancer related diseases, findings and abnormalities. The NCIt OBO Edition aims to increase integration of the NCIt with OBO Library ontologies. NCIt OBO Edition releases should be considered experimental. + OWL + 2023-10-19 Creative Commons 4.0 - https://ontome.net/namespace/6#summary - Scholarly Knowledge - Bibliographic Records - 2.4 + https://terminology.tib.eu/ts/ontologies/NCIT + Medicine + Cancer, Oncology + 24.04e - - SystemCapabilities - System Capabilities Ontology (SystemCapabilities) - This ontology describes system capabilities, operating ranges, and survival ranges. - W3C/OGC Spatial Data on the Web Working Group + + HPOnt + The Heat Pump Ontology (HPOnt) + The Heat Pump Ontology (HPOnt) aims to formalize and represent all the relevant information of Heat Pumps. The HPOnt has been developed as part of the REACT project which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 824395. + REACT project team OWL - 2017-05-14 - W3C Software and Document License - https://terminology.tib.eu/ts/ontologies/SSNSYSTEM + Creative Commons 4.0 + https://react2020.github.io/REACT-ONTOLOGY/HPOnt/index-en.html/ Materials Science and Engineering - Materials Science, Engineering, Systems + Materials Science + 0.2 + + + GPO + General Process Ontology (GPO) + Basically, this ontology aims to model processes. Processes are holistic perspective elements that transform inputs/educts (matter, energy, information) into output/products (matter, energy, information) with the help of tools (devices, algorithms). They can be decomposed into sub-processes and have predecessor and successor processes. + Simon Stier + TTL + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/General-Process-Ontology/ontology + Materials Science and Engineering + Materials Science + + + GND + Gemeinsame Normdatei (GND) + GND stands for Gemeinsame Normdatei (Integrated Authority File) and offers a broad range of elements to describe authorities. The GND originates from the German library community and aims to solve the name ambiguity problem in the library world. + Alexander Haffner + RDF + 2024-08-26 + Creative Commons 1.0 + https://d-nb.info/standards/elementset/gnd + Library and Cultural Heritage + Authority Files + 1.2.0 - - WiLD - Workflows in Linked Data (WiLD) - Ontology to describe Workflows in Linked Data. - Tobias Käfer + + CHAMEO + Characterisation Methodology Domain Ontology (CHAMEO) + An ontology for materials characterization which represents the evolution of the CHADA template in an ontological form, allowing to generate FAIR documentation of Characterisation Experiments and that has been used as a basis for the development of a number of technique-specific or application-specific ontologies in the materials characterisation domain. CHAMEO has been used as a foundation for the definition of the new CHADA template during the CWA. + https://orcid.org/0000-0002-4181-2852, https://orcid.org/0000-0002-5174-8508, https://orcid.org/0000-0002-9668-6961 TTL - 2020-06-10 - DBpedia License - https://databus.dbpedia.org/ontologies/purl.org/wild--vocab/2020.06.10-210552 - Scholarly Knowledge + 2024-04-12 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/emmo-repo/domain-characterisation-methodology + Materials Science and Engineering Materials Science + 1.0.0 - - SWEET - Semantic Web for Earth and Environment Technology Ontology (SWEET) - The Semantic Web for Earth and Environment Technology Ontology (SWEET) is an investigation in improving discovery and use of Earth science data, through software understanding of the semantics of web resources. SWEET is a collection of ontologies conceptualizing a knowledge space for Earth system science, represented using the web ontology language (OWL). It includes both orthogonal concepts (space, time, Earth realms, physical quantities, etc.) and integrative science knowledge concepts (phenomena, events, etc.). - NASA, JPL, Caltech + + PODO + Point Defects Ontology (PODO) + PODO focuses on the description of point defects in crystalline materials. + https://orcid.org/0000-0001-7564-7990 OWL - July 14, 2022 - Creative Commons 4.0 - https://bioportal.bioontology.org/ontologies/SWEET - Ecology and Environment - Earth Science, Geoscience - 3.6.0 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/OCDO/podo + Materials Science and Engineering + Materials Science + 1.0.0 - - OntoKin - Chemical Kinetics Ontology (OntoKin) - OntoKin is an ontology developed for representing chemical kinetic reaction mechanisms. - IEEE - OWL - 08 February 2022 - Creative Commons 4.0 - https://www.ontologyportal.org/ - Chemistry - 1.0 + + SAREF + Smart Applications REFerence ontology (SAREF) + The Smart Applications REFerence (SAREF) suite of ontologies forms a shared model of consensus intended to enable semantic interoperability between solutions from different providers and among various activity sectors in the Internet of Things (IoT), thus contributing to the development of data spaces. SAREF is published as a set of open standards produced by ETSI Technical Committee Smart Machine-to-Machine communications (SmartM2M). + ETSI Technical Committee Smart Machine-to-Machine communications (SmartM2M) + RDF + 2020-12-31 + https://saref.etsi.org/core/v3.2.1/ + Web and Internet + interoperability + 3.2.1 - - BMO - Building Material Ontology (BMO) - Building Material Ontology defines the main concepts of building material, types, layers, and properties. - Janakiram Karlapudi, Prathap Valluru + + OIEModels + Open Innovation Environment Models (OIEModels) + The models module defines models as semiotic signs that stands for an object by resembling or imitating it, in shape or by sharing a similar logical structure. + Adham Hashibon, Daniele Toti, Emanuele Ghedini, Georg J. Schmitz, Gerhard Goldbeck, Jesper Friis, Pierluigi Del Nostro TTL - 2019-12-10 Creative Commons Attribution 4.0 International (CC BY 4.0) - https://matportal.org/ontologies/BUILDMAT + https://github.com/emmo-repo/OIE-Ontologies/ Materials Science and Engineering Materials - 0.1 - - BTO - BRENDA Tissue Ontology (BTO) - A structured controlled vocabulary for the source of an enzyme comprising tissues, cell lines, cell types and cell cultures. + + CiTO + Citation Typing Ontology (CiTO) + The Citation Typing Ontology (CiTO) is an ontology that enables characterization of the nature or type of citations, both factually and rhetorically. + Silvio Peroni, David Shotton OWL - 2021-10-26 + 2018-02-16 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/BTO - Medicine - Enzyme - 2021-10-26 + https://github.com/SPAROntologies/cito/tree/master/docs/current + Scholarly Knowledge + Scholarly Communication + 2.8.1 - - CopyrightOnto - Copyright Ontology (CopyrightOnto) - The Copyright Ontology tries to formalise the copyright domain as a way to facilitate automated (or computer-supported) copyright management through the whole content value chain, as it is shaped by copyright law. Therefore, it does not focus just on the last step, end-users permissions to consume content, like many rights languages and ontologies do. - Rhizomik + + ONTORULE + Ontology for the Steel Domain (ONTORULE) + This deliverable consists of the ontology developed in ONTORULE for the steel industry use case. It is presented as an attachment to this document as an html document which was generated by SpecGen from the OWL file. The original OWL file is also included. This document describes the different concepts and attributes included in the ontology. For a better understanding of the decisions taken at the time of representing the knowledge in the ontology, the reader is encouraged to also read the document D5.4. + Diego Daz TTL - 2019-09 - Creative Commons 4.0 - https://rhizomik.net/ontologies/copyrightonto/ - Law - Legal Knowledge - - - SIO - Semanticscience Integrated Ontology (SIO) - The semanticscience integrated ontology (SIO) provides a simple, integrated upper level ontology (types, relations) for consistent knowledge representation across physical, processual and informational entities. This project provides foundational support for the Bio2RDF (http://bio2rdf.org) and SADI (http://sadiframework.org) projects. - M. Dumontier - OWL - 03/25/2024 - Creative Commons 4.0 - https://bioportal.bioontology.org/ontologies/SIO - Upper Ontology - Basic - 1.59 + 2010-05-31 + N/A + https://raw.githubusercontent.com/ISE-FIZKarlsruhe/mseo.github.io/master/Ontology_files/ONTORULEsteel.ttl + Materials Science and Engineering + Materials Science - - DBpedia - DBpedia Ontology (DBpedia) - The DBpedia ontology is generated from the manually created specifications in the DBpedia Mappings Wiki. Each release of this ontology corresponds to a new release of the DBpedia dataset, which contains instance data extracted from various language versions of Wikipedia. The DBpedia ontology has evolved into a crowd-sourced effort, resulting in a shallow cross-domain ontology. - DBpedia Maintainers and Contributors - OWL - 2008-11-17 - Creative Commons 3.0 - https://wiki.dbpedia.org/ + + DublinCore + Dublin Core Vocabulary (DublinCore) + The Dublin Core Schema is a small set of vocabulary terms that can be used to describe several kinds of resources. Dublin Core Metadata may be used for multiple purposes, from simple resource description, to combining metadata vocabularies of different metadata standards, to providing interoperability for metadata vocabularies in the Linked Data cloud and Semantic Web implementations. + The Dublin Core Metadata Initiative + RDF + February 17, 2017 + Public Domain + https://bioportal.bioontology.org/ontologies/DC General Knowledge - Knowledge Graph + Metadata + 1.1 - - QUDV - Quantities, Units, Dimensions and Values (QUDV) - The SysML QUDV (Quantities, Units, Dimensions and Values) modelLibrary is specified in a UML/SysML class/block diagram. In order to generalize its potential usage and alignment with other standardization efforts concerning quantities and units, it is of interest to verify that the QUDV model can also be represented in the form of an ontology using a formal ontology definition language. - SysML + + MicroStructures + EMMO-based ontology for microstructures (MicroStructures) + This is intended to be a domain ontology for metallic microstructures, covering aspects like: composition, particles, both stable (primary) and metastable (precipitates), grains, subgrains, grain boundaries & particle free zones (PFZs), texture, dislocations. The aim is to support both microstructure modelling as well as characterisation. OWL - 2009-10-30 - Apache License 2.0 - https://www.omgwiki.org/OMGSysML/doku.php?id=sysml-qudv:qudv_owl + https://github.com/jesper-friis/emmo-microstructure + Materials Science and Engineering + Microstructure + + + OM + Ontology of Units of Measure (OM) + The Ontology of units of Measure (OM) models concepts and relations important to scientific research. It has a strong focus on units, quantities, measurements, and dimensions. It includes, for instance, common units such as the SI units metre and kilogram, but also units from other systems of units such as the mile or nautical mile. For many application areas it includes more specific units and quantities, such as the unit of the Hubble constant or the quantity vaselife. The following application areas are supported by OM: Geometry; Mechanics; Thermodynamics; Electromagnetism; Fluid mechanics; Chemical physics; Photometry; Radiometry and Radiobiology; Nuclear physics; Astronomy and Astrophysics; Cosmology; Earth science; Meteorology; Material science; Microbiology; Economics; Information technology and Typography. + Hajo Rijgersberg, Don Willems, Jan Top + RDF + June 28, 2024 + Creative Commons 4.0 + https://bioportal.bioontology.org/ontologies/OM Units and Measurements - 2009-10-30 + 2.0.57 - - SSN - Semantic Sensor Network Ontology (SSN) - The Semantic Sensor Network (SSN) ontology is an ontology for describing sensors and their observations, the involved procedures, the studied features of interest, the samples used to do so, and the observed properties, as well as actuators. SSN follows a horizontal and vertical modularization architecture by including a lightweight but self-contained core ontology called SOSA (Sensor, Observation, Sample, and Actuator) for its elementary classes and properties. With their different scope and different degrees of axiomatization, SSN and SOSA are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Web of Things. Both ontologies are described below, and examples of their usage are given. - W3C/OGC Spatial Data on the Web Working Group - TTL - 2017-04-17 - http://www.w3.org/Consortium/Legal/2015/copyright-software-and-document - https://github.com/w3c/sdw-sosa-ssn/tree/482484fe2edc1ba8aa7f19214a72bdb77123e833 + + VIMMP + Virtual Materials Marketplace Ontologies (VIMMP) + The Virtual Materials Marketplace (VIMMP) project is developing an open platform for providing and accessing services related to materials modelling. Within VIMMP, a system of marketplace-level ontologies is developed to characterize services, models, and interactions between users; the European Materials and Modelling Ontology (EMMO, recently renamed while keeping the original acronym) is employed as a top-level ontology. The ontologies are used to annotate data that are stored in the ZONTAL Space component of VIMMP and to support the ingest and retrieval of data and metadata at the VIMMP marketplace front-end. + Ilian T. Todorov, Martin Thomas Horsch, Michael A. Seaton, Silvia Chiacchiera + OWL + 2021-01-02 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://matportal.org/ontologies/VIMMP_ONTOLOGIES Materials Science and Engineering - Sensor Networks - 1.0 + Materials Modeling - - TUBES - TUBES System Ontology (TUBES) - The scope of the TUBES System Ontology is to explicitly define interconnected building service system in the AECO industry, their hierarchical subdivisions, structural and functional aspects, and links to spatial entities. As such, TSO supports the effort to represent linkable information in a future semantic web of building data. It has a strong alignment to other ontologies within the W3C community. - Nicolas Pauen + + BIO + BIO: A vocabulary for biographical information (BIO) + The BIO vocabulary contains terms useful for finding out more about people and their backgrounds and has some cross-over into genealogical information. The approach taken is to describe a person's life as a series of interconnected key events, around which other information can be woven. This vocabulary defines the event framework and supplies a set of core event types that cover many use cases, but it is expected that it will be extended in other vocabularies to suit their needs. The intention of this vocabulary is to describe biographical events of people and this intention carries through to the definitions of the properties and classes which are person-centric rather than neutral. For example the Employment event puts the person being employed as the principal agent in the event rather than the employer. + Ian Davis and David Galbraith RDF - 2022-02-01 + 2010-05-10 + Public Domain + https://vocab.org/bio/ + Social Sciences + Biographical Information + 0.1 + + + NMRCV + Nuclear Magnetic Resonance Controlled Vocabulary (NMRCV) + This artefact is an MSI-approved controlled vocabulary primarily developed under COSMOS EU and PhenoMeNal EU governance. The nmrCV is supporting the nmrML XML format with standardized terms. nmrML is a vendor agnostic open access NMR raw data standard. Its primaly role is analogous to the mzCV for the PSI-approved mzML XML format. It uses BFO2.0 as its Top level. This CV was derived from two predecessors (The NMR CV from the David Wishart Group, developed by Joseph Cruz) and the MSI nmr CV developed by Daniel Schober at the EBI. This simple taxonomy of terms (no DL semantics used) serves the nuclear magnetic resonance markup language (nmrML) with meaningful descriptors to amend the nmrML xml file with CV terms. Metabolomics scientists are encouraged to use this CV to annotrate their raw and experimental context data, i.e. within nmrML. The approach to have an exchange syntax mixed of an xsd and CV stems from the PSI mzML effort. The reason to branch out from an xsd into a CV is, that in areas where the terminology is likely to change faster than the nmrML xsd could be updated and aligned, an externally and decentrallised maintained CV can accompensate for such dynamics in a more flexible way. A second reason for this set-up is that semantic validity of CV terms used in an nmrML XML instance (allowed CV terms, position/relation to each other, cardinality) can be validated by rule-based proprietary validators: By means of cardinality specifications and XPath expressions defined in an XML mapping file (an instances of the CvMappingRules.xsd ), one can define what ontology terms are allowed in a specific location of the data model. + Daniel Schober + OWL + 2017-10-19 Creative Commons 4.0 - https://rwth-e3d.github.io/tso/ - Industry - Building Services - 0.3.0 + https://terminology.tib.eu/ts/ontologies/NMRCV + Chemistry + 1.1.0 - - BattINFO - Battery Interface Ontology (BattINFO) - BattINFO is a foundational resource for harmonizing battery knowledge representation and enhancing data interoperability. The primary objective is to provide the necessary tools to create FAIR (Findable, Accessible, Interoperable, Reusable) battery data that can be integrated into the Semantic Web. + + MDS + Materials Data Science Ontology (MDS) + Materials Data Science (MDS) is an ontology encompassing multiple domains relevant to materials science, chemical synthesis and characterizations, photovoltaics and geospatial datasets. The terms used for classes, subclasses and instances are mapped to PMDCo and BFO Ontologies. + SDLE Research Center TTL - https://github.com/BIG-MAP/BattINFO + 03/24/2024 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://matportal.org/ontologies/MDS Materials Science and Engineering Materials Science + 0.3.0.0 + + + TribAIn + Tribology and Artificial Intelligence Ontology (TribAIn) + TribAIn is an ontology for the description of tribological experiments and their results. It is designed to be used in the context of the TribAIn project, which aims to develop a knowledge-based system for the design of tribological systems. + Patricia Kügler + TTL + Creative Commons 4.0 + https://github.com/snow0815/tribAIn + Scholarly Knowledge - - SUMO - Suggested Upper Merged Ontology (SUMO) - The Suggested Upper Merged Ontology (SUMO) and its domain ontologies form the largest formal public ontology in existence today. They are being used for research and applications in search, linguistics and reasoning. SUMO is the only formal ontology that has been mapped to all of the WordNet lexicon. + + PeriodicTable + Periodic Table of the Elements Ontology (PeriodicTable) + PeriodicTable.owl is a representation of the Periodic Table of the Elements in the OWL Web Ontology Language. It provides reference data to support Semantic Web applications in chemistry and related disciplines. + Michael Cook OWL - 2025-02-17 - Creative Commons 4.0 - https://www.ontologyportal.org/ - Upper Ontology - 1.0 + 2004/02/05 + https://www.daml.org/2003/01/periodictable/ + Materials Science and Engineering + Periodic Table of Elements + 1.10 LDO @@ -1066,67 +836,211 @@ Materials Defects 1.0.0 - - Nomisma - Nomisma Ontology (Nomisma) - Nomisma Ontology is a collaborative project to provide stable digital representations of numismatic concepts according to the principles of Linked Open Data. These take the form of http URIs that provide access to the information about a concept in various formats. The project is a collaborative effort of the American Numismatic Society and the Institute for the Study of the Ancient World at New York University. - American Numismatic Society, Institute for the Study of the Ancient World + + BBCBusiness + BBC Business News Ontology (BBCBusiness) + The Business News Ontology describes the concepts that occur in BBC business news. + https://www.bbc.co.uk/blogs/internet/authors/Jeremy_Tarling, https://uk.linkedin.com/in/amaalmohamed TTL - 2025-01-22 + 2014-11-09 Creative Commons 4.0 - https://www.dainst.org/forschung/projekte/noslug/2098 - Arts and Humanities - Numismatics + https://www.bbc.co.uk/ontologies/business-news-ontology + News and Media + Business News + 0.5 - - EDAM - The ontology of data analysis and management (EDAM) - EDAM is a domain ontology of data analysis and data management in bio- and other sciences, and science-based applications. It comprises concepts related to analysis, modelling, optimisation, and data life cycle. Targetting usability by diverse users, the structure of EDAM is relatively simple, divided into 4 main sections: Topic, Operation, Data (incl. Identifier), and Format. - Federico Bianchini, Hervé Ménager, Jon Ison, Matúš Kalaš + + SWEET + Semantic Web for Earth and Environment Technology Ontology (SWEET) + The Semantic Web for Earth and Environment Technology Ontology (SWEET) is an investigation in improving discovery and use of Earth science data, through software understanding of the semantics of web resources. SWEET is a collection of ontologies conceptualizing a knowledge space for Earth system science, represented using the web ontology language (OWL). It includes both orthogonal concepts (space, time, Earth realms, physical quantities, etc.) and integrative science knowledge concepts (phenomena, events, etc.). + NASA, JPL, Caltech OWL - 24.09.2024 + July 14, 2022 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/edam - General Knowledge - General - 1.25-20240924T0027Z-unstable(1.26) + https://bioportal.bioontology.org/ontologies/SWEET + Ecology and Environment + Earth Science, Geoscience + 3.6.0 - - CIFCore - Crystallographic Information Framework Core Dictionary (CIFCore) - (1) to explain the historical development of CIF dictionaries to define in a machine-actionable manner the contents of data files covering various aspects of crystallography and related structural sciences; (2) to demonstrate some of the more complex types of information that can be handled with this approach. + + LexInfo + LexInfo (LexInfo) + LexInfo allows us to associate linguistic information to elements in an ontology with respect to any level of linguistic description and expressivity. LexInfo has been implemented as an OWL ontology and is available together with an API. + RDF + Apache 2.0 + https://lexinfo.net/index.html + Scholarly Knowledge + Linguistics + 3.0 + + + NanoMine + NanoMine Ontology (NanoMine) + Polymer Nanocomposites based ontology which enable researchers to develop and test broad-reaching hypotheses about how inter-relationships between different materials processing methods and composition result in specific changes in material properties. TTL - May 24, 2023 + APACHE 2.0 + https://github.com/tetherless-world/nanomine-ontology + Materials Science and Engineering + Materials Science + + + MAMBO + Molecules And Materials Basic Ontology (MAMBO) + MAMBO (Molecules And Materials Basic Ontology) is a domain ontology for molecular materials. Its main targets are: Allowing the retrieval of structured information regarding molecular materials and related applications (i.e. devices based on molecular materials) Supporting the development of new, complex workflows for modelling systems based on molecular materials (computational modelling and data-driven techniques) Integrating data generated via computational simulations and empirical experiments. + OWL + General Public License v3.0 (GPL-3.0) + https://github.com/daimoners/MAMBO + Materials Science and Engineering + Materials Science + + + PRIMA + PRovenance Information in MAterials science (PRIMA) + An ontology that captures the provenance information in the materials science domain. + Ahmad Zainul Ihsan, Mehrdad Jalali, Rossella Aversa + TTL + 2024-01-29 + Creative Commons Attribution 3.0 Unported (CC BY 3.0) + https://materials-data-science-and-informatics.github.io/MDMC-NEP-top-level-ontology/PRIMA/complete/ver_2_0/index.html + Materials Science and Engineering + Materials Science + 2.0 + + + Photovoltaics + EMMO Domain Ontology for Photovoltaics (Photovoltaics) + This ontology is describing Perovskite solar cells. + Casper Welzel Andersen, Simon Clark + TTL + Creative Commons license Attribution 4.0 International (CC BY 4.0) + https://github.com/emmo-repo/domain-photovoltaics + Materials Science and Engineering + Materials Science + 0.0.1 + + + PMDco + The Platform MaterialDigital core ontology (PMDco) + The PMD Core Ontology (PMDco) is a comprehensive framework for representing knowledge that encompasses fundamental concepts from the domains of materials science and engineering (MSE). The PMDco has been designed as a mid-level ontology to establish a connection between specific MSE application ontologies and the domain neutral concepts found in established top-level ontologies. The primary goal of the PMDco is to promote interoperability between diverse domains. + Jannis Grundmann + OWL + 2025-03-20 Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/CIF-ontology?tab=readme-ov-file + https://github.com/materialdigital/core-ontology?tab=readme-ov-file Materials Science and Engineering Materials Science - 0.1.0 + 3.0.0-alpha1 - - LODE - Linking Open Descriptions of Events (LODE) - People conventionally refer to an action or occurrence taking place at a certain time at a specific location as an event. This notion is potentially useful for connecting individual facts recorded in the rapidly growing collection of linked data sets and for discovering more complex relationships between data. The LODE provide an overview and comparison of existing event models, looking at the different choices they make of how to represent events. It is a model for publishing records of events as Linked Data. A tools for populating this model and a prototype “event directory” web service, which can be used to locate stable URIs for events that have occurred, provide RDFS+OWL descriptions and link to related resources. - Ryan Shaw + + DBO + Digital Buildings Ontology (DBO) + The Digital Buildings ontology (DBO) is used by Google to represent structured information about buildings and building-installed equipment. + Google RDF - 2020-10-31 - Creative Commons Attribution 3.0 - https://linkedevents.org/ontology/ - Events - 2020-10-31 + 02/23/2023 + Apache 2.0 + https://github.com/google/digitalbuildings?tab=readme-ov-file + Industry + Building Information + 0.0.1 - - BBCStoryline - BBC Storyline Ontology (BBCStoryline) - The News Storyline Ontology is a generic model for describing and organising the stories news organisations tell. The ontology is intended to be flexible to support any given news or media publisher's approach to handling news stories. At the heart of the ontology, is the concept of Storyline. As a nuance of the English language the word 'story' has multiple meanings. In news organisations, a story can be an individual piece of content, such as an article or news report. It can also be the editorial view on events occurring in the world. - http://uk.linkedin.com/in/paulwilton, http://www.bbc.co.uk/blogs/internet/authors/Jeremy_Tarling, http://uk.linkedin.com/in/jarredmcginnis + + DCAT + Data Catalog Vocabulary (DCAT) + Data Catalog Vocabulary (DCAT) is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. This document defines the schema and provides examples for its use. DCAT enables a publisher to describe datasets and data services in a catalog using a standard model and vocabulary that facilitates the consumption and aggregation of metadata from multiple catalogs. This can increase the discoverability of datasets and data services. It also makes it possible to have a decentralized approach to publishing data catalogs and makes federated search for datasets across catalogs in multiple sites possible using the same query mechanism and structure. Aggregated DCAT metadata can serve as a manifest file as part of the digital preservation process. + Digital Enterprise Research Institute (DERI) + RDF + 22 August 2024 + W3C Document License + https://www.w3.org/TR/vocab-dcat-3/ + Scholarly Knowledge + Data Catalogs + 3.0 + + + GEO + Geographical Entities Ontology (GEO) + Geographical Entities Ontology (GEO) is an inventory of geopolitical entities (such as sovereign states and their administrative subdivisions) as well as various geographical regions (including but not limited to the specific ones over which the governments have jurisdiction) + William R Hogan + OWL + 2019-02-17 + Creative Commons 4.0 + https://github.com/mcwdsi/geographical-entity-ontology/blob/master/geo-all.owl + Geography + Geographic Knowledge + + + BioPAX + Biological Pathways Exchange (BioPAX) + BioPAX is a standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. Specifically, BioPAX supports data exchange between pathway data groups and thus reduces the complexity of interchange between data formats by providing an accepted standard format for pathway data. + OWL + 16 April 2015 + http://www.biopax.org/ + Biology and Life Sciences + Bioinformatics + 1.0 + + + Contact + Contact Ontology (Contact) + Ontology to capture concepts related to contact information (addresses, phone numbers). Reuses the iContact Ontology developed by the Enterprise Integration Lab in Toronto. The iContact ontology is extended to introduce a specialized definition of Hours of Operation, defined as a subclass of both the iContact definition of hours of operation, and a subclass of the Recurring Event class defined in the iCity Recurring Event ontology. The Contact ontology also extends the definition of address to include an associated location. + Mark Fox, Megan Katsumi + RDF + 2018-07-06 + https://enterpriseintegrationlab.github.io/icity/Contact/Contact_1.0/doc/index-en.html + Social Sciences + Social + 1.0 + + + MO + Microscopy Ontology (MO) + The Microscopy Ontology (MO) extends the ontological framework of the PMDco. The MO facilitates semantic integration and the interoperable connection of diverse data sources from the fields of microscopy and microanalysis. Consequently, the MO paves the way for new, adaptable data applications and analyses across various experiments and studies + https://orcid.org/0000-0002-3717-7104,https://orcid.org/0000-0002-7094-5371 TTL - 2013-05-01 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/materialdigital/microscopy-ontology?tab=readme-ov-file + Biology and Life Sciences + Microscopy + 2.0 + + + EURIO + EUropean Research Information Ontology (EURIO) + EURIO (EUropean Research Information Ontology) conceptualises, formally encodes and makes available in an open, structured and machine-readable format data about resarch projects funded by the EU's framework programmes for research and innovation. + Publications Office of the European Commission + RDF + 2023-10-19 Creative Commons 4.0 - https://iptc.org/thirdparty/bbc-ontologies/storyline.html + https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurio + Scholarly Knowledge + Research Information + 2.4 + + + Common + Common Ontology (Common) + Ontology for the representation of commons elements in the Trias ontology + Jhon Toledo, Miguel Angel García, Oscar Corcho + RDF + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://w3id.org/mobility/trias/common/0.1.0 + Education + Computer Science + 0.1.0 + + + BBCWildlife + BBC Wildlife Ontology (BBCWildlife) + A simple vocabulary for describing biological species and related taxa. The vocabulary defines terms for describing the names and ranking of taxa, as well as providing support for describing their habitats, conservation status, and behavioural characteristics, etc. + https://www.ldodds.com#me, http://tomscott.name/ + TTL + 2013/12/18 + Creative Commons 4.0 + https://www.bbc.co.uk/ontologies/wildlife-ontology News and Media - Storyline - 0.3 + Wildlife + 1.1 UO @@ -1139,183 +1053,238 @@ https://bioportal.bioontology.org/ontologies/UO Units and Measurements - - Contact - Contact Ontology (Contact) - Ontology to capture concepts related to contact information (addresses, phone numbers). Reuses the iContact Ontology developed by the Enterprise Integration Lab in Toronto. The iContact ontology is extended to introduce a specialized definition of Hours of Operation, defined as a subclass of both the iContact definition of hours of operation, and a subclass of the Recurring Event class defined in the iCity Recurring Event ontology. The Contact ontology also extends the definition of address to include an associated location. - Mark Fox, Megan Katsumi - RDF - 2018-07-06 - https://enterpriseintegrationlab.github.io/icity/Contact/Contact_1.0/doc/index-en.html - Social Sciences - Social - 1.0 - - - MOLBRINELL - MatoLab Brinell Test Ontology (MOL_BRINELL) - An ontology for describing the Brinell hardness testing process, made in the Materials Open Lab Project. - Birgit Skrotzki, Hossein Beygi Nasrabadi, Philipp von Hartrott, Vinicius Carrillo Beber, Yue Chen - TTL - 05/05/2022 - https://matportal.org/ontologies/MOL_BRINELL - Materials Science and Engineering - Materials Testing - 0.1 - - - GND - Gemeinsame Normdatei (GND) - GND stands for Gemeinsame Normdatei (Integrated Authority File) and offers a broad range of elements to describe authorities. The GND originates from the German library community and aims to solve the name ambiguity problem in the library world. - Alexander Haffner - RDF - 2024-08-26 - Creative Commons 1.0 - https://d-nb.info/standards/elementset/gnd - Library and Cultural Heritage - Authority Files - 1.2.0 + + ChEBI + Chemical Entities of Biological Interest (ChEBI) + Chemical Entities of Biological Interest (ChEBI) is a dictionary of molecular entities focused on ‘small’ chemical compounds. The term ‘molecular entity’ refers to any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. The molecular entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms. ChEBI incorporates an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. + OWL + 01/01/2025 + Creative Commons 4.0 + https://www.ebi.ac.uk/chebi/ + Chemistry + Chemical Entities + 239 - - FOAF - Friend of a Friend (FOAF) - FOAF is a project devoted to linking people and information using the Web. Regardless of whether information is in people's heads, in physical or digital documents, or in the form of factual data, it can be linked. - Dan Brickley, Libby Miller + + GIST + GIST Upper Ontology (GIST) + Gist is Semantic Arts' minimalist upper ontology for the enterprise. It is designed to have the maximum coverage of typical business ontology concepts with the fewest number of primitives and the least amount of ambiguity. + Semantic Arts RDF - 14 January 2014 - Creative Commons - http://xmlns.com/foaf/0.1/ - Social Sciences - Social - 0.1 + 2024-Feb-27 + Creative Commons 4.0 + https://semanticarts.com/gist + General Knowledge + Upper Ontology + 12.1.0 - - MAMBO - Molecules And Materials Basic Ontology (MAMBO) - MAMBO (Molecules And Materials Basic Ontology) is a domain ontology for molecular materials. Its main targets are: Allowing the retrieval of structured information regarding molecular materials and related applications (i.e. devices based on molecular materials) Supporting the development of new, complex workflows for modelling systems based on molecular materials (computational modelling and data-driven techniques) Integrating data generated via computational simulations and empirical experiments. + + CDCO + Crystallographic Defect Core Ontology (CDCO) + CDCO defines the common terminology shared across all types of crystallographic defects, providing a unified framework for data integration in materials science. + https://orcid.org/0000-0001-7564-7990 OWL - General Public License v3.0 (GPL-3.0) - https://github.com/daimoners/MAMBO + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/OCDO/cdco Materials Science and Engineering Materials Science + 1.0.0 - - MDO - Materials Design Ontology (MDO) - MDO is an ontology for materials design field, representing the domain knowledge specifically related to solid-state physics and computational materials science. - Materials Design Division, National Institute for Materials Science (NIMS) + + SWO + Software Ontology (SWO) + The Software Ontology (SWO) is a resource for describing software tools, their types, tasks, versions, provenance and associated data. It contains detailed information on licensing and formats as well as software applications themselves, mainly (but not limited) to the bioinformatics community. + Allyson Lister, Andy Brown, Duncan Hull, Helen Parkinson, James Malone, Jon Ison, Nandini Badarinarayan, Robert Stevens OWL - 2022-08-02 + 2013-07-01 Creative Commons 4.0 - https://github.com/LiUSemWeb/Materials-Design-Ontology/tree/master/ - Materials Science and Engineering - Materials Design - 1.1 + https://terminology.tib.eu/ts/ontologies/SWO + Scholarly Knowledge + Software + 1.0 - - HPOnt - The Heat Pump Ontology (HPOnt) - The Heat Pump Ontology (HPOnt) aims to formalize and represent all the relevant information of Heat Pumps. The HPOnt has been developed as part of the REACT project which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 824395. - REACT project team + + FoodOn + Food Ontology (FoodON) + FoodOn, the food ontology, contains vocabulary for naming food materials and their anatomical and taxonomic origins, from raw harvested food to processed food products, for humans and domesticated animals. It provides a neutral and ontology-driven standard for government agencies, industry, nonprofits and consumers to name and reference food products and their components throughout the food supply chain. OWL + 2025-01-16 Creative Commons 4.0 - https://react2020.github.io/REACT-ONTOLOGY/HPOnt/index-en.html/ - Materials Science and Engineering - Materials Science - 0.2 - - - PTO - Product Types Ontology (PTO) - The Product Types Ontology is designed to be used in combination with GoodRelations, a standard vocabulary for the commercial aspects of offers. - Martin Hepp - RDF - 2025-02-21 - Creative Commons 3.0 - http://www.productontology.org/ - Industry - 1.0 + http://purl.obolibrary.org/obo/foodon.owl + Agriculture + Diet, Metabolomics, and Nutrition - - VIMMP - Virtual Materials Marketplace Ontologies (VIMMP) - The Virtual Materials Marketplace (VIMMP) project is developing an open platform for providing and accessing services related to materials modelling. Within VIMMP, a system of marketplace-level ontologies is developed to characterize services, models, and interactions between users; the European Materials and Modelling Ontology (EMMO, recently renamed while keeping the original acronym) is employed as a top-level ontology. The ontologies are used to annotate data that are stored in the ZONTAL Space component of VIMMP and to support the ingest and retrieval of data and metadata at the VIMMP marketplace front-end. - Ilian T. Todorov, Martin Thomas Horsch, Michael A. Seaton, Silvia Chiacchiera + + SIO + Semanticscience Integrated Ontology (SIO) + The semanticscience integrated ontology (SIO) provides a simple, integrated upper level ontology (types, relations) for consistent knowledge representation across physical, processual and informational entities. This project provides foundational support for the Bio2RDF (http://bio2rdf.org) and SADI (http://sadiframework.org) projects. + M. Dumontier OWL - 2021-01-02 - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://matportal.org/ontologies/VIMMP_ONTOLOGIES - Materials Science and Engineering - Materials Modeling + 03/25/2024 + Creative Commons 4.0 + https://bioportal.bioontology.org/ontologies/SIO + Upper Ontology + Basic + 1.59 - - GTS - Geologic Timescale model (GTS) - This is an RDF/OWL representation of the GeoSciML Geologic Timescale model, which has been adapted from the model described in Cox, S.J.D, & Richard, S.M. (2005) A formal model for the geologic timescale and GSSP, compatible with geospatial information transfer standards, Geosphere, Geological Society of America. - Simon J D Cox (simon.cox@csiro.au) of CSIRO + + CCO + Common Core Ontologies (CCO) + The Common Core Ontologies (CCO) is a widely-used suite of eleven ontologies that consist of logically well-defined generic terms and relations among them reflecting entities across all domains of interest. TTL - 2020-05-31 - Creative Commons 1.0 - https://raw.githack.com/CGI-IUGS/timescale-ont/master/html/gts.html - Geography - geospatial Information, Geology - 1.0 + 2024-11-06 + BSD-3-Clause license + https://github.com/CommonCoreOntology/CommonCoreOntologies + General Knowledge + General + 2.0 - - OWLTime - Time Ontology in OWL (OWL-Time) - OWL-Time is an OWL-2 DL ontology of temporal concepts, for describing the temporal properties of resources in the world or described in Web pages. The ontology provides a vocabulary for expressing facts about topological (ordering) relations among instants and intervals, together with information about durations, and about temporal position including date-time information. Time positions and durations may be expressed using either the conventional (Gregorian) calendar and clock, or using another temporal reference system such as Unix-time, geologic time, or different calendars. - World Wide Web Consortium + + BBCPolitics + BBC Politics News Ontology (BBCPolitics) + The Politics Ontology describes the concepts that occur in BBC politics news. + https://www.r4isstatic.com/ TTL - 15 November 2022 - W3C Software Notice and Document License - https://www.w3.org/TR/owl-time/ - Units and Measurements - Temporal Reasoning - 1.0 + 2014-01-06 + Creative Commons 4.0 + https://www.bbc.co.uk/ontologies/politics-ontology + News and Media + Politics + 0.9 - - BioPAX - Biological Pathways Exchange (BioPAX) - BioPAX is a standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. Specifically, BioPAX supports data exchange between pathway data groups and thus reduces the complexity of interchange between data formats by providing an accepted standard format for pathway data. + + BBCSport + BBC Sport Ontology (BBCSport) + The Sport Ontology is a simple lightweight ontology for publishing data about competitive sports events. The terms in this ontology allow data to be published about: The structure of sports tournaments as a series of eventsThe competing of agents in a competitionThe type of discipline a event involvesThe award associated with the competition and how received it...etc Whilst it originates in a specific BBC use case, the Sport Ontology should be applicable to a wide range of competitive sporting events data publishing use cases. Care has been taken to try and ensure interoperability with more general ontologies in use. In particular, it draws heavily upon the events ontology. + https://uk.linkedin.com/pub/jem-rayfield/27/b19/757, https://uk.linkedin.com/in/paulwilton, https://www.blockslabpillar.com, https://www.linkedin.com/in/tfgrahame, https://uk.linkedin.com/pub/stuart-williams/8/684/351, https://uk.linkedin.com/in/brianwmcbride + TTL + Creative Commons 4.0 + https://www.bbc.co.uk/ontologies/sport-ontology + News and Media + Sport + 3.2 + + + BBCFood + BBC Food Ontology (BBCFood) + The Food Ontology is a simple lightweight ontology for publishing data about recipes, including the foods they are made from and the foods they create as well as the diets, menus, seasons, courses and occasions they may be suitable for. Whilst it originates in a specific BBC use case, the Food Ontology should be applicable to a wide range of recipe data publishing across the web. + TTL + 2014/03/18 + Creative Commons 4.0 + https://www.bbc.co.uk/ontologies/food-ontology + News and Media + Food and Beverage + 0.1 + + + SPDocument + SMART Protocols Ontology: Document Module (SP-Document) + SMART Protocols Ontology: Document Module is an ontology designed to represent metadata used to report an experimental protocol. + http://oxgiraldo.wordpress.com OWL - 16 April 2015 - http://www.biopax.org/ - Biology and Life Sciences - Bioinformatics + 2013-07-01 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/SMARTProtocols/SMART-Protocols + Scholarly Knowledge + Materials Science + 4.0 + + + AIISO + Academic Institution Internal Structure Ontology (AIISO) + The Academic Institution Internal Structure Ontology (AIISO) provides classes and properties to describe the internal organizational structure of an academic institution. AIISO is designed to work in partnership with Participation (http://purl.org/vocab/participation/schema), FOAF (http://xmlns.com/foaf/0.1/) and aiiso-roles (http://purl.org/vocab/aiiso-roles/schema) to describe the roles that people play within an institution. + Open University + RDF + 2008-05-14 + Creative Commons 4.0 + https://vocab.org/aiiso/ + Scholarly Knowledge + Academic Institution 1.0 - - Atomistic - Atomistic Ontology (Atomistic) - An EMMO-based domain ontology for atomistic and electronic modelling. - Francesca L. Bleken, Jesper Friis + + FIX + FIX Ontology (FIX) + An ontology of physico-chemical methods and properties. + OWL + 2020-04-13 + https://terminology.tib.eu/ts/ontologies/FIX + Chemistry + Chemicals, Properties + 2020-04-13 + + + BattINFO + Battery Interface Ontology (BattINFO) + BattINFO is a foundational resource for harmonizing battery knowledge representation and enhancing data interoperability. The primary objective is to provide the necessary tools to create FAIR (Findable, Accessible, Interoperable, Reusable) battery data that can be integrated into the Semantic Web. TTL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/domain-atomistic + https://github.com/BIG-MAP/BattINFO Materials Science and Engineering Materials Science - 0.0.2 - - LexInfo - LexInfo (LexInfo) - LexInfo allows us to associate linguistic information to elements in an ontology with respect to any level of linguistic description and expressivity. LexInfo has been implemented as an OWL ontology and is available together with an API. + + MOLTENSILE + Matolab Tensile Test Ontology (MOL_TENSILE) + An ontology for describing the tensile test process, made in the Materials Open Lab Project. + Markus Schilling, markus.schilling@bam.de; Philipp von Hartrott, philipp.von.hartrott@iwm.fraunhofer.de RDF - Apache 2.0 - https://lexinfo.net/index.html + 04/16/2021 + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://matportal.org/ontologies/MOL_TENSILE + Materials Science and Engineering + Materials Testings + 0.4 + + + MOP + Molecular Process Ontology (MOP) + MOP is the molecular process ontology. It contains the molecular processes that underlie the name reaction ontology RXNO, for example cyclization, methylation and demethylation. + OWL + 2022-05-11 + Creative Commons 4.0 + https://terminology.tib.eu/ts/ontologies/MOP + Chemistry + Chemistry, Molecular Biology + 2022-05-11 + + + EDAM + The ontology of data analysis and management (EDAM) + EDAM is a domain ontology of data analysis and data management in bio- and other sciences, and science-based applications. It comprises concepts related to analysis, modelling, optimisation, and data life cycle. Targetting usability by diverse users, the structure of EDAM is relatively simple, divided into 4 main sections: Topic, Operation, Data (incl. Identifier), and Format. + Federico Bianchini, Hervé Ménager, Jon Ison, Matúš Kalaš + OWL + 24.09.2024 + Creative Commons 4.0 + https://terminology.tib.eu/ts/ontologies/edam + General Knowledge + General + 1.25-20240924T0027Z-unstable(1.26) + + + Metadata4Ing + Metadata for Intelligent Engineering (Metadata4Ing) + The ontology Metadata4Ing provides a framework for the semantic description of research data and of the whole data generation process, embracing the object of investigation, all sample and data manipulation methods and tools, the data files themselves, and the roles of persons and institutions. The structure and application of the ontology are based on the principles of modularity and inheritance. + Metadata4Ing Workgroup + TTL + 2025-03-10 + Creative Commons 4.0 + https://git.rwth-aachen.de/nfdi4ing/metadata4ing/metadata4ing Scholarly Knowledge - Linguistics - 3.0 + Materials Science + 1.3.1 - - Wine - Wine Ontology (Wine) - A project to define an RDF style ontology for wines and the wine-industry + + SIOC + Semantically-Interlinked Online Communities (SIOC) + The SIOC (Semantically-Interlinked Online Communities) Ontology is an ontology for describing the information in online communities. This includes sites that support online discussions, blogging, file sharing, photo sharing, social networking, etc. + Data Science Institute, NUI Galway RDF - https://github.com/UCDavisLibrary/wine-ontology - Food and Beverage - Wine + 2018/02/28 + Creative Commons 3.0 + http://rdfs.org/sioc/spec/ + Social Sciences + Social Networks + 1.36 Conference @@ -1329,109 +1298,224 @@ Events Conferences - - DOID - Human Disease Ontology (DOID) - The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts. - The Open Biological and Biomedical Ontology Foundry + + OEO + The Open Energy Ontology (OEO) + The Open Energy Ontology (OEO) is a domain ontology of the energy system analysis context. It is developed as part of the Open Energy Family. The OEO is published on GitHub under an open source license. The language used is the Manchester OWL Syntax, which was chosen because it is user-friendly for editing and viewing differences of edited files. The OEO is constantly being extended. The first version of the OEO has been released on June 11th 2020. A Steering Committee (OEO-SC) was created to accompany the development, increase awareness of the ontology and include it in current projects. OWL - 2024-12-18 - Creative Commons 1.0 - http://purl.obolibrary.org/obo/doid/releases/2024-12-18/doid.owl - Medicine - Human Diseases + 03/2025 + Creative Commons Attribution 1.0 Generic (CC BY 1.0) + https://github.com/OpenEnergyPlatform/ontology?tab=readme-ov-file + Ecology and Environment + Energy + 2.7.0 - - TribAIn - Tribology and Artificial Intelligence Ontology (TribAIn) - TribAIn is an ontology for the description of tribological experiments and their results. It is designed to be used in the context of the TribAIn project, which aims to develop a knowledge-based system for the design of tribological systems. - Patricia Kügler + + SSN + Semantic Sensor Network Ontology (SSN) + The Semantic Sensor Network (SSN) ontology is an ontology for describing sensors and their observations, the involved procedures, the studied features of interest, the samples used to do so, and the observed properties, as well as actuators. SSN follows a horizontal and vertical modularization architecture by including a lightweight but self-contained core ontology called SOSA (Sensor, Observation, Sample, and Actuator) for its elementary classes and properties. With their different scope and different degrees of axiomatization, SSN and SOSA are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Web of Things. Both ontologies are described below, and examples of their usage are given. + W3C/OGC Spatial Data on the Web Working Group TTL + 2017-04-17 + http://www.w3.org/Consortium/Legal/2015/copyright-software-and-document + https://github.com/w3c/sdw-sosa-ssn/tree/482484fe2edc1ba8aa7f19214a72bdb77123e833 + Materials Science and Engineering + Sensor Networks + 1.0 + + + MMO + Materials Mechanics Ontology (MMO) + The materials mechanics ontology is an application-level ontology that was created for supporting named entity recognition tasks for materials fatigue domain. The ontology covers some fairly general MSE concepts that could prospectively be merged into PMDco or other upper materials ontologies such as descriptions of crystallographic defects and microstructural entities. Furthermore, concepts related to the materials fatigue subdomain are also heavily incorporated. + Akhil Thomas, Ali Riza Durmaz + RDF + 2024-01-30 Creative Commons 4.0 - https://github.com/snow0815/tribAIn + https://iwm-micro-mechanics-public.pages.fraunhofer.de/ontologies/materials-mechanics-ontology/index-en.html + Materials Science and Engineering Scholarly Knowledge + 1.0.1 - - AUTO - Automotive Ontology (AUTO) - The AUTOMOTIVE ONTOLOGY (AUTO) defines the shared conceptual structures in the automotive industry. It is an OWL ontology. It is built upon the auto schema.org extension created by the W3C Automotive Ontology Community Group. AUTO's development process follows the best practices established by the EDMC FIBO Community. - EDM Council - RDF - 2021-03-01 - MIT - https://github.com/edmcouncil/auto/tree/master - Industry - Automotive + + BBCProgrammes + BBC Programmes Ontology (BBCProgrammes) + This ontology aims at providing a simple vocabulary for describing programmes. It covers brands, series (seasons), episodes, broadcast events, broadcast services,etc. Its development was funded by the BBC, and is heavily grounded on previous programmes data modelling work done there. + https://moustaki.org/foaf.rdf#moustaki + TTL + 2009/02/20 + Creative Commons 4.0 + https://www.bbc.co.uk/ontologies/programmes-ontology + News and Media + Programmes + 1.1 - - PreMOn - Pre-Modern Ontology (PreMOn) - The PreMOn Ontology is an extension of lemon (W3C Ontology Lexicon Community Group, 2015) for representing predicate models and their mappings. The Core Module of the PreMOn Ontology defines the main abstractions for modelling semantic classes with their semantic roles, mappings between different predicate models, and annotations. - Francesco Corcoglioniti, Marco Rospocher <https://dkm.fbk.eu/rospocher> + + FAIR + FAIR Vocabulary (FAIR) + This is the formal vocabulary (ontology) describing the FAIR principles. OWL - 2018-02-15 Creative Commons 4.0 - https://premon.fbk.eu/ontology/core# + https://terminology.tib.eu/ts/ontologies/FAIR + Upper Ontology + Data, Metadata + + + EXPO + Ontology of Scientific Experiments (EXPO) + Formalise generic knowledge about scientific experimental design, methodology, and results representation. + OWL + Academic Free License (AFL) + https://expo.sourceforge.net/ Scholarly Knowledge - Linguistics - 2018a + Scientific Experiments - - MicroStructures - EMMO-based ontology for microstructures (MicroStructures) - This is intended to be a domain ontology for metallic microstructures, covering aspects like: composition, particles, both stable (primary) and metastable (precipitates), grains, subgrains, grain boundaries & particle free zones (PFZs), texture, dislocations. The aim is to support both microstructure modelling as well as characterisation. + + ICON + Icon Ontology (ICON) + The ICON ontology deals with high granularity art interpretation. It was developed by conceptualizing Panofsky's theory of levels of interpretation, therefore artworks can be described according to Pre-iconographical, Iconographical and Iconological information. + Knowledge Media Institute OWL - https://github.com/jesper-friis/emmo-microstructure + April 26th, 2024 + Creative Commons 4.0 + https://w3id.org/icon/ontology/ + Arts and Humanities + Art History, Cultural Heritage + 2.1.0 + + + MatWerk + NFDI MatWerk Ontology (MatWerk) + NFDI-MatWerk aims to establish a digital infrastructure for Materials Science and Engineering (MSE), fostering improved data sharing and collaboration. This repository provides comprehensive documentation for NFDI MatWerk Ontology (MWO) v3.0, a foundational framework designed to structure research data and enhance interoperability within the MSE community. To ensure compliance with top-level ontology standards, MWO v3.0 is aligned with the Basic Formal Ontology (BFO) and incorporates the modular approach of the NFDIcore mid-level ontology, enriching metadata through standardized classes and properties. The MWO addresses key aspects of MSE research data, including the NFDI-MatWerk community structure, covering task areas, infrastructure use cases, projects, researchers, and organizations. It also describes essential NFDI resources, such as software, workflows, ontologies, publications, datasets, metadata schemas, instruments, facilities, and educational materials. Additionally, MWO represents NFDI-MatWerk services, academic events, courses, and international collaborations. As the foundation for the MSE Knowledge Graph, MWO facilitates efficient data integration and retrieval, promoting collaboration and knowledge representation across MSE domains. This digital transformation enhances data discoverability, reusability, and accelerates scientific exchange, innovation, and discoveries by optimizing research data management and accessibility. + Hossein Beygi Nasrabadi, Jörg Waitelonis, Ebrahim Norouzi, Kostiantyn Hubaiev, Harald Sack + TTL + 2025-03-01 + Creative Commons 1.0 + https://github.com/ISE-FIZKarlsruhe/mwo?tab=readme-ov-file Materials Science and Engineering - Microstructure + Research Data, Interoperability + 3.0.0 - - FIX - FIX Ontology (FIX) - An ontology of physico-chemical methods and properties. - OWL - 2020-04-13 - https://terminology.tib.eu/ts/ontologies/FIX - Chemistry - Chemicals, Properties - 2020-04-13 + + DOAP + The Description of a Project vocabulary (DOAP) + The Description of a Project vocabulary (DOAP), described using W3C RDF Schema and the Web Ontology Language to describe software projects, and in particular open source projects. + Edd Wilder-James + RDF + 2020-04-03 + Apache License 2.0 + https://github.com/ewilderj/doap/blob/master/schema/doap.rdf + Industry + Software - - CDCO - Crystallographic Defect Core Ontology (CDCO) - CDCO defines the common terminology shared across all types of crystallographic defects, providing a unified framework for data integration in materials science. - https://orcid.org/0000-0001-7564-7990 + + OPMW + Open Provenance Model for Workflows (OPMW) + The Open Provenance Model for Workflows (OPMW) is an ontology for describing workflow traces and their templates based on the Open Provenance Model. It has been designed as a profile for OPM, extending and reusing OPM's core ontologies OPMV (OPM-Vocabulary) and OPMO (OPM-Ontology). + http://delicias.dia.fi.upm.es/members/DGarijo/#me, http://www.isi.edu/~gil/ + OWL + 2014-12-22 + Creative Commons Attribution 2.0 Generic (CC BY 2.0) + https://www.opmw.org/model/OPMW_20141222/ + Scholarly Knowledge + Workflows + 3.1 + + + GFO + General Formal Ontology (GFO) + The General Formal Ontology is a top-level ontology for conceptual modeling, which is being constantly further developed by Onto-Med. It includes elaborations of categories like objects, processes, time and space, properties, relations, roles, functions, facts, and situations. Moreover, we are working on an integration with the notion of levels of reality in order to more appropriately capture entities in the material, mental, and social areas. OWL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/OCDO/cdco + 2024-11-18 + Creative Commons 4.0 + https://onto-med.github.io/GFO/release/2024-11-18/index-en.html + Upper Ontology + + + MOLBRINELL + MatoLab Brinell Test Ontology (MOL_BRINELL) + An ontology for describing the Brinell hardness testing process, made in the Materials Open Lab Project. + Birgit Skrotzki, Hossein Beygi Nasrabadi, Philipp von Hartrott, Vinicius Carrillo Beber, Yue Chen + TTL + 05/05/2022 + https://matportal.org/ontologies/MOL_BRINELL Materials Science and Engineering - Materials Science - 1.0.0 + Materials Testing + 0.1 - - SWO - Software Ontology (SWO) - The Software Ontology (SWO) is a resource for describing software tools, their types, tasks, versions, provenance and associated data. It contains detailed information on licensing and formats as well as software applications themselves, mainly (but not limited) to the bioinformatics community. - Allyson Lister, Andy Brown, Duncan Hull, Helen Parkinson, James Malone, Jon Ison, Nandini Badarinarayan, Robert Stevens + + MGED + MGED Ontology (MGED) + An ontology for microarray experiments in support of MAGE v.1. Concepts, definitions, terms, and resources for standardized description of a microarray experiment in support of MAGE v.1. The MGED ontology is divided into the MGED Core ontology which is intended to be stable and in synch with MAGE v.1; and the MGED Extended ontology which adds further associations and classes not found in MAGE v.1 + Chris Stoeckert, Helen Parkinson, Trish Whetzel, Paul Spellman, Catherine A. Ball, Joseph White, John Matese, Liju Fan, Gilberto Fragoso, Mervi Heiskanen, Susanna Sansone, Helen Causton, Laurence Game, Chris Taylor OWL - 2013-07-01 + Feb. 9, 2007 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/SWO - Scholarly Knowledge - Software + https://mged.sourceforge.net/ontologies/MGEDontology.php/ + Biology and Life Sciences + Domain Ontology + 1.3.1.1 + + + AgrO + Agronomy Ontology (AgrO) + An ontology is a formal representation of a disciplinary domain, representing a semantic standard that can be employed to annotate data where key concepts are defined, as well as the relationships that exist between those concepts (Gruber, 2009). Ontologies provide a common language for different kinds of data to be easily interpretable and interoperable allowing easier aggregation and analysis. The Agronomy Ontology (AgrO) provides terms from the agronomy domain that are semantically organized and can facilitate the collection, storage and use of agronomic data, enabling easy interpretation and reuse of the data by humans and machines alike. To fully understand the implications of varying practices within cropping systems and derive insights, it is often necessary to pull together information from data in different disciplinary domains. For example, data on field management, soil, weather and crop phenotypes may need to be aggregated to assess performance of particular crop under different management interventions. However, agronomic data are often collected, described, and stored in inconsistent ways, impeding data comparison, mining, interpretation reuse. The use of standards for metadata and data annotation play a key role in addressing these challenges. While the CG Core Metadata Schema provides a metadata standard to describe agricultural datasets, the Agronomy Ontology enables the description of agronomic data variables using standard terms. + The Crop Ontology Consortium + RDF + 2022-11-02 + Creative Commons 4.0 + https://agroportal.lirmm.fr/ontologies/AGRO?p=summary + Agriculture + Agronomy 1.0 - - PLDO - Planar Defects Ontology (PLDO) - PLDO is an ontology designed to describe planar defects in crystalline materials, such as grain boundaries and stacking faults, with a focus on their atomic-scale structure and properties. - https://orcid.org/0000-0001-7564-7990 + + YAGO + YAGO Ontology (YAGO) + YAGO is a large semantic knowledge base, derived from Wikipedia, WordNet, and GeoNames. It contains knowledge about more than 10 million entities and contains more than 120 million facts about these entities. YAGO is special in several ways: It has a clean taxonomy, which was manually built, and it is the only knowledge base with such a large coverage, the clean taxonomy, and the extraction from Wikipedia, WordNet, and GeoNames. + Max Planck Institute for Informatics + TTL + April, 2024 + Creative Commons 3.0 + https://yago-knowledge.org/downloads/yago-4-5 + General Knowledge + People, Cities, Countries, Movies, Organizations + 4.5 + + + DOLCE + Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) + The Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) is a foundational ontology that provides a conceptual framework for the formalization of domain ontologies. + Laboratory for Applied Ontology, ISTC-CNR OWL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/OCDO/pldo - Materials Science and Engineering - Materials Defects - 1.0.0 + Creative Commons 4.0 + https://www.loa.istc.cnr.it/index.php/dolce/ + Upper Ontology + Linguistics, Cognitive Science + + + Nomisma + Nomisma Ontology (Nomisma) + Nomisma Ontology is a collaborative project to provide stable digital representations of numismatic concepts according to the principles of Linked Open Data. These take the form of http URIs that provide access to the information about a concept in various formats. The project is a collaborative effort of the American Numismatic Society and the Institute for the Study of the Ancient World at New York University. + American Numismatic Society, Institute for the Study of the Ancient World + TTL + 2025-01-22 + Creative Commons 4.0 + https://www.dainst.org/forschung/projekte/noslug/2098 + Arts and Humanities + Numismatics + + + TUBES + TUBES System Ontology (TUBES) + The scope of the TUBES System Ontology is to explicitly define interconnected building service system in the AECO industry, their hierarchical subdivisions, structural and functional aspects, and links to spatial entities. As such, TSO supports the effort to represent linkable information in a future semantic web of building data. It has a strong alignment to other ontologies within the W3C community. + Nicolas Pauen + RDF + 2022-02-01 + Creative Commons 4.0 + https://rwth-e3d.github.io/tso/ + Industry + Building Services + 0.3.0 MSLE @@ -1444,212 +1528,163 @@ Materials Science 1.1 - - DublinCore - Dublin Core Vocabulary (DublinCore) - The Dublin Core Schema is a small set of vocabulary terms that can be used to describe several kinds of resources. Dublin Core Metadata may be used for multiple purposes, from simple resource description, to combining metadata vocabularies of different metadata standards, to providing interoperability for metadata vocabularies in the Linked Data cloud and Semantic Web implementations. - The Dublin Core Metadata Initiative - RDF - February 17, 2017 - Public Domain - https://bioportal.bioontology.org/ontologies/DC - General Knowledge - Metadata - 1.1 - - - Juso - Juso Ontology (Juso) - Juso Ontology is a Web vocabulary for describing geographical addresses and features. - James G. Kim, LiST Inc. - TTL - 2015-11-10 - Creative Commons 4.0 - https://rdfs.co/juso/0.1.1/html - Geography - geographical knowledge - 0.1.1 - - - SPDocument - SMART Protocols Ontology: Document Module (SP-Document) - SMART Protocols Ontology: Document Module is an ontology designed to represent metadata used to report an experimental protocol. - http://oxgiraldo.wordpress.com + + SEPIO + Scientific Evidence and Provenance Information Ontology (SEPIO) + The SEPIO ontology is in its early stages of development, undergoing iterative refinement as new requirements emerge and alignment with existing standards is explored. The SEPIO core file imports two files which can be resolved at the URLs below: IAO ontology-metadata import: https://raw.githubusercontent.com/monarch-initiative/SEPIO-ontology/master/src/ontology/imports/ontology-metadata.owl bfo mireot: https://raw.githubusercontent.com/monarch-initiative/SEPIO-ontology/master/src/ontology/mireots/bfo-mireot.owl OWL - 2013-07-01 - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/SMARTProtocols/SMART-Protocols + 2015-02-23 + Creative Commons 4.0 + https://terminology.tib.eu/ts/ontologies/SEPIO Scholarly Knowledge - Materials Science - 4.0 - - - GPO - General Process Ontology (GPO) - Basically, this ontology aims to model processes. Processes are holistic perspective elements that transform inputs/educts (matter, energy, information) into output/products (matter, energy, information) with the help of tools (devices, algorithms). They can be decomposed into sub-processes and have predecessor and successor processes. - Simon Stier - TTL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/General-Process-Ontology/ontology - Materials Science and Engineering - Materials Science - - - GoodRelations - Good Relations Language Reference (GoodRelations) - GoodRelations is a standardized vocabulary (also known as "schema", "data dictionary", or "ontology") for product, price, store, and company data that can (1) be embedded into existing static and dynamic Web pages and that (2) can be processed by other computers. This increases the visibility of your products and services in the latest generation of search engines, recommender systems, and other novel applications. - Martin Hepp - OWL - 2011-10-01 - Creative Commons 3.0 - https://www.heppnetz.de/ontologies/goodrelations/v1 - Finance - E-commerce - 1.0 + Scientific Evidence - - NMRCV - Nuclear Magnetic Resonance Controlled Vocabulary (NMRCV) - This artefact is an MSI-approved controlled vocabulary primarily developed under COSMOS EU and PhenoMeNal EU governance. The nmrCV is supporting the nmrML XML format with standardized terms. nmrML is a vendor agnostic open access NMR raw data standard. Its primaly role is analogous to the mzCV for the PSI-approved mzML XML format. It uses BFO2.0 as its Top level. This CV was derived from two predecessors (The NMR CV from the David Wishart Group, developed by Joseph Cruz) and the MSI nmr CV developed by Daniel Schober at the EBI. This simple taxonomy of terms (no DL semantics used) serves the nuclear magnetic resonance markup language (nmrML) with meaningful descriptors to amend the nmrML xml file with CV terms. Metabolomics scientists are encouraged to use this CV to annotrate their raw and experimental context data, i.e. within nmrML. The approach to have an exchange syntax mixed of an xsd and CV stems from the PSI mzML effort. The reason to branch out from an xsd into a CV is, that in areas where the terminology is likely to change faster than the nmrML xsd could be updated and aligned, an externally and decentrallised maintained CV can accompensate for such dynamics in a more flexible way. A second reason for this set-up is that semantic validity of CV terms used in an nmrML XML instance (allowed CV terms, position/relation to each other, cardinality) can be validated by rule-based proprietary validators: By means of cardinality specifications and XPath expressions defined in an XML mapping file (an instances of the CvMappingRules.xsd ), one can define what ontology terms are allowed in a specific location of the data model. - Daniel Schober + + MassSpectrometry + Mass Spectrometry Ontology (MassSpectrometry) + A structured controlled vocabulary for the annotation of experiments concerned with proteomics mass spectrometry. + Andreas Bertsch OWL - 2017-10-19 + 12:02:2025 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/NMRCV + https://terminology.tib.eu/ts/ontologies/MS Chemistry - 1.1.0 + Mass Spectrometry, Proteomics - - MSEO - Materials Science and Engineering Ontology (MSEO) - MSEO utilizes the IOF Ontology stack giving materials scientists and engineers the ability to represent their experiments and resulting data. The goal is to create machine and human readable sematic data which can be easily digested by other science domains. It is a product of the joint venture Materials Open Lab Project between the Bundesanstalt für Materialforschung und -prüfung (BAM) and the Fraunhofer Group MATERIALS and uses the BWMD ontology created by Fraunhofer IWM as a starting point. - Thomas Hanke, Fraunhofer IWM + + OWLTime + Time Ontology in OWL (OWL-Time) + OWL-Time is an OWL-2 DL ontology of temporal concepts, for describing the temporal properties of resources in the world or described in Web pages. The ontology provides a vocabulary for expressing facts about topological (ordering) relations among instants and intervals, together with information about durations, and about temporal position including date-time information. Time positions and durations may be expressed using either the conventional (Gregorian) calendar and clock, or using another temporal reference system such as Unix-time, geologic time, or different calendars. + World Wide Web Consortium TTL - MIT License - https://github.com/Mat-O-Lab/MSEO - Materials Science and Engineering - Materials Science + 15 November 2022 + W3C Software Notice and Document License + https://www.w3.org/TR/owl-time/ + Units and Measurements + Temporal Reasoning + 1.0 - - PROCO - PROcess Chemistry Ontology (PROCO) - PROCO (PROcess Chemistry Ontology) is a formal ontology that aims to standardly represent entities and relations among entities in the domain of process chemistry. - Anna Dun, Wes A. Schafer, Yongqun "Oliver" He (YH), Zachary Dance - OWL - 04-14-2022 + + BBC + BBC Ontology (BBC) + The BBC ontology codifies the logic that connects web documents, BBC products and platforms for which content is available. Currently, there are 10 major products in Future Media which produce content for BBC online. The majority of those contain more products dedicated in thematic areas, for example Education propositions are part of the K&L (Knowledge and Learning) product portfolio. + LinkedData@bbc.co.uk + TTL + 2012-12-01 Creative Commons 4.0 - https://github.com/proco-ontology/PROCO - Chemistry - Chemicals, Processes - 04-14-2022 + https://www.bbc.co.uk/ontologies/bbc-ontology/ + News and Media + News + 1.37 - - iCalendar - iCalendar Vocabulary (iCalendar) - iCalendar is an Internet standard for exchanging calendar and scheduling data across different applications and platforms using a standardized text-based format (.ics). It enables interoperability for events, tasks, and scheduling, supporting features like recurring events, invitations, and time zone adjustments. While widely used in applications like Google Calendar and Outlook, its complexity and partial implementations pose challenges, leading to efforts to integrate it with Semantic Web technologies for enhanced data linking and automation. - Dan Connolly, W3C, Libby Miller, ASemantics - RDF - 2004/04/07 - Open Publication License - https://www.w3.org/2002/12/cal/ - Events - Calendar and Scheduling - 1.14 + + BFO + Basic Formal Ontology (BFO) + The Basic Formal Ontology (BFO) is a small, upper-level ontology that describes the basic types of entities in the world and how they relate to each other. + University at Buffalo + OWL + 2020 + Creative Commons 4.0 + https://github.com/BFO-ontology/BFO-2020/ + Upper Ontology + Basic + 2.0 - - CHIRO - CHEBI Integrated Role Ontology (CHIRO) - CHEBI provides a distinct role hierarchy. Chemicals in the structural hierarchy are connected via a 'has role' relation. CHIRO provides links from these roles to useful other classes in other ontologies. This will allow direct connection between chemical structures (small molecules, drugs) and what they do. This could be formalized using 'capable of', in the same way Uberon and the Cell Ontology link structures to processes. + + EMMO + The Elementary Multiperspective Material Ontology (EMMO) + The Elementary Multiperspective Material Ontology (EMMO) is the result of a multidisciplinary effort within the EMMC, aimed at the development of a standard representational ontology framework based on current materials modelling and characterization knowledge. Instead of starting from general upper level concepts, as done by other ontologies, the EMMO development started from the very bottom level, using the actual picture of the physical world coming from applied sciences, and in particular from physics and material sciences. + European Materials Modelling Council (EMMC) OWL - 2015-11-23 - Creative Commons 1.0 - https://terminology.tib.eu/ts/ontologies/chiro - Chemistry - Chemicals, Roles - 2015-11-23 + 2024-03 + Creative Commons 4.0 + https://emmo-repo.github.io/ + Materials Science and Engineering + Materials Modelling + 1.0.0-rc3 - - OIESoftware - Open Innovation Environment Software (OIESoftware) - EMMO-compliant, domain-level OIE ontology tackling the areas of software products. - Adham Hashibon, Daniele Toti, Emanuele Ghedini, Georg J. Schmitz, Gerhard Goldbeck, Jesper Friis, Pierluigi Del Nostro + + BMO + Building Material Ontology (BMO) + Building Material Ontology defines the main concepts of building material, types, layers, and properties. + Janakiram Karlapudi, Prathap Valluru TTL + 2019-12-10 Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/OIE-Ontologies/ + https://matportal.org/ontologies/BUILDMAT Materials Science and Engineering Materials 0.1 - - MOP - Molecular Process Ontology (MOP) - MOP is the molecular process ontology. It contains the molecular processes that underlie the name reaction ontology RXNO, for example cyclization, methylation and demethylation. + + ChMO + Chemical Methods Ontology (ChMO) + The Chemical Methods Ontology contains more than 3000 classes and describes methods used to: - collect data in chemical experiments, such as mass spectrometry and electron microscopy. - prepare and separate material for further analysis, such as sample ionisation, chromatography, and electrophoresis - synthesise materials, such as epitaxy and continuous vapour deposition It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns and their outputs. OWL - 2022-05-11 + 2022-04-19 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/MOP + https://github.com/rsc-ontologies/rsc-cmo Chemistry - Chemistry, Molecular Biology - 2022-05-11 - - MDS - Materials Data Science Ontology (MDS) - Materials Data Science (MDS) is an ontology encompassing multiple domains relevant to materials science, chemical synthesis and characterizations, photovoltaics and geospatial datasets. The terms used for classes, subclasses and instances are mapped to PMDCo and BFO Ontologies. - SDLE Research Center - TTL - 03/24/2024 + + MechanicalTesting + Mechanical Testing Ontology (MechanicalTesting) + A domain ontology for mechanical testing based on EMMO. + Fraunhofer IWM + OWL Creative Commons Attribution 4.0 International (CC BY 4.0) - https://matportal.org/ontologies/MDS + https://github.com/emmo-repo/domain-mechanical-testing Materials Science and Engineering - Materials Science - 0.3.0.0 + Mechanical Testing + 1.0.0 - - OBOE - Extensible Observation Ontology (OBOE) - The Extensible Observation Ontology (OBOE) is a formal ontology for capturing the semantics of scientific observation and measurement. The ontology supports researchers to add detailed semantic annotations to scientific data, thereby clarifying the inherent meaning of scientific observations. - The Regents of the University of California - OWL - Creative Commons 3.0 - https://terminology.tib.eu/ts/ontologies/OBOE + + FRBRoo + Functional Requirements for Bibliographic Records - object-oriented (FRBRoo) + The FRBRoo (Functional Requirements for Bibliographic Records - object-oriented) initiative is a joint effort of the CIDOC Conceptual Reference Model and Functional Requirements for Bibliographic Records international working groups to establish a formal ontology intended to capture and represent the underlying semantics of bibliographic information and to facilitate the integration, mediation, and interchange of bibliographic and museum information. + RDF + November 2015 + Creative Commons 4.0 + https://ontome.net/namespace/6#summary Scholarly Knowledge - Scientific Observation - 1.2 - - - PSIMOD - Protein Modifications Ontology (PSIMOD) - PSI-MOD is an ontology developed by the Proteomics Standards Initiative (PSI) that describes protein chemical modifications, logically linked by an is_a relationship in such a way as to form a direct acyclic graph (DAG). The PSI-MOD ontology has more than 45 top-level nodes, and provides alternative hierarchical paths for classifying protein modifications either by the molecular structure of the modification, or by the amino acid residue that is modified. - OWL - 2022-06-13 - Creative Commons Attribution 4.0 - https://github.com/HUPO-PSI/psi-mod-CV - Chemistry - Protein Modifications - 1.031.6 + Bibliographic Records + 2.4 - - Common - Common Ontology (Common) - Ontology for the representation of commons elements in the Trias ontology - Jhon Toledo, Miguel Angel García, Oscar Corcho + + MAT + Material Properties Ontology (MAT) + The Material Properties Ontology aims to provide the vocabulary to describe the building components, materials, and their corresponding properties, relevant within the construction industry. More specifically, the building elements and properties covered in this ontology support applications focused on the design of building renovation projects. + María Poveda-Villalón, Serge Chávez-Feria RDF - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://w3id.org/mobility/trias/common/0.1.0 - Education - Computer Science - 0.1.0 + Creative Commons 4.0 + https://bimerr.iot.linkeddata.es/def/material-properties/ + Materials Science and Engineering + Materials Properties + 0.0.8 - - PO - Plant Ontology (PO) - The Plant Ontology (PO) is a structured vocabulary and database resource that links plant anatomy, morphology and growth and development to plant genomics data. + + SystemCapabilities + System Capabilities Ontology (SystemCapabilities) + This ontology describes system capabilities, operating ranges, and survival ranges. + W3C/OGC Spatial Data on the Web Working Group OWL - Creative Commons 4.0 - https://github.com/Planteome/plant-ontology - Agriculture - Plant Anatomy, Morphology, Growth and Development + 2017-05-14 + W3C Software and Document License + https://terminology.tib.eu/ts/ontologies/SSNSYSTEM + Materials Science and Engineering + Materials Science, Engineering, Systems + + + DOID + Human Disease Ontology (DOID) + The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts. + The Open Biological and Biomedical Ontology Foundry + OWL + 2024-12-18 + Creative Commons 1.0 + http://purl.obolibrary.org/obo/doid/releases/2024-12-18/doid.owl + Medicine + Human Diseases DEB @@ -1664,255 +1699,265 @@ Biomaterials 06/2021 - - MarineTLO - Marine Taxonomy and Life Ontology (MarineTLO) - MarineTLO is a top level ontology, generic enough to provide consistent abstractions or specifications of concepts included in all data models or ontologies of marine data sources and provide the necessary properties to make this distributed knowledge base a coherent source of facts relating observational data with the respective spatiotemporal context and categorical (systematic) domain knowledge. It can be used as the core schema for publishing Linked Data, as well as for setting up integration systems for the marine domain. It can be extended to any level of detail on demand, while preserving monotonicity. For its development and evolution we have adopted an iterative and incremental methodology where a new version is released every two months. For the implementation we use OWL 2, and to evaluate it we use a set of competency queries, formulating the domain requirements provided by the related communities. - Information System Laboratory (ISL), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH) - OWL - 2017-01-05 - Creative Commons 4.0 - https://projects.ics.forth.gr/isl/MarineTLO/ - Biology and Life Sciences - Marine Science, Oceanography - 1.0 + + FOAF + Friend of a Friend (FOAF) + FOAF is a project devoted to linking people and information using the Web. Regardless of whether information is in people's heads, in physical or digital documents, or in the form of factual data, it can be linked. + Dan Brickley, Libby Miller + RDF + 14 January 2014 + Creative Commons + http://xmlns.com/foaf/0.1/ + Social Sciences + Social + 0.1 - - PKO - Provenance Knowledge Ontology (PKO) - Procedural Knowledge (PK) is knowing how to perform some tasks, as opposed to descriptive/declarative knowledge, which is knowing what in terms of facts and notions. In industry, PK refers in general to structured processes to be followed, and can be related to both production (e.g., procedure on the production line in a plant) and services (e.g., procedure for troubleshooting during customer support); to specific technical expertise (e.g., procedure to set up a specific machine) and general regulations and best practices (e.g., safety procedures, activities to minimise environmental impact). - Mario Scrocca (Cefriel), Valentina Carriero (Cefriel) + + MusicOntology + Music Ontology (MusicOntology) + The Music Ontology Specification provides main concepts and properties fo describing music (i.e. artists, albums and tracks) on the Semantic Web. + Knowledge Media Institute, Open University RDF - 2025-03-01 + 2013/07/22 Creative Commons 4.0 - https://github.com/perks-project/pk-ontology/tree/master - Industry - Provenance - 1.0.0 + https://github.com/motools/musicontology + Arts and Humanities + Music Theory + 2.1.5 - - CHAMEO - Characterisation Methodology Domain Ontology (CHAMEO) - An ontology for materials characterization which represents the evolution of the CHADA template in an ontological form, allowing to generate FAIR documentation of Characterisation Experiments and that has been used as a basis for the development of a number of technique-specific or application-specific ontologies in the materials characterisation domain. CHAMEO has been used as a foundation for the definition of the new CHADA template during the CWA. - https://orcid.org/0000-0002-4181-2852, https://orcid.org/0000-0002-5174-8508, https://orcid.org/0000-0002-9668-6961 - TTL - 2024-04-12 + + CMSO + Computational Material Sample Ontology (CMSO) + CMSO is an ontology that aims to describe computational materials science samples (or structures), including crystalline defects. Initially focusing on the description at the atomic scale. + https://orcid.org/0000-0001-7564-7990 + OWL Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/domain-characterisation-methodology + https://github.com/OCDO/cmso/tree/main Materials Science and Engineering Materials Science - 1.0.0 + 0.0.1 - - LIFO - Life Ontology (LifO) - The Life Ontology (LifO) is an ontology of the life of organism. LifO represents the life processes of organisms and related entities and relations. LifO is a general purpose ontology that covers the common features associated with different organisms such as unicellular prokaryotes (e.g., E. coli) and multicellular organisms (e.g., human). - Yongqun "Oliver" He (YH) + + BTO + BRENDA Tissue Ontology (BTO) + A structured controlled vocabulary for the source of an enzyme comprising tissues, cell lines, cell types and cell cultures. OWL - March 11, 2018 + 2021-10-26 Creative Commons 4.0 - https://bioportal.bioontology.org/ontologies/LIFO - Biology and Life Sciences - General Purpose - 1.0.17 + https://terminology.tib.eu/ts/ontologies/BTO + Medicine + Enzyme + 2021-10-26 - - YAGO - YAGO Ontology (YAGO) - YAGO is a large semantic knowledge base, derived from Wikipedia, WordNet, and GeoNames. It contains knowledge about more than 10 million entities and contains more than 120 million facts about these entities. YAGO is special in several ways: It has a clean taxonomy, which was manually built, and it is the only knowledge base with such a large coverage, the clean taxonomy, and the extraction from Wikipedia, WordNet, and GeoNames. - Max Planck Institute for Informatics - TTL - April, 2024 - Creative Commons 3.0 - https://yago-knowledge.org/downloads/yago-4-5 - General Knowledge - People, Cities, Countries, Movies, Organizations - 4.5 + + AUTO + Automotive Ontology (AUTO) + The AUTOMOTIVE ONTOLOGY (AUTO) defines the shared conceptual structures in the automotive industry. It is an OWL ontology. It is built upon the auto schema.org extension created by the W3C Automotive Ontology Community Group. AUTO's development process follows the best practices established by the EDMC FIBO Community. + EDM Council + RDF + 2021-03-01 + MIT + https://github.com/edmcouncil/auto/tree/master + Industry + Automotive - - CMSO - Computational Material Sample Ontology (CMSO) - CMSO is an ontology that aims to describe computational materials science samples (or structures), including crystalline defects. Initially focusing on the description at the atomic scale. - https://orcid.org/0000-0001-7564-7990 + + BIBFRAME + Bibliographic Framework Ontology (BIBFRAME) + The Bibframe vocabulary consists of RDF classes and properties used for the description of items cataloged principally by libraries, but may also be used to describe items cataloged by museums and archives. Classes include the three core classes - Work, Instance, and Item - in addition to many more classes to support description. Properties describe characteristics of the resource being described as well as relationships among resources. For example: one Work might be a "translation of" another Work; an Instance may be an "instance of" a particular Bibframe Work. Other properties describe attributes of Works and Instances. For example: the Bibframe property "subject" expresses an important attribute of a Work (what the Work is about), and the property "extent" (e.g. number of pages) expresses an attribute of an Instance. + United States, Library of Congress + RDF + 2022-10-03 + Creative Commons 1.0 + https://id.loc.gov/ontologies/bflc.html + Education + Library, Museums, Archives + 2.5.0 + + + OntoCAPE + Ontology of Computer-Aided Process Engineering (OntoCAPE) + OntoCAPE is a large-scale ontology for the domain of Computer Aided Process Engineering (CAPE). Represented in a formal, machine-interpretable ontology language, OntoCAPE captures consensual knowledge of the process engineering domain in a generic way such that it can be reused and shared by groups of people and across software systems. On the basis of OntoCAPE, novel software support for various engineering activities can be developed; possible applications include the systematic management and retrieval of simulation models and design documents, electronic procurement of plant equipment, mathematical modeling, as well as the integration of design data from distributed sources. + RWTH Aachen University OWL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/OCDO/cmso/tree/main + GNU General Public License. + https://www.avt.rwth-aachen.de/cms/avt/forschung/sonstiges/software/~ipts/ontocape/?lidx=1 Materials Science and Engineering - Materials Science - 0.0.1 + Manufacturing + 2.0 - - ChEBI - Chemical Entities of Biological Interest (ChEBI) - Chemical Entities of Biological Interest (ChEBI) is a dictionary of molecular entities focused on ‘small’ chemical compounds. The term ‘molecular entity’ refers to any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. The molecular entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms. ChEBI incorporates an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. + + VIBSO + Vibrational Spectroscopy Ontology (VIBSO) + The Vibration Spectroscopy Ontology defines technical terms with which research data produced in vibrational spectroscopy experiments can be semantically enriched, made machine readable and FAIR. + VIBSO Workgroup OWL - 01/01/2025 - Creative Commons 4.0 - https://www.ebi.ac.uk/chebi/ + 2024-09-23 + Creative Commons Attribution 4.0 + https://terminology.tib.eu/ts/ontologies/vibso Chemistry - Chemical Entities - 239 + Spectroscopy + 2024-09-23 - - EXPO - Ontology of Scientific Experiments (EXPO) - Formalise generic knowledge about scientific experimental design, methodology, and results representation. + + PROCO + PROcess Chemistry Ontology (PROCO) + PROCO (PROcess Chemistry Ontology) is a formal ontology that aims to standardly represent entities and relations among entities in the domain of process chemistry. + Anna Dun, Wes A. Schafer, Yongqun "Oliver" He (YH), Zachary Dance OWL - Academic Free License (AFL) - https://expo.sourceforge.net/ - Scholarly Knowledge - Scientific Experiments + 04-14-2022 + Creative Commons 4.0 + https://github.com/proco-ontology/PROCO + Chemistry + Chemicals, Processes + 04-14-2022 - - MatOnto - Material Ontology (MatOnto) - The Material Ontology (MatOnto) is based on the upper level ontology, the BFO. + + LODE + Linking Open Descriptions of Events (LODE) + People conventionally refer to an action or occurrence taking place at a certain time at a specific location as an event. This notion is potentially useful for connecting individual facts recorded in the rapidly growing collection of linked data sets and for discovering more complex relationships between data. The LODE provide an overview and comparison of existing event models, looking at the different choices they make of how to represent events. It is a model for publishing records of events as Linked Data. A tools for populating this model and a prototype “event directory” web service, which can be used to locate stable URIs for events that have occurred, provide RDFS+OWL descriptions and link to related resources. + Ryan Shaw + RDF + 2020-10-31 + Creative Commons Attribution 3.0 + https://linkedevents.org/ontology/ + Events + 2020-10-31 + + + MFOEM + Mental Functioning Ontology of Emotions - Emotion Module (MFOEM) + The Mental Functioning Ontology - Emotion Module (MFOEM) aims to include all relevant aspects of affective phenomena including their bearers, the different types of emotions, moods, etc., their different parts and dimensions of variation, their facial and vocal expressions, and the role of emotions and affective phenomena in general in influencing human behavior.This class processes Mental Functioning Ontology of Emotions (MFOEM) using default behavior. + Swiss Centre for Affective Sciences & University at Buffalo OWL - https://github.com/EngyNasr/MSE-Benchmark/blob/main/testCases/secondTestCase/MatOnto.owl - Materials Science and Engineering - Scholarly Knowledge + Creative Commons 3.0 + http://purl.obolibrary.org/obo/MFOEM.owl + Medicine + Emotion - - MOLTENSILE - Matolab Tensile Test Ontology (MOL_TENSILE) - An ontology for describing the tensile test process, made in the Materials Open Lab Project. - Markus Schilling, markus.schilling@bam.de; Philipp von Hartrott, philipp.von.hartrott@iwm.fraunhofer.de - RDF - 04/16/2021 + + AMOntology + Additive Manufacturing Ontology (AMOntology) + The AM ontology has been developed following two major milestones. The ontology developed within the first milestone includes AMProcessOntology, ModelOntology and AMOntology files. AMProcessOntology contains the set of entities used to capture knowledge about additive manufacturing processes. ModelOntology contains the set of entities used to capture knowledge about modeling concepts that represent (possibly) multi-physics multi-scale processes. AMOntology uses AMProcessOntology and ModelOntology files to describe entities that capture knowledge about characteristics of computational models for AM processes. + Iassou Souroko, Ali Riza Durmaz + TTL + 2023-05-10 Creative Commons Attribution 4.0 International (CC BY 4.0) - https://matportal.org/ontologies/MOL_TENSILE + https://github.com/iassouroko/AMontology Materials Science and Engineering - Materials Testings - 0.4 - - - DOAP - The Description of a Project vocabulary (DOAP) - The Description of a Project vocabulary (DOAP), described using W3C RDF Schema and the Web Ontology Language to describe software projects, and in particular open source projects. - Edd Wilder-James - RDF - 2020-04-03 - Apache License 2.0 - https://github.com/ewilderj/doap/blob/master/schema/doap.rdf - Industry - Software + Manufacturing + 1.0 - - ASMO - Atomistic Simulation Methods Ontology (ASMO) - ASMO is an ontology that aims to define the concepts needed to describe commonly used atomic scale simulation methods, i.e. density functional theory, molecular dynamics, Monte Carlo methods, etc. ASMO uses the Provenance Ontology (PROV-O) to describe the simulation process. - https://orcid.org/0000-0001-7564-7990 + + DISO + Dislocation Ontology (DISO) + DISO is an ontology that defines the linear defect, in particular dislocation concepts and relations between them in crystalline materials. + Ahmad Zainul Ihsan OWL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/OCDO/asmo?tab=readme-ov-file#atomistic-simulation-methods-ontology-asmo + 21.03.202 + Creative Commons Attribution 3.0 International (CC BY 3.0) + https://github.com/Materials-Data-Science-and-Informatics/dislocation-ontology Materials Science and Engineering Materials Science - 1.0.0 + 1.0 - - AS2 - Activity Streams 2.0 Ontology (AS2) - The Activity Streams 2.0 ontology is a vocabulary for describing social activities and actions. It is based on the Activity Streams 2.0 specification and provides a set of classes and properties for describing activities on the web. - TTL - 23 May 2017 - W3C Document License - https://github.com/w3c/activitystreams?tab=License-1-ov-file#readme - Social Sciences - Social - 2.0 + + CSO + Computer Science Ontology (CSO) + The Computer Science Ontology (CSO) is a large-scale ontology of research areas in computer science. It provides a comprehensive vocabulary of research topics in computing, organized in a hierarchical structure. This class processes the Computer Science Ontology (CSO) with custom hooks for: - Topic-based class detection - superTopicOf relationships - contributesTo relationships + Knowledge Media Institute, Open University + OWL + Creative Commons 4.0 + https://cso.kmi.open.ac.uk/home + Scholarly Knowledge + Computer Science + 3.4 - - EMMOCrystallography - Crystallography Ontology (EMMOCrystallography) - A crystallography domain ontology based on EMMO and the CIF core dictionary. It is implemented as a formal language. - TTL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/domain-crystallography - Materials Science and Engineering - Crystallography - 0.0.1 + + AGROVOC + AGROVOC Multilingual Thesaurus (AGROVOC) + AGROVOC is a relevant Linked Open Data set about agriculture available for public use and facilitates access and visibility of data across domains and languages. It offers a structured collection of agricultural concepts, terms, definitions and relationships which are used to unambiguously identify resources, allowing standardized indexing processes and making searches more efficient. + Food and Agriculture Organization of the United Nations + RDF + August 12, 2024 + Creative Commons 4.0 + https://agroportal.lirmm.fr/ontologies/AGROVOC + Agriculture + Agricultural Knowledge + 2024-04 - - OIEModels - Open Innovation Environment Models (OIEModels) - The models module defines models as semiotic signs that stands for an object by resembling or imitating it, in shape or by sharing a similar logical structure. - Adham Hashibon, Daniele Toti, Emanuele Ghedini, Georg J. Schmitz, Gerhard Goldbeck, Jesper Friis, Pierluigi Del Nostro + + BVCO + Battery Value Chain Ontology (BVCO) + Basically, Battery Value Chain Ontology (BVCO) aims to model processes along the Battery value chain. Processes are holistic perspective elements that transform inputs/educts (matter, energy, information) into output/products (matter, energy, information) with the help of tools (devices, algorithms). They can be decomposed into sub-processes and have predecessor and successor processes. + Lukas Gold, Simon Stier TTL Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/OIE-Ontologies/ + https://github.com/Battery-Value-Chain-Ontology/ontology Materials Science and Engineering - Materials + Materials Science + 0.4.3 - - IAO - Information Artifact Ontology (IAO) - The Information Artifact Ontology (IAO) is an ontology of information entities, originally driven by work by the OBI digital entity and realizable information entity branch. + + PO + Plant Ontology (PO) + The Plant Ontology (PO) is a structured vocabulary and database resource that links plant anatomy, morphology and growth and development to plant genomics data. OWL - 2022-11-07 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/IAO - General Knowledge - Information, Data, Knowledge + https://github.com/Planteome/plant-ontology + Agriculture + Plant Anatomy, Morphology, Growth and Development - - NCIt - NCI Thesaurus (NCIt) - NCI Thesaurus (NCIt) is a reference terminology that includes broad coverage of the cancer domain, including cancer related diseases, findings and abnormalities. The NCIt OBO Edition aims to increase integration of the NCIt with OBO Library ontologies. NCIt OBO Edition releases should be considered experimental. + + MarineTLO + Marine Taxonomy and Life Ontology (MarineTLO) + MarineTLO is a top level ontology, generic enough to provide consistent abstractions or specifications of concepts included in all data models or ontologies of marine data sources and provide the necessary properties to make this distributed knowledge base a coherent source of facts relating observational data with the respective spatiotemporal context and categorical (systematic) domain knowledge. It can be used as the core schema for publishing Linked Data, as well as for setting up integration systems for the marine domain. It can be extended to any level of detail on demand, while preserving monotonicity. For its development and evolution we have adopted an iterative and incremental methodology where a new version is released every two months. For the implementation we use OWL 2, and to evaluate it we use a set of competency queries, formulating the domain requirements provided by the related communities. + Information System Laboratory (ISL), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH) OWL - 2023-10-19 + 2017-01-05 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/NCIT - Medicine - Cancer, Oncology - 24.04e - - - MaterialInformation - Material Information Ontology (MaterialInformation) - The Material Information ontology is divided into smaller ontologies (partitions). The partitions are Environment, Geometry, Material Information, Manufacturing Process, Property, Substance, Unit Dimension, Structure, Equation and Physical Constant. - Toshihiro Ashino - OWL - https://github.com/EngyNasr/MSE-Benchmark/blob/main/testCases/secondTestCase/MaterialInformation.owl - Materials Science and Engineering - Materials Science + https://projects.ics.forth.gr/isl/MarineTLO/ + Biology and Life Sciences + Marine Science, Oceanography + 1.0 - - GEO - Geographical Entities Ontology (GEO) - Geographical Entities Ontology (GEO) is an inventory of geopolitical entities (such as sovereign states and their administrative subdivisions) as well as various geographical regions (including but not limited to the specific ones over which the governments have jurisdiction) - William R Hogan + + ATOL + Animal Trait Ontology for Livestock (ATOL) + ATOL (Animal Trait Ontology for Livestock) is an ontology of characteristics defining phenotypes of livestock in their environment (EOL). ATOL aims to: - provide a reference ontology of phenotypic traits of farm animals for the international scientific and educational - communities, farmers, etc.; - deliver this reference ontology in a language which can be used by computers in order to support database management, semantic analysis and modeling; - represent traits as generic as possible for livestock vertebrates; - make the ATOL ontology as operational as possible and closely related to measurement techniques; - structure the ontology in relation to animal production. + INRAE, France OWL - 2019-02-17 + May 11, 2020 Creative Commons 4.0 - https://github.com/mcwdsi/geographical-entity-ontology/blob/master/geo-all.owl - Geography - Geographic Knowledge + https://bioportal.bioontology.org/ontologies/ATOL + Agriculture + Animal Science + 6.0 - - BIO - BIO: A vocabulary for biographical information (BIO) - The BIO vocabulary contains terms useful for finding out more about people and their backgrounds and has some cross-over into genealogical information. The approach taken is to describe a person's life as a series of interconnected key events, around which other information can be woven. This vocabulary defines the event framework and supplies a set of core event types that cover many use cases, but it is expected that it will be extended in other vocabularies to suit their needs. The intention of this vocabulary is to describe biographical events of people and this intention carries through to the definitions of the properties and classes which are person-centric rather than neutral. For example the Employment event puts the person being employed as the principal agent in the event rather than the employer. - Ian Davis and David Galbraith + + iCalendar + iCalendar Vocabulary (iCalendar) + iCalendar is an Internet standard for exchanging calendar and scheduling data across different applications and platforms using a standardized text-based format (.ics). It enables interoperability for events, tasks, and scheduling, supporting features like recurring events, invitations, and time zone adjustments. While widely used in applications like Google Calendar and Outlook, its complexity and partial implementations pose challenges, leading to efforts to integrate it with Semantic Web technologies for enhanced data linking and automation. + Dan Connolly, W3C, Libby Miller, ASemantics RDF - 2010-05-10 - Public Domain - https://vocab.org/bio/ - Social Sciences - Biographical Information - 0.1 + 2004/04/07 + Open Publication License + https://www.w3.org/2002/12/cal/ + Events + Calendar and Scheduling + 1.14 - - OPMW - Open Provenance Model for Workflows (OPMW) - The Open Provenance Model for Workflows (OPMW) is an ontology for describing workflow traces and their templates based on the Open Provenance Model. It has been designed as a profile for OPM, extending and reusing OPM's core ontologies OPMV (OPM-Vocabulary) and OPMO (OPM-Ontology). - http://delicias.dia.fi.upm.es/members/DGarijo/#me, http://www.isi.edu/~gil/ - OWL - 2014-12-22 - Creative Commons Attribution 2.0 Generic (CC BY 2.0) - https://www.opmw.org/model/OPMW_20141222/ - Scholarly Knowledge - Workflows - 3.1 + + OIESoftware + Open Innovation Environment Software (OIESoftware) + EMMO-compliant, domain-level OIE ontology tackling the areas of software products. + Adham Hashibon, Daniele Toti, Emanuele Ghedini, Georg J. Schmitz, Gerhard Goldbeck, Jesper Friis, Pierluigi Del Nostro + TTL + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/emmo-repo/OIE-Ontologies/ + Materials Science and Engineering + Materials + 0.1 BBCProvenance @@ -1927,18 +1972,18 @@ Provenance 1.9 - - GIST - GIST Upper Ontology (GIST) - Gist is Semantic Arts' minimalist upper ontology for the enterprise. It is designed to have the maximum coverage of typical business ontology concepts with the fewest number of primitives and the least amount of ambiguity. - Semantic Arts - RDF - 2024-Feb-27 + + FSO + Flow Systems Ontology (FSO) + The Flow Systems Ontology (FSO) is an ontology for describing interconnected systems with material or energy flow connections, and their components. + Ali Kücükavci, Mads Holten Rasmussen, Ville Kukkonen + TTL + 2020-08-06 Creative Commons 4.0 - https://semanticarts.com/gist - General Knowledge - Upper Ontology - 12.1.0 + https://github.com/alikucukavci/FSO/ + Materials Science and Engineering + Materials Science + 0.1.0 OIEMaterials @@ -1951,283 +1996,238 @@ Materials Science and Engineering Materials - - TimelineOntology - Timeline Ontology (TimelineOntology) - The Timeline Ontology is centered around the notion of timeline, seen here as a way to identify a temporal backbone. A timeline may support a signal, a video, a score, a work, etc. - Christopher Sutton, Yves Raimond, Matthias Mauch - RDF - 25th October 2007 - Creative Commons 1.0 - https://github.com/motools/timelineontology - Arts and Humanities - Music Theory - 1.0 + + RO + Relation Ontology (RO) + The Relations Ontology (RO) is a collection of OWL relations (ObjectProperties) intended for use across a wide variety of biological ontologies. + OWL + 2024-04-24 + CC0 + http://purl.obolibrary.org/obo/ro.owl + General Knowledge + Relations + 2024-04-24 - - ChMO - Chemical Methods Ontology (ChMO) - The Chemical Methods Ontology contains more than 3000 classes and describes methods used to: - collect data in chemical experiments, such as mass spectrometry and electron microscopy. - prepare and separate material for further analysis, such as sample ionisation, chromatography, and electrophoresis - synthesise materials, such as epitaxy and continuous vapour deposition It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns and their outputs. + + PLDO + Planar Defects Ontology (PLDO) + PLDO is an ontology designed to describe planar defects in crystalline materials, such as grain boundaries and stacking faults, with a focus on their atomic-scale structure and properties. + https://orcid.org/0000-0001-7564-7990 OWL - 2022-04-19 - Creative Commons 4.0 - https://github.com/rsc-ontologies/rsc-cmo - Chemistry + Creative Commons Attribution 4.0 International (CC BY 4.0) + https://github.com/OCDO/pldo + Materials Science and Engineering + Materials Defects + 1.0.0 - - EURIO - EUropean Research Information Ontology (EURIO) - EURIO (EUropean Research Information Ontology) conceptualises, formally encodes and makes available in an open, structured and machine-readable format data about resarch projects funded by the EU's framework programmes for research and innovation. - Publications Office of the European Commission - RDF - 2023-10-19 + + LIFO + Life Ontology (LifO) + The Life Ontology (LifO) is an ontology of the life of organism. LifO represents the life processes of organisms and related entities and relations. LifO is a general purpose ontology that covers the common features associated with different organisms such as unicellular prokaryotes (e.g., E. coli) and multicellular organisms (e.g., human). + Yongqun "Oliver" He (YH) + OWL + March 11, 2018 Creative Commons 4.0 - https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurio - Scholarly Knowledge - Research Information - 2.4 - - - Photovoltaics - EMMO Domain Ontology for Photovoltaics (Photovoltaics) - This ontology is describing Perovskite solar cells. - Casper Welzel Andersen, Simon Clark - TTL - Creative Commons license Attribution 4.0 International (CC BY 4.0) - https://github.com/emmo-repo/domain-photovoltaics - Materials Science and Engineering - Materials Science - 0.0.1 + https://bioportal.bioontology.org/ontologies/LIFO + Biology and Life Sciences + General Purpose + 1.0.17 - - DISO - Dislocation Ontology (DISO) - DISO is an ontology that defines the linear defect, in particular dislocation concepts and relations between them in crystalline materials. - Ahmad Zainul Ihsan + + GoodRelations + Good Relations Language Reference (GoodRelations) + GoodRelations is a standardized vocabulary (also known as "schema", "data dictionary", or "ontology") for product, price, store, and company data that can (1) be embedded into existing static and dynamic Web pages and that (2) can be processed by other computers. This increases the visibility of your products and services in the latest generation of search engines, recommender systems, and other novel applications. + Martin Hepp OWL - 21.03.202 - Creative Commons Attribution 3.0 International (CC BY 3.0) - https://github.com/Materials-Data-Science-and-Informatics/dislocation-ontology - Materials Science and Engineering - Materials Science + 2011-10-01 + Creative Commons 3.0 + https://www.heppnetz.de/ontologies/goodrelations/v1 + Finance + E-commerce 1.0 - - BBC - BBC Ontology (BBC) - The BBC ontology codifies the logic that connects web documents, BBC products and platforms for which content is available. Currently, there are 10 major products in Future Media which produce content for BBC online. The majority of those contain more products dedicated in thematic areas, for example Education propositions are part of the K&L (Knowledge and Learning) product portfolio. - LinkedData@bbc.co.uk - TTL - 2012-12-01 - Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/bbc-ontology/ - News and Media - News - 1.37 - - - BBCBusiness - BBC Business News Ontology (BBCBusiness) - The Business News Ontology describes the concepts that occur in BBC business news. - https://www.bbc.co.uk/blogs/internet/authors/Jeremy_Tarling, https://uk.linkedin.com/in/amaalmohamed - TTL - 2014-11-09 + + RXNO + Reaction Ontology (RXNO) + RXNO is the name reaction ontology. It contains more than 500 classes representing organic reactions such as the Diels–Alder cyclization. + OWL + 2021-12-16 Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/business-news-ontology - News and Media - Business News - 0.5 + https://github.com/rsc-ontologies/rxno + Chemistry - - PROV - PROV Ontology (PROV-O) - The PROV Ontology (PROV-O) expresses the PROV Data Model [PROV-DM] using the OWL2 Web Ontology Language (OWL2) [OWL2-OVERVIEW]. It provides a set of classes, properties, and restrictions that can be used to represent and interchange provenance information generated in different systems and under different contexts. It can also be specialized to create new classes and properties to model provenance information for different applications and domains. The PROV Document Overview describes the overall state of PROV, and should be read before other PROV documents. - OWL - 2013-04-30 - W3C Software License - https://terminology.tib.eu/ts/ontologies/PROV + + UMBEL + Upper Mapping and Binding Exchange Layer Vocabulary (UMBEL) + UMBEL is the Upper Mapping and Binding Exchange Layer, designed to help content interoperate on the Web. UMBEL provides two valuable functions: First, it is a broad, general reference structure of 34,000 concepts, which provides a scaffolding to link and interoperate other datasets and domain vocabularies. Second, it is a base vocabulary for the construction of other concept-based domain ontologies, also designed for interoperation. + n3 + May 10, 2016 + https://github.com/structureddynamics/UMBEL/tree/master/Ontology General Knowledge - General - 2013-04-30 + Web Development + 1.50 - - Framester - Framester Ontology (Framester) - Framester is a a frame-based ontological resource acting as a hub between linguistic resources such as FrameNet, WordNet, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, and leveraging this wealth of links to create an interoperable predicate space formalized according to frame semantics and semiotics. Framester uses WordNet and FrameNet at its core, expands it to other resources transitively, and represents them in a formal version of frame semantics. - Aldo Gangemi - RDF - 19-04-2016 - Creative Commons 4.0 - http://150.146.207.114/lode/extract?url=http://ontologydesignpatterns.org/ont/framester/framester.owl + + OBOE + Extensible Observation Ontology (OBOE) + The Extensible Observation Ontology (OBOE) is a formal ontology for capturing the semantics of scientific observation and measurement. The ontology supports researchers to add detailed semantic annotations to scientific data, thereby clarifying the inherent meaning of scientific observations. + The Regents of the University of California + OWL + Creative Commons 3.0 + https://terminology.tib.eu/ts/ontologies/OBOE Scholarly Knowledge - Linguistics - 1.0 + Scientific Observation + 1.2 - - OM - Ontology of Units of Measure (OM) - The Ontology of units of Measure (OM) models concepts and relations important to scientific research. It has a strong focus on units, quantities, measurements, and dimensions. It includes, for instance, common units such as the SI units metre and kilogram, but also units from other systems of units such as the mile or nautical mile. For many application areas it includes more specific units and quantities, such as the unit of the Hubble constant or the quantity vaselife. The following application areas are supported by OM: Geometry; Mechanics; Thermodynamics; Electromagnetism; Fluid mechanics; Chemical physics; Photometry; Radiometry and Radiobiology; Nuclear physics; Astronomy and Astrophysics; Cosmology; Earth science; Meteorology; Material science; Microbiology; Economics; Information technology and Typography. - Hajo Rijgersberg, Don Willems, Jan Top + + FRAPO + Funding, Research Administration and Projects Ontology (FRAPO) + The Funding, Research Administration and Projects Ontology (FRAPO) is an ontology for describing the administrative information of research projects, e.g., grant applications, funding bodies, project partners, etc. + David Shotton RDF - June 28, 2024 Creative Commons 4.0 - https://bioportal.bioontology.org/ontologies/OM - Units and Measurements - 2.0.57 + http://www.sparontologies.net/ontologies/frapo + Scholarly Knowledge + Administration - - MO - Microscopy Ontology (MO) - The Microscopy Ontology (MO) extends the ontological framework of the PMDco. The MO facilitates semantic integration and the interoperable connection of diverse data sources from the fields of microscopy and microanalysis. Consequently, the MO paves the way for new, adaptable data applications and analyses across various experiments and studies - https://orcid.org/0000-0002-3717-7104,https://orcid.org/0000-0002-7094-5371 - TTL - Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/materialdigital/microscopy-ontology?tab=readme-ov-file - Biology and Life Sciences - Microscopy - 2.0 + + CHIRO + CHEBI Integrated Role Ontology (CHIRO) + CHEBI provides a distinct role hierarchy. Chemicals in the structural hierarchy are connected via a 'has role' relation. CHIRO provides links from these roles to useful other classes in other ontologies. This will allow direct connection between chemical structures (small molecules, drugs) and what they do. This could be formalized using 'capable of', in the same way Uberon and the Cell Ontology link structures to processes. + OWL + 2015-11-23 + Creative Commons 1.0 + https://terminology.tib.eu/ts/ontologies/chiro + Chemistry + Chemicals, Roles + 2015-11-23 - - BBCProgrammes - BBC Programmes Ontology (BBCProgrammes) - This ontology aims at providing a simple vocabulary for describing programmes. It covers brands, series (seasons), episodes, broadcast events, broadcast services,etc. Its development was funded by the BBC, and is heavily grounded on previous programmes data modelling work done there. - https://moustaki.org/foaf.rdf#moustaki - TTL - 2009/02/20 - Creative Commons 4.0 - https://www.bbc.co.uk/ontologies/programmes-ontology - News and Media - Programmes - 1.1 + + DSIM + Dislocation Simulation and Model Ontology (DSIM) + Dislocation simulation and model ontology (DSIM) is an ontology developed to model various concepts and relationships in the discrete dislocation dynamics domain and microscopy techniques used in the dislocation domain. The various concepts are the numerical representation of dislocation applied in the dislocation dynamic simulation and the pictorial concept of pixel applied in representing dislocation in the experimental image, eg., TEM image, SEM image, and FIM image. + Ahmad Zainul Ihsan + OWL + 17.08.2023 + Creative Commons Attribution 3.0 Unported (CC BY 3.0) + https://github.com/OCDO/DSIM + Materials Science and Engineering + Materials Science + 1.0 - - ATOL - Animal Trait Ontology for Livestock (ATOL) - ATOL (Animal Trait Ontology for Livestock) is an ontology of characteristics defining phenotypes of livestock in their environment (EOL). ATOL aims to: - provide a reference ontology of phenotypic traits of farm animals for the international scientific and educational - communities, farmers, etc.; - deliver this reference ontology in a language which can be used by computers in order to support database management, semantic analysis and modeling; - represent traits as generic as possible for livestock vertebrates; - make the ATOL ontology as operational as possible and closely related to measurement techniques; - structure the ontology in relation to animal production. - INRAE, France + + GO + Gene Ontology (GO) + The Gene Ontology (GO) Provides structured controlled vocabularies for the annotation of gene products with respect to their molecular function, cellular component, and biological role. OWL - May 11, 2020 + 2024-11-03 Creative Commons 4.0 - https://bioportal.bioontology.org/ontologies/ATOL - Agriculture - Animal Science - 6.0 + https://geneontology.org/docs/download-ontology/ + Biology and Life Sciences + Molecular Biology, Genetics - - MFOEM - Mental Functioning Ontology of Emotions - Emotion Module (MFOEM) - The Mental Functioning Ontology - Emotion Module (MFOEM) aims to include all relevant aspects of affective phenomena including their bearers, the different types of emotions, moods, etc., their different parts and dimensions of variation, their facial and vocal expressions, and the role of emotions and affective phenomena in general in influencing human behavior.This class processes Mental Functioning Ontology of Emotions (MFOEM) using default behavior. - Swiss Centre for Affective Sciences & University at Buffalo + + NFDIcore + National Research Data Infrastructure Ontology (NFDIcore) + The National Research Data Infrastructure (NFDI) initiative has led to the formation of various consortia, each focused on developing a research data infrastructure tailored to its specific domain. To ensure interoperability across these consortia, the NFDIcore ontology has been developed as a mid-level ontology for representing metadata related to NFDI resources, including individuals, organizations, projects, data portals, and more. + Jörg Waitelonis, Oleksandra Bruns, Tabea Tietz, Etienne Posthumus, Hossein Beygi Nasrabadi, Harald Sack OWL - Creative Commons 3.0 - http://purl.obolibrary.org/obo/MFOEM.owl - Medicine - Emotion + 2025-02-07 + Creative Commons 1.0 + https://ise-fizkarlsruhe.github.io/nfdicore/ + Scholarly Knowledge + Research Data Infrastructure + 3.0.0 - - MusicOntology - Music Ontology (MusicOntology) - The Music Ontology Specification provides main concepts and properties fo describing music (i.e. artists, albums and tracks) on the Semantic Web. - Knowledge Media Institute, Open University - RDF - 2013/07/22 - Creative Commons 4.0 - https://github.com/motools/musicontology - Arts and Humanities - Music Theory - 2.1.5 + + MaterialInformation + Material Information Ontology (MaterialInformation) + The Material Information ontology is divided into smaller ontologies (partitions). The partitions are Environment, Geometry, Material Information, Manufacturing Process, Property, Substance, Unit Dimension, Structure, Equation and Physical Constant. + Toshihiro Ashino + OWL + https://github.com/EngyNasr/MSE-Benchmark/blob/main/testCases/secondTestCase/MaterialInformation.owl + Materials Science and Engineering + Materials Science - - CCO - Common Core Ontologies (CCO) - The Common Core Ontologies (CCO) is a widely-used suite of eleven ontologies that consist of logically well-defined generic terms and relations among them reflecting entities across all domains of interest. - TTL - 2024-11-06 - BSD-3-Clause license - https://github.com/CommonCoreOntology/CommonCoreOntologies - General Knowledge - General - 2.0 + + OBI + Ontology for Biomedical Investigations (OBI) + The Ontology for Biomedical Investigations (OBI) helps you communicate clearly about scientific investigations by defining more than 2500 terms for assays, devices, objectives, and more. + OWL + 2025-01-09 + Creative Commons 4.0 + https://github.com/obi-ontology/obi/tree/master + Medicine + Biomedical Investigations - - DCAT - Data Catalog Vocabulary (DCAT) - Data Catalog Vocabulary (DCAT) is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. This document defines the schema and provides examples for its use. DCAT enables a publisher to describe datasets and data services in a catalog using a standard model and vocabulary that facilitates the consumption and aggregation of metadata from multiple catalogs. This can increase the discoverability of datasets and data services. It also makes it possible to have a decentralized approach to publishing data catalogs and makes federated search for datasets across catalogs in multiple sites possible using the same query mechanism and structure. Aggregated DCAT metadata can serve as a manifest file as part of the digital preservation process. - Digital Enterprise Research Institute (DERI) - RDF - 22 August 2024 - W3C Document License - https://www.w3.org/TR/vocab-dcat-3/ - Scholarly Knowledge - Data Catalogs - 3.0 + + CHEMINF + Chemical Information Ontology (CHEMINF) + The chemical information ontology (cheminf) describes information entities about chemical entities. It provides qualitative and quantitative attributes to richly describe chemicals. Includes terms for the descriptors commonly used in cheminformatics software applications and the algorithms which generate them. + Egon Willighagen, Nina Jeliazkova, Ola Spjuth, Valery Tkachenko + OWL + Creative Commons 1.0 + https://terminology.tib.eu/ts/ontologies/CHEMINF + Chemistry + 2.1.0 - - BVCO - Battery Value Chain Ontology (BVCO) - Basically, Battery Value Chain Ontology (BVCO) aims to model processes along the Battery value chain. Processes are holistic perspective elements that transform inputs/educts (matter, energy, information) into output/products (matter, energy, information) with the help of tools (devices, algorithms). They can be decomposed into sub-processes and have predecessor and successor processes. - Lukas Gold, Simon Stier + + EMMOCrystallography + Crystallography Ontology (EMMOCrystallography) + A crystallography domain ontology based on EMMO and the CIF core dictionary. It is implemented as a formal language. TTL Creative Commons Attribution 4.0 International (CC BY 4.0) - https://github.com/Battery-Value-Chain-Ontology/ontology + https://github.com/emmo-repo/domain-crystallography Materials Science and Engineering - Materials Science - 0.4.3 + Crystallography + 0.0.1 - - IOF - Industrial Ontology Foundry (IOF) - The IOF Core Ontology contains notions found to be common across multiple manufacturing domains. This file is an RDF implementation of these notions. The ontology utilizes the Basic Formal Ontology or BFO as a top-level ontology but also borrows terms from various domain-independent or mid-level ontologies. The purpose of the ontology is to serve as a foundation for ensuring consistency and interoperability across various domain-specific reference ontologies the IOF publishes. - IOF Core Working Group + + MatVoc + Materials Vocabulary (MatVoc) + The official ontology produced in the context of the STREAM project. + Tatyana Sheveleva, Javad Chamanara RDF - 2020 - MIT - https://oagi.org/pages/Released-Ontologies - Industry - Manufacturing - 1.0 + 2022-12-12 + MIT License + https://stream-project.github.io/#overv + Materials Science and Engineering + Materials Science + 1.0.0 - - RXNO - Reaction Ontology (RXNO) - RXNO is the name reaction ontology. It contains more than 500 classes representing organic reactions such as the Diels–Alder cyclization. + + DUO + Data Use Ontology (DUO) + DUO is an ontology which represent data use conditions. OWL - 2021-12-16 + 2025-02-17 Creative Commons 4.0 - https://github.com/rsc-ontologies/rxno - Chemistry + https://terminology.tib.eu/ts/ontologies/DUO/ + Scholarly Knowledge + 1.0 - - DOLCE - Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) - The Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) is a foundational ontology that provides a conceptual framework for the formalization of domain ontologies. - Laboratory for Applied Ontology, ISTC-CNR + + EFO + Experimental Factor Ontology (EFO) + The Experimental Factor Ontology (EFO) provides a systematic description of many experimental variables available in EBI databases, and for projects such as the GWAS catalog. It combines parts of several biological ontologies, such as UBERON anatomy, ChEBI chemical compounds, and Cell Ontology. The scope of EFO is to support the annotation, analysis and visualization of data handled by many groups at the EBI and as the core ontology for Open Targets. EFO is developed by the EMBL-EBI Samples, Phenotypes and Ontologies Team (SPOT). OWL - Creative Commons 4.0 - https://www.loa.istc.cnr.it/index.php/dolce/ - Upper Ontology - Linguistics, Cognitive Science + 2025-02-17 + Apache 2.0 + https://www.ebi.ac.uk/efo + Biology and Life Sciences + Biology + 3.75.0 - - FAIR - FAIR Vocabulary (FAIR) - This is the formal vocabulary (ontology) describing the FAIR principles. + + PATO + Phenotype and Trait Ontology (PATO) + An ontology of phenotypic qualities (properties, attributes or characteristics). OWL + 2025-02-01 Creative Commons 4.0 - https://terminology.tib.eu/ts/ontologies/FAIR - Upper Ontology - Data, Metadata - - - Hydra - Hydra Ontology (Hydra) - Hydra is a lightweight vocabulary to create hypermedia-driven Web APIs. By specifying a number of concepts commonly used in Web APIs it enables the creation of generic API clients. - Hydra W3C Community Group - JSONLD - 13 July 2021 - Creative Commons 4.0 - https://www.hydra-cg.com/spec/latest/core/#references - Web and Internet - Web Development + https://terminology.tib.eu/ts/ontologies/PATO + Biology and Life Sciences + Biology + 1.2 \ No newline at end of file diff --git a/ontolearner/VERSION b/ontolearner/VERSION index e516bb9..be05bba 100644 --- a/ontolearner/VERSION +++ b/ontolearner/VERSION @@ -1 +1 @@ -1.4.5 +1.4.7 diff --git a/ontolearner/base/learner.py b/ontolearner/base/learner.py index e0792f6..505039d 100644 --- a/ontolearner/base/learner.py +++ b/ontolearner/base/learner.py @@ -238,7 +238,7 @@ def load(self, model_id: str) -> None: if self.device == "cpu": device_map = "cpu" else: - device_map = "auto" + device_map = "balanced" self.model = AutoModelForCausalLM.from_pretrained( model_id, device_map=device_map, @@ -271,7 +271,10 @@ def generate(self, inputs: List[str], max_new_tokens: int = 50) -> List[str]: Responses include the original input plus generated continuation. """ # Tokenize inputs and move to device - encoded_inputs = self.tokenizer(inputs, return_tensors="pt", padding=True).to(self.model.device) + encoded_inputs = self.tokenizer(inputs, + return_tensors="pt", + padding=True, + truncation=True).to(self.model.device) input_ids = encoded_inputs["input_ids"] input_length = input_ids.shape[1] diff --git a/ontolearner/learner/__init__.py b/ontolearner/learner/__init__.py index a07e851..0baf580 100644 --- a/ontolearner/learner/__init__.py +++ b/ontolearner/learner/__init__.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from .llm import AutoLLMLearner +from .llm import AutoLLMLearner, FalconLLM, MistralLLM from .retriever import AutoRetrieverLearner from .rag import AutoRAGLearner from .prompt import StandardizedPrompting diff --git a/ontolearner/learner/llm.py b/ontolearner/learner/llm.py index f6bf103..e8d373a 100644 --- a/ontolearner/learner/llm.py +++ b/ontolearner/learner/llm.py @@ -13,23 +13,27 @@ # limitations under the License. from ..base import AutoLLM, AutoLearner -from typing import Any +from typing import Any, List import warnings from tqdm import tqdm from torch.utils.data import DataLoader - +import torch +from transformers import Mistral3ForConditionalGeneration +from mistral_common.protocol.instruct.request import ChatCompletionRequest +from mistral_common.tokens.tokenizers.mistral import MistralTokenizer class AutoLLMLearner(AutoLearner): def __init__(self, prompting, label_mapper, + llm: AutoLLM = AutoLLM, token: str = "", max_new_tokens: int = 5, batch_size: int = 10, device='cpu') -> None: super().__init__() - self.llm = AutoLLM(token=token, label_mapper=label_mapper, device=device) + self.llm = llm(token=token, label_mapper=label_mapper, device=device) self.prompting = prompting self.batch_size = batch_size self.max_new_tokens = max_new_tokens @@ -136,3 +140,69 @@ def _non_taxonomic_re(self, data: Any, test: bool = False) -> Any: return self._non_taxonomic_re_predict(dataset=dataset) else: warnings.warn("No requirement for fiting the non-taxonomic-re model, the predict module will use the input data to do the task.") + + +class FalconLLM(AutoLLM): + + def generate(self, inputs: List[str], max_new_tokens: int = 50) -> List[str]: + encoded_inputs = self.tokenizer(inputs, + return_tensors="pt", + padding=True, + truncation=True).to(self.model.device) + input_ids = encoded_inputs["input_ids"] + input_length = input_ids.shape[1] + outputs = self.model.generate( + input_ids, + max_new_tokens=max_new_tokens, + pad_token_id=self.tokenizer.eos_token_id + ) + generated_tokens = outputs[:, input_length:] + decoded_outputs = [self.tokenizer.decode(g, skip_special_tokens=True).strip() for g in generated_tokens] + return self.label_mapper.predict(decoded_outputs) + +class MistralLLM(AutoLLM): + + def load(self, model_id: str) -> None: + self.tokenizer = MistralTokenizer.from_hf_hub(model_id) + if self.device == "cpu": + device_map = "cpu" + else: + device_map = "balanced" + self.model = Mistral3ForConditionalGeneration.from_pretrained( + model_id, + device_map=device_map, + torch_dtype=torch.bfloat16, + token=self.token + ) + if not hasattr(self.tokenizer, "pad_token_id") or self.tokenizer.pad_token_id is None: + self.tokenizer.pad_token_id = self.model.generation_config.eos_token_id + self.label_mapper.fit() + + def generate(self, inputs: List[str], max_new_tokens: int = 50) -> List[str]: + tokenized_list = [] + for prompt in inputs: + messages = [{"role": "user", "content": [{"type": "text", "text": prompt}]}] + tokenized = self.tokenizer.encode_chat_completion(ChatCompletionRequest(messages=messages)) + tokenized_list.append(tokenized.tokens) + max_len = max(len(tokens) for tokens in tokenized_list) + input_ids, attention_masks = [], [] + for tokens in tokenized_list: + pad_length = max_len - len(tokens) + input_ids.append(tokens + [self.tokenizer.pad_token_id] * pad_length) + attention_masks.append([1] * len(tokens) + [0] * pad_length) + + input_ids = torch.tensor(input_ids).to(self.model.device) + attention_masks = torch.tensor(attention_masks).to(self.model.device) + + outputs =self.model.generate( + input_ids=input_ids, + attention_mask=attention_masks, + eos_token_id=self.model.generation_config.eos_token_id, + pad_token_id=self.tokenizer.pad_token_id, + max_new_tokens=max_new_tokens, + ) + decoded_outputs = [] + for i, tokens in enumerate(outputs): + output_text = self.tokenizer.decode(tokens[len(tokenized_list[i]):]) + decoded_outputs.append(output_text) + return self.label_mapper.predict(decoded_outputs) diff --git a/pyproject.toml b/pyproject.toml index 4a2418b..4422243 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,6 +29,7 @@ transformers = "^4.56.0" sentence-transformers = "^5.1.0" dspy = "^2.6.14" bitsandbytes="^0.45.1" +mistral-common = { version = "^1.8.5", extras = ["sentencepiece"] } [tool.poetry.dev-dependencies] ruff = "*" diff --git a/requirements.txt b/requirements.txt index 2d3e66e..3ce19f7 100644 --- a/requirements.txt +++ b/requirements.txt @@ -19,3 +19,4 @@ torch~=2.8.0 sentence-transformers~=5.1.0 scikit-learn~=1.6.1 bitsandbytes~=0.45.1 +mistral-common[sentencepiece]~=1.8.5