Merge branch 'main' into main

Author: blahner

datasets/askap.yaml

@@ -0,0 +1,49 @@
+Name: ASKAP Radio Telescope
+Description: | 
+
+   ASKAP is the CSIRO’s newest radio telescope. It is situated at the Inyarrimanha Ilgari Bundara, the CSIRO Murchison Radio-astronomy Observatory on Wajarri Yamaji Country in the Murchison region of Western Australia, about 800 km north of Perth. 
+  
+   ASKAP consists of 36 12m dishes, spread-out as far as 6km apart. It uses a new technology called Phased Array Feeds (PAFs), which allows it to see more of the sky at once. This novel technology allows ASKAP to achieve extremely high survey speed, making it one of the best instruments in the world for mapping the sky at radio wavelengths. 
+
+   Initial dataset available - The Rapid ASKAP Continuum Survey (RACS)
+
+   RACS is the first large-area survey completed with ASKAP. This survey is revolutionary as the entire sky was observed in a matter of weeks, doing what previously took telescopes years to do. RACS initially covered the whole sky at 890 MHz (RACS-Low), and has since expanded to ASKAP’s other bands (1.4 and 1.7 GHz). RACS also covers the sky in multiple epochs, with a second epoch of RACS-Low and RACS-Mid obtained and processed.  
+
+   RACS provides astronomers with a unique opportunity to study the radio sky and radio populations, in particular supermassive blackholes (active galactic nuclei) and their role in galaxy evolution. The multi-epoch approach also allows a study of the transient sky and testing and verification of calibration methods. The large area allows for cosmological studies, such as a search for anisotropy in the galaxy population, or cosmic dipole. 
+
+Documentation: https://www.atnf.csiro.au/facilities/askap-radio-telescope/
+Contact: [email protected]
+ManagedBy: "[Australia Telescope National Facility, CSIRO](http://www.atnf.csiro.au/)"
+Citation: Please see the [ATNF acknowledgement page](https://www.atnf.csiro.au/resources/publications/atnf-publication-acknowledgement-statements/) for full citation instructions. 
+UpdateFrequency: Roughly quarterly
+Tags:
+  - aws-pds
+  - astronomy
+  - archives
+License: CC-BY-4.0. Attribution required for refereed scientific papers.
+Resources:
+  - Description: The Rapid ASKAP Continuum Survey (RACS) Public Data Releases
+    ARN: arn:aws:s3:::askap/racs
+    Region: ap-southeast-2
+    Type: S3 Bucket
+    RequesterPays: False
+  - Description: Notifications for new Rapid ASKAP Continuum Survey (RACS) data
+    ARN: arn:aws:sns:ap-southeast-2:336305517014:racs-low1-object_created
+    Region: sp-southeast-2
+    Type: SNS Topic
+DataAtWork:
+  Tutorials:
+    - Title: CSIRO ASKAP Science Data Archive User Guide
+      URL: https://research.csiro.au/casda/casda-user-guide/
+      AuthorName: CSIRO, ATNF
+    - Title: Rapid Askap Continuum Survey (RACS) Home Page
+      URL: https://research.csiro.au/racs/
+      AuthorName: CSIRO, ATNF
+  Tools & Applications:
+  Publications:
+    - Title: ASKAP Publication List
+      URL: https://www.atnf.csiro.au/facilities/askap-radio-telescope/publications/
+      AuthorName: various, list maintained by CSIRO, ATNF
+    - Title: ASKAP System Description paper
+      URL: https://doi.org/10.1017/pasa.2021.1
+      AuthorName: Hotan, A. et al. 

datasets/aws-public-blockchain.yaml

@@ -13,6 +13,7 @@ Description: >
   - XRP Ledger              - SonarX  - <code>s3://aws-public-blockchain/v1.1/sonarx/xrp/</code><br>
   - Stellar(<a href="https://developers.stellar.org/docs/learn/fundamentals/data-format/xdr" rel="noopener noreferrer">XDR files</a>)              - Stellar - <code>s3://aws-public-blockchain/v1.1/stellar/</code><br>
   - The Open Network (TON)  - TON - <code>s3://aws-public-blockchain/v1.1/ton/</code><br>
+  - Cronos                  - Cronos - <code>s3://aws-public-blockchain/v1.1/cronos/</code><br>
   </br> 
 
   <h4>Become a Data Provider</h4>
@@ -24,6 +25,7 @@ Contact: [email protected]
 ManagedBy: "[Amazon Web Services](https://aws.amazon.com/)"
 UpdateFrequency: New data is delivered daily to the current date folders Parquet files.
 Tags:
+  - aws-pds
   - blockchain
   - web3
 License: https://github.com/aws-samples/digital-assets-examples/blob/main/LICENSE

datasets/clinical-ultrasound-image-data.yaml

@@ -0,0 +1,20 @@
+Name: Clinical Ultrasound Image Repository
+Description: Generic Clinical Ultrasound Data from Random Subjects acquired for Clinical Reasons, to be used for Developing Artificial Intelligence Applications. This dataset is complete with 2000 studies from 2000 subjects (one third each from abdominal, cardiac, and OB/GYN cases)
+Documentation: https://clinical-ultrasound-image-repository.s3.amazonaws.com/index.html
+Contact: [email protected]
+ManagedBy: "[MONAI Development Team](https://github.com/Project-MONAI/MONAI)"
+UpdateFrequency: This is a static dataset; however, tutorials and resources will be updated as they are developed.
+Tags:
+  - medicine
+  - medical imaging
+  - machine learning
+  - life sciences
+  - aws-pds
+License: "[CC-BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)"
+Resources:
+  - Description: Clinical Ultrasound Image Repository
+    ARN: arn:aws:s3:::clinical-ultrasound-image-repository
+    Region: us-west-2
+    Type: S3 Bucket
+    Explore:
+    - "[Browse Bucket](https://clinical-ultrasound-image-repository.s3.amazonaws.com/download.html)"

datasets/cmas-data-warehouse.yaml

@@ -73,6 +73,12 @@ Resources:
     Type: S3 Bucket
     Explore:
     - '[Browse Bucket](https://cmaq-12us4-cracmm3-modeling-platform-2023.s3.amazonaws.com/index.html)'
+  - Description: CMAQ Model Versions 5.5 CRACMM2 Input Data (2022r1) -- 12/22/2021 - 12/31/2022 12km CONUS
+    ARN:  arn:aws:s3::::::cmaq-12us1-cracmm2-modeling-platform-2022
+    Region: us-east-1
+    Type: S3 Bucket
+    Explore:
+    - '[Browse Bucket](https://cmaq-12us1-cracmm2-modeling-platform-2022.s3.amazonaws.com/index.html)'
   - Description: EPA 2022 Modeling Platform
     ARN: arn:aws:s3:::epa-2022-modeling-platform
     Region: us-east-1

datasets/colorado-elevation-data.yaml

@@ -2,7 +2,7 @@ Name: State of Colorado Elevation Data
 Description: The State of Colorado has gathered public historical elevation data.
 Documentation: https://docs.google.com/document/d/1HMO-d4cCrBvFa2F6-N3lhP6rkezlvBmSUFA5S8t_ekQ/edit?usp=sharing
 Contact: [email protected]
-ManagedBy: State of Colorado Governor's Office of Information Technology (OIT) GIS team
+ManagedBy: State of Colorado Governors Office of Information Technology OIT GIS team
 UpdateFrequency: Periodically
 Tags:
   - aws-pds

datasets/colorado-imagery.yaml

@@ -2,7 +2,7 @@ Name: State of Colorado Imagery
 Description: The State of Colorado has gathered public historical imagery ranging from 2005 to 2021.
 Documentation: https://docs.google.com/document/d/1YDHignUj9lQTMw2J-SqA96MTP8KmJYtk2ZKKC2ZYuPE/edit?usp=sharing
 Contact: [email protected]
-ManagedBy: State of Colorado Governor's Office of Information Technology (OIT) GIS team
+ManagedBy: State of Colorado Governors Office of Information Technology OIT GIS team
 UpdateFrequency: Periodically
 Collabs:
   ASDI:

datasets/deepdrug-dpeb.yaml

@@ -0,0 +1,38 @@
+Name: DeepDrug Protein Embeddings Bank (DPEB)
+Description: DPEB is a multimodal database of human protein embeddings integrating four biologically complementary representations—AlphaFold2, BioEmbeddings, ESM-2, and ProtVec—designed for enhanced protein-protein interaction prediction and functional classification.
+Documentation: https://github.com/deepdrugai/DPEB
+Contact: https://github.com/deepdrugai/DPEB/issues
+ManagedBy: "Louisiana State University"
+UpdateFrequency: Initial release; maintained for at least 2 years with updates planned based on new embedding models and protein coverage.
+Tags:
+  - bioinformatics
+  - protein
+  - structural biology
+  - machine learning
+  - life sciences
+  - aws-pds
+License: MIT
+Citation: "Sajol MSI et al. DeepDrug Protein Embeddings Bank (DPEB) was accessed on [DATE] at https://registry.opendata.aws/dpeb"
+Resources:
+  - Description: Multimodal human protein embeddings (AlphaFold2, BioEmbeddings, ESM-2, ProtVec) with JSONL-formatted metadata containing FASTA, UniProt IDs, and embeddings.
+    ARN: arn:aws:s3:::deepdrug-dpeb
+    Region: us-west-2
+    Type: S3 Bucket
+DataAtWork:
+  Tutorials:
+    - Title: Aggregating and Clustering AlphaFold2 Embeddings from DPEB
+      URL: https://github.com/deepdrugai/DPEB/tree/main
+      AuthorName: Md. Saiful Islam Sajol
+      AuthorURL: https://github.com/deepdrugai
+  Tools & Applications:
+    - Title: DPEB Explorer Tool
+      URL: https://github.com/deepdrugai/DPEB
+      AuthorName: DeepDrug Lab
+      AuthorURL: https://github.com/deepdrugai
+  Publications:
+    - Title: A Multimodal Human Protein Embeddings Database - DeepDrug Protein Embeddings Bank (DPEB)
+      URL: https://doi.org/10.XXXX/nar.dpeb2025
+      AuthorName: Sajol MSI, Rajasekaran M, Bess A, Alvin C, Mukhopadhyay S
+      AuthorURL: https://github.com/deepdrugai/DPEB
+ADXCategories:
+  - Healthcare & Life Sciences Data

datasets/depmap-omics-ccle.yaml

@@ -0,0 +1,71 @@
+Name: The Cancer Dependency Map (DepMap) Cancer Cell Line Encyclopedia (CCLE) Dataset
+Description: This dataset consists of whole genome sequencing (WGS), whole exome sequencing (WES), and RNA sequencing files generated from ~1000 cancer cell lines described in Ghandi et al., 2019.
+Documentation: https://github.com/broadinstitute/depmap-omics-ccle
+Contact: https://forum.depmap.org
+ManagedBy: "[Cancer Data Science](https://cancerdatascience.org/), [Broad Institute](https://www.broadinstitute.org/)"
+UpdateFrequency: occasionally (as additional sequencings are generated for publicly-releasible CCLE models)
+Tags:
+  - aws-pds
+  - bam
+  - biology
+  - bioinformatics
+  - cancer
+  - genetic
+  - genomic
+  - Homo sapiens
+  - life sciences
+  - short read sequencing
+  - transcriptomics
+  - whole exome sequencing
+  - whole genome sequencing
+License: https://grants.nih.gov/policy-and-compliance/policy-topics/sharing-policies/accessing-data/using-genomic-data
+Citation: Ghandi, Huang, Jané-Valbuena et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature 569, 503–508 (2019). https://doi.org/10.1038/s41586-019-1186-3
+Resources:
+  - Description: CRAM/BAM files (and their corresponding CRAI/BAI indexes) for RNA, WES, and WGS samples released by The Cancer Dependency Map (DepMap) as part of the Cancer Cell Line Encyclopedia (CCLE) project
+    ARN: arn:aws:s3:::depmap-omics-ccle
+    Region: us-east-1
+    Type: S3 Bucket
+  - Description: Notifications for new depmap-omics-ccle data
+    ARN: arn:aws:sns:us-east-1:019511184952:depmap-omics-ccle-object_created
+    Region: us-east-1
+    Type: SNS Topic
+DataAtWork:
+  Tutorials:
+    - Title: DepMap Omics CCLE data on the AWS Open Data Registry
+      URL: https://github.com/broadinstitute/depmap-omics-ccle
+      AuthorName: Devin McCabe
+  Tools & Applications:
+    - Title: The Cancer Dependency Map (DepMap)
+      URL: https://depmap.org
+      AuthorName: Arafeh, Shibue, Dempster et al.
+    - Title: Cancer Cell Line Encyclopedia (CCLE)
+      URL: https://sites.broadinstitute.org/ccle
+      AuthorName: Ghandi, Huang, Jané-Valbuena et al.
+  Publications:
+    - Title: Next-generation characterization of the Cancer Cell Line Encyclopedia
+      URL: https://www.nature.com/articles/s41586-019-1186-3
+      AuthorName: Ghandi, Huang, Jané-Valbuena et al.
+    - Title: The present and future of the Cancer Dependency Map
+      URL: https://www.nature.com/articles/s41568-024-00763-x
+      AuthorName: Arafeh, Shibue, Dempster et al.
+      AuthorURL: https://depmap.org
+    - Title: Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal
+      URL: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-03020-w
+      AuthorName: Krill-Burger, Dempster, Borah et al.
+    - Title: Genetic dependencies associated with transcription factor activities in human cancer cell lines
+      URL: https://www.sciencedirect.com/science/article/pii/S2211124724005035
+      AuthorName: Thatikonda, Supper, Wachter et al.
+    - Title: Bridging the gap between cancer cell line models and tumours using gene expression data
+      URL: https://www.nature.com/articles/s41416-021-01359-0
+      AuthorName: Noorbakhsh, Vazquez & McFarland
+    - Title: Integrated cross-study datasets of genetic dependencies in cancer
+      URL: https://www.nature.com/articles/s41467-021-21898-7
+      AuthorName: Pacini, Dempster, Boyle et al.
+    - Title: Machine learning multi-omics analysis reveals cancer driver dysregulation in pan-cancer cell lines compared to primary tumors
+      URL: https://www.nature.com/articles/s42003-022-04075-4
+      AuthorName: Sanders, Chandra, Zebarjadi et al.
+    - Title: "The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks"
+      URL: https://link.springer.com/article/10.1186/s13059-023-02877-1
+      AuthorName: Ben Guebila, Wang, Lopes-Ramos et al.
+ADXCategories:
+  - Healthcare & Life Sciences Data

datasets/dmi-danra-05.yaml

@@ -0,0 +1,50 @@
+Name: Danish Meteorological Institute (DMI) Reanalysis dataset v0.5
+Description: DANRA is a high-resolution meteorological reanalysis dataset for Denmark and Northwestern Europe covering the period September 1990 to December 2023
+Documentation: https://dmidk.github.io/danradocs/intro.html
+Contact: https://www.dmi.dk/kontakt
+ManagedBy: "[Danish Meteorological Institute](https://www.dmi.dk/)"
+UpdateFrequency: Not updated
+Collabs:
+  ASDI:
+    Tags:
+      - climate
+      - weather
+Tags:
+  - aws-pds
+  - air temperature
+  - atmosphere
+  - geospatial
+  - global
+  - land
+  - meteorological
+  - near-surface air temperature
+  - near-surface relative humidity
+  - near-surface specific humidity
+  - model
+  - water
+  - weather
+  - zarr
+License: DMI Reanalysis dataset v0.5 is distributed under the [Creative Commons License CC BY 4.0](https://creativecommons.org/licenses/by/4.0/legalcode.en)
+Resources:
+  - Description: DMI Reanalysis dataset v0.5
+    ARN: arn:aws:s3:::dmi-danra-05
+    Region: eu-north-1
+    Type: S3 Bucket
+DataAtWork:
+  Tutorials:
+    - Title: Looking at distributions
+      URL: https://dmidk.github.io/danradocs/notebooks/distributions.html
+      NotebookURL: https://dmidk.github.io/danradocs/_sources/notebooks/distributions.ipynb
+      AuthorName: Danish Meteorological Institute
+      AuthorURL: https://www.dmi.dk/
+      Services:
+        - Amazon S3
+    - Title: DANRA figures
+      URL: https://dmidk.github.io/danradocs/notebooks/paper-figures.html
+      NotebookURL: https://dmidk.github.io/danradocs/_sources/notebooks/paper-figures.ipynb
+      AuthorName: Danish Meteorological Institute
+      AuthorURL: https://www.dmi.dk/
+      Services:
+        - Amazon S3
+ADXCategories:
+  - Environmental Data

datasets/e11bio-prism.yaml

@@ -0,0 +1,62 @@
+Name: E11bio PRISM
+Description: |
+  This dataset was generated using E11.bio's PRISM technology (Protein Reconstruction and Identification through Multiplexing),
+  a platform that combines viral barcoding, expansion microscopy, and iterative immunolabeling for large-scale neuronal reconstruction.
+
+  Neurons in the mouse hippocampal CA3 were transduced with a library of adeno-associated viruses (AAVs)
+  encoding diverse “protein bits”—small epitope tags that act as combinatorial barcodes. 
+  Tissue was then processed with an expansion microscopy protocol, physically enlarging the sample ~5×
+  to achieve an effective voxel size of ~35 × 35 × 80 nm.
+  Across multiple cycles of staining, imaging, and antibody stripping, the same expanded tissue was repeatedly labeled,
+  enabling iterative immunostaining for dozens of molecular targets.
+
+  The dataset includes:
+  1) Light microscopy data of multiplexed brain tissue
+  2) Segmentations of cell morphology and protein expression in the tissue
+  3) Files for faster visualization of the data (e.g. precomputed format)
+  4) Additional supporting files (e.g. model predictions, manual annotations etc.)
+Documentation: https://github.com/e11bio/e11-open-data
+Contact: [email protected]
+ManagedBy: "[E11.bio](https://e11.bio)"
+UpdateFrequency: As required
+Tags:
+  - bioinformatics
+  - biology
+  - brain images
+  - cell imaging
+  - computer vision
+  - fluorescence imaging
+  - high-throughput imaging
+  - image processing
+  - imaging
+  - ion channels
+  - life sciences
+  - machine learning
+  - microscopy
+  - morphological reconstructions
+  - Mus musculus
+  - neurobiology
+  - neuroimaging
+  - neuroscience
+  - protein
+  - segmentation
+  - zarr
+  - aws-pds
+License: https://e11.bio/terms-of-use
+Resources:
+  - Description: Data files in a public bucket
+    ARN: arn:aws:s3:::e11bio-prism
+    Region: us-east-1
+    Type: S3 Bucket
+DataAtWork:
+  Tutorials:
+    - Title: E11.Bio PRISM OpenData
+      URL: https://github.com/e11bio/e11-open-data
+      NotebookURL:
+      AuthorName: Arlo Sheridan & Johan Winnubst
+      AuthorURL: https://e11.bio/team
+  Tools & Applications:
+    - Title: Volara 
+      URL: https://github.com/e11bio/volara
+      AuthorName: Arlo Sheridan & Will Patton
+      AuthorURL: https://e11.bio/team