Last version: 2025-01-03
Dimensions is a database of abstracts and citations and of research grants, which links grants to resulting publications, clinical trials and patents. Dimension is part of Digital Science (or Digital Science & Research Solutions Ltd) - a technology company headquartered London, United Kingdom.
| Name | Dimensions |
|---|---|
| Website | https://app.dimensions.ai/discover/publication |
| Owner | Digital Science & Research Solutions Ltd |
| Owner type | Private company |
| Owner country | UK |
| Launch year | 2018 |
| Scope | Any |
| Number of items | 140M Publications |
| Access for index users | Free for Dimensions (account needed) Subscription fees for advanced functionalities (API access, etc.) |
| Access for index data providers | Free (via registered datasources only) |
| Documentation | https://figshare.com/articles/online_resource/A_Guide_to_the_Dimensions_Data_Approach/5783094?file=42590014 |
| Application form for providers | None |
| Service type | Fully automated aggregator |
|---|---|
| Content type | Publications, Data Sets, Grants, Patents, Clinical Trials, Policy Documents, Technical Reports |
| Content language | Any |
| Content geographical provenance | Any |
| Indexing level for publications | Articles, journals |
| Full text | Link to the Full text |
| Index sources | Crossref, PubMed, Europe PubMed Central, arXiv, J-STAGE and direct contacts with more than 130 publishers |
| Supported standards | Not communicated |
| Bibliodiversity support | Majority of english content |
Additional services
Dimensions Analytics: (https://www.dimensions.ai/products/all-products/dimensions-analytics/=)
Dimensions API: (https://www.dimensions.ai/products/all-products/dimensions-api/)
Dimensions Knowledge Graph: (https://www.dimensions.ai/products/all-products/dimensions-knowledge-graph/)
By joining one of the datasources mentionned in the index sources
Data Collection Process
Collection of data from other databases.
The data is converted to a common data model, cleaned, and then enriched so it is ready for use. The enrichment steps include disambiguation of people (“Researchers”) and Organizations, and categorizing the data into topics (“Categories”) through machine-learning based algorithmic classification.
Editorial minimum requirements
None
Technical minimum requirements
Metadata standard
Not communicated (depends on index sources)
Data file format
Not communicated (depends on index sources)
Metadata file format
Not communicated (depends on index sources)
Metadata mandatory fields
Not communicated (reuse of the minimum metadata of index sources)
Editorial additional specifications
Same requirements as the index sources
Technical additional specifications
Metadata recommended fields
Depends on index sources.
For example, recommandations when the index source is Crossref:
Full author / Contributo information
ORCID IDs
Author affiliations
Abstracts
References
Structured funding information and grants references
Metadata optional fields
none
SEO/UX requirements
Not communicated