eLifeBioinformaticsPeer-reviewed journal article
Wikidata as a FAIR knowledge graph for the life sciences
Andra WaagmeesteriD, Gregory S. StuppiD, Sebastian Burgstaller-MuehlbacheriD, Benjamin M. GoodiD, Malachi GriffithiD, Obi L. GriffithiD, Kristina HanspersiD, Henning HermjakobiD, Toby HudsoniD, Kevin HybiskeiD, Sarah KeatingiD, Magnus ManskeiD, Michael MayersiD, Daniel MietcheniD, Elvira MitrakaiD, Alexander R. PicoiD, Tim PutmaniD, Anders RiuttaiD, Núria Queralt-RosiñachiD, Lynn M. SchrimliD, Thomas M. A. ShafeeiD, Denise SlenteriD, Ralf StephaniD, Katherine ThorntoniD, Ginger TsuengiD, , Andrew I. SuiD
- Citations
- 154
- FWCI
- 8.91
- Field percentile
- top 1%
Abstract
Wikidata is a community-maintained knowledge base that epitomizes the FAIR principles of Findability, Accessibility, Interoperability, and Reusability. Here, we describe the breadth and depth of biomedical knowledge contained within Wikidata, assembled from primary knowledge repositories on genomics, proteomics, genetic variants, pathways, chemical compounds, and diseases. We built a collection of open-source tools that simplify the addition and synchronization of Wikidata with source databases. We furthermore demonstrate several use cases of how the continuously updated, crowd-contributed knowledge in Wikidata can be mined. These use cases cover a diverse cross section of biomedical analyses, from crowdsourced curation of biomedical ontologies, to phenotype-based diagnosis of disease, to drug repurposing.
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