RT Journal Article
SR Electronic
T1 Wikidata as a FAIR knowledge graph for the life sciences
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 799684
DO 10.1101/799684
A1 Andra Waagmeester
A1 Gregory Stupp
A1 Sebastian Burgstaller-Muehlbacher
A1 Benjamin M. Good
A1 Malachi Griffith
A1 Obi Griffith
A1 Kristina Hanspers
A1 Henning Hermjakob
A1 Toby S. Hudson
A1 Kevin Hybiske
A1 Sarah M. Keating
A1 Magnus Manske
A1 Michael Mayers
A1 Daniel Mietchen
A1 Elvira Mitraka
A1 Alexander R. Pico
A1 Timothy Putman
A1 Anders Riutta
A1 Núria Queralt-Rosinach
A1 Lynn M. Schriml
A1 Thomas Shafee
A1 Denise Slenter
A1 Ralf Stephan
A1 Katherine Thornton
A1 Ginger Tsueng
A1 Roger Tu
A1 Sabah Ul-Hasan
A1 Egon Willighagen
A1 Chunlei Wu
A1 Andrew I. Su
YR 2020
UL http://biorxiv.org/content/early/2020/02/11/799684.abstract
AB 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.