A protocol for adding knowledge to Wikidata, a case report

Andra Waagmeester; Egon L. Willighagen; Andrew I. Su; Martina Kutmon; Jose Emilio Labra Gayo; Daniel Fernández-Álvarez; Peter J. Schaap; Lisa M. Verhagen; Jasper J. Koehorst

The Gene Wiki project has been tearing down the different research silos on genetics, biological processes, related diseases and associated drugs (10) . In contrast to legacy databases, where data models follow a relational data schema of connected tables, Wikidata ( https://wikidata.org/ ) uses statements to store facts (see Figure 1 ) (10) (11) (12) (13) . This model of statements aligns well with the RDF triple model of the semantic web and the content of Wikidata is also serialized as Resource Description Framework (RDF) triples (14, 15) , acting as stepping stone for data resources to the semantic web. Through its SPARQL endpoint other nodes in the semantic web, using either mappings between these resources or through federated SPARQL queries (16) . Automated editing of Wikidata simplifies a lot of things, however, the quality control of that process must be monitored carefully. This requires a clear data schema that allows the various resources to be linked with additional provenance. This schema describes the key concepts required for the integrations of the resources we are interested in: NCBI Taxonomy (17) , NCBI Gene (18) , UniProt (19) , the Protein Data Bank (PDB) (20) , WikiPathways (21) , and PubMed. Therefore , the key elements for which we need a model include viruses, virus strains, virus genes, and virus proteins. The first two provide the link to taxonomies, the models for genes and proteins link to UniProt, PDB, and WikiPathways. These key concepts are also required to annotate research output such as journal articles and datasets related to these topics. Wikidata calls such keywords 'main subjects'. The introduction of this model and the actual SARS-CoV-2 genes and proteins in Wikidata enables the integration of these resources.