A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses

Abstract

Background Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a “commons.” Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons and uses unique identifiers to link knowledge in other knowledge bases. However, Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modeled with entity schemas represented by Shape Expressions. Results As a telling example, we describe the process of aligning resources on the genomes and proteomes of the SARS-CoV-2 virus and related viruses as well as how Shape Expressions can be defined for Wikidata to model the knowledge, helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable is demonstrated by integrating data from NCBI (National Center for Biotechnology Information) Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates. Conclusions Although this workflow is developed and applied in the context of the COVID-19 pandemic, to demonstrate its broader applicability it was also applied to other human coronaviruses (MERS, SARS, human coronavirus NL63, human coronavirus 229E, human coronavirus HKU1, human coronavirus OC4).

WikiProject Clinical Trials for Wikidata

“…For example, we had no need to develop models for researchers, organizations, medical conditions, or drugs, because the Wikidata community had already modeled these things and developed precedents for data import. Other projects have also shared methods for importing research into Wikidata, such as for medical resources[43] and for researchers themselves. [44] We could therefore anticipate that by aligning the WikiProject Clinical Trials data model with properties used in other projects, synergies such as links between principal investigators and their institutional affiliations would arise.…”

BridgeDb and Wikidata: a powerful combination generating interoperable open research (BridgeDb)

“…extending the functionality of the webservice to deploy identifier (ID) mapping databases effortlessly, by extending the support of creating ID mappings databases from Wikidata (Waagmeester et al 2021, Waagmeester et al 2020, and 3.…”

“…We intend to widen the scope of ELIXIR resources supported in the ID mapping databases, to make more resources interoperable (and therefore more FAIR). Here, we will increasingly use Wikidata and its international scientific collaborations (Waagmeester et al 2021, Waagmeester et al 2020). These mapping databases will continue to be released via public archives (e.g.…”

MIKB: A manually curated and comprehensive knowledge base for myocardial infarction

“…Furthermore, the links of GO [26] and KEGG [27] were provided for GO terms and KEGG pathways involved in MI-related genes, respectively. We also provided links to Wikidata [28] and ChEMBL [29] for gene-related drugs.…”