Ontology Integration for Discovering Bioresources Contributing
                         to Medical Science Research
                         Tatsuya Kushida 1, Daiki Usuda 1, Toyoyuki Takada 1, Yuki Yamagata 2 and Hiroshi Masuya 1
                         1
                                RIKEN BioResource Research Center, Tsukuba, Japan
                         2
                                RIKEN Center for Biosystems Dynamics Research, Kobe, Japan


                                                               Abstract
                                                               We integrated the RIKEN bioresource RDF data with external public RDF data, such as OMA,
                                                               and disease ontologies, such as DOID and MONDO. Thus, we can discover the resources
                                                               relevant to diseases by performing a SPARQL query for the integrated RDF graph.

                                                               Keywords 1
                                                               Bioresource, Data Integration, Knowledge Graph, SPARQL


                         1. Introduction                                                                                                  SPARQL query for the knowledge graph
                                                                                                                                          (https://knowledge.brc.riken.jp/sparql).
                             RIKEN BioResource Research Center is one
                         of the largest comprehensive bioresource centers
                         that provide various kinds of bioresources such as
                         experimental animals (e.g., gene-modified mice),
                         cell materials (e.g., iPS cells), and DNA materials
                         (e.g., human cDNA clones). One of its missions is
                         to contribute to developing human health and
                         medical science research through the RIKEN
                         bioresources. We unitarily manage information
                         on the bioresources and provide it. In addition, we                                                              Figure 1: The bioresource RDF Graph integrated
                         develop the bioresource RDF data to promote data                                                                 with external RDF data and ontologies
                         sharing and improve interoperability.
                                                                                                                                          3. Reference
                         2. External data and ontology
                            integration    and     discovering                                                                            [1] Altenhoff AM, Train CM, Gilbert KJ, et al.
                                                                                                                                              OMA orthology in 2021: website overhaul,
                            bioresources relevant to diseases                                                                                 conserved isoforms, ancestral gene order and
                                                                                                                                              more. Nucleic          Acids            Res.
                            We integrated the bioresource RDF data with                                                                       2021;49(D1):D373-D379.
                         OMA RDF data [1], DisGeNET RDF data, and                                                                             doi:10.1093/nar/gkaa1007
                         disease ontologies, such as DOID, and MONDO
                         (Figure 1), to be able to simultaneously discover
                         mouse resources, cell materials, and DNA
                         materials relevant to diseases by performing a


                         ICBO 2022: International Conference on Biomedical Ontology,
                         September 25-28, 2022, Ann Arbor, MI, USA
                         EMAIL: tatsuya.kushida@riken.jp (A. 1); daiki.usuda@riken.jp
                         (A. 2); toyoyuki.takada@riken.jp (A. 3); yuki.yamagata@riken.jp
                         (A. 4); hiroshi.masuya@riken.jp (A. 5)
                         ORCID: 0000-0002-0784-4113 (A. 1); 0000-0001-6796-2085 (A.
                         3); 0000-0002-9673-1283 (A. 4); 0000-0002-3392-466X (A. 5)
                                                           © 2022 Copyright for this paper by its authors. Use permitted under Creative
                                                           Commons License Attribution 4.0 International (CC BY 4.0).
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