FHIR-Ontop-OMOP: Querying OMOP clinical databases as FHIR-compliant Clinical Knowledge Graphs Christopher G. Chute 1 7 Guoqian Jiang jiang.guoqian@mayo.edu 2 7 Guohui Xiao guohui.xiao@uib.no 3 5 7 Emily Pfaff 4 7 Eric P`rud'hommeaux 0 7 David Booth 6 7 Deepak K. Sharma 2 7 Nan Huo 2 7 Yue Yu 2 7 Nansu Zong 2 7 Kathryn J. Ruddy 2 7 Ontopic S.r.l. 7 Italy 7 Janeiro Digital , Boston, MA , USA Johns Hopkins University , Baltimore, MD , USA Mayo Clinic , Rochester, MN , USA University of Bergen , Norway University of North Carolina , Chapel Hill, NC , USA University of Oslo , Norway Yosemite Project , Somerville, MA , USA like W3C languages RDF , SPARQL, OWL, and the ShEx language

The Observational Medical Outcomes Partnership (OMOP)1 is an open community data standard, designed to standardize the structure and content of observational data and to enable efficient analyses that can produce reliable evidence. OMOP relies on relational databases and many datasets are already available in the OMOP format. The Fast Healthcare Interoperability Resources (FHIR)2 is a more recent effort in the Semantic Web community, which relies on technologies OMOP and FHIR is an important research topic.

 FHIR-Ontop-OMOP is an open-source system published at Github 4 under Apache 2 license -

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virtualize FHIR Ontology OMOP-FHIR Mapping OMOP database

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FHIR ShEx (a) System architecture (b) The SPARQL endpoint Data Model. . Instructions on how to use these datasets are described in detail in the README file on Github.

The system architecture is illustrated in Figure 1a. It consists of the following modules (from the bottom to up): ( 1 ) an input module that takes input from the FHIR model ontology, the OMOP data repository, and OMOP-FHIR mappings represented by a mapping template; ( 2 ) a CKG generation module that relies on the Ontop system to generate a virtual CKG; and (3) a semantic query module that establishes SPARQL endpoints with reasoning capability.

Once the system is running, users can pose SPARQL queries to the virtual Clinical Knowledge Graph following the FHIR data model. The query module relies on the query answering interface of Ontop. The Ontop system translates SPARQL queries over the CKG to SQL queries over the OMOP database, using the FHIR ontology and FHIR-OMOP mapping. Figure 1b shows a SPARQL query example against the MIMIC III OMOP database, and its answers. Further example queries are also provided.

 [1] G. Xiao , E. Pfaff , E. Prud'hommeaux, D. Booth , D. K. Sharma , N. Huo , Y. Yu , N. Zong , K. J. Ruddy , C. G. Chute , G. Jiang, FHIR- Ontop-OMOP: Building clinical knowledge graphs in FHIR RDF with the OMOP common data model , Journal of Biomedical Informatics 134 ( 2022 ) 104201 . [2] G. Xiao , D. Lanti , R. Kontchakov , S. Komla-Ebri , E. Güzel-Kalayci , L. Ding , J. Corman , B. Cogrel , D. Calvanese , E. Botoeva, The virtual knowledge graph system Ontop , in: International Semantic Web Conference (ISWC) , volume 2 , 2020 , pp. 259 - 277 .