=Paper=
{{Paper
|id=Vol-3415/paper-41
|storemode=property
|title=FHIR-Ontop-OMOP: Querying OMOP clinical databases as FHIR-compliant Clinical Knowledge
                                       Graphs
|pdfUrl=https://ceur-ws.org/Vol-3415/paper-41.pdf
|volume=Vol-3415
|dblpUrl=https://dblp.org/rec/conf/swat4ls/0001PPBSHYZRCJ23
}}
==FHIR-Ontop-OMOP: Querying OMOP clinical databases as FHIR-compliant Clinical Knowledge
                                       Graphs==
<pdf width="1500px">https://ceur-ws.org/Vol-3415/paper-41.pdf</pdf>
<pre>
FHIR-Ontop-OMOP:
Querying
OMOP
clinical
databases
as
FHIR-compliant
Clinical
Knowledge
Graphs
Guohui Xiao1,2,3, Emily Pfaff4, Eric P`rud’hommeaux5, David Booth6,
Deepak K. Sharma7, Nan Huo7, Yue Yu7, Nansu Zong7, Kathryn J. Ruddy7,
Christopher G. Chute8 and Guoqian Jiang7
1
 University of Bergen, Norway
2
 University of Oslo, Norway
3
 Ontopic S.r.l., Italy
4
  University of North Carolina, Chapel Hill, NC, USA
5
 Janeiro Digital, Boston, MA, USA
6
 Yosemite Project, Somerville, MA, USA
7
 Mayo Clinic, Rochester, MN, USA
8
 Johns Hopkins University, Baltimore, MD, USA




1. Introduction
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
like W3C languages RDF, SPARQL, OWL, and the ShEx language. Interoperability between
OMOP and FHIR is an important research topic.
   In this demo, we present the FHIR-Ontop-OMOP system for querying clinical OMOP databases
as Clinical Knowledge Graphs (CKGs) [1]. To be more precise, the system exposes the OMOP
data as a queryable Knowledge Graph compliant with the HL7 FHIR standard using the Ontop3
Virtual Knowledge Graph engine [2].
   FHIR-Ontop-OMOP is an open-source system, published at Github4 under Apache 2 license.
The system requires a working connection to the OMOP PostgreSQL database. For example,
in paper [1], we have used the full MIMIC-III data sets in the OMOP model. The system also
comes with a small demo data set from the MIMIC-IV project available in the OMOP Common
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d guohui.xiao@uib.no (A. 1); jiang.guoqian@mayo.edu (A. 11)
                                       © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
    CEUR
    Workshop
            CEUR Workshop Proceedings (CEUR-WS.org)
    Proceedings
                  http://ceur-ws.org
                  ISSN 1613-0073




1
  https://www.ohdsi.org/data-standardization/the-common-data-model/
2
  https://www.hl7.org/fhir/
3
  https://ontop-vkg.org/
4
  https://github.com/fhircat/FHIROntopOMOP
         Semantic Query Module   Query             Query Result




         CKG Generation Module


                                  Virtual                 Materialize & Validate
                                  Knowledge Graph in
                                  FHIR RDF
                                                                            FHIR ShEx
                                            virtualize

          Input Module
                                         FHIR Ontology
                                         OMOP-FHIR Mapping
                                         OMOP database




                         (a) System architecture                                        (b) The SPARQL endpoint

Figure 1: The FHIR-Ontop-OMOP system


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.


References
[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.

5
    https://physionet.org/content/mimic-iv-demo-omop/0.9/

</pre>