To improve patient outcomes after trauma, the need to decrypt the post-traumatic immune response has been identified. One prerequisite to drive advancement in understanding that domain is the implementation of surgical biobanks. This paper focuses on the outcomes of patients with one of two diagnoses: post-traumatic arthritis and osteomyelitis. In creating surgical biobanks, currently, many obstacles must be overcome. Roadblocks exist around scoping of data that is to be collected, and the semantic integration of these data. In this paper, the generic component model and the Semantic Web technology stack are used to solve issues related to data integration. The results are twofold: (a) a scoping analysis of data and the ontologies required to harmonize and integrate it, and (b) resolution of common data integration issues in integrating data relevant to trauma surgery.

1st Medical Faculty Charles University 11636 Prague 1 Czech Republic

BioVentures LLC Little Rock AR 72205 USA

Central Biobank Institute of Pathology University and University Clinic of Regensburg 93053 Regensburg Germany

Department of Animal Sciences University of Florida Gainesville FL 32611 USA

Department of Biomedical Informatics University of Arkansas for Medical Sciences Little Rock AR 72205 USA

Department of Health Outcomes and Biomedical Informatics University of Florida Gainesville FL 32611 USA

Department of Surgery University of Arkansas for Medical Sciences Little Rock AR 72205 USA

eHealth Competence Center Bavaria Deggendorf Institute of Technology 94469 Deggendorf Germany

Emerging Pathogens Institute University of Florida Gainesville FL 32611 USA

Institute for Digital Health and Innovation University of Arkansas for Medical Sciences Little Rock AR 72205 USA

Medical Faculty University of Regensburg 93053 Regensburg Germany

Trauma Performance Improvement Coordinator University of Arkansas for Medical Sciences Little Rock AR 72205 USA

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The Representational Challenge of Integration and Interoperability in Transformed Health Ecosystems

Linguistic and ontological challenges of multiple domains contributing to transformed health ecosystems