Objective Biomedical research increasingly relies on
the integration of information from multiple
heterogeneous data sources. Despite the fact that
structural and terminological aspects of interoperability
are interdependent and rely on a common set of
requirements, current efforts typically address them in
isolation. We propose a unified ontology-based
knowledge framework to facilitate interoperability
between heterogeneous sources, and investigate if using
the LexEVS terminology server is a viable implementation
method.
Materials and methods We developed a framework
based on an ontology, the general information model
(GIM), to unify structural models and terminologies,
together with relevant mapping sets. This allowed a
uniform access to these resources within LexEVS to
facilitate interoperability by various components and data
sources from implementing architectures.
Results Our unified framework has been tested in the
context of the EU Framework Program 7 TRANSFoRm
project, where it was used to achieve data integration in
a retrospective diabetes cohort study. The GIM was
successfully instantiated in TRANSFoRm as the clinical
data integration model, and necessary mappings were
created to support effective information retrieval for
software tools in the project.
Conclusions We present a novel, unifying approach to
address interoperability challenges in heterogeneous data
sources, by representing structural and semantic models
in one framework. Systems using this architecture can
rely solely on the GIM that abstracts over both the
structure and coding. Information models, terminologies
and mappings are all stored in LexEVS and can be
accessed in a uniform manner (implementing the HL7
CTS2 service functional model). The system is flexible
and should reduce the effort needed from data sources
personnel for implementing and managing the
integration.