Semantic and schematic similarities between database objects: a context-based approach
The VLDB Journal — The International Journal on Very Large Data Bases
Ontologies for semantically interoperable systems
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
A reference ontology for biomedical informatics: the foundational model of anatomy
Journal of Biomedical Informatics - Special issue: Unified medical language system
Implementing electronic medical records
Communications of the ACM - Scratch Programming for All
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Semantic web technology for agent communication protocols
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Model-driven interoperability: MDI 2010
MODELS'10 Proceedings of the 2010 international conference on Models in software engineering
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The use of Electronic Health Records (EHRs) has brought multiple benefits to the healthcare domain. However, those advantages would be greater if seamless interoperability of EHRs between heterogeneous Health Information Systems were achieved. Nowadays, achieving that kind of interoperability is on the agenda of many national and regional initiatives, and in the majority of the cases, the problem is addressed through the use of different standards. In this paper we present a proposal that goes one step further and tackles the interoperability problem from a formal ontology driven perspective. So, our proposal allows one system to interpret on the fly clinical data sent by another one even when they use different representations. We present in the paper the three key components of the proposal: 1. An ontology that provides -- in its upper level--a canonical representation of EHR statements, more precisely of medical observations, which can be then specialized -- in the lower level -- by health institutions according to their proprietary models, 2. A translator module that facilitates the definition of the lower level of the ontology from the particular EHRs data storage structures following a semi-automatic approach: first a translation process of underlying data structures, using -- whenever possible -- information about properties (functional dependencies, etc.) into ontology elements described in OWL2, and next, an edition process where the health system administrators can define new axioms to adjust and enrich the result obtained in the semi-automatic process. Finally we show the third component, a mapping module that helps in the task of defining the links among the terms of the upper and lower levels of the ontology. It obtains a declarative mapping specified in OWL2 and puts a wide range of mapping scenarios within reach of health systems' administrators.