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Constructing Healthcare Ontologies of any Data Format

Authors:
Athanasios Kiourtis
Argyro Mavrogiorgou
Dimosthenis Kyriazis

Keywords: healthcare; interoperability; ontologies; heterogeneous data

Abstract:
Current health systems are becoming stronger and more efficient, with promises for better and healthier life quality. However, one of the prerequisites for this promise is that health systems are able to connect and interact with each other, by quickly and seamlessly exchanging data, using open standards and bypassing interoperability constraints. For that purpose, several researches have been proposed focusing on the field of interoperability, dealing with specific one-to-one scenarios of data transformation. Among these solutions, the translation of healthcare data into ontologies is considered as a solution towards interoperability. However, healthcare data can be found in multiple formats, while most of the current approaches are dealing with specific data formats and designs. To address this gap, in this paper, we are proposing an extended approach to create an ontology model from any data format, taking into account complex cases arising from multiple data design styles, by transforming the healthcare data into XML Schema Graphs (XSG) for providing it as an input to the Apache Jena, and finally generating Resource Description Framework (RDF) entities.

Pages: 43 to 48

Copyright: Copyright (c) IARIA, 2019

Publication date: February 24, 2019

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-688-0

Location: Athens, Greece

Dates: from February 24, 2019 to February 28, 2019