Ontology based semantic representation for Public Health data integration

Rohini R. Rao, Krishnamoorthi Makkithaya, Neha Gupta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many health care providers have adopted Electronic Health Records to represent patient's health conditions. A patient visits many health care facilities like hospitals, private practices or primary health care centres for treatment of different ailments. There is a need to integrate the patient's health data from various sources, to provide a comprehensive view of the patient's health status. This data integration has to be seamless and unaffected by technology issues related to the data representation or exchange. The authors modeled data requirements and designed a Public Health Ontology to represent domain knowledge. The relational health data was mapped into instances of the Public Health Ontology to form a knowledge base of health records. The quality of the ontology and the knowledge base was analyzed using a metric based approach. The semantic representation enables interoperability and results prove that the knowledge base is rich in detail and diversity. The Public Health Ontology uses standardized medical terminology and unique patient identifiers to enable data integration which can enable a complete new level of reasoning over health data. However the public health knowledge base is fairly isolated and it needs to be connected to well-known ontology for meaningful use of the public health knowledge base.

Original languageEnglish
Title of host publicationProceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages357-362
Number of pages6
ISBN (Electronic)9781479966295
DOIs
Publication statusPublished - 23-01-2014
Event2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 - Mysuru, India
Duration: 27-11-201429-11-2014

Conference

Conference2014 International Conference on Contemporary Computing and Informatics, IC3I 2014
CountryIndia
CityMysuru
Period27-11-1429-11-14

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Rao, R. R., Makkithaya, K., & Gupta, N. (2014). Ontology based semantic representation for Public Health data integration. In Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 (pp. 357-362). [7019701] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IC3I.2014.7019701