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Articles | Volume XL-8
https://doi.org/10.5194/isprsarchives-XL-8-239-2014
https://doi.org/10.5194/isprsarchives-XL-8-239-2014
27 Nov 2014
 | 27 Nov 2014

Ontology-Driven Knowledge-Based Health-Care System, An Emerging Area – Challenges And Opportunities – Indian Scenario

A. Sunitha and G. Suresh Babu

Keywords: Knowledge Base, Interoperability, Query, Visualization, Semantic Retrieval, Ontology

Abstract. Recent studies in the decision making efforts in the area of public healthcare systems have been tremendously inspired and influenced by the entry of ontology. Ontology driven systems results in the effective implementation of healthcare strategies for the policy makers. The central source of knowledge is the ontology containing all the relevant domain concepts such as locations, diseases, environments and their domain sensitive inter-relationships which is the prime objective, concern and the motivation behind this paper. The paper further focuses on the development of a semantic knowledge-base for public healthcare system. This paper describes the approach and methodologies in bringing out a novel conceptual theme in establishing a firm linkage between three different ontologies related to diseases, places and environments in one integrated platform. This platform correlates the real-time mechanisms prevailing within the semantic knowledgebase and establishing their inter-relationships for the first time in India. This is hoped to formulate a strong foundation for establishing a much awaited basic need for a meaningful healthcare decision making system in the country. Introduction through a wide range of best practices facilitate the adoption of this approach for better appreciation, understanding and long term outcomes in the area. The methods and approach illustrated in the paper relate to health mapping methods, reusability of health applications, and interoperability issues based on mapping of the data attributes with ontology concepts in generating semantic integrated data driving an inference engine for user-interfaced semantic queries.