Enrichment of Human Health Information Using Ontology Based Geospatial Semantic Query Processing

Abstract

With the developing measure of health data and continuous episodes of sicknesses, the recovery of health information is given a ton of concern. Machine understanding of spatial data will enhance the interpretation of health data semantics. The greater part of this investigation focused on the non-spatial semantics of health data, utilizing ontology and standards. Using the spatial component of health data will help inside the understanding of health marvels. This investigation proposes a semantic health data query engineering that empowers the consolidation of each non-spatial semantics and geospatial semantics in health data incorporation and recovery. We tend to expect to give a center layer between ontology storehouses and semantically commented on databases to help semantic queries specifically inside the databases with informative standard database query languages. We have built up a semantic query engine that has semantic reasoning and query process, and translates the queries into ontology repository tasks. Semantic administrators are upheld inside the database as client sketched out capacities reached out to the database engine, so semantic queries is straightforwardly determined in standard database query languages like SQL and XQuery. The framework gives storing administration to supports query execution.