Semantic information integration of Health Care Network for Physical-Cyber-Social computing approach

The Health Care Network (HCN ) related information of a country is one of the most influential fields of data sharing and integrating with disparate data sources of physical world and compatible health care organizations on the exponentially growing World Wide Web (WWW ) for improving and maintaining health related services of mass people. Although these accessible HCN related unstructured or semi-structured data in multiple heterogeneous repositories on the web originate challenges to develop a smarter method in finding specific information using traditional keyword-based search engines. Moreover, it is also a formidable task to harmonize spatial data with our HCN for exploring implicit knowledge that assist people in making their decisions regarding of health services and it is getting researchers´ attention at a rapid pace. In this regard, we applied the Physical-Cyber-Social (PCS) computing approach on HCN that demonstrates the feasibility of semantic web technologies to represent domain information in the machine understandable format and we also integrate data from accessible Cyber Space Data Sources (CSDSs) to address these challenges. We published our HCN related data using Resource Description Framework (RDF ) to build a knowledge-base. We call this repository as HCN - BD, which is HCN related machine understandable data source of Bangladesh. This yields a huge knowledge graph with 0.25 million nodes, i.e. RDF triples to facilitate reasoning important information pattern by a graph based query language, SPARQL. Furthermore, we integrate this semantic repository with our generic spatial knowledge-base, Geo - Bangladesh, a machine understandable geographic data source related to the administrative structure of Bangladesh, to examine health care locations using SPARQL and therefore, we achieved the semantic interoperability in our Linked Open Data (LOD) application. Moreover, our research effectively addresses nearest health care centers using real time spat- al data from Global Positioning System (GPS) and maps these locality to increase searching ability by mass people.