Spatial Semantic Web, a Framework for Affordance-based POI's Information Storage and Retrieval

Rapid expansion of web data containing spatial information requires new approaches which are capable of huge data handling. Semantic web paradigm offers appealing solutions for heterogeneous and sporadic data sets by setting new and different definitions of Data Base Management Systems (DBMS). On the other hand, due to various understanding of place among different individuals, there are many criteria for cognition of place and place categories, so these different criteria lead to more distinctive annotations (so-called affordance) for Points Of Interest (POI) modeling. The design of specific schemas for these types of POI’s affordances is heinous in relational DBMS while spatial semantic modeling through graph DBMS expedites deployment of affordance-based storage and retrieval frameworks. In this study, available specifications and technologies related to spatial semantic functionalities are addressed and the current state of spatial semantic data formatting and interpretation is presented. The designed information system utilizes semantic web specifications to store and retrieve affordance-based POI’s information and a sample data set is used for applicability of the system. In order to evaluate achieved results, retrieved data by spatial semantic queries are compared to similar information in relational data bases, therefore spatial data loading in GDBMSs and RDBMSs are compared and results are analyzed.