Towards Handling Spatio-Temporal Contexts on Linked Open Data for Points of Interest

Points of Interest (POIs) are important features to be considered to assess the value of a specific real estate to be used or bought. We address POIs' assessment as an event that occurs in the temporal period and the objects are primarily space or locations then study this feature as Linked Open Data (LOD). In this paper, we present our ontology-based approach using our designed LOD schema. The purpose of this works is for handling spatio-temporal contexts on LOD to be used for realizing data-driven assessment of real estates in various aspects of them. To build our schema, as the first step we collect actual instances to be used and extract possible features to be included in the design of an ontology. Then we investigate relatedness among the concepts to fit them into the target scenario. Finally, the LOD schema includes the relationships between the events and the (side-)effects of them to be affected to the assessment status.