ONTOLOGICAL ASSESSMENT AND SIGNIFICANCE OF SEMANTIC LEVELS OF TAGS IN OPENSTREETMAP

Abstract

Abstract. User-generated contents are developing rapidly through VGI and contributors create the tags through the Web applications in a free mechanism. Semantic Knowledge in VGI like other user-generated contents needs to be combined with other authoritative data sources. One of the main challenges of integration is the semantic heterogeneity of user-generated contents which are describing the geographical objects as POIs. Geographical objects can be described in different semantic levels such as purpose or function. Significance of semantic levels defines the importance of related attributes. Analysis of significance for semantic levels of different POIs can be considered as a base to enhance the semantic quality of VGI. This paper proposes an approach based on the notions of rough set theory to measure the significance of semantic levels of tags which are applied to describe the buildings in OpenStreetMap. The proposed approach is implemented for tags which are applied to describe buildings in OpenStreetMap. Results show the high significance for tags which describing the semantic levels of geographic information constructs and purpose/ function for buildings.