Geospatial data sharing is a concern in geospatial science because of the heterogeneity of existing geographical information systems. This study aims to examine the use of Geospatial Semantic Web technologies such as ontology, web services and the service-oriented architecture for enabling disparate heterogeneous legacy GIS to share and integrate information in a cost effective way to reduce sp...

The geospatial domain is influenced by the Web developments; consequently, an increasing number of geospatial web services become available through Internet. A rich description of geospatial web services is required to resolve semantic heterogeneity and achieve semantic interoperability of geospatial web services. However, existing geospatial web services descriptions and semantic mapping appro...

Huge volumes of geospatial data have been collected by both public and private sectors. In order for the geospatial data to be useful, information has to be extracted from the data and converted to knowledge. However, currently it is very difficult for most of users to obtain the geospatial data and to turn them into useful information and knowledge. In order for geospatial information and know...

Provisioning of virtual machines for efficient geospatial query management on cloud is an interesting and challenging work. The aim of this paper is to distribute workloads of different types of spatial queries into suitable virtual machine efficiently. To increase the effectiveness of the system serving geospatial queries, we use real-time geospatial query pattern learning methodology. This me...

Today, with the common availability of Internet technologies, interoperability of geospatial data has become a necessity for sharing and integrating geospatial data. More specifically, it is seen as a solution to solve syntactic, structural, semantic, geometric and temporal heterogeneities between data sources. In Canada, we observe such heterogeneities from existing geospatial databases. For e...