ologies and technologies have strengthened their position in the areas of data and knowledge management. Standards for organizing and querying semantic information, such as RDF(S) and SPARQL are adopted by large academic communities, while corporate vendors adopt semantic technologies to organize, expose, exchange and retrieve their data as Linked Data [1]. RDF stores have become robust enough ...

Geospatial extensions of SPARQL like GeoSPARQL and stSPARQL have recently been defined and corresponding geospatial RDF stores have been implemented. However, there is no widely used benchmark for evaluating geospatial RDF stores which takes into account recent advances to the state of the art in this area. In this paper, we develop a benchmark, called Geographica, which uses both real-world an...

To provide a timely snapshot of current research that utilizes geospatial analysis and modeling in urban environment, the Korea-America Association for Geospatial and Environmental Sciences (KAGES) and the editorship of the International Journal of Geospatial and Environmental Research (IJGER) organized a special issue of IJGER on the theme of geospatial analysis and urban environment. Eight ar...

Huge volumes of geospatial data have been collected and open geospatial information service have been set up by both public and private sectors in Antarctica Spatial Data Infrastructure (AntSDI). In order for the geospatial data to be useful, data and service have to be registered into one or more federated registry centre. However, currently it is very difficult for most of users to obtain the...

Modern geographical information systems make it possible to integrate information from multiple sources in different forms for querying and analysing information. So the importance of geospatial databases is growing from day to day, and their applications extend beyond the traditional applications of geospatial databases and GIS. One of the most recent challenges is integrating geospatial data ...

Recently, Geospatial data and Geographic Information Systems (GIS) have been increasingly used. As a result, the integration of geospatial data has become a crucial task for decision makers. Since GIS and geospatial databases are designed by different organizations using different representation models and there are diverse levels of detail for the spatial features, it is much more complex to a...

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...

Geospatial Web services allow to access and to process Geospatial data. Despite significant standardisation efforts, severe heterogeneity and interoperability problems remain. The SWING environment leverages the Semantic Web Services (SWS) paradigm to address these problems. The environment supports the entire life-cycle of Geospatial SWS. To this end, it integrates a genuine end-user tool, a t...

In this paper, we present The gEoSpatial Language Annotator (TESLA)—a tool which supports human annotation of geospatial language corpora. TESLA interfaces with a GIS database for annotating grounded geospatial entities and uses Google Earth for visualization of both entity search results and evolving object and speaker position from GPS tracks. We also discuss a current annotation effort using...

The rapid development of crowd-sourcing or volunteered geographic information both challenges and provides opportunities to authoritative geospatial information. Matching geospatial ontologies is an essential element to realizing the synergistic use of disparate geospatial information. We propose a new semiautomatic method to match formal and informal real life geospatial ontologies, at both te...