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 and synthetic data to test the offered functionality and the performance of some prominent geospatial RDF stores.
a b s t r a c tAdvances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many scientific and application domains. When Earth Observation data is coupled with other data sources many pioneering applications can be developed. In this paper we show how Earth Observation data, ontologies, and linked geospatial data can be combined for the development of a wildfire monitoring service that goes beyond applications currently deployed in various Earth Observation data centers. The service has been developed in the context of European project TELEIOS that faces the challenges of extracting knowledge from Earth Observation data head-on, capturing this knowledge by semantic annotation encoded using Earth Observation ontologies, and combining these annotations with linked geospatial data to allow the development of interesting applications.
B ig Earth-observation (EO) data that are made freely available by space agencies come from various archives. Therefore, users trying to develop an application need to search within these archives, discover the needed data, and integrate them into their application. In this article, we argue that if EO data are published using the linked data paradigm, then the data discovery, data integration, and development of applications becomes easier. We present the life cycle of big, linked, and open EO data and show how to support their various stages using the software stack developed by the European Union (EU) research projects TELEIOS and the Linked Open EO Data for Precision Farming (LEO). We also show how this stack of tools can be used to implement an operational wildfire-monitoring service.
Abstract. We present SexTant, a Web-based system for the visualization and exploration of time-evolving linked geospatial data and the creation, sharing, and collaborative editing of "temporally-enriched" thematic maps which are produced by combining different sources of such data.
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