Temporal GIS and spatiotemporal data sources

Abstract

The recent technological advances in geospatial data collection have created massive data sets with better spatial and temporal resolution than ever. To properly deal with these data sets, geographical information systems (GIS) must evolve to represent, access, analyze and visualize big spatiotemporal data in an efficient and integrated way. In this paper, we highlight challenges in temporal GIS development and present a proposal to overcome one of them: how to access spatiotemporal data sets from distinct kinds of data sources. Our approach uses Semantic Web techniques and is based on a data model that takes observations as basic units to represent spatiotemporal information from different application domains. We define a RDF vocabulary for describing data sources that store or provide spatiotemporal observations.