GeoTriples: a Tool for Publishing Geospatial Data as RDF Graphs Using R2RML Mappings
Presented at the International Semantic Web Conference , Riva del Garda, Italy
A plethora of Earth Observation data that is becoming available at no charge in Europe and the US recently reflects the strong push for more open Earth Observation data. Linked data is a paradigm which studies how one can make data available on the Web, and interconnect it with other data with the aim of making the value of the resulting “Web of data” greater than the sum of its parts. Open Earth Observation data that are currently made available by space agencies such as ESA and NASA are not following the linked data paradigm. Therefore, Earth Observation data and other kinds of geospatial data that are necessary for a user to satisfy her information needs can only be found in different data silos, where each silo may contain only part of the needed data. Publishing the content of these silos as RDF graphs, enables the development of data analytics applications with great environmental and financial value. In this paper we present the tool GeoTriples that allows for the transformation of Earth Observation data and geospatial data into RDF graphs. GeoTriples goes beyond the state of the art by extending the R2RML mapping language to be able to deal with the specificities of geospatial data. GeoTriples is a semi-automated tool that allows the publication of geospatial information into an RDF graph using the state of the art vocabularies like GeoSPARQL and stSPARQL, but at the same time it is not tightly coupled to a specific vocabulary.
|THEME||Information (theme 2)|
|Project||Linked Open Earth Observation Data for Precision Farming|
|Conference||International Semantic Web Conference|
Kyzirakos, K, Vlachopoulos, I, Savva, D, Manegold, S, & Koubarakis, M. (2015). GeoTriples: a Tool for Publishing Geospatial Data as RDF Graphs Using R2RML Mappings. In Terra Cognita 2014, 6th International Workshop on the Foundations, Technologies and Applications of the Geospatial Web. CEUR-WS.org.