Exposing Open Street Map in the Linked Data cloud

Proceedings of the 29th International Conference on Industrial, Engineering & other Applications of Applied Intelligent Systems - 2016
Download the publication : Exposing Open Street Map in the Linked Data cloud - IEA AIE 2016.pdf [400Ko]  
After the mobile revolution, geographical knowledge has getting more and more importance in many location-aware application scenarios. Its popularity influenced also the production and publication of dedicated datasets in the Linked Data (LD) cloud. In fact, its most recent representation shows Geonames competing with DBpedia as the largest and most linked knowledge graph available in the Web. Among the various projects related to the collection and publication of geographical information, as of today, Open Street Map (OSM) is for sure one of the most complete and mature one exposing a huge amount of data which is continually updated in a crowdsourced fashion. In order to make all this knowledge available as Linked Data, we developed LOSM: a SPARQL endpoint able to query the data available in OSM by an on-line translation form SPARQL syntax to a sequence of calls to the OSM overpass API. The endpoint makes also possible an on-the-fly integration among Open Street Map information and the one contained in external knowledge graphs such as DBpedia, Freebase or Wikidata.

BibTex references


@InProceedings{RDACP16,
author = {Azzurra Ragone and Tommaso {Di Noia} and Vito Walter Anelli and Andrea Cal\`{\i} and Matteo Palmonari},
title = "Exposing Open Street Map in the Linked Data cloud",
booktitle = "Proceedings of the 29th International Conference
on Industrial, Engineering \& other
Applications of Applied Intelligent Systems",
year = "2016",
note = "to appear",
url = "http://www-ictserv.poliba.it/publications/2016/RDA
CP16"
}

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SisInf Lab - Information Systems Laboratory

Research group of Politecnico di Bari
Edoardo Orabona St, 4 Bari, Italy