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 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.

Anelli, V., Calì, A., Di Noia, T., Palmonari, M., Ragone, A. (2016). Exposing open street map in the linked data cloud. In Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Morioka, Japan, August 2-4, 2016, Proceedings (pp.344-355). Springer Verlag [10.1007/978-3-319-42007-3_29].

Exposing open street map in the linked data cloud

PALMONARI, MATTEO LUIGI
Penultimo
;
RAGONE, AZZURRA
2016

Abstract

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 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.
paper
Computer Science (all); Theoretical Computer Science
English
29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016
2016
Hamido Fujita, Moonis Ali, Ali Selamat, Jun Sasaki, Masaki Kurematsu
Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Morioka, Japan, August 2-4, 2016, Proceedings
9783319420066
2016
9799
344
355
http://springerlink.com/content/0302-9743/copyright/2005/
none
Anelli, V., Calì, A., Di Noia, T., Palmonari, M., Ragone, A. (2016). Exposing open street map in the linked data cloud. In Trends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Morioka, Japan, August 2-4, 2016, Proceedings (pp.344-355). Springer Verlag [10.1007/978-3-319-42007-3_29].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/136405
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