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| Titel |
Smart POI: Open and linked spatial data |
| VerfasserIn |
Otakar Cerba, Raitis Berzins, Karel Charvat, Tomas Mildorf |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250131828
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| Publikation (Nr.) |
 EGU/EGU2016-12272.pdf |
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| Zusammenfassung |
| The Smart Point of Interest (SPOI) represents an unique seamless spatial data set based on standards recommended for Linked and open data, which are supported by scientist and researchers as well as by several government authorities and European Union. This data set developed in cooperation of partners of SDI4Apps project contains almost 24 millions points of interest focused mainly on tourism, natural features, transport or citizen services. The SPOI data covers almost all countries and territories over the world. It is created as a harmonized combination of global data resources (selected points from OpenStreetMap, Natural Earth and GeoNames.org) and several local data sets (for example data published by the Citadel on the Move project, data from Posumavi region in the Czech Republic or experimental ontologies developed in the University of West Bohemia including ski regions in Europe or historical sights in Rome).
The added value of the SDI4Apps approach in comparison to other similar solutions consists in implementation of linked data approach (several objects are connected to DBpedia or GeoNames.org), using of universal RDF format, using of standardized and respected properties or vocabularies (for example FOAF or GeoSPARQL) and development of the completely harmonized data set with uniform data model and common classification (not only a copy of original resources). The SPOI data is published as SPARQL endpoint as well as in the map client. The SPOI dataset is a specific set of POIs which could be “a data fuel” for applications and services related to tourism, local business, statistics or landscape monitoring. It can be used also as a background data layer for thematic maps. |
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