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Geospatial Data and the Semantic Web

Geospatial data or geographic information is the data that identifies a geographic location of natural or constructed features and boundaries on the Earth (e.g. oceans, buildings, countries, rivers, etc). Geographical knowledge bases are among the largest in existence and have high importance in a variety of everyday applications. The data can be mapped and often manipulated with Geographic Information Systems (GIS), however the integration of external data sets into these systems is time-consuming and complex. GeoKnow will provide the necessary tools and methods to easily integrate and process data across a wide range of data sources on the web of data.

Possibly one of the most interesting and promising outcomes of the activity surrounding the Web 2.0 evolution has been the large-scale adoption of Linked Data. Among the largest data sets are those with explicit geographic references, e.g. LinkedGeoData (2 billion triples), DBpedia (1 billion triples) and GeoNames (146 million triples). Other data sets carry implicit geographic references such as PubMed (797 million triples) or Freebase (1 billion triples). A problem GeoKnow aims to solve is the lack of rich geospatial links between the data.

The Linked Open Data cloud as of September 2011

GeoKnow in a nutshell

What

  • Bring geospatial knowledge integration to the Linked Data Web
  • Billion-triple geospatial reasoning and data provenance
  • Qualitative interlinking and fusing of geospatial and semantic information
  • Adaptive geospatial exploration, authoring and curation

Why

  • Unlock isolated islands of geographic information
  • 80% of all data has some spatial dimension, most of it is not processable today
  • Geographic data authoring with millions of users requires powerful tools

For whom

  • Added value for the companies and the Linked Data Web community
  • Cost-effective data integration for SMEs
  • Enterprises can add value to their data with volunteered geographic information
  • Users from travel industry will benefit from more background information

Hosted by

Universität Leipzig , InfAI: Institut für Angewandte Informatik

Funded by

EU Seventh Framework Programme (FP7)

Community and Social Media

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