LODatio: using a schema-level index to support users infinding relevant sources of linked data

  • Authors:

  • Thomas Gottron;Ansgar Scherp;Bastian Krayer;Arne Peters

  • Affiliations:

  • University of Koblenz-Landau, Landau, Germany;University of Koblenz-Landau & University of Mannheim, Landau, Germany;University of Koblenz-Landau, Landau, Germany;University of Koblenz-Landau, Landau, Germany

  • Venue:
  • Proceedings of the seventh international conference on Knowledge capture
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

The Linked Open Data (LOD) cloud provides a vast amount of heterogeneous data, distributed over numerous data sources. This makes it difficult to find those data sources in the cloud which are relevant for a given information need. Existing search engines for the Semantic Web focus on instance-oriented information needs, i. e., searching for specific RDF instances or literals and exploring the search results. However, they do not address the question of finding linked data sources relevant to a schema-oriented information need, i. e., queries based on triple patterns relating to a specific combination of RDF types and/or properties. In this paper, we present the semantic search system LODatio leveraging a schema-level index for finding sources of Linked Data relevant to a schema-oriented information need. Beyond its capability to retrieve relevant data sources, LODatio actively supports the user in his schema-oriented search tasks. To this end, it provides ranked result lists of relevant data sources together with example snippets and an estimation of the result set size. Furthermore, LODatio provides support for novel features in semantic search such as recommending alternative queries in order to refine or broaden the result set.