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FAGI: A Framework for Fusing Geospatial RDF Data

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 8841)

Abstract

In this paper, we present FAGI, a framework for fusing geospatial RDF data. Starting from two interlinked datasets, FAGI handles all the steps of the fusion process, producing an integrated, richer dataset that combines entities and attributes from both initial ones. In contrast to existing approaches and tools, which deal either with RDF fusion or with spatial conflation, FAGI specifically addresses the fusion of geospatial RDF data. We describe the main components of the framework and their functionalities, which include aligning dataset vocabularies, processing geospatial features, applying -manually or automatically- fusion strategies, and recommending link creation or rejection between RDF entities, with emphasis on their geospatial properties.

Keywords

  • Spatial Object
  • Fusion Strategy
  • Geospatial Data
  • Fusion Action
  • Fusion Framework

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Giannopoulos, G., Skoutas, D., Maroulis, T., Karagiannakis, N., Athanasiou, S. (2014). FAGI: A Framework for Fusing Geospatial RDF Data. In: , et al. On the Move to Meaningful Internet Systems: OTM 2014 Conferences. OTM 2014. Lecture Notes in Computer Science, vol 8841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45563-0_33

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  • DOI: https://doi.org/10.1007/978-3-662-45563-0_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45562-3

  • Online ISBN: 978-3-662-45563-0

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