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Linked Data Indexing Methods: A Survey

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2011 Workshops (OTM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7046))

Abstract

Documents on the contemporary Web are based especially on HTML formats and, therefore, it is rather difficult to retrieve hidden structured information from them using automated agents. The concept of Linked Data based primarily on RDF data triples seems to successfully solve this drawback. However, we cannot directly adopt the existing solutions from relational databases or XML technologies, because RDF triples are modelled as graph data and not relational or tree data. Despite the research effort in recent years, several questions in the area of Linked Data indexing and querying remain open, not only since the amount of Linked Data globally available significantly increases each year. This paper attempts to introduce advantages and disadvantages of the state-of-the-art solutions and discuss several issues related to our ongoing research effort – the proposal of an efficient querying framework over Linked Data. In particular, our goal is to focus on large amounts of distributed and highly dynamic data.

This work was supported by the Charles University Grant Agency grant 4105/2011, the Czech Science Foundation grant P202/10/0573 and the grant SVV-2011-263312.

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Authors and Affiliations

  1. Department of Software Engineering, Charles University in Prague, Malostranske namesti 25, 118 00, Prague 1, Czech Republic

    Martin Svoboda & Irena Mlýnková

Authors
  1. Martin Svoboda
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  2. Irena Mlýnková
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Editor information

Editors and Affiliations

  1. STAR Lab, Vrije Universiteit Brussel (VUB), Bldg G/10, Pleinlaan 2, 1050, Brussel, Belgium

    Robert Meersman

  2. DEBII, Curtin University of Technology, Technology Park, De Laeter Way, 6102, Bentley, WA, Australia

    Tharam Dillon

  3. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, 28660, Boadilla del Monte, Madrid, Spain

    Pilar Herrero

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Svoboda, M., Mlýnková, I. (2011). Linked Data Indexing Methods: A Survey. In: Meersman, R., Dillon, T., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2011 Workshops. OTM 2011. Lecture Notes in Computer Science, vol 7046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25126-9_59

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  • DOI: https://doi.org/10.1007/978-3-642-25126-9_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25125-2

  • Online ISBN: 978-3-642-25126-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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