Database techniques for linked data management

  • Authors:

  • Andreas Harth;Katja Hose;Ralf Schenkel

  • Affiliations:

  • Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany;Max-Planck Institute for Informatics, Saarbruecken, Germany;Saarland University, Saarbrucken, Germany

  • Venue:
  • SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
  • Year:
  • 2012

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Abstract

Linked Data refers to data published in accordance with a number of principles rooted in web standards. In the past few years we have witnessed a tremendous growth in Linked Data publishing on the web, leading to tens of billions of data items published online. Querying the data is a key functionality required to make use of the wealth of rich interlinked data. The goal of the tutorial is to introduce, motivate, and detail techniques for querying heterogeneous structured data from across the web. Our tutorial aims to introduce database researchers and practitioners to the new publishing paradigm on the web, and show how the abundance of data published as Linked Data can serve as fertile ground for database research and experimentation. As such, the tutorial focuses on applying database techniques to processing Linked Data, such as optimized indexing and query processing methods in the centralized setting as well as distributed approaches for querying. At the same time, we make the connection from Linked Data best practices to established technologies in distributed databases and the concept of Dataspaces and show differences as well as commonalities between the fields.