BEAR: Benchmarking the Efficiency of RDF Archiving

Javier David Fernandez Garcia, Jürgen Umbrich, Axel Polleres

Publikation: Buch, Herausgeberschaft, BerichtForschungsbericht/Gutachten


There is an emerging demand on techniques addressing the problem of efficiently archiving and (temporal) querying different versions of evolving semantic Web data. While systems archiving and/or temporal querying are still in their early days, we consider this a good time to discuss benchmarks for evaluating storage space efficiency for archives, retrieval functionality they serve, and the performance of various retrieval operations. To this end, we provide a blueprint on benchmarking archives of semantic data by defining a concise set of operators that cover the major aspects of querying of and interacting with such archives. Next, we introduce BEAR, which instantiates this blueprint to serve a concrete set of queries on the basis of real-world evolving data. Finally, we perform an empirical evaluation of current archiving techniques that is meant to serve as a first baseline of future developments on querying archives of evolving RDF data.
PublikationsstatusVeröffentlicht - 2015

Österreichische Systematik der Wissenschaftszweige (ÖFOS)

  • 102 not use (Altbestand)
  • 102001 Artificial Intelligence
  • 502050 Wirtschaftsinformatik
  • 102015 Informationssysteme

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