BEAR: Benchmarking the Efficiency of RDF Archiving

Javier David Fernandez Garcia, Jürgen Umbrich, Axel Polleres

Publication: Book/Editorship/ReportResearch report, expert opinion


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.
Original languageEnglish
Place of PublicationVienna
Publication statusPublished - 2015

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102 not use (legacy)
  • 102001 Artificial intelligence
  • 502050 Business informatics
  • 102015 Information systems

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