How much semantic data on small devices?

  • Authors:

  • Mathieu D’Aquin;Andriy Nikolov;Enrico Motta

  • Affiliations:

  • Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK

  • Venue:
  • EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
  • Year:
  • 2010

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Abstract

Semantic tools such as triple stores, reasoners and query engines tend to be designed for large-scale applications. However, with the rise of sensor networks, smart-phones and smart-appliances, new scenarios appear where small devices with restricted resources have to handle limited amounts of data. It is therefore important to assess how existing semantic tools behave on such small devices, and how much data they can reasonably handle. There exist benchmarks for comparing triple stores and query engines, but these benchmarks are targeting large-scale applications and would not be applicable in the considered scenarios. In this paper, we describe a set of small to medium scale benchmarks explicitly targeting applications on small devices. We describe the result of applying these benchmarks on three different tools (Jena, Sesame and Mulgara) on the smallest existing netbook (the Asus EEE PC 700), showing how they can be used to test and compare semantic tools in resource-limited environments.