On benchmarking data translation systems for semantic-web ontologies

  • Authors:
  • Carlos R. Rivero;Inma Hernández;David Ruiz;Rafael Corchuelo

  • Affiliations:
  • University of Sevilla, Sevilla, Spain;University of Sevilla, Sevilla, Spain;University of Sevilla, Sevilla, Spain;University of Sevilla, Sevilla, Spain

  • Venue:
  • Proceedings of the 20th ACM international conference on Information and knowledge management
  • Year:
  • 2011

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Abstract

Data translation, also known as data exchange, is an integration task that aims at populating a target model using data from a source model. This task is gaining importance in the context of semantic-web ontologies due to the increasing interest in graph databases and semantic-web agents. Currently, there are a variety of semantic-web technologies that can be used to implement data translation systems. This makes it difficult to assess them from an empirical point of view. In this paper, we present a benchmark that provides a catalogue of seven data translation patterns that can be instantiated by means of seven parameters. This allows us to create a variety of synthetic, domain-independent scenarios one can use to test existing data translation systems. We also illustrate how to analyse three such systems using our benchmark. The main benefit of our benchmark is that it allows to compare data translation systems side by side within a homogeneous framework.