Relationalization of provenance data in complex RDF reification nodes

  • Authors:

  • Sunitha Ramanujam;Anubha Gupta;Latifur Khan;Steven Seida;Bhavani Thuraisingham

  • Affiliations:

  • The University of Texas at Dallas, Richardson, USA 75080;The University of Texas at Dallas, Richardson, USA 75080;The University of Texas at Dallas, Richardson, USA 75080;Raytheon Company, Garland, USA 75042;The University of Texas at Dallas, Richardson, USA 75080

  • Venue:
  • Electronic Commerce Research
  • Year:
  • 2010

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Abstract

The plethora of information available to today's users due to the Internet phenomenon has brought forth an associated concern, namely, determination of the trustworthiness of information. Provenance information, such as who is responsible for the data or how the data came to be, plays a pivotal role in addressing this concern by providing additional facts that could serve as a basis for establishing the authenticity of information. Awareness of the importance of data provenance has ensured that current technologies include support for the ability to record provenance information. These include Semantic Web technologies such as Resource Description Framework (RDF) that records data provenance through the process of reification. Reification enables the association of a level of trust with RDF triples, thereby enabling the validation of the authenticity of the triples. RDF's rapid acceptance has created an associated demand for RDF data modeling and visualization tools and our research, called R2D, is aimed at addressing and providing a solution for this demand by leveraging and reusing existing mature technologies. The work presented in this paper extends our earlier work on relationalization of the RDF concept of reification by providing support for complex reifications that include a variety of blank nodes. Algorithmic enhancements that were incorporated into the various R2D components in order to support relationalization of complex reifications are presented along with performance graphs and screenshots of the relational equivalent of a reified RDF store as seen through an open source relational visualization tool.