My reading group presentation, entitled “An overview of RDB2RDF techniques and tools”, was be based on the RDB2RDF XG reports [2,3] and an overview of the performance of the reported tools .
The slides of the presentation can be found here.
Abstract (from ):
Many science archive centres publish very large volumes of image, simulation, and experiment data. In order to integrate and analyse the available data, scientists need to be able to (i) identify and locate all the data relevant to their work; (ii) understand the multiple heterogeneous data models in which the data is published; and (iii) interpret and process the data they retrieve. RDF has been shown to be a generally successful framework within which to perform such data integration work. It can be equally successful in the context of scientiﬁc data, if it is demonstrably practical to expose that data as RDF. In this paper we investigate the capabilities of RDF to enable the
integration of scientiﬁc data sources. Speciﬁcally, we discuss the suitability of sparql for expressing scientiﬁc queries, and the performance of several triple stores and RDB2RDF tools for executing queries over a moderately sized sample of a large astronomical data set. We found that more research and improvements are required into SPARQL and RDB2RDF tools to efficiently expose existing science archives for data integration.
 A. J. G. Gray, N. Gray, and I. Ounis. Can RDB2RDF Tools Feasibily Expose Large Science Archives for Data Integration? In L. Aroyo, P. Traverso, F. Ciravegna, P. Cimiano, T. Heath, E. Hyvönen, R. Mizoguchi, E. Oren, M. Sabou, and E. P. B. Simperl, editors, ESWC, volume 5554 of Lecture Notes in Computer Science, pages 491–505. Springer, 2009.
 A. Malhotra. W3C RDB2RDF Incubator Group Report. http://www.w3.org/2005/Incubator/rdb2rdf/XGR-rdb2rdf/, January 2009.
 S. S. Sahoo, W. Halb, S. Hellmann, K. Idehen, T. T. Jr, S. Auer, J. Sequeda, and A. Ezzat. A Survey of Current Approaches for Mapping of Relational Databases to RDF. W3C RDB2RDF XG Report, W3C, 2009.