Integrating open sources and relational data with SPARQL

1Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

We believe that the possibility to use SPARQL as a front end to heterogeneous data without significant cost in performance or expressive power is key to RDF taking its rightful place as the lingua franca of data integration. To this effect, we demonstrate how RDF and SPARQL can tackle a mix of standard relational workload and data mining in public data sources. We discuss extending SPARQL for business intelligence (BI) workloads and relate experiences on running SPARQL against relational and native RDF databases. We use the well known TPC H benchmark as our reference schema and workload. We define a mapping of the TPC H schema to RDF and restate the queries as BI extended SPARQL. To this effect, we define aggregation and nested queries for SPARQL. We demonstrate that it is possible to perform the TPC H workload restated in SPARQL against an existing RDBMS without loss of performance or expressivity and without changes to the RDBMS. Finally, we demonstrate how to combine TPC-H or XBRL financial reports with RDF data from CIA factbook and DBpedia. © 2008 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Erling, O., & Mikhailov, I. (2008). Integrating open sources and relational data with SPARQL. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5021 LNCS, pp. 838–842). https://doi.org/10.1007/978-3-540-68234-9_69

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free