Paper Info
Title
Can RDB2RDF Tools Feasibily Expose Large Science Archives for Data Integration?
Abstract
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 rdbrdf 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 rdbrdf tools to efficiently expose existing science archives for data integration.
Year
DOI
Venue
2009
10.1007/978-3-642-02121-3_37
ESWC
Keywords
Field
DocType
scientific data source,available data,large science archives,data integration,multiple heterogeneous data model,data integration work,rdb2rdf tools feasibily expose,scientific data,scientific query,large astronomical data,experiment data,rdbrdf tool,data integrity
Data integration,Publication,Data modeling,Data mining,Relational database,Information retrieval,Computer science,Linked data,SPARQL,Data virtualization,RDF
Conference
Volume
ISSN
Citations 
5554
0302-9743
6
PageRank 
References 
Authors
0.66
12
3
Name
Order
Citations
PageRank
Alasdair J. G. Gray141735.91
Norman Gray2214.85
Iadh Ounis33438234.59