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Storing and Querying Scientific Workflow Provenance Metadata Using an RDBMS (2007)
| Venue: | THIRD IEEE INTERNATIONAL CONFERENCE ON E-SCIENCE AND GRID COMPUTING |
| Citations: | 14 - 10 self |
BibTeX
@MISC{Chebotko07storingand,
author = {Artem Chebotko and Xubo Fei and Cui Lin and Shiyong Lu and Farshad Fotouhi},
title = { Storing and Querying Scientific Workflow Provenance Metadata Using an RDBMS},
year = {2007}
}
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Abstract
Provenance management has become increasingly important to support scientific discovery reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. This paper proposes an approach to provenance management that seamlessly integrates the interoperability, extensibility, and reasoning advantages of Semantic Web technologies with the storage and querying power of an RDBMS. Specifically, we propose: i) two schema mapping algorithms to map an arbitrary OWL provenance ontology to a relational database schema that is optimized for common provenance queries; ii) two efficient data mapping algorithms to map provenance RDF metadata to relational data according to the generated relational database schema, and iii) a schema-independent SPARQL-to-SQL translation algorithm that is optimized on-the-fly by using the type information of an instance available from the input provenance ontology and the statistics of the sizes of the tables in the database. Experimental results are presented to show that our algorithms are efficient and scalable.
Keyphrases
scientific workflow provenance metadata using relational database schema arbitrary owl provenance ontology type information provenance management semantic web technology scientific discovery reproducibility result interpretation input provenance ontology schema-independent sparql-to-sql translation algorithm scientific workflow environment efficient data common provenance query experimental result provenance rdf metadata problem diagnosis
