Provenance metadata has become increasingly important to support scientific discovery, reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. The provenance management problem concerns the efficiency and effectiveness of the modeling, recording, representation, integration, storage, and querying of provenance metadata. The authors present an approach to provenance management which they claim "seamlessly integrates the interoperability, extensibility, and inference advantages of Semantic Web technologies with the storage and querying power of an RDBMS to meet the emerging requirements of scientific workflow provenance management". In this paper, they elaborate on the design of a relational RDF store, called RDFProv, which is optimized for scientific workflow provenance querying and management.
Keywords: Provenance, RDBMS, Web Ontology Language (OWL), Triple store
Author: Fotouhi, Farshad
Date created: 2010-08-08 04:00:00.000
Time required: P1H
Educational use: professionalDevelopment
Educational audience: professional
Interactivity type: expositive
- Articulates differences between the RDF abstract data model and the XML and relational models.
- Understands that owl:equivalentProperty and owl:equivalentClass may be used when equivalencies between properties or between classes are exact.
- Understands the difference between SQL query language (which operates on database tables) and SPARQL (which operates on RDF graphs).