RDFProv: A relational RDF store for querying and managing scientific workflow provenance

Artem Chebotko, Shiyong Lu, Xubo Fei, Farshad Fotouhi
2010 Data & Knowledge Engineering  
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. Our approach to provenance management seamlessly integrates the interoperability, extensibility, and inference advantages of Semantic
more » ... b technologies with the storage and querying power of an RDBMS to meet the emerging requirements of scientific workflow provenance management. In this paper, we elaborate on the design of a relational RDF store, called RDFProv, that is optimized for scientific workflow provenance querying and management. Specifically, we propose: i) two schema mapping algorithms to map an OWL provenance ontology to a relational database schema that is optimized for common provenance queries; ii) three 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. The comparison with two popular relational RDF stores, Jena and Sesame, and two commercial native RDF stores, AllegroGraph and BigOWLIM, showed that our optimizations result in improved performance and scalability for provenance metadata management. Finally, our case study for provenance management in a real-life biological simulation workflow showed the production quality and capability of the RDFProv system. Although presented in the context of scientific workflow provenance management, many of our proposed techniques apply to general RDF data management as well. [43] scientific workflow, exploring the production quality and capability of RDFProv for this real-life provenance application. Provenance Model Management Provenance Ontology Repository Model Mapping Layer Schema Mapping Data Mapping Query Mapping Relational Provenance Storage Provenance Model Layer Relational Model Layer OWL ontology to relational DB schema RDF triples to relational tuples SPARQL queries to SQL queries OWL RDF SPARQL Inference RDBMS SQL
doi:10.1016/j.datak.2010.03.005 fatcat:hbwenralmjeephtly2bmcnx7qe