Communications of the ACM - Organic user interfaces
Provenance and scientific workflows: challenges and opportunities
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Atomicity and provenance support for pipelined scientific workflows
Future Generation Computer Systems
Provenance as data mining: combining file system metadata with content analysis
TAPP'09 First workshop on on Theory and practice of provenance
A characterization of the problem of secure provenancemanagement
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Augmenting geospatial data provenance through metadata tracking in geospatial service chaining
Computers & Geosciences
RDFProv: A relational RDF store for querying and managing scientific workflow provenance
Data & Knowledge Engineering
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
Linked provenance data: A semantic Web-based approach to interoperable workflow traces
Future Generation Computer Systems
SciProv: an architecture for semantic query in provenance metadata on e-science context
ITBAM'11 Proceedings of the Second international conference on Information technology in bio- and medical informatics
Formal verification of data provenance records
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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Provenance is critically important for scientific workflow systems, as it allows users to verify data, repeat experiments, and discover dependencies. The Semantic Web is a natural fit for representing provenance, as it contains explicit support for representing and inferring connections between data and processes, as well as for adding annotations to data. In this article, we present a Semantic Web approach to the Provenance Challenge (Concurrency Computat.: Pract. Exper. 2007; DOI: 10.1002-cpe.1233). We use web services, ontologies, OWL reasoners, triple stores, and the SPARQL query language to implement the workflow, represent the data and the connections within it, and execute queries. We successfully implemented and answered all of the challenge queries. The flexibility of the Semantic Web also makes it quite easy to convert different provenance systems' data representation to a form we can work with. We illustrate this by integrating data from the PASS approach into our system, and successfully executing all of the challenge queries on it as well. Copyright © 2007 John Wiley & Sons, Ltd.