ePrints Soton (University of Southampton) · 2007 · 144 citations · 3 references
Open access
ComputingData ScienceDigital HumanitiesDocumentationKnowledge RepresentationAnnotationArtifact DocumentationData ProvenanceKnowledge AnnotationProvenance ResearchProvenance AnnotationProvenance ModelsProvenance Representation
Provenance is well established in art and digital libraries, and its growing importance in e‑science for reproducibility led to the 2006 IPAW workshop where a consensus emerged that the community needed to better understand provenance systems and representations. The authors aimed to create and refine a unified provenance data model. They organized the first Provenance Challenge, having participants simulate an fMRI workflow and execute predefined provenance queries to assess system capabilities, and later iterated the model in a Salt Lake City workshop. Sixteen teams completed the first challenge and thirteen the second, and discussions.
Provenance is well understood in the context of art or digital libaries, where it respectivelyrefers to the documented history of an art object, or the documentation of processes in adigital object’s life cycle [3]. Interest for provenance in the “e-science community” [9] isalso growing, since provenance is perceived as a crucial component of workflow systems [2]that can help scientists ensure reproducibility of their scientific analyses and processes.Against this background, the International Provenance and Annotation Workshop(IPAW’06), held on May 3-5, 2006 in Chicago, involved some 50 participants interestedin the issues of data provenance, process documentation, data derivation, and data an-notation [5, 1]. During a session on provenance standardization, a consensus began toemerge, whereby the provenance research community needed to understand better thecapabilities of the different systems, the representations they used for provenance, theirsimilarities, their differences, and the rationale that motivated their designs.Hence, the first Provenance Challenge was born, and from the outset, the challengewas set up to be informative rather than competitive. The first Provenance Challenge wasset up in order to provide a forum for the community to understand the capabilities ofdifferent provenance systems and the expressiveness of their provenance representations.Participants simulated or ran a Functional Magnetic Resonance Imaging workflow, fromwhich they implemented and executed a pre-identified set of “provenance queries”. Six-teen teams responded to the challenge, and reported their experience in a journal specialissue [6].The first Provenance Challenge was followed by the second Provenance Challenge,aiming at establishing inter-operability of systems, by exchanging provenance publica-tion. Thirteen teams [8] responded to this second challenge. Discussions indicated thatthere was substantial agreement on a core representation of provenance. As a result, ina workshop on August 7-8 in Salt Lake City, the authors met, and crafted and iterateda data model, which is presented in this paper.1
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A survey of data provenance in e-science
Yogesh Simmhan, Beth Plale, Dennis Gannon · ACM SIGMOD Record · 2005 · 1.2K citations
Workshop on the Challenges of Scientific Workflows
May, Ewa Deelman, Marina del Rey et al. · 2006 · 33 citations