A Formal Account of the Open Provenance Model

Author:

Kwasnikowska Natalia1,Moreau Luc2,Bussche Jan Van Den1

Affiliation:

1. Hasselt University and Transnational University of Limburg, Diepenbeek, Belgium

2. University of Southampton, Southampton, United Kingdom

Abstract

On the Web, where resources such as documents and data are published, shared, transformed, and republished, provenance is a crucial piece of metadata that would allow users to place their trust in the resources they access. The open provenance model (OPM) is a community data model for provenance that is designed to facilitate the meaningful interchange of provenance information between systems. Underpinning OPM is a notion of directed graph, where nodes represent data products and processes involved in past computations and edges represent dependencies between them; it is complemented by graphical inference rules allowing new dependencies to be derived. Until now, however, the OPM model was a purely syntactical endeavor. The present article extends OPM graphs with an explicit distinction between precise and imprecise edges. Then a formal semantics for the thus enriched OPM graphs is proposed, by viewing OPM graphs as temporal theories on the temporal events represented in the graph. The original OPM inference rules are scrutinized in view of the semantics and found to be sound but incomplete. An extended set of graphical rules is provided and proved to be complete for inference. The article concludes with applications of the formal semantics to inferencing in OPM graphs, operators on OPM graphs, and a formal notion of refinement among OPM graphs.

Funder

EPSRC SOCIAM

ORCHID projects

FP7 SmartSociety project

ESRC ebook project

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference38 articles.

1. Curated databases

2. Causality and the Semantics of Provenance

3. James Cheney. 2013. Semantics of the PROV Data Model. W3C Working Draft WD-prov-sem-20130312. World Wide Web Consortium. James Cheney. 2013. Semantics of the PROV Data Model. W3C Working Draft WD-prov-sem-20130312. World Wide Web Consortium.

4. Provenance in Databases: Why, How, and Where

5. James Cheney Paolo Missier Luc Moreau and Tom De Nies (Eds.). 2013. Constraints of the PROV Data Model. W3C Recommendation REC-prov-constraints-20130430. World Wide Web Consortium. http://www.w3.org/TR/2013/REC-prov-constraints-20130430/. James Cheney Paolo Missier Luc Moreau and Tom De Nies (Eds.). 2013. Constraints of the PROV Data Model. W3C Recommendation REC-prov-constraints-20130430. World Wide Web Consortium. http://www.w3.org/TR/2013/REC-prov-constraints-20130430/.

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