Provabs: Model, policy, and tooling for abstracting PROV graphs

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Abstract

Provenance metadata can be valuable in data sharing settings, where it can be used to help data consumers form judgements regarding the reliability of the data produced by third parties. However, some parts of provenance may be sensitive, requiring access control, or they may need to be simplified for the intended audience. Both these issues can be addressed by a single mechanism for creating abstractions over provenance, coupled with a policy model to drive the abstraction. Such mechanism, which we refer to as abstraction by grouping, simultaneously achieves partial disclosure of provenance, and facilitates its consumption. In this paper we introduce a formal foundation for this type of abstraction, grounded in the W3C PROV model; describe the associated policy model; and briefly present its implementation, the ProvAbs tool for interactive experimentation with policies and abstractions.

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Missier, P., Bryans, J., Gamble, C., Curcin, V., & Danger, R. (2015). Provabs: Model, policy, and tooling for abstracting PROV graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8628, pp. 3–15). Springer Verlag. https://doi.org/10.1007/978-3-319-16462-5_1

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