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2015 | OriginalPaper | Buchkapitel

ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs

verfasst von : Paolo Missier, Jeremy Bryans, Carl Gamble, Vasa Curcin, Roxana Danger

Erschienen in: Provenance and Annotation of Data and Processes

Verlag: Springer International Publishing

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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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Fußnoten
1
Conventionally, we orient these edges from right to left, to denote that the relation “points back to the past”.
 
4
Note that removing an arbitrary node may result in disconnected fragments of the graph, as in general one cannot simply add edges to reconnect the remaining nodes, unless those can be inferred from standard PROV constraints. For instance, if activity \(a\) is removed from the graph: \(\{ used (a, e_1)\), \( genBy (e_2, a) \}\), this results in two disconnected nodes \(e_1\), \(e_2\), because no relationship can be inferred between them from the original graph.
 
5
A default value can be specified, i.e. for the cases where a data node has no Status property, or the property has no value.
 
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Metadaten
Titel
ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs
verfasst von
Paolo Missier
Jeremy Bryans
Carl Gamble
Vasa Curcin
Roxana Danger
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-16462-5_1

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