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

Paolo Missier; J. Bryans; Carl Gamble; Vasa Curcin; Roxana Danger

doi:10.1007/978-3-319-16462-5_1

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

Paolo Missier, J. Bryans, Carl Gamble, Vasa Curcin, Roxana Danger

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

16 Citations (Scopus)

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.

Original language	English
Title of host publication	Provenance and Annotation of Data and Processes
Editors	Bertram Ludäscher, Beth Plale
Place of Publication	Cham
Publisher	Springer Verlag
Pages	3-15
Number of pages	13
Volume	8628
ISBN (Electronic)	978-3-319-16462-5
ISBN (Print)	978-3-319-16461-8
DOIs	https://doi.org/10.1007/978-3-319-16462-5_1
Publication status	Published - 21 Mar 2015
Event	5th International Provenance and Annotation Workshop: IPAW 2014 - Cologne, Germany Duration: 9 Jun 2014 → 13 Jun 2014

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	8628

Conference

Conference	5th International Provenance and Annotation Workshop
Country/Territory	Germany
City	Cologne
Period	9/06/14 → 13/06/14

Keywords

Artificial Intelligence (incl. Robotics)
Database Management
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
Management of Computing and Information Systems
Computers and Society

Access to Document

10.1007/978-3-319-16462-5_1

Cite this

Provabs: Model, policy, and tooling for abstracting PROV graphs. / Missier, Paolo; Bryans, J.; Gamble, Carl; Curcin, Vasa; Danger, Roxana.

Provenance and Annotation of Data and Processes. ed. / Bertram Ludäscher; Beth Plale. Vol. 8628 Cham : Springer Verlag, 2015. p. 3-15 (Lecture Notes in Computer Science ; Vol. 8628).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Missier, P, Bryans, J, Gamble, C, Curcin, V & Danger, R 2015, Provabs: Model, policy, and tooling for abstracting PROV graphs. in B Ludäscher & B Plale (eds), Provenance and Annotation of Data and Processes. vol. 8628, Lecture Notes in Computer Science , vol. 8628, Springer Verlag, Cham, pp. 3-15, 5th International Provenance and Annotation Workshop, Cologne, Germany, 9/06/14. https://doi.org/10.1007/978-3-319-16462-5_1

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keywords = "Artificial Intelligence (incl. Robotics), Database Management, Information Storage and Retrieval, Information Systems Applications (incl. Internet), Management of Computing and Information Systems, Computers and Society",

author = "Paolo Missier and J. Bryans and Carl Gamble and Vasa Curcin and Roxana Danger",

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AU - Missier, Paolo

AU - Bryans, J.

AU - Gamble, Carl

AU - Curcin, Vasa

AU - Danger, Roxana

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AB - 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.

KW - Artificial Intelligence (incl. Robotics)

KW - Database Management

KW - Information Storage and Retrieval

KW - Information Systems Applications (incl. Internet)

KW - Management of Computing and Information Systems

KW - Computers and Society

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DO - 10.1007/978-3-319-16462-5_1

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SN - 978-3-319-16461-8

VL - 8628

T3 - Lecture Notes in Computer Science

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EP - 15

BT - Provenance and Annotation of Data and Processes

A2 - Ludäscher, Bertram

A2 - Plale, Beth

PB - Springer Verlag

CY - Cham

T2 - 5th International Provenance and Annotation Workshop

Y2 - 9 June 2014 through 13 June 2014

ER -

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

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