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

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

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

Fingerprint Dive into the research topics of 'ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs'. Together they form a unique fingerprint.

Cite this

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, pp. 3-15). Cham: Springer Verlag. https://doi.org/10.1007/978-3-319-16462-5_1

@inproceedings{0a3f0d33578b4a6eb3bdd03e0ea1fb21,

title = "ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs",

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.",

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",

year = "2015",

month = "3",

day = "21",

doi = "10.1007/978-3-319-16462-5_1",

language = "English",

isbn = "978-3-319-16461-8",

volume = "8628",

pages = "3--15",

editor = "Bertram Lud{\"a}scher and Beth Plale",

booktitle = "Provenance and Annotation of Data and Processes",

publisher = "Springer Verlag",

address = "Austria",

}

TY - GEN

T1 - ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs

AU - Missier, Paolo

AU - Bryans, J.

AU - Gamble, Carl

AU - Curcin, Vasa

AU - Danger, Roxana

PY - 2015/3/21

Y1 - 2015/3/21

N2 - 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.

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

U2 - 10.1007/978-3-319-16462-5_1

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

M3 - Conference proceeding

SN - 978-3-319-16461-8

VL - 8628

SP - 3

EP - 15

BT - Provenance and Annotation of Data and Processes

A2 - Ludäscher, Bertram

A2 - Plale, Beth

PB - Springer Verlag

CY - Cham

ER -