A template-based graph transformation system for the PROV data model
A template-based graph transformation system for the PROV data model
As data provenance becomes a significant metadata in validating the origin of information and asserting its quality, it is crucial to hide the sensitive information of provenance data to enable trustworthiness prior to sharing provenance in open environments such as the Web. In this paper, a graph rewriting system is constructed from the PROV data model to hide restricted provenance information while preserving the integrity and connectivity of the provenance graph. The system is formally established as a template-based framework and formalised using category theory concepts, such as functors, diagrams, and natural transformation.
Hussein, Jamal
41a89fd5-49d2-48eb-9fe5-95bb940e2566
Sassone, vladi
df7d3c83-2aa0-4571-be94-9473b07b03e7
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
4 July 2016
Hussein, Jamal
41a89fd5-49d2-48eb-9fe5-95bb940e2566
Sassone, vladi
df7d3c83-2aa0-4571-be94-9473b07b03e7
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Hussein, Jamal, Sassone, vladi and Moreau, Luc
(2016)
A template-based graph transformation system for the PROV data model.
GCM 2016: Seventh International Workshop on Graph Computation Models, Vienna, Austria.
04 Jul 2016.
15 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
As data provenance becomes a significant metadata in validating the origin of information and asserting its quality, it is crucial to hide the sensitive information of provenance data to enable trustworthiness prior to sharing provenance in open environments such as the Web. In this paper, a graph rewriting system is constructed from the PROV data model to hide restricted provenance information while preserving the integrity and connectivity of the provenance graph. The system is formally established as a template-based framework and formalised using category theory concepts, such as functors, diagrams, and natural transformation.
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More information
Accepted/In Press date: 26 May 2016
e-pub ahead of print date: 4 July 2016
Published date: 4 July 2016
Venue - Dates:
GCM 2016: Seventh International Workshop on Graph Computation Models, Vienna, Austria, 2016-07-04 - 2016-07-04
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 397032
URI: http://eprints.soton.ac.uk/id/eprint/397032
PURE UUID: 9d8c85af-18b4-458f-9146-2b4700bbf111
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Date deposited: 22 Jun 2016 14:58
Last modified: 15 Mar 2024 01:04
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Contributors
Author:
Jamal Hussein
Author:
vladi Sassone
Author:
Luc Moreau
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