Research Article
On Data Provenance in Group-centric Secure Collaboration
@INPROCEEDINGS{10.4108/icst.collaboratecom.2011.247192, author={Jaehong Park and Dang Nguyen and Ravi Sandhu}, title={On Data Provenance in Group-centric Secure Collaboration}, proceedings={7th International Conference on Collaborative Computing: Networking, Applications and Worksharing}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2012}, month={4}, keywords={provenance security collaboration group collaboration information sharing access control}, doi={10.4108/icst.collaboratecom.2011.247192} }- Jaehong Park
Dang Nguyen
Ravi Sandhu
Year: 2012
On Data Provenance in Group-centric Secure Collaboration
COLLABORATECOM
ICST
DOI: 10.4108/icst.collaboratecom.2011.247192
Abstract
In this paper, we explore data provenance in a group-centric secure collaboration environment. In collabora- tions, participating organizations are likely to want certain trustworthiness on the data that are shared from other or- ganizations and some assurance on how the shared data are used by users regardless of their organizations. By utilizing data provenance in group collaboration environment, we can provide the participating organizations with various provenance information that can establish trustworthiness and assurance on the shared data. To achieve this, we first identify what kind of operation information can be and should be captured as provenance data and how this information can be expressed in a formal representation which can be queried via the provenance system for certain utilities. We show the identified provenance data for a group collaboration application can provide some unique provenance utilities such as ability to trace the origins or usages of a shared data object even if it was created in a different organization. We utilize Open Provenance Model (OPM) [13] to capture various group collaboration operations identified in [12] and introduce a provenance system for a group collaboration en- vironment that utilizes Resource Description Framework (RDF) data representations [10] and GLEEN-enabled SPARQL query language [7].
