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Propagating Data Policies: a User Study

Daga, Enrico; d'Aquin, Mathieu and Motta, Enrico (2017). Propagating Data Policies: a User Study. In: Proceedings of the Knowledge Capture Conference, ACM, New York, NY, USA, article no. 3.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1145/3148011.3148022
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Abstract

When publishing data, data licences are used to specify the actions that are permitted or prohibited, and the duties that target data consumers must comply with. However, in complex environments such as a smart city data portal, multiple data sources are constantly being combined, processed and redistributed. In such a scenario, deciding which policies apply to the output of a process based on the licences attached to its input data is a difficult, knowledge- intensive task. In this paper, we evaluate how automatic reasoning upon semantic representations of policies and of data flows could support decision making on policy propagation. We report on the results of a user study designed to assess both the accuracy and the utility of such a policy-propagation tool, in comparison to a manual approach.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 The Authors
ISBN: 1-4503-5553-6, 978-1-4503-5553-7
Project Funding Details:
Funded Project NameProject IDFunding Body
MK:SMART, an integrated innovation and training programme leveraging large-scale city data to drive economic growth (Q-13-037-EM)H04HEFCE
Keywords: information systems; expert systems; computing methodologies; knowledge representation; knowledge reasoning; applied computing; data licences; data flows; policy propagation
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 52707
Depositing User: Enrico Daga
Date Deposited: 21 Dec 2017 10:15
Last Modified: 11 Jan 2018 16:37
URI: http://oro.open.ac.uk/id/eprint/52707
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