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Propagating data policies: a user study

Daga, Enrico
; 
d’Aquin, Mathieu
; 
Motta, Enrico
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Identifiers
http://hdl.handle.net/10379/7465
 https://doi.org/10.13025/21057
Publication Date
2017-11-04
Keywords
Data licences, Data flows, Policy propagation, User study
Type
Conference Paper
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Citation
Daga, Enrico, d'Aquin, Mathieu, & Motta, Enrico. (2017). Propagating Data Policies: a User Study. Paper presented at the Proceedings of the Knowledge Capture Conference, Austin, TX, USA, December 04 – 06.
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, knowledgeintensive 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.
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Publisher
ACM
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Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Data Science Institute (Conference Papers)