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Towards decision support for disclosing data

Closed or open data

Bibliographic Data

ID6148963
AuthorsAnneke Zuiderwijk (0000-0002-3552-7289, Delft University of Technology), Marijn Janssen (0000-0001-6211-8790, Delft University of Technology)
EditorsJing Zhang (0000-0002-6431-9286), Gabriel Purón-Cid (0000-0002-6272-7374), J Ramon Gil-Garcia
Year2015
Volume20
Issue2,3
Pages103-117
Publication date2015-08-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInformation Polity (JOURNAL)
Journal identifiersISSN: 1875-8754 • E-ISSN: 1570-1255
PublisherIOS Press (PUBLISHER • NL)
DOI10.3233/ip-150358
OpenAlexW1477783891
LanguageEN
Citations received11
References cited16

The disclosure of open government data is a complex activity that may create public value yet might also encounter risks, such as the misinterpretation and misuse of data. While politicians support data release and assume that the positive value of open data will dominate, many governmental organizations are reluctant to open their data, as they are afraid of the dark side. The objective of this paper is to provide a decision-making model that assists in trade-offs between the pros and cons of open data. Data disclosure is dependent on the type of data (e.g. its sensitivity, structure and quality) and the context (e.g. organizational policies, legislation and the political influences). Based on the literature and fifteen in-depth interviews with public sector officials and data archivists, this paper identifies contextual and dataset-related variables which influence a trade-off. A decision-making model is presented capturing trade-offs, and in this way providing guidance for weighing the creation of public value and the risks. The model can be used for decision-making to open or not to open data. It is likely that the decision regarding which data should be opened or closed will shift over time

Business · Context (archaeology · Data quality · Government (linguistics · Legislation · Open data · Open government · Political science · Public relations · Public sector · Quality (philosophy · Value (mathematics · World Wide Web · Computer Science · Data Quality and Management · E-Government and Public Services · Privacy-Preserving Technologies in Data · Marketing

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Unique citing works11
Citations per year1,22
Citation span2017 - 2026 (10)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 11

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