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Connecting Citizens: Designing for Data Collection and Dissemination in the Smart City
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2017 (English)In: Internet Science: Proceedings / [ed] Ioannis Kompatsiaris, Jonathan Cave, Anna Satsiou, Georg Carle, Antonella Passan, iEfstratios Kontopoulos, Sotiris Diplaris, Donald McMillan, Springer, 2017, p. 119-131Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents two case studies of citizen data collection and dissemination applications, developed for or by three different local authorities in Northern Europe. These case studies highlight the challenges in meeting the goals of Open Data, of involving citizens as sources of information, and of engendering and maintaining trust as a service provider all at the same time. The challenge of making data open can be seen as at odds with protecting the privacy and safety of citizens when it is sourced directly or indirectly from their actions. Encouraging citizens to collect, curate, and submit data can create misguided expectations of influence over the processes of local government, and disillusionment where action or feedback are not forthcoming. A local authority is trusted to provide information that is verified and for which it is accountable. Balancing this with goal of disseminating the results of citizen sourced data collection activities can result in frustration for developers, users, and local authority employees. In response to these issues this paper presents the following four design opportunities: probabilistic and personalised representations of data, making accountable the use of collected data, respecting the boundaries of data, and designing for the graceful degradation of resources.

Place, publisher, year, edition, pages
Springer, 2017. p. 119-131
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10673
Keywords [en]
Smart city, Big data, Open data, Crowdsourced data
National Category
Human Computer Interaction
Research subject
Man-Machine-Interaction (MMI)
Identifiers
URN: urn:nbn:se:su:diva-150351DOI: 10.1007/978-3-319-70284-1_10ISI: 000440850000010ISBN: 978-3-319-70283-4 (print)ISBN: 978-3-319-70284-1 (electronic)OAI: oai:DiVA.org:su-150351DiVA, id: diva2:1167135
Conference
4th International Conference, INSCI 2017, Thessaloniki, Greece, November 22-24, 2017
Available from: 2017-12-18 Created: 2017-12-18 Last updated: 2022-02-28Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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