Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/599
Title: A Framework for Data-Driven Public Service Co-production
Authors: Toots, Maarja
McBride, Keegan
Kalvet, Tarmo
Krimmer, Robert
Tambouris, Efthimios
Panopoulou, Eleni
Kalampokis, Evangelos
Tarabanis, Konstantinos
Editors: Jansenn, Marijn
Axelsson, Karin
Glassey, Olivier
Klienink, Bram
Krimmer, Robert
Lindgren, Ida
Parycek, Peter
Scholl, Hans J.
Trutnev, Dmitrii
Type: Conference Paper
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Keywords: Open data
Public services
Co-production
Co-creation
Agile development
Issue Date: 2017
Publisher: Springer International Publishing
Volume: 10428
First Page: 264
Last Page: 275
Volume Title: Electronic Government
Part of Series: Lecture Notes in Computer Science
Part of Series: Lecture Notes in Computer Science
Abstract: Governments are creating and maintaining increasing amounts of data, and, recently, releasing data as open government data. As the amount of data available increases, so too should the exploitation of this data. However, this potential currently seems to be unexploited. Since exploiting open government data has the potential to create new public value, the absence of this exploitation is something that should be explored. It is therefore timely to investigate how the potential of existing datasets could be unleashed to provide services that create public value. For this purpose, we conducted a literature study and an empirical survey of the relevant drivers, barriers and gaps. Based on the results, we propose a framework that addresses some of the key challenges and puts forward an agile co-production process to support effective data-driven service creation. The proposed framework incorporates elements from agile development, lean startups, co-creation, and open government data literature and aims to increase our understanding on how open government data may be able to drive public service co-creation.
URI: https://doi.org/10.1007/978-3-319-64677-0_22
https://ruomo.lib.uom.gr/handle/7000/599
ISBN: 978-3-319-64676-3
978-3-319-64677-0
ISSN: 0302-9743
1611-3349
Other Identifiers: 10.1007/978-3-319-64677-0_22
Appears in Collections:Department of Applied Informatics

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