Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development

Iryna Susha; Marijn Janssen; Stefaan Verhulst

Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development

Iryna Susha
, Marijn Janssen
, Stefaan Verhulst

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Data collaboratives present a new form of cross-sector and public-private partnership to leverage (often corporate) data for addressing a societal challenge. They can be seen as the latest attempt to make data accessible to solve public problems. Although an increasing number of initiatives can be found, there is hardly any analysis of these emerging practices. This paper seeks to develop a taxonomy of forms of data collaboratives. The taxonomy consists of six dimensions related to data sharing and eight dimensions related to data use. Our analysis shows that data collaboratives exist in a variety of models. The taxonomy can help organizations to find a suitable form when shaping their efforts to create public value from corporate and other data. The use of data is not only dependent on the organizational arrangement, but also on aspects like the type of policy problem, incentives for use, and the expected outcome of data collaborative.

Original language	English
Title of host publication	Proceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017
Editors	Tung X. Bui, Ralph Sprague
Publisher	IEEE
Pages	2691-2700
Number of pages	10
ISBN (Electronic)	9780998133102
Publication status	Published - 2017
Externally published	Yes
Event	50th Annual Hawaii International Conference on System Sciences, HICSS 2017 - Big Island, United States Duration: 3 Jan 2017 → 7 Jan 2017

Publication series

Name	Proceedings of the Annual Hawaii International Conference on System Sciences
Volume	2017-January
ISSN (Print)	1530-1605

Conference

Conference	50th Annual Hawaii International Conference on System Sciences, HICSS 2017
Country/Territory	United States
City	Big Island
Period	3/01/17 → 7/01/17

Bibliographical note

Funding Information:
This research was funded by the Swedish Research Council under the grant agreement 2015-06563 as part of the project “Data collaboratives as a new form of innovation for addressing societal challenges in the age of data”.

Publisher Copyright:
© 2017 Proceedings of the Annual Hawaii International Conference on System Sciences. All rights reserved.

Funding

This research was funded by the Swedish Research Council under the grant agreement 2015-06563 as part of the project “Data collaboratives as a new form of innovation for addressing societal challenges in the age of data”.

Cite this

Susha, I., Janssen, M., & Verhulst, S. (2017). Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development. In T. X. Bui, & R. Sprague (Eds.), Proceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017 (pp. 2691-2700). (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2017-January). IEEE.

Susha, Iryna ; Janssen, Marijn ; Verhulst, Stefaan. / Data collaboratives as a new frontier of cross-sector partnerships in the age of open data : Taxonomy development. Proceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017. editor / Tung X. Bui ; Ralph Sprague. IEEE, 2017. pp. 2691-2700 (Proceedings of the Annual Hawaii International Conference on System Sciences).

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title = "Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development",

abstract = "Data collaboratives present a new form of cross-sector and public-private partnership to leverage (often corporate) data for addressing a societal challenge. They can be seen as the latest attempt to make data accessible to solve public problems. Although an increasing number of initiatives can be found, there is hardly any analysis of these emerging practices. This paper seeks to develop a taxonomy of forms of data collaboratives. The taxonomy consists of six dimensions related to data sharing and eight dimensions related to data use. Our analysis shows that data collaboratives exist in a variety of models. The taxonomy can help organizations to find a suitable form when shaping their efforts to create public value from corporate and other data. The use of data is not only dependent on the organizational arrangement, but also on aspects like the type of policy problem, incentives for use, and the expected outcome of data collaborative.",

author = "Iryna Susha and Marijn Janssen and Stefaan Verhulst",

note = "Funding Information: This research was funded by the Swedish Research Council under the grant agreement 2015-06563 as part of the project “Data collaboratives as a new form of innovation for addressing societal challenges in the age of data”. Publisher Copyright: {\textcopyright} 2017 Proceedings of the Annual Hawaii International Conference on System Sciences. All rights reserved.; 50th Annual Hawaii International Conference on System Sciences, HICSS 2017 ; Conference date: 03-01-2017 Through 07-01-2017",

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Susha, I, Janssen, M & Verhulst, S 2017, Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development. in TX Bui & R Sprague (eds), Proceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017. Proceedings of the Annual Hawaii International Conference on System Sciences, vol. 2017-January, IEEE, pp. 2691-2700, 50th Annual Hawaii International Conference on System Sciences, HICSS 2017, Big Island, United States, 3/01/17.

Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development. / Susha, Iryna; Janssen, Marijn; Verhulst, Stefaan.
Proceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017. ed. / Tung X. Bui; Ralph Sprague. IEEE, 2017. p. 2691-2700 (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N1 - Funding Information: This research was funded by the Swedish Research Council under the grant agreement 2015-06563 as part of the project “Data collaboratives as a new form of innovation for addressing societal challenges in the age of data”. Publisher Copyright: © 2017 Proceedings of the Annual Hawaii International Conference on System Sciences. All rights reserved.

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AB - Data collaboratives present a new form of cross-sector and public-private partnership to leverage (often corporate) data for addressing a societal challenge. They can be seen as the latest attempt to make data accessible to solve public problems. Although an increasing number of initiatives can be found, there is hardly any analysis of these emerging practices. This paper seeks to develop a taxonomy of forms of data collaboratives. The taxonomy consists of six dimensions related to data sharing and eight dimensions related to data use. Our analysis shows that data collaboratives exist in a variety of models. The taxonomy can help organizations to find a suitable form when shaping their efforts to create public value from corporate and other data. The use of data is not only dependent on the organizational arrangement, but also on aspects like the type of policy problem, incentives for use, and the expected outcome of data collaborative.

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Susha I, Janssen M, Verhulst S. Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development. In Bui TX, Sprague R, editors, Proceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017. IEEE. 2017. p. 2691-2700. (Proceedings of the Annual Hawaii International Conference on System Sciences).

Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: Taxonomy development

Abstract

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Cite this