Future government data strategies: Data-driven enterprise or data steward?: Exploring definitions and challenges for the government as data enterprise

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

4 Citations (Scopus)
62 Downloads (Pure)

Abstract

Comparable to the concept of a data(-driven) enterprise, the concept of a ggovernment as data (-driven) enterprise' is gaining popularity as a data strategy. However, what it implies is unclear. The objective of this paper is to clarify the concept of the government as data (-driven) enterprise, and identify the challenges and drivers that shape future data strategies. Drawing on literature review and expert interviews, this paper provides a rich understanding of the challenges for developing sound future government data strategies. Our analysis shows that two contrary data strategies dominate the debate. On the one hand is the data-driven enterprise strategy that focusses on collecting and using data to improve or enrich government processes and services (internal orientation). On the other hand, respondents point to the urgent need for governments to take on data stewardship, so other parties can use data to develop value for society (external orientation). Since these data strategies are not mutually exclusive, some government agencies will attempt to combine them, which is very difficult to pull off. Nonetheless, both strategies demand a more data minded culture. Moreover, the successful implementation of either strategy requires mature data governance - something most organisations still need to master. This research contributes by providing more depth to these strategies. The main challenge for policy makers is to decide on which strategy best fits their agency's roles and responsibilities and develop a shared roadmap with the external actors while at the same time mature on data governance.

Original languageEnglish
Title of host publicationProceedings of the 21st Annual International Conference on Digital Government Research
Subtitle of host publicationIntelligent Government in the Intelligent Information Society, DGO 2020
EditorsSeok-Jin Eom, Jooho Lee
PublisherAssociation for Computing Machinery (ACM)
Pages196-204
Number of pages9
ISBN (Electronic)9781450387910
DOIs
Publication statusPublished - 2020
Event21st Annual International Conference on Digital Government Research: Intelligent Government in the Intelligent Information Society, DGO 2020 - Seoul, Korea, Republic of
Duration: 15 Jun 202019 Jun 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference21st Annual International Conference on Digital Government Research: Intelligent Government in the Intelligent Information Society, DGO 2020
Country/TerritoryKorea, Republic of
CitySeoul
Period15/06/2019/06/20

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Data enterprise
  • Data governance
  • Data stewardship
  • Data-driven government
  • E-government

Fingerprint

Dive into the research topics of 'Future government data strategies: Data-driven enterprise or data steward?: Exploring definitions and challenges for the government as data enterprise'. Together they form a unique fingerprint.

Cite this