Open Data Against All Odds: How Institutions Manage

Aida Darmenova, Zhanl Mamykova, Kim Normann Andersen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents a research-in-progress case study of al-Farabi Kazakh National University (KazNU). While KazNU develops data management strategy, the paper aims to explore and analyse how data governance may help crystalize strategy objectives to ensure smooth implementation. The paper also examines drivers and inhibitors for adoption of open data by a public organization in Kazakhstan, in order to develop applicable scenarios on identification of data in need.
Original languageEnglish
Title of host publicationThe Proceedings of the 21st Annual International Conference on Digital Government Research (DGO2020) : Intelligent Government in the Intelligent Information Society
EditorsSeok-Jin Eom, Jooho Lee
Number of pages3
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Publication dateJun 2020
Pages351-353
ISBN (Electronic)9781450387910
DOIs
Publication statusPublished - Jun 2020
Event21st Annual International Conference on Digital Government Research: Intelligent Government in the Intelligent Information Society. DGO 2020 - Seoul National University, Seoul, Korea, Republic of
Duration: 15 Jun 202019 Jun 2020
Conference number: 21
http://dgsoc.org/dgo-2020/

Conference

Conference21st Annual International Conference on Digital Government Research: Intelligent Government in the Intelligent Information Society. DGO 2020
Number21
LocationSeoul National University
CountryKorea, Republic of
CitySeoul
Period15/06/202019/06/2020
Internet address

Keywords

  • Open data
  • Data governance
  • Adoption issues
  • Drives
  • Inhibitors
  • Government transformation
  • Public organizations
  • Higher education system
  • Kazakhstan

Cite this

Darmenova, A., Mamykova, Z., & Andersen, K. N. (2020). Open Data Against All Odds: How Institutions Manage. In S-J. Eom, & J. Lee (Eds.), The Proceedings of the 21st Annual International Conference on Digital Government Research (DGO2020): Intelligent Government in the Intelligent Information Society (pp. 351-353). Association for Computing Machinery. https://doi.org/10.1145/3396956.3397006