Open Data Against All Odds: How Institutions Manage

Aida Darmenova, Zhanl Mamykova, Kim Normann Andersen

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

Abstrakt

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.
OriginalsprogEngelsk
TitelThe Proceedings of the 21st Annual International Conference on Digital Government Research (DGO2020) : Intelligent Government in the Intelligent Information Society
RedaktørerSeok-Jin Eom, Jooho Lee
Antal sider3
Udgivelses stedNew York
ForlagAssociation for Computing Machinery
Publikationsdatojun. 2020
Sider351-353
ISBN (Elektronisk)9781450387910
DOI
StatusUdgivet - jun. 2020
Begivenhed21st Annual International Conference on Digital Government Research: Intelligent Government in the Intelligent Information Society. DGO 2020 - Seoul National University, Seoul, Sydkorea
Varighed: 15 jun. 202019 jun. 2020
Konferencens nummer: 21
http://dgsoc.org/dgo-2020/

Konference

Konference21st Annual International Conference on Digital Government Research: Intelligent Government in the Intelligent Information Society. DGO 2020
Nummer21
LokationSeoul National University
LandSydkorea
BySeoul
Periode15/06/202019/06/2020
Internetadresse

Emneord

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

Citationsformater

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