TY  - JOUR
U1  - Wissenschaftlicher Artikel
A1  - Bozkurt, Yusuf
A1  - Rossmann, Alexander
A1  - Konanahalli, Ashwini
A1  - Pervez, Zeeshan
T1  - Toward urban data governance: status-quo, challenges, and success factors
JF  - IEEE access : practical research, open solutions
N2  - The benefits of urban data cannot be realized without a political and strategic view of data use. A core concept within this view is data governance, which aligns strategy in data-relevant structures and entities with data processes, actors, architectures, and overall data management. Data governance is not a new concept and has long been addressed by scientists and practitioners from an enterprise perspective. In the urban context, however, data governance has only recently attracted increased attention, despite the unprecedented relevance of data in the advent of smart cities. Urban data governance can create semantic compatibility between heterogeneous technologies and data silos and connect stakeholders by standardizing data models, processes, and policies. This research provides a foundation for developing a reference model for urban data governance, identifies challenges in dealing with data in cities, and defines factors for the successful implementation of urban data governance. To obtain the best possible insights, the study carries out qualitative research following the design science research paradigm, conducting semi-structured expert interviews with 27 municipalities from Austria, Germany, Denmark, Finland, Sweden, and the Netherlands. The subsequent data analysis based on cognitive maps provides valuable insights into urban data governance. The interview transcripts were transferred and synthesized into comprehensive urban data governance maps to analyze entities and complex relationships with respect to the current state, challenges, and success factors of urban data governance. The findings show that each municipal department defines data governance separately, with no uniform approach. Given cultural factors, siloed data architectures have emerged in cities, leading to interoperability and integrability issues. A city-wide data governance entity in a cross-cutting function can be instrumental in breaking down silos in cities and creating a unified view of the city’s data landscape. The further identified concepts and their mutual interaction offer a powerful tool for developing a reference model for urban data governance and for the strategic orientation of cities on their way to data-driven organizations.
KW  - cognitive mapping
KW  - design science research
KW  - urban data governance
KW  - smart city
KW  - expert interviews
KW  - data governance
Y1  - 2023
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-47236
SN  - 2169-3536
SS  - 2169-3536
U6  - https://doi.org/10.1109/ACCESS.2023.3302835
DO  - https://doi.org/10.1109/ACCESS.2023.3302835
VL  - 11
SP  - 85656
EP  - 85677
S1  - 22
PB  - IEEE
CY  - New York
ER  -