TY - JOUR
T1 - Building open government data platform ecosystems
T2 - A dynamic development approach that engages users from the start
AU - Hein, Andreas
AU - Engert, Martin
AU - Ryu, Sunghan
AU - Schaffer, Norman
AU - Hermes, Sebastian
AU - Krcmar, Helmut
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/10
Y1 - 2023/10
N2 - Open government data (OGD) platform ecosystems hold immense potential for promoting transparency, civic engagement, economic growth, and improved governmental offerings. The prevailing strategy to building OGD platform ecosystems follows a sequential approach where the OGD platform is built first and the ecosystem is built second, resulting in low engagement. In this paper, we derive insights into an alternative approach to developing OGD platform ecosystems from TourismData, a state-owned tourism initiative in Germany. We report on the phases between 2018 and 2022 and derive four dynamic and incremental phases from which we derive three learnings: context specificity, continuous adaptation, and organic expansion. Our findings have theoretical and practical implications for developing high-engagement OGD platform ecosystems that include and engage ecosystem actors from the start and, hence, take advantage of the generative potential of OGD. This approach illustrates the importance of developing OGD platform ecosystems with high contextual relevance to ensure that data can be used to enable meaningful interactions between ecosystem actors and promote continuous adaptation and expansion.
AB - Open government data (OGD) platform ecosystems hold immense potential for promoting transparency, civic engagement, economic growth, and improved governmental offerings. The prevailing strategy to building OGD platform ecosystems follows a sequential approach where the OGD platform is built first and the ecosystem is built second, resulting in low engagement. In this paper, we derive insights into an alternative approach to developing OGD platform ecosystems from TourismData, a state-owned tourism initiative in Germany. We report on the phases between 2018 and 2022 and derive four dynamic and incremental phases from which we derive three learnings: context specificity, continuous adaptation, and organic expansion. Our findings have theoretical and practical implications for developing high-engagement OGD platform ecosystems that include and engage ecosystem actors from the start and, hence, take advantage of the generative potential of OGD. This approach illustrates the importance of developing OGD platform ecosystems with high contextual relevance to ensure that data can be used to enable meaningful interactions between ecosystem actors and promote continuous adaptation and expansion.
KW - Open data
KW - Open government
KW - Open government data
KW - Open government data platform ecosystem development
KW - Open government data platform ecosystems
UR - http://www.scopus.com/inward/record.url?scp=85176094542&partnerID=8YFLogxK
U2 - 10.1016/j.giq.2023.101878
DO - 10.1016/j.giq.2023.101878
M3 - Article
AN - SCOPUS:85176094542
SN - 0740-624X
VL - 40
JO - Government Information Quarterly
JF - Government Information Quarterly
IS - 4
M1 - 101878
ER -