TY - GEN
T1 - Barriers to Openly Sharing Government Data
T2 - 15th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2022
AU - Nikiforova, Anastasija
AU - Zuiderwijk, Anneke
N1 - 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.
PY - 2022
Y1 - 2022
N2 - Open Government Data (OGD) is a fundamental source for sustainability-oriented and data-driven innovation by citizens, companies, and other actors. However, many government agencies are reluctant to openly share their data with the public. While the resistance of public organizations to openly share government data has been investigated in previous research, most of these studies are focused on the reuse of open government data by companies and citizens. There is a paucity of research applying theoretical models to study the provision of OGD, and more specifically, the resistance of public organizations to make government data publicly available. We argue that Innovation Resistance Theory (IRT), which considers both functional and psychological factors, can be used to study OGD barriers, where OGD is seen as a source of innovation. This study aims to develop an OGD-adapted IRT model to empirically identify predictors affecting public agencies' resistance to openly sharing government data. Based on a review of the literature on both IRT research and barriers associated with open data sharing by public agencies, we develop an initial version of the model. In our future research, we plan to conduct exploratory interviews in multiple countries to refine the model. Ultimately, we will validate the refined model to study the resistance of public authorities to openly sharing government data in a quantitative study.
AB - Open Government Data (OGD) is a fundamental source for sustainability-oriented and data-driven innovation by citizens, companies, and other actors. However, many government agencies are reluctant to openly share their data with the public. While the resistance of public organizations to openly share government data has been investigated in previous research, most of these studies are focused on the reuse of open government data by companies and citizens. There is a paucity of research applying theoretical models to study the provision of OGD, and more specifically, the resistance of public organizations to make government data publicly available. We argue that Innovation Resistance Theory (IRT), which considers both functional and psychological factors, can be used to study OGD barriers, where OGD is seen as a source of innovation. This study aims to develop an OGD-adapted IRT model to empirically identify predictors affecting public agencies' resistance to openly sharing government data. Based on a review of the literature on both IRT research and barriers associated with open data sharing by public agencies, we develop an initial version of the model. In our future research, we plan to conduct exploratory interviews in multiple countries to refine the model. Ultimately, we will validate the refined model to study the resistance of public authorities to openly sharing government data in a quantitative study.
KW - Barrier
KW - Innovation Resistance Theory
KW - OGD
KW - Open data
KW - Open Government Data
UR - http://www.scopus.com/inward/record.url?scp=85142663951&partnerID=8YFLogxK
U2 - 10.1145/3560107.3560143
DO - 10.1145/3560107.3560143
M3 - Conference contribution
AN - SCOPUS:85142663951
T3 - ACM International Conference Proceeding Series
SP - 215
EP - 220
BT - Proceedings of the 15th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2022
A2 - Amaral, Luis
A2 - Soares, Delfina
A2 - Zheng, Lei
PB - Association for Computing Machinery (ACM)
Y2 - 4 October 2022 through 7 October 2022
ER -