Data Want to be Free: An Innovation Resistance Theory Model for Identifying Barriers to Government Data Sharing
University of Tartu（塔尔图大学）；Umeå University（于默奥大学）；Delft University of Technology（代尔夫特理工大学）；The Swedish National Road and Transport Research Institute（瑞典国家道路交通研究所）；University of Priština - Kosovska Mitrovica（普里什蒂纳大学-科索沃米特罗维察分校）；University of the Aegean（爱琴海大学）
Anastasija Nikiforova, Antoine Clarinval, Anneke Zuiderwijk, Daniel Rudmark, Petar Milic, Charalampos Alexopoulos, Katrin Rajamäe-Soosaar
Data sharing is increasingly essential for digital government and data-driven innovation, yet many public organizations remain reluctant to make their data openly available. While prior research has examined factors influencing open data adoption, little theoretical work explores why resistance persists within public agencies. This study develops an Innovation Resistance Theory (IRT) model tailored to government data sharing to identify predictors of organizational resistance. An initial model was derived from literature and refined through interviews with 21 public organizations across six European countries. The resulting IRT4DS model identifies 39 barriers spanning usage, value, risk, tradition, and image dimensions, and 23 countermeasures mapped to the most critical barriers and the actors responsible for addressing them. By extending IRT into the context of governmental data sharing, the study advances theoretical understanding of why public data often remains closed and provides actionable guidance for policymakers seeking to design enabling data ecosystems and reduce structural and cultural barriers to OGD adoption.
The Algorithmic State Architecture (ASA): An Integrated Framework for AI-Enabled Government
Data for Policy CIC（数据政策社区利益公司）；University College London (UCL)（伦敦大学学院）；University of Cambridge（剑桥大学）；The Alan Turing Institute（艾伦·图灵研究所）；Imperial College London（帝国理工学院）
The Promises and Perils of using LLMs for Effective Public Services
University of Toronto（多伦多大学）；Georgia Institute of Technology（佐治亚理工学院）；Child Welfare Institute, CAS of Toronto（多伦多儿童福利研究所）；University of Wisconsin-Madison（威斯康星大学麦迪逊分校）
Open Data, Privacy, and Fair Information Principles: Towards a Balancing Framework
Institute for Information Law, University of Amsterdam Law School（阿姆斯特丹大学法学院信息法研究所）；Digital Methods Initiative, University of Amsterdam（阿姆斯特丹大学数字方法倡议）；Open Knowledge（开放知识）；University of Nijmegen（奈梅亨大学）；Center for Internet & Society, Stanford University（斯坦福大学互联网与社会中心）；Birkbeck University of London（伦敦大学伯贝克学院）
