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Abstract: For many government departments, uncertainty aversion is a source of barriers in the advancement of data openness. A more active response to potential risks is needed and necessitates an in-depth examination of risks related to open government data (OGD). With a cross-case study in which three cases from the United Kingdom, the United States and China are examined, this study identifies potential risks that might emerge at different stages of the life cycle of OGD programs and constructs a taxonomy model for them. The taxonomy model distinguishes the “risks from OGD” from the “risks to OGD”, which can help government departments make better responses. Finally, risk response strategies are suggested based on the research results.
Keywords: Open government data; Risk; Taxonomy; Life cycle; risk management
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Fang Wang (Corresponding Author)is a professor of library and information Science in the Business School and the director of the Center for Network Society Governance of Nankai University, China. She received her Ph.D degree from Peking University. She has presided more than 20 projects of NSFC and other foundations and published more than 100 papers in Chinese and English as well as 10 books. Her research interests include government information management and knowledge discovery.
An Zhao is currently working in a government agency of Beijing. She received her master degree in archive science from Nankai University. Her research interest is e-government.
Hong Zhao is currently a Ph.D. student in Department of Information Resource Management, Business School, Nankai University, China. He received his M.S. degree in Information Science in 2008 from Nankai University, China. His research interest is Government Information Resources Management and Intelligent Processing.
Wang, F., Zhao, A., Zhao, H. & Chu, J. Building a Holistic Taxonomy Model for OGD Related Risks: Based on a lifecycle analysis. Data Intelligence 1(2019), 1-24.
Published: Aug. 13, 2019 （Versions1）