Data Intelligence (Nov 2019)

Building a Holistic Taxonomy Model for OGD-Related Risks: Based on a Lifecycle Analysis

  • Wang, Fang,
  • Zhao, An,
  • Zhao, Hong,
  • Chu, Jun

DOI
https://doi.org/10.1162/dint_a_00018
Journal volume & issue
Vol. 1, no. 4
pp. 309 – 332

Abstract

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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 lifecycle 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.