Open data for evidence-based decision-making: Data-driven government resulting in uncertainty and polarization

Ahmad Luthfi, Marijn Janssen

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
499 Downloads (Pure)


Over the last decade, more and more data are collected and opened. Governments actively stimulate the opening of data to increase citizen engagement to support policy-making processes. Evidence-based policy-making is the situation whereby decisions made are based on factual data. The common expectation is that releasing data will result in evidence-based decision-making and more trust in government decisions. This study aims to provide insight into how evidence-based policy based on open data can result into uncertainty and even polarize the policy-making process. We analyze a case study in which traffic and road utilization datasets are used and model the decision-making process using the Business Process Model and Notation (BPMN). The BPMN model shows how the government and business organizations can use the data and give different interpretations. Data-driven decision-making might potentially create uncertainty, polarization, and less trust in decisions as stakeholders can give different meanings to the data and arrive at different outcomes. In contrast to the common belief, we found that the more data released, the more discussions happened about what is desired according to the data. The various directions derived from the data can even polarize decisionmaking. In other words, the more data opened, the more people can construct their perception of reality. For further research, we recommend understanding the types and role of data to create an evidence-based approach.

Original languageEnglish
Pages (from-to)1071-1078
Number of pages8
JournalInternational Journal on Advanced Science, Engineering and Information Technology
Issue number3
Publication statusPublished - 2019


  • Data-driven
  • Decision-making
  • Evidence-based
  • Open data
  • Polarization
  • Trust
  • Uncertainty


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