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Abstract COVID-19 has demonstrated the importance of data for scientific policy advice. Mechanisms by which data is generated, shared, and ultimately lead to policy responses are crucial for enhancing transparency and legitimacy of decisions. At the same time, the volume, complexity and volatility of data are growing. Against this background, mechanisms, actors, and problems of data-driven scientific policy advice are analysed. The study reveals role conflicts, ambiguities, and tensions in the interaction between scientific advisors and policy-makers. The assumption of a technocratic model, promoted by well-established structures and functioning processes of data-driven government, cannot be confirmed. Reality largely corresponds to the pragmatic model, in parts also the decisionist model, albeit with dysfunctional characteristics.
Kuhlmann et al. (Wed,) studied this question.