Dataspaces, public administration and collective rationality: opportunities and limits for data-driven policy-making

This article assesses the obstacles and best practices in data gathering and reuse for public administrations (PAs). Through a qualitative analysis, it finds that smaller PAs often lack the resources to harness data in policy-making. This means that data-driven policy-making is currently more applicable to larger organizations. Theoretically, this article critically challenges the idea that pooling data from various sources expands the boundaries of rationality through collective rationality, as several institutional actors remain excluded from data-driven policy-making due to lack of resources.