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

To foster data-driven policy-making practices there is a need for capacity-building within the public administration (PA) to collect, access, manage and reuse data. This article draws from focus groups and interviews to propose measures to make dataspaces scalable and accessible for smaller actors so that they can participate in data-driven policy-making-both in terms of their capacity to input data in a dataspace and to reuse existing data. This article speaks to PA and data governance scholars, as well as PA and data management practitioners-particularly at the local level in Europe. 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.