Recently, attention has been paid to the opportunities of data sharing across government sectors for complex public problems. These so-called ‘data collaboratives’ are seen as a novel way of leveraging different sources of data and expertise for societal impact. Data collaboratives come with new challenges that might require new governance structures and processes. So far, scant attention has been paid in the literature to data collaborative governance. This study aims to fill that gap. Building upon the collaborative governance and information sharing literature, a framework for Data Collaborative Governance is developed. This framework was tested in a living lab that focused on the public problem of anti-social behavior. Empirical data was collected over a period of one and a half years and analyzed based on an abductive research approach. The findings show that data sharing adds new elements to collaborative governance theory and practice. This study also demonstrates that a living lab is a promising methodology for studying data collaboratives. Finally, it shows that working across boundaries of organizations and sharing data to address complex problems in more collaborative ways has the potential to generate insights for complex public problems.

近来，政府部门对复杂公共问题的数据共享机会引起了关注。这些所谓的“数据协作”被视为一种利用不同数据源和专业知识来产生社会影响的新颖方式。数据协作带来了新的挑战，可能需要新的治理结构和流程。到目前为止，文献中很少关注数据协同治理。本研究旨在填补这一空白。在协作治理和信息共享文献的基础上，开发了数据协作治理框架。该框架在一个生活实验室中进行了测试，该实验室专注于反社会行为的公共问题。实证数据是在一年半的时间内收集的，并基于溯因研究方法进行分析。研究结果表明，数据共享为协作治理理论和实践增添了新元素。这项研究还表明，生活实验室是研究数据协作的一种很有前途的方法。最后，它表明跨组织边界工作并共享数据以更协作的方式解决复杂问题有可能为复杂的公共问题产生洞察力。