The buzz surrounding big data has taken shape in various theoretical and practical forms when it comes to policymaking. The paper combines current research streams with long-standing discussions on government and technology in public policy and public administration, such as e-government and evidence-based policymaking. The goal is to answer the question whether big data is a fleeting trend or has long-lasting effects on policymaking. Three larger themes in the literature are identified: First, the role that institutional capacity has within government to utilize big data analytics; second, government use of big data analytics in the context of digital public services; and finally, the way that big data information enters the policy cycle, focusing on substantive and procedural policy instruments. Examples from the education, crisis management, environmental and healthcare domain highlight the opportunities and challenges for each of these themes. Exploring the various aspects of big data and policymaking shows that big data is here to stay, but that its utilization by government will take time due to institutional barriers and capacity bottlenecks.

The paper addresses the growing scepticism around big data use in the context of smart cities. Big data is said to transform city governments into being more efficient, effective and evidencebased. However, critics point towards the limited capacity of government to overcome the siloed structure of data storage and manage the diverse stakeholders involved in setting up a data ecosystem. On the basis of this, the paper investigates the challenges city governments face when dealing with big data in the context of carbon emission reduction. Through the lens of the evidence-based policy and policy capacity literature, the cities of Copenhagen (Denmark), London (UK), Malmö (Sweden), Oxford (UK) and Vienna (Austria) are analysed. The cases reveal that the institutional complexity underlying big data integration limits local government capacity to set up data management structures that would allow further utilization of big data and that current solutions focus on local pilot sites and outsourcing of data analytics. ARTICLE HISTORY

Cities and municipalities are vital actors in addressing climate change. Because they are directly affected by the consequences of environmental transformations, cities are motivated to shape adaptation and mitigation. This paper looks at the possible mechanisms which cities can use to engage in climate change issues without decoupling themselves from the national or sub-national level and while remaining consistent with other local initiatives. The paper analyses the European approach towards transnational municipal networks (TMNs) and community collective efforts and assesses its possible application in other jurisdictions. We argue that while TMNs are the institutional foundation for a concerted effort in climate change within and between countries; they are also subject to provisions from national and regional governments, which might hamper their benefits. Based on a typology of TMNs and an analysis of the national contexts, the paper finds that those networks that target a specific region and are supported by government have the most benefits for climate change.

Policy and data scientists have paid ample attention to the amount of data being collected and the challenge for policymakers to use and utilize it. However, far less attention has been paid towards the quality and coverage of this data specifically pertaining to minority groups. The paper makes the argument that while there is seemingly more data to draw on for policymakers, the quality of the data in combination with potential known or unknown data gaps limits government's ability to create inclusive policies. In this context, the paper defines primary, secondary, and unknown data gaps that cover scenarios of knowingly or unknowingly missing data and how that is potentially compensated through alternative measures. Based on the review of the literature from various fields and a variety of examples highlighted throughout the paper, we conclude that the big data movement combined with more sophisticated methods in recent years has opened up new opportunities for government to use existing data in different ways as well as fill data gaps through innovative techniques. Focusing specifically on the representativeness of such data, however, shows that data gaps affect the economic opportunities, social mobility, and democratic participation of marginalized groups. The big data movement in policy may thus create new forms of inequality that are harder to detect and whose impact is more difficult to predict.