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The PoliVisu project has the goal to investigate the potential of data use and visualisation in urban policy making. The project has explored how data supported policy making is adopted by public administrations and what we can learn from their experience. This is done by enrolling pilot cases with different and specific policy problems. From the experience of the PoliVisu pilots the influence and added value of data in the policy making process is assessed. Considering the recent “shake” in data production and use, PoliVisu has adopted four driving questions, as follow: what are the new roles data can play in the policy making process?, What is the added value of data for policy making? How can innovative visualisations contribute to improve the use of data in policy making processes? To what extent can an increased adoption of data affect the policy making process? How is the data shake affecting the involvement of non-institutional actors in the policy making process? This paper explores these questions, by presenting the experiences and the lessons learnt, also focussing on specific pilots’ initiatives and results.

This entry contains all the slides from the presentations given during theEvidence Based Policymaking in Europe Summit 2021 which was organised by the Data Driven Policy Clustertook place 9-10 December 2021.

The session showcases examples of Smart Government initiatives across Europe that integrate AI, Digital Twins and Big Data solutions. A focus lies on co-creating services with the use of the 3 aforementioned technologies. Thethe three panel members are:Mr. Lieven Raes Smart City expert at Information Flanders, Belgium, Ms. Leire Orue-Echevarria Arrieta Coloud Technologies expert at TECNALIA R&I, Spain, andIskra Yovkova from the Municipality of Sofia wholeadsPolicy Cloud's use case of urban policy making through analysis of crowdsourced data.

As part of the rhetoric surrounding the Smart City concept, cities are increasingly facing challenges related to data (management, governance, processing, storage, publishing etc.). The growing power acquired by the data market and the great relevance assigned to data ownership rather than to data-exploitation knowhow is affecting the development of a data culture and is slowing down the embedding of data-related expertise inside public administrations. Concurrently, policies call for more open data to foster service innovation and government transparency. What are the consequences of these phenomena when imagining the potential for policy making consequent to the growing data quantity and availability? Which strategic challenges and decisions do public authorities face in this regard? What are valuable approaches to arm public administrations in this “war on data”? The Smart Flanders program was initiated by the Flemish Government (Belgium) in 2017 to research and support cities with defining and implementing a common open data policy. As part of the program, a “maturity check” was performed, evaluating the cities on several quantitative and qualitative parameters. This exercise laid to bare some challenges in the field of open data and led to a checklist that cities can employ to begin tackling them, as well as a set of model clauses to be used in the procurement of new technologies.

This open access book represents one of the key milestones of PoliVisu, an H2020 research and innovation project funded by the European Commission under the call “Policy-development in the age of big data: data-driven policy-making, policy-modelling and policy-implementation”. It investigates the operative and organizational implications related to the use of the growing amount of available data on policy making processes, highlighting the experimental dimension of policy making that, thanks to data, proves to be more and more exploitable towards more effective and sustainable decisions. The first section of the book introduces the key questions highlighted by the PoliVisu project, which still represent operational and strategic challenges in the exploitation of data potentials in urban policy making. The second section explores how data and data visualisations can assume different roles in the different stages of a policy cycle and profoundly transform policy making.