The field of public participation is developing fast, with phenomena such as citizen science and crowdsourcing extending the resource base of research, stimulating innovation and making science more accessible to the general population.Promoting public participation means giving more weight to citizens and civil society actors in the definition of research needs and in the implementation of research and innovation. As yet, there is limited understanding of the implications of widespread use of public participation and as a result, there is a risk that it will become a burden for research and an obstacle to bridging the gap between research and society. This volume presents the findings of a three-year international study on innovative public participation. The resulting work studies the characteristics and trends of innovative public participation through a global sample of 38 case studies. It provides theoretical generalisations on the dynamics of public participation, suggestions for an evaluation framework and clear empirical examples of how public participation works in practice. Illustrated by best practice cases, the authors identify characteristics which contribute to successful public participation.The book is aimed primarily at scholars and practitioners of public participation, as well as research managers, policy makers and business actors interested in related issues. There is also a secondary market for students and scholars of European governance studies, sociology and political sciences.

Online deliberation research has recently developed automated indicators to assess the deliberative quality of much user-generated online data. While most previous studies have developed indicators based on content analysis and network analysis, time-series data and associated methods have been studied less thoroughly. This article contributes to the literature by proposing indicators based on a combination of network analysis and time-series analysis, arguing that it will help monitor how online deliberation evolves. Based on Habermasian deliberative criteria, we develop six throughput indicators and demonstrate their applications in the OmaStadi participatory budgeting project in Helsinki, Finland. The study results show that these indicators consist of intuitive figures and visualizations that will facilitate collective intelligence on ongoing processes and ways to solve problems promptly.

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The next generation of Science, Technology & Innovation (STI) policies will be defined by mission orientation and co-creation processes and implemented by dynamic public-private partnerships. However, the experience of European countries up to now in attempting to boost cooperation in innovation reveals a very different story. Beyond some contextual factors, the characteristics of the agents involved, the dynamics of their relationships and the design of the collaboration tools also have a critical influence at organisational level. This paper aims to identify these organisational factors in different contexts through the analysis of the Demola model, a university-industry innovation platform created in Finland which has spread to other countries, including Spain. Demola applies a standardised model but it has differences in its functioning depending on the national levels of collaboration in the innovation systems. In our case study, we have compared Finland and Spain, bearing in mind the features of the agents involved and their relationships, through a content analysis of primary and secondary information. The results of the study show that the institutional structure of the collaboration and the organisational culture of each institution are key factors in its functioning. These results can be useful for innovation managers, university leaders, educational experts and policy makers.