For universities, the science park concept offers large opportunities to play a prominent role in international innovation. In addition to forming science parks, there exists an additional attractive option. In this alternative, a creative university team creates a virtual scientific platform around a specific knowledge area that is of great strategic importance for a group of international companies. Potential platform members have in common that progress in this specific area is critical for their future. Membership fees are used to finance the team’s research program. An enterprising university may have one science park but it will have many platforms.
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If we consider the immense complexity of the present socio-economic transitions, current scientific models are unable to give a satisfactory answer to the major global issues we are facing today. Experience shows that it is a naive approach to deeply study all individual components and then expect that we will understand the entire system by bringing all these knowledge components together. In complex adaptive systems we observe properties that cannot be derived from the constituent parts (think of the human brains, the labor market or the earth’s climate). We need a different emphasis that gives much more focus on systems as a whole. For this effort we require large volumes of multi-disciplinary and multi-sectorial data (‘mass data sensing’) that, together with domain knowledge reveal the total system behavior and that provide information on the essential interactions between the individual system components (‘model-supported data analytics’). With knowledge of both – the components and the total – we will better understand the continuously changing complexity around us, with the ultimate ambition to predict ánd to influence the behavior of the involved systems. The use of multidisciplinary sensor networks will generate a wealth of information that is used to validate the assumptions in our models and to give fast feedback on the performance of new solutions. We may hope that results will improve the quality of life on our planet in a sustainable way, meaning that economic growth must be accompanied by social inclusion and environmental care.
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Today, innovation is carried out by alliances (‘innovation clusters’) with highly diverse players from different sectors. This means that in innovative industrial sectors competition goes hand in hand with new forms of collaboration. All innovation activities require information about (emerging) changes in society. This is why the combination of data science and domain knowledge (‘model-supported data analytics’) is a fast growing field. Innovation models that give good insight in the dynamics of successful projects are inclusive. They bring together natural scientists and industrial engineers as well as social scientists and market intelligence experts. All these diverse players are inspired by the same goal. In addition, together they function in a cluster with a circular architecture (‘Cyclic Innovation Model, CIM’). This circular architecture makes ample use of feedback paths, allowing a wealth of self-organized interactions. Moreover, the circular architecture emphasizes that the knowledge being generated by successes and failures must be utilized in new projects: the innovation circle is also a learning system. The transformation to a sustainable society may be the biggest challenge mankind is facing. It requires interrelated changes in technological development, human behavior as well as financial arrangements. It also requires highly diverse clusters, where academic institutions work together with leading industries and facilitating governments. The proposition is to make CIM the common innovation framework for the transformation to a better world.
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Today, we see that Western democracies fail to address the important issues in modern society, both globally and locally. Politicians show little or no interest in long-term issues; many of them appear more interested in party politics and personal benefit than caring for the future of their country. In addition, the very segmented governmental organizations come up with highly complex solutions that do not perform. Governments are consistent in asking more money from their citizens, but in return they deliver less value. We have to rethink the role of politicians and redesign the governmental system to diminish their bureaucratic footprint on society. It is time to reinvent our democracy.
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