Abstracts - EA European Academy of Technology and
Transcription
Abstracts - EA European Academy of Technology and
Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps List of Abstracts • “Predictions, forecasts and scenarios: what can models of complex socio-economic systems tell us?” Nigel Gilbert | University of Surrey, UK | [email protected] _______________________________________4 • “Technological spillovers and innovation networks – agent-based modelling of strategic scenarios” Andreas Pyka | University of Hohenheim, Germany | [email protected] _____________________________________11 • “Possibilistic prediction and risk analyses” Bruce Edmonds | Manchester Metropolitan University Business School, UK | [email protected] _______________________________________5 • “The big data science revolution” Scott Rickard | Salesforce, Seattle (WA), USA | [email protected] _____________________________________12 • “Innovation policy simulation for the smart economy – scenarios for fostering innovation in Ireland” Petra Ahrweiler / Michel Schilperoord | EA European Academy of Technology and Innovation Assessment, Bad Neuenahr-Ahrweiler, Germany | [email protected] / [email protected] _____________________________________6–7 • “Exploration of the unknown unknowns. Planning, anticipation and understanding in an uncertain world” John Casti | X-Center Network, Vienna, Austria / Hoboken (NJ), USA | [email protected] _____________________________________8–9 • “From predictive planning to anticipatory governance: combining simulation and participation in forward-looking decision-making” Matthias Weber | AIT Austrian Institute of Technology, Vienna, Austria | [email protected] _______________________________________10 • “Modelling research funding distributions, co-evolving publication-author networks, and career trajectories” Katy Börner | Indiana University, Bloomington (IN), USA | [email protected] _____________________________________13 • “Drowning in information – visual enhanced information seeking technologies – past and present” Andrea Scharnhorst | Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands | [email protected] _____________________________________14 • “FP7 collaboration networks: accepted vs. rejected proposals” Panos Argyrakis | University of Thessaloniki, Greece | [email protected] __________________________________15–16 2 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps • “What is the relation between prediction and explanation?” Paul Hoyningen-Huene | Leibniz Universität Hannover, Germany / University of Zurich, Switzerland | [email protected] _______________________________________17 • “Anticipation between prediction and speculation: different modes of orientation” Armin Grunwald | Karlsruhe Institute of Technology/ITAS, Germany | [email protected] _______________________________________18 • “Bibliometric-based visualizations and maps for technology foresight – a work in progress report” Marcus John | Fraunhofer Institute for Technological Trend Analysis INT, Euskirchen, Germany | [email protected] _______________________________________19 • “Fostering user-directed innovation – Fraunhofer´s participatory methodology” Martina Schraudner | Fraunhofer-Center for Responsible Research and Innovation, Berlin, Germany | [email protected] ____________________________________20–21 • “Delving for diamonds – understanding the research base in a comprehensive university“ Aoibheann Gibbons | University College Dublin, Ireland | [email protected] ____________________________________22–23 • “Planning and developing the Ruhr Metropolis” Hadia Straub | Ruhr Regional Association, Essen, Germany | [email protected] _______________________________________24 3 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Nigel Gilbert | University of Surrey, UK Title: Predictions, forecasts and scenarios: what can models of complex socio-economic systems tell us? Abstract: The policy-maker’s dream is to have a crystal ball which will tell him or her what the effect of a proposed new policy will be before it is implemented. Unfortunately, magic is in short supplying the policy world, but agent-based models have sometimes been called upon to act as such crystal balls, providing ex ante evaluations of policy actions. In this talk, I’ll explain why forecasting the consequences of policy changes is so difficult, and discuss some of the conceptual issues that arise from policy focused agent-based modelling. I shall also review some of the mathematical and statistical methods have been proposed to alleviate the problem of making accurate forecasts. CV: Nigel Gilbert is a Professor at the University of Surrey, United Kingdom. He is a sociologist with a special interest in computational social science. He was one of the first social scientists to use agent-based models, in the early 1990s, and has since published widely on the methodology underlying computer modelling, on basic issues in social science that can be addressed effectively using such models, and on the value of simulation for applied problems such as understanding commercial innovation and managing environmental resources such as energy and water. 4 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Bruce Edmonds | Manchester Metropolitan University Business School, UK Title: Possibilistic prediction and risk analyses Abstract: It is in the nature of complex systems that predictions that give a probability are not possible. Indeed I argue that giving "the most likely" or "rough" prediction is more harmful than useful. Rather an approach which maps out some of the possible outcomes is outlined. Agent-based modelling is ideal for producing these - including, crucially, possibilities that could not have been conceived just by thinking about it (due to the fact that events can combine in ways that are more complex than the human brain can cope with directly). A characterisation of the real future possibilities and their nature allows some positive responses to events: putting in place 'early warning indicators' for the emergence of identified possibilities, and contingency planning for when they are indicated. Such an approach would allow policy makers to better 'drive' their decision making, without abnegating responsibility to experts. CV: Bruce Edmonds is the Director of the Centre for Policy Modelling (CPM) and Professor of Social Simulation at the Manchester Metropolitan University Business School. His first degree was in mathematics and his doctorate in philosophy on the nature and definition of complexity. He publishes widely in philosophy, computer and social sciences. More about him can be found at: http://cfpm.org/~bruce 5 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Petra Ahrweiler / Michel Schilperoord | EA European Academy of Technology and Innovation Assessment, Bad Neuenahr-Ahrweiler, Germany Title: Innovation policy simulation for the smart economy – scenarios for fostering innovation in Ireland Abstract: The research in the computational work package of the “Innovation Policy Simulation for the Smart Economy” (IPSE) research project can be described with the following questions: (1) How have Irish research and innovation networks developed over time and how have their structural features evolved? (e.g. considering the Irish patent-based innovation networks, state-funded research networks, etc.) (2) What if the Irish government changes its funding rules for research and innovation networks? (e.g. bigger/smaller projects, more applied projects with the participation of SMEs, increased international scope, etc.) (3) What if the Irish government combines these changes in public funding rules with actions in other policy dimensions? (e.g. technology transfer, entrepreneurship policy, research prioritisation.) The IPSE-SKIN simulation platform, built on the Simulating Knowledge Dynamics in Innovation Networks (SKIN) model (cf. Gilbert, Ahrweiler and Pyka 2014), is designed to address these and other questions. Modules in IPSE-SKIN are made to offer realistic simulations of the dynamics of research, innovation and entrepreneurial networks in the Irish context, and new empirical databases are developed for its calibration and validation. In the final stage of the research, the impact of strategy and policy options for Ireland will be examined using the IPSE-SKIN platform, along with the development, analysis and comparison of a baseline scenario and what-if scenarios. 6 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Petra Ahrweiler / Michel Schilperoord CV: Prof. Dr. Petra Ahrweiler is Director and CEO of the EA European Academy of Technology and Innovation Assessment in Bad NeuenahrAhrweiler, Germany. She also holds a professorship for Technology and Innovation Assessment at Johannes Gutenberg-University Mainz (JGU). Her main research interests are innovation networks, simulating complex social systems, agent-based modelling, social network analysis and policy research. She has long experience as Principal Investigator of international projects on simulating innovation networks. Ahrweiler holds various research awards, is member of a number of advisory boards in both governmental and academic organisations and has published widely on innovation processes in complex social systems. Michel Schilperoord, Ph.D., is since 1/2013 (assoc.) Senior Researcher at the EA and since 1/2015 Head of the EA Lab. His main research interests are: complex social systems, agent-based modelling and innovation policy simulation. 7 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps John Casti | X-Center Network, Vienna, Austria / Hoboken (NJ), USA Title: Exploration of the unknown unknowns. Planning, anticipation and understanding in an uncertain world Abstract: A central question in planning of all types is how to allow for the so-called “unknown unknowns,” those unforeseeable events that dramatically shift the playing fields of social, political and economic life. Generally speaking, strategic planners default to trend-following in their efforts to forecast the future. But it is exactly those points where the current trend, whatever it may be, rolls over into its opposite that we most want to know about. These critical points and the events they represent are what I’ve termed elsewhere, “X-events”. The biggest problem surrounding X-events is that they are generally something that has never happened before. This means that there is no database of past events of the same sort that we can draw upon to create probabilistic estimates for the likelihood of the occurrence of such an event. In short, probability theory and statistics are of no use. But there is still plenty of risk associated with such an X-event. So what to do? How can we characterize and calculate risk in an environment where we have no data? How we might address this question will be the key focus of this presentation. In this talk, I will focus on understanding the way X-events arise, together with how to at least anticipate, if not predict, them. Methodological tools for exploring the spectrum of “would-be worlds” of the future, such as scenario planning and agent-based simulations will be discussed, along with examples of their use in uncovering the veil of uncertainty surrounding these unknown unknowns. 8 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps John Casti CV: Dr. Casti received his Ph.D. in mathematics at the University of Southern California. He worked at the RAND Corporation in Santa Monica, CA, and served as a Professor at Princeton and New York University in the USA before becoming one of the first members of the research staff at the International Institute for Applied Systems Analysis (IIASA) in Vienna, Austria. He has also been on the faculty of the Technical University of Vienna and the Santa Fe Institute in the USA. He has published eight technical monographs in the area of system theory and mathematical modeling, as well as 12 volumes of popular science, including Paradigms Lost, Complexification, Would-Be Worlds, The Cambridge Quintet, and Mood Matters. His 2012 book, XEVENTS addresses the role complexity overload plays in the creation of potentially lifechanging events such as the crash of the Internet or the outbreak of a global pandemic. Dr. Casti is currently Director of The X-Center, a private research institute in Vienna focusing on the development of tools for anticipation of extreme events in human society. He is also a Senior Research Fellow at the Center for Complex Systems and Enterprise at the Stevens Institute of Technology in New York. 9 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Matthias Weber | AIT Austrian Institute of Technology, Vienna, Austria Title: From predictive planning to anticipatory governance: Combining simulation and participation in forward-looking decision-making Abstract: The fast changing and complex nature of many future challenges requires faster, more experimental and more adaptive forms of forward-looking decision-making. Expert and stakeholder participation and public engagement are increasingly important to draw on a broader pool of knowledge, to mobilize action and enhance the legitimacy of foresight results. Foresight also needs to be properly embedded in decision-making, both in process terms along the different phases of decision-making and in structural/organizational terms as a network across policy areas. Novel simulation techniques can help explore future developments, and assess the impacts of policy interventions on these. Against this backdrop, a framework for combining and integrating novel simulation approaches in the context of participatory foresight processes are suggested. Particular attention will be paid to the embedding of these forms of future exploration in decision-preparing and decision-making processes. Recent developments at European level will be used to illustrate this. CV: Dr. Matthias Weber is Head of Research, Technology and Innovation (RTI) Policy Unit at Austrian Institute of Technology AIT, Innovation Systems Department. Before, he had been working for several years at the European Commission’s Institute for Prospective Technological Studies (IPTS) in Spain. He has a background in engineering, political sciences and economics. For the past twenty years he has been doing research on innovation systems analysis, foresight and RTI policy. He is also regularly advising government institutions at national, European and international levels on matters of RTI policy and governance. His thematic expertise covers a broad range of thematic areas (e.g. ICT, transport, energy, security, environment) as well as structural matters of RTI policy (e.g. R&D collaboration networks, priority setting, policy coordination). Current research interests of his include the impact of foresight on policy-making, system innovation and transitions, ex-ante impact assessment of policy interventions, and the governance of R&D collaboration networks. Matthias Weber is also co-chair of the European Commission’s high-level expert group on Research, Innovation and Science Policy (RISE) and President of the European Techno-Economic Policy Support Network (ETEPS). 10 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Andreas Pyka | University of Hohenheim, Germany Title: Technological spillovers and innovation networks – agent-based modelling of strategic scenarios Abstract: In economics two contradictory views on technological spillovers are prevailing: In economic growth theory technological spillovers are introduced as a solution against diminishing returns of capital and therefore are decisive to guarantee long run growth. Because of the public good character of new technological knowledge, not only the innovating firm but also others agents potentially benefit from the new technological knowledge – the sum is more than its parts because of the idea-creating features of technological spillovers and long-term growth becomes possible. Also because of the public good features of new technological knowledge, technological spillovers are considered as incentive reducing in industrial economics. The rate of investment in R&D remains below the social optimal rate and public intervention is required to restore the incentives to innovate. Obviously, this situation is not convincing, in particular because meanwhile innovation processes moved into the centre of interest of policy makers. Neo-Schumpeterian economics offers a way out of this dilemma focussing on the real nature of new technological knowledge and placing emphasis on interfirm and interindustry learning. The focus is on the channels of knowledge transfer, how they are built up in long-run trust based processes and on the requirements of firms to absorb external knowledge, which is not automatically given when we consider heterogeneous knowledge and experience-based learning. With AgentBased Modelling a methodology is available which allows for a formal analysis of collective innovation processes. The presentation will introduce to developments in the analysis of innovation processes in economics over the last 50 years. An Agent-based Model of innovation networks will be used to demonstrate the scope of innovation analysis within a Neo-Schumpeterian Economics framework. CV: Andreas Pyka graduated in Economics and Management at the University of Augsburg in 1998 and spent afterwards two years as a Post Doc in Grenoble, France participating an European research project on innovation networks. Following the Post Doc he worked as an assistant professor at the chair of Prof. Dr. Horst Hanusch at the University of Augsburg. His fields of research are NeoSchumpeterian Economics and Evolutionary Economics with a special emphasis on numerical techniques of analysing dynamic processes of qualitative change and structural development. From October 2006 to March 2009 he worked at the University of Bremen as Professor in Economic Theory. Since April 2009 Andreas Pyka holds the chair for innovation economics at the University of Hohenheim, Stuttgart. 11 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Scott Rickard | Salesforce, Seattle, USA Title: The Big Data science revolution Abstract: The combination of massive data sets, high-performance computing, and data science is transforming everything, from the way that we do science and mathematics, to the way that businesses are run and the products they produce. In this talk, I will describe and reflect on some of my experiences working in the field of big data science. Specifically, I will describe big data investigations in number theory, creating a hedge fund, and the work I do for Salesforce (which Forbes ranks as the world's most innovative company for the past four years running). CV: Scott Rickard is VP for Data Science at Salesforce. Prior to joining Salesforce, he served as CEO of Probability Dynamics, a hedge fund run out of Dublin's IFSC. For many years he was an Associate Professor in the School of Electronic, Electrical and Communications Engineering at University College Dublin (UCD) where he was the Founding Director of UCD's Complex & Adaptive Systems Laboratory (the CASL). Prior to UCD, he worked for a decade with Siemens Corporate Research applying machine learning to industrial research problems, including developing a source separation tool used by the FBI. He is also the co-founder of ScienceWithMe!, an educational website dedicated to presenting scientific concepts in engaging ways for children. He has a B.S. in Mathematics, a B.S. in Computer Science, and a M.S. in Electrical Engineering from M.I.T., and MA and PhD degrees in Applied and Computational Mathematics from Princeton University. 12 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Katy Börner | Indiana University, Bloomington IN, USA Title: Modelling research funding distributions, co-evolving publication-author networks, and career trajectories Abstract: This work discusses results from Börner, Katy, Jeegar Maru, and Robert Goldstone. 2004. "The Simultaneous Evolution of Author and Paper Networks". Proceedings of the National Academy of Sciences of the United States of America 101 (Suppl. 1): 5266-5273. Mazloumian, Amin, Dirk Helbing, Sergi Lozano, Robert Light, and Katy Börner. 2013. "Global Multi-Level Analysis of the 'Scientific Food Web'". Scientific Reports 3, 1167; DOI:10.1038/srep01167. Bollen, Johan, David Crandall, Damion Junk, Ying Ding, and Katy Börner. 2014. "From funding agencies to scientific agency: Collective allocation of science funding as an alternative to peer review". EMBO Reports 15 (1): 1-121. As well as work in progress. CV: Katy Börner is the Victor H. Yngve Professor of Information Science in the Department of Information and Library Science, School of Informatics and Computing, Adjunct Professor at the Department of Statistics in the College of Arts and Sciences, Core Faculty of Cognitive Science, Research Affiliate of the Center for Complex Networks and Systems Research and Biocomplexity Institute, Member of the Advanced Visualization Laboratory, Leader of the Information Visualization Lab, and Founding Director of the Cyberinfrastructure for Network Science Center at Indiana University in Bloomington, IN and Visiting Professor at the Royal Netherlands Academy of Arts and Sciences (KNAW) in The Netherlands. She is a curator of the international Places & Spaces: Mapping Science exhibit. She holds a MS in Electrical Engineering from the University of Technology in Leipzig, 1991 and a Ph.D. in Computer Science from the University of Kaiserslautern, 1997. She became an American Association for the Advancement of Science (AAAS) Fellow in 2012. 13 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Andrea Scharnhorst | Royal Netherlands Academy of Art and Sciences, Amsterdam, The Netherlands Title: Drowning in information – visual enhanced information seeking technologies – past and present Abstract: That we use visual techniques to create order and structure information is not new. Sketches and scribbles have accompanied knowledge production and innovation since the very beginning. One of the pioneers of modern knowledge organisation – Paul Otlet – is still famous for his visual arguments and his visual searches to how best organise knowledge and so enhance civilisation. This paper looks into those beginnings, re-inspectes current maps of science, and contemplates about missing links when it comes to the use of visual aids, maps for information navigation. CV: Dr. Andrea Scharnhorst is Head of Research and Innovation at Data Archiving and Networked Services (DANS) an institute of the Royal Netherlands Academy (KNAW) and NWO. DANS hosts two services EASY – a Trusted Digital Repository for research data primarily from the social sciences and humanities, and NARCIS – a portal to Dutch Research Information. Dr. Scharnhorst is also affiliated as scientific coordinator of the Computational Humanities Programme with the e-humanities group of the KNAW in Amsterdam. Starting in physics she got her PhD in philosophy of science. She co-edited books on Innovation Networks (with A. Pyka) and on Models of Science Dynamics (with K. Börner and P. van den Besselaar). She is editorial board member of Scientometrics. Her current work in the information sciences is devoted to the development of knowledge maps for library collections, research data archives and online knowledge spaces such as Wikipedia. She is chair of the COST Action TD1210 KnoweScape (2013–2017). 14 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Panos Argyrakis | University of Thessaloniki, Greece Title: FP7 collaboration networks: accepted vs. rejected proposals Abstract: The Framework Programmes promote and fund collaboration projects in which European research institutions and companies participate. It is a strategy developed by the European Commission to enhance research and technology advances in its member countries, while aiming for social, economic and technological convergence. In past work, several groups attempted to assess the FP5 and FP6 effectiveness, using largely statistical methods, and network analysis. Here, we study the data of FP7, following the network approach. We first construct the collaboration network of the participants of the FP7 accepted proposals. Each participant is a network node and each collaboration between two participants is a network link. We aggregate the data at the level of institute, city, region and country and get a total of four scales, which reveal a more comprehensive picture of the network. We first determine the basic network properties in all scales, and compare them to those of the accepted FP6 proposals network that were studied in previous studies. All previous publications focused exclusively on the set of the accepted proposals, which were implemented as projects. However, the set of rejected proposals could involve potentially valuable information complementary to that of the accepted ones. Therefore, we set out to to examine the network of collaborations formed by the rejected proposals, too, and compare it to that of the accepted. Any differences, or lack thereof, between these two networks in the four scales, could be useful in further assessing the effectiveness of the FP Programmes. Focusing on the country scale, we compare a selection of structural properties of these networks. Using Minimum Spanning Trees and centrality indices we determine which countries appear as the most influential and significant nodes, in each case. Our results show that there are some interesting differences between the two networks, especially on the country scale. 15 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Panos Argyrakis CV: Panos Argyrakis (b. 1950) is Professor of Physics at the University of Thessaloniki in Greece, since 1985. He studied in USA at the University of Illinois (B.S., M.S. 1974), and The University of Michigan (PhD, 1978). Before joining the faculty at Thessaloniki, he taught at the University of Crete, Greece (1980-1985). His research interests are in Theoretical Condensed Matter Physics, Computational Physics, Complexity, Networks, SocioPhysics, EconoPhysics, Large-scale computer simulation techniques. Monte-Carlo methods, Grid Computing and Parallel Computing, Smart algorithms for solution of Complex problems. Author of about 350 publications in international refereed journals, and in Conference Proceedings, Books, etc. Expert Evaluator in Scientific Journals, in Projects of the Framework Programs of the European Commission, in Projects of COST, of ESF (European Science Foundation), of ESA (European Space Agency). Expert reviewer in National Research Proposals in Greece, Belgium, the United Kingdom, in Czech Republic. Principal Investigator in over 50 projects funded by the European Commission, NATO, DAAD, Greek Secretariat of Research and Technology, Bilateral scientific agreements with Germany, France, USA, Belgium, Russia, Bulgaria, etc. Representative of Greece in several European Commission Programme Committees, Chairman of the PSWG (Physical Sciences Working Group) in ESA (European Space Agency, 2010-2015), Member of the Board in GRNET (agency responsible for software services in the Greek Academic network), and Member of the Board of GuNet (agency responsible for hardware services in the Greek Academic network). 16 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Paul Hoyningen-Huene | Leibniz Universität Hannover, Germany / University of Zurich, Switzerland Title: What is the relation between prediction and explanation? Abstract: Half a century ago, in mainstream philosophy of science the relation between prediction and explanation seemed simple: structural identity. The logical situation was assumed to be: From general sentences (laws) conjoined with singular sentences (antecedent conditions) a sentence would logically follow which, depending on circumstances, would provide an explanation or a prediction of the event in question. Today, we have a much more nuanced picture of the situation. There are different forms of both prediction and explanation, and certainly not every explanation is potentially a prediction, and vice versa. In the talk, I shall discuss some of these forms and analyze why in many cases predictions and explanations do not even potentially coincide. CV: Paul Hoyningen-Huene was until 2014 director of the Center for Philosophy and Ethics of Science at the Leibniz University of Hannover, Germany, and Professor of Philosophy at the same University. He is a physicist and a philosopher by training, was a Visiting Scholar at M.I.T., a Senior Visiting Fellow at the Center for Philosophy of Science of the University of Pittsburgh, and Professor for Philosophy at the University of Konstanz, Germany. His best-known books are Reconstructing Scientific Revolutions: Thomas S. Kuhn's Philosophy of Science (Chicago, 1993) and Systematicity: The Nature of Science (Oxford, 2013). 17 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Armin Grunwald | Karlsruhe Institute of Technology/ITAS, Germany Title: Anticipation between prediction and speculation: different modes of orientation Abstract: Debates about the future are an essential medium of modern societies' self-understanding and governance. In particular, anticipations and their assessment and reflection shall frequently advising opinion-forming and decision-making processes. The validity of anticipations, however, often is drawn into doubt. There is large space between anticipations as well-founded predictions, in some fields, and anticipations as mere speculations without any epistemic validity, in others. The more divergent the envisioned futures, the more providing reliable orientation might be without any chance of success. Against this background the aim of this paper is to distinguish three different modes of orientation which can be delivered by anticipations and their assessment. The mode 1 (predictive) orientation corresponds to the decision-theoretical model: Statements about the future are interpreted as a reliable framework into which decisions and actions have to fit as good as possible. The mode 2 orientation takes a broader picture of possible futures into account and is the scenario-based: the futures form a set of diverse possibilities within which some “robust” strategies for action might be identified. Beyond this distinction between mode 1 and mode 2 futures are more or less speculative and may completely diverge between, so to speak, paradise and apocalypse. For this case I would like to suggest a ‘mode 3’ type orientation: even diverging future studies' results can be made subject to a 'hermeneutics' of the present, where we can learn about ourselves from the diversity, variety and divergence of statements about the future. CV: Prof. Dr. rer. nat. Armin Grunwald studied physics at the universities Münster and Cologne, 1984 diploma, 1987 dissertation on thermal transport processes in semiconductors at Cologne university, 1987– 1991 software engineering and systems specialist, 1991–1995 researcher at the DLR (German Aerospace Center) in the field of technology assessment, 1996 vice director of the European Academy Bad Neuenahr-Ahrweiler, 1998 habilitation at the faculty of social sciences and philosophy at Marburg university with a study on culturalistic planning theory. Since October 1999 director of the institute for Technology Assessment and systems analysis (ITAS) at the research center Karlsruhe. Since 2002 he is also director of the Office of Technology Assessment at the German Bundestag (TAB). Since 2007 Armin Grunwald also holds the university chair of philosophy of technology at Karlsruhe Institute of Technology. Working areas: theory and methodology of technology assessment, ethics of technology, philosophy of science, approaches to sustainable development. 18 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Marcus John | Fraunhofer Institute for Technological Trend Analysis INT, Euskirchen, Germany Title: Bibliometric-based visualizations and maps for technology foresight – a work in progress report Abstract: Technology foresight is an important element of any strategic planning process, since it assists decision makers in identifying and assessing future technologies. One important assumption of this process is that tomorrow's technologies are based on today’s daily work in scientific laboratories. Thus the identification and tracking of emerging topics, i.e. the process of technology scanning and monitoring, must be based on a kind of science observatory, that continuously scans all relevant fields of science and technology. As a consequence not so much a lack but contrary a plethora of information forms a challenge for present-day researchers and decision makers. Bibliometric methods and visualizations offer the chance to tackle this ever growing amount of scientific publications by analysing and visualising the structure of the landscape of a specific scientific theme. This work in progress report will give an overview of the ongoing research at the Fraunhofer INT and addresses the question if and how bibliometric methods might enlarge the classic portfolio of technology foresight. First it will discuss the different aspects and phases of a typical technology foresight process. Then it will be demonstrated, how eavesdropping into today's scientific communication by bibliometric means might support this process. To this end a procedure coined "trend archaeology" will be presented. This approach examines historic scientific trends and seeks for specific patterns within their temporal evolution. The proposed method is a multidimensional approach, since it tries to examine multiple aspects of a scientific theme using bibliometrics. Additionally, "trend archaeology" is based on the synoptic inspection of different scientific themes, which emanate from different fields like nanotechnology or materials science. It will be argued that “trend archaeology” might be able to provide predictive information, which assists researchers in projecting current developments onto the future – an essential part of any technology foresight process. CV: Dr. Marcus John studied physics at the Technical University Berlin where he obtained his PhD in the field of theoretical astrophysics. Afterwards he worked as a post-doc at the Theory Department of the Fritz Haber Institute of the Max Planck Society in the field of protein physics. Since 2007 he has been a senior scientist at the Fraunhofer Institute for Technological Trend Analysis where he is mainly concerned with technology foresight and future-oriented technology analysis. His main fields of interest are nanotechnology, complex systems science, physics of socioeconomic systems, simulation methods and human enhancement. Additionally his work focuses on the application of bibliometric methods for technology foresight. 19 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Martina Schraudner | Fraunhofer-Center for Responsible Research and Innovation, Berlin, Germany Title: Fostering user-directed innovation – Fraunhofer´s participatory methodology Abstract: When seeking sustainable and successful ideas in the innovation process, the importance of two approaches is increasingly emphasized in the scientific community: (1) the involvement of end-users and stakeholders; and (2) the involvement of design. Processes which combine both – the early involvement of end-users and stakeholders with the early involvement of design – are not widespread and have barely been discussed in scientific research. Including and enabling end-users and stakeholders provides access to a wider range of knowledge and allows the matching of technological advances to social developments and preferences. Recognizing the value of public input, the European Commission has declared the cultivation of a participatory, knowledge-based innovation culture to be a major part of its political agenda (Horizon 2020). Furthermore, by adhering to notions of “lead users” (von Hippel 1988), “open innovation” (Chesbrough 2003) and by increasingly regarding the needs and values of laypersons as a key driver of demand-oriented innovation (Edler & Georghiou 2007), we can ultimately produce more marketable advances. However, the integration of laypersons raises methodological problems. The contribution of design in innovation processes has been well explored in consultant and research literature. The benefits, however, are mostly seen with incremental innovations. The few existing approaches that focus on the role of design in radical innovation emphasize that there is a large potential to be captured (e.g. Cooper et al. 2009; Sanders 2014, Christensen & Junginger 2014). Motivated by these considerations, the Fraunhofer Center for Responsible Research and Innovation has developed the Discover Markets process that combines both approaches. Through the use of design expertise, potential end-users and stakeholders are enabled to generate ideas for future innovations. To exemplify this approach, the presentation will outline the process model, focusing on new methods of early engagement and participatory design in innovation processes. 20 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Martina Schraudner CV: Prof. Dr. Martina Schraudner is the Head of Fraunhofer Center for Responsible Research and Innovation and professor at Berlin Institute of Technology. Her research interests include (need-oriented) research planning, process design, gender diversity management and corporate cultures. 21 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Aoibheann Gibbons | University College Dublin, Ireland Title: Delving for diamonds – understanding the research base in a comprehensive University Abstract: Publicly funded Research Universities are viewed as engines of innovation and economic renewal in national systems. In recent years, science policy makers drive university leaders to express their research base as both economically relevant and internationally competitive so as to attract foreign direct investment into a national economy. Tying public funding for research to economic policy goals can create difficult choices for comprehensive universities carrying out basic research and supporting a wide range of discipline across the Arts and Sciences. The concept of the university as a globally connected and dynamic research network is presented using two dimensional maps of science drawn from bibliographic databases and datasets from UCDs in-house research information systems. 11 candidate priority themes are used to visually profile UCDs research capacity, citation impact, collaborations and industry relationships. Key observations are Science maps allow for the representation of diverse and large sets of data in a succinct way that is understandable by non-expert viewers Science maps are a very effective communications tool when brokering change Linking science maps of research priorities back to university social structures is necessary to win academic acceptance Mapping international co-authorship on publications instead of funding partnerships reveals a university network that is wider and more inclusive of Humanities and Social Science scholarship. The concept of the university as a globally connected dynamic research network within a national system is useful. It allows a university to formulate agile responses to diverse pressures from policy makers, funders and industry. 22 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Aoibheann Gibbons CV: As Director of Research Strategy and Development in University College Dublin, Dr. Aoibheann Gibbons developed and led an ambitious strategy programme that led to the transformation of the universities research reputation from below world average in 2004 to 60% above world average in 2014. Before UCD, Aoibheann spent a number of years in senior leadership roles in Telecoms and Digital Media. Throughout her career, Aoibheann has developed many international collaborations with diverse organisations to deliver programmes supported by industry and by research investment in Life sciences, Information & communication technologies, education and culture. With a PhD in Science (Neuroscience), Aoibheann developed her early career in the U.S. pharmaceutical industry progressing from laboratory to business settings. Based in California and New York, she gained international experience in protecting and licensing technologies and in developing fundraising propositions for start-up technology organisations. 23 Abstracts of the Annual EA Conference 2015, 11–12 May Planning, Prediction, Scenarios – Using Simulations and Maps Hadia Straub | Ruhr Regional Association, Essen, Germany Title: Planning and developing the Ruhr Metropolis Abstract: Ruhr Regional Association (RVR), founded in 1920, is the first organisation for developing regional settlements in Germany on a statutory basis including a wide range of rights within the planning sector including developments of settlements, infrastructure corridors, regional green belts. Since 2010, RVR is responsible again for regional planning, that is, a formal spatial development strategy for the next 15 years which is binding for municipalities and public bodies. In this context, we have developed the “regional discourse” ahead of the formal process in order to integrate all stakeholders (municipalities, institutions, business and civil society) into planning the future Ruhr Metropolis. It not only focuses on Ruhr regional plan, but integrates all planning activities of RVR – formal and informal approaches – in the process of developing the draft of Ruhr regional plan. Therefore, we have developed methods to tackle different aspects of the development of settlement areas: change (ruhrFIS monitoring of the development of settlement areas) and future demand of settlement areas. Both approaches will be presented. CV: Dr. rer. nat. Hadia Straub, née Köhler, graduated in Geography at Humboldt-Universität zu Berlin. Here doctoral scholarship from DFG in research training programme 780/2 “Perspectives on Urban Ecology”. Work in the fields of settlement development, urban infrastructures, and mobility at German Institute of Urban Affairs (Difu), the state planning authority of the federal state of North Rhine-Westphalia and Ruhr Regional Association (RVR; since 2011). Team leader of the team master planning at RVR since 2015. 24