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 |
n.gilbert@surrey.ac.uk
_______________________________________4
• “Technological spillovers and innovation
networks – agent-based modelling of strategic
scenarios”
Andreas Pyka | University of Hohenheim,
Germany | a.pyka@uni-hohenheim.de
_____________________________________11
• “Possibilistic prediction and risk analyses”
Bruce Edmonds | Manchester Metropolitan
University Business School, UK |
bruce@edmonds.name
_______________________________________5
• “The big data science revolution”
Scott Rickard | Salesforce, Seattle (WA), USA |
srickard@salesforce.com
_____________________________________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 |
petra.ahrweiler@ea-aw.de /
michel.schilperoord@ea-aw.de
_____________________________________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 | castiwien@cs.com
_____________________________________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 |
matthias.weber@ait.ac.at
_______________________________________10
• “Modelling research funding distributions,
co-evolving publication-author networks, and
career trajectories”
Katy Börner | Indiana University, Bloomington
(IN), USA | katy@indiana.edu
_____________________________________13
• “Drowning in information – visual enhanced
information seeking technologies – past and
present”
Andrea Scharnhorst | Royal Netherlands
Academy of Arts and Sciences, Amsterdam, The
Netherlands |
andrea.scharnhorst@dans.knaw.nl
_____________________________________14
• “FP7 collaboration networks: accepted vs.
rejected proposals”
Panos Argyrakis | University of Thessaloniki,
Greece | panos@auth.gr
__________________________________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 | hoyningen@ww.uni-hannover.de
_______________________________________17
• “Anticipation between prediction and
speculation: different modes of orientation”
Armin Grunwald | Karlsruhe Institute of
Technology/ITAS, Germany |
armin.grunwald@kit.edu
_______________________________________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 | marcus.john@int.fraunhofer.de
_______________________________________19
• “Fostering user-directed innovation –
Fraunhofer´s participatory methodology”
Martina Schraudner | Fraunhofer-Center for
Responsible Research and Innovation, Berlin,
Germany | martina.schraudner@zv.fraunhofer.de
____________________________________20–21
• “Delving for diamonds – understanding the
research base in a comprehensive university“
Aoibheann Gibbons | University College Dublin,
Ireland | gibbons.aoibheann@gmail.com
____________________________________22–23
• “Planning and developing the Ruhr Metropolis”
Hadia Straub | Ruhr Regional Association, Essen,
Germany | straub@rvr-online.de
_______________________________________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.
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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.
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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.
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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.
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