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It was suggested that maybe technology foresight could learn something from the past 20 30 years in socioeconomic study of science and technology,
The second paper by Porter illustrates a technique to carry out quick empirical technology analyses based on wide availability of rich science
and tracing the role of dirreversibilitiest of technological changes (i e. expectations that guide the research activities of scientists and firms,
Foresight has become particularly important in science and technology policy 3, 4, but also in relation to sustainability and other long-term, uncertainty-ridden policy issues.
First of all, it has moved away from a forecastingtyyp focus on science and technology to an incorporation of first market and then also increasingly social considerations.
This strand of thinking has been developed by many researchers and practitioners over a considerable time-span.
Priority-Setting in Science, Pinter Publishers, London, 1989.8 M. Decker, M. Ladikas (Eds. Bridges Between Science, Society and Policy Technology assessment Methods and Impacts, Springer, Berlin, 2004.9 S. Joss, S. Belluci (Eds.
Participatory Technology assessment, European Perspectives, CSD, London, 2002.480 E. A. Eriksson, K. M. Weber/Technological forecasting & Social Change 75 (2008) 462 482
opportunities in wood material science and engineering. This consultation process involved eighteen funding organizations fromeight European countries
aswell as over 400 participantswho represented relevant stakeholder groups, most notably leading researchers and industrialists. Methodologically, the processwas based on the Internet-based solicitation and assessment of research issues, the deployment ofrobust Portfoliomodeling (RPM) in the identification of promising research issues,
and implementation of an embedded foresight process that was organized in the ERA NET program on wood material sciences 8. Building on the experiences from this process,
each with a focus on a specific field of science and/or technology, for the purpose of supporting mutual learning, opening-up of national innovation systems and the development of new collaborative forms of European RTD funding.
, availability of funding to foreign researchers. Furthermore, they have different management practices as concerns the launching, monitoring and evaluation of RTD projects;
Its goal is to deepen the collaboration between the European funding organizations in the field of wood material science in order to coordinate the use of research funds,
United kingdom) eventually have decided to launch a cofunnde research program in the field of wood material science.
Drawing upon experiences from earlier collaboration with the Systems analysis Laboratory at Helsinki University of Technology in the development of a Scandinavian co-funded Wood Material Science Research program 16, the project plan for the Woodwisdom
by developing a framework for the field of wood material science, consisting of four research areas and 23 sub-areas. 6 Stakeholder participation,
For example, he/she invited Researchers and Industrial leaders to participate in the different phases of the process.
Furthermore, the process engaged an extensive set of RTD stakeholders from eight countries, most notably Researchers and Industrial leaders:
Researchers consisted of leading researchers at universities, research institutes or industrial research organizations on wood material science and related sciences.
from each participating country, prominent Researchers and Industrial leaders were invited to three interactive workshops to discuss
the Researchers proposed a total of 317 issues. These issues were assessed by Researchers and Industrial Table 1 Phases of the Woodwisdom-Net consultation process Task Participants Schedule 1. Solicitation of research issues Researchers Mid-july Mid-october05
2. Assessment of research issues Researchers December05 Mid-january06 3. Assessment of research issues Industrial leaders Three last weeks of January06 4. Initial
screening of research issues Project team January February06 5. Three one-day workshops for Researchers and Industrial leaders 10 12 Researchers and Industrial leaders
/workshop Mid-february,06 6. A one-day workshop for funding organizations Representatives from funding organizations End of March
In the first phase, National Coordinators invited Researchers in their respective countries to submit research issues through the Internet questionnaire. 8 These questionnaires were implemented by using Opinions-Online decision support tool9
which allowed the Researchers to submit as many issues as they desired. For the purpose of information management, Researchers were asked to indicate which research area
and sub-area the issue would fit best within a taxonomical framework that was developed for the research issues.
Researchers were requested first to provide a short title and a short description (about 200 words).
Researchers were asked also to justify the issue by describing expected results and impacts (e g.,, enhancement of competitiveness),
In total, well over 200 Researchers from the participating countries submitted research issues. 3. 2. 2. 2. Assessment of research issues from the research perspective.
In the second phase, National Coordinators invited Researchers to assess the research issues that had been submitted in the first phase.
Researchers were asked first to choose which sub-areas they were interested in, whereafter they could assess those issues that they were interested in.
Within each of the 23 sub-areas, some 10 to 50 Researchers provided assessments while more than 200 Researchers in total took part in the assessment activity.
The questionnaire was open from December 2005 until Mid-january 2006. For each issue, Researchers were asked first to assess the issue with regard to Novelty (i e.,
, the extent to which they felt that the proposed issue was novel in wood material science.
Second, they were asked to estimate how interested they would be in participating in eventual projects on the issue.
Researchers that were interested in working on a particular research theme were asked also to identify themselves and, moreover, to describe how they would like to contribute to a possible project later on. 3. 2. 2. 3. Assessment of research issues from the industrial perspective.
and the workshop participants were welcome to highlight any other issues that they regarded interesting on any other grounds. 3. 2. 2. 5. Workshops for researchers and industrial leaders.
and the workshops were attended by 10 15 experts on wood material science. Thematically, the workshops focused on the following topics:
In effect, the bottom up consultation process in Woodwisdom-Net where the participating researchers and industrialists interacted with a large shared pool of research issues can be contrasted with less transparent processes of international RTD priority setting where the preliminary priorities
Another benefit is that the funding organizations can define the priorities based on a realistic understanding of what issues researchers are keen on pursuing
together with an analysis of how interested the researchers are in working on these issues, may assist in the formation of new collaborative networks.
2005) is Researcher and doctoral student at the Systems analysis Laboratory of Helsinki University of Technology, with research interests in foresight, decision support systems and strategic decision making.
Totti Könnölä (M. Sc. 2001, D. Tech. 2006) is Researcher at the Institute for Prospective Technological Studies (IPTS) in Seville.
Previously, he has been Senior researcher at the VTT Technical research Centre of Finland, Researcher at the Systems analysis Laboratory in the Helsinki University of Technology and Expert in Gaia Group Oy
which makes use of science and technology indicators and enables the identification of possible fields which may cause challenges for the regulatory framework and the regulatory bodies.
we have to mention the other tradition of science and technology foresight exercises as instruments for governments,
whereas traditional technology foresight studies look for new promising fields in science and technology or new trends or needs in the market.
and policy-makers responsible for regulatory regimes but not for science and technology policy in the narrower sense to identify future requirements for regulations
and often part of larger foresight exercises driven by stakeholders of science and technology policies. Moreover national SDOS, including some in the USA
indicator-based approaches surveys Delphi studies. 3. Methodologies 3. 1. Indicator-based approaches 3. 1. 1. Introduction and definition New developments in science and technology
Changes and dynamics in science and technology can be identified and traced by different indicators. These indicators allow the creation of comparisons between scientific and technological fields, between countries, organisations,
The most important science and technology indicators are publications in scientific journals and patents 20. The former indicator reflects better the activities in basic research
Fig. 2 gives an overview of the science and technology indicators. The use of indicators to perform regulatory foresight exercises is just beginning.
Since there are numerous regulatory challenges triggered by the dynamics in science and technology one has to differentiate the analysis in those fields of high dynamics.
This procedure allows a rough assessment of the possible regulatory challenges caused by the dynamics in science
which use science and technology indicators in order to explain future challenges for regulatory authorities, including standardisation organisations. Blind 25 shows, based on international and inter-sectoral cross-section data, that the output of formal standardisation bodies can be explained significantly by the patent applications as a reliable indicator for the dynamics in the respective technologies.
and innovation activities may challenge the existing regulatory framework and Fig. 2. Science and technology indicators (Source: Blind 21 modifying Grupp 24). 502 K. Blind/Technological forecasting
However, the proved link between science and technology, on the one hand, and changes in existing regulations or new regulations, on the other hand, underlines that the former can in general be used to determine possible challenges for the regulatory framework in the future.
Whereas standardisation activities are connected meanwhile to science and technology indicators in a reliable way 21, the link between science and technology indicators and indicators describing the regulatory framework is established not yet.
This deficit is caused by a significant lack of regulatory indicators and especially of respective time series and of rather differentiated sub-categories in regulation.
Furthermore, not all new developments in science and technology, but especially those with possible impacts on health, safety, the environment and on the functioning of markets require an adjustment of the regulatory framework.
and requires further methodological efforts. 3. 1. 3. General assessment Science and especially technology indicators are a possible source to detect challenges for the regulatory framework in the future.
Furthermore, simple quantitative approaches by constructing time series of science and technology indicators are not sufficient. It is necessary to focus, in a second step,
Science and technology indicators are easily available in publicly provided or commercially distributed databases. However, the methodological challenge is to meet the adequate level of specification and differentiation of the technology indicators,
The simple quantitative use of science and technology indicators in order to detect future challenges for the regulatory framework is not sufficient.
The scope of science-and technology-based indicator approaches is certainly in detecting possible fields
Further more technology specific surveys focusing on the future regulatory requirements to react to progress in science
33 was one of the first researchers who conducted first case studies on standards for services
and lead to representative results, the data can be combined with indicator-based approaches representing the universe in science and technology.
Regulation was included in a set of possible obstacles, like lack of capital or human resources, for the development of science and technology.
The relatively small importance of the regulatory framework for the future development of new issues in science and technology compared to other policy instruments is confirmed in the follow-up studies,
but also in the field business regarding e-commerce-related issues. 4 In summary, Delphi exercises focusing on the future of science and technology take the general regulatory framework into account as one kind of obstacle,
This is a different target group compared to science and technology foresights focusing both on active researchers and stakeholders responsible for shaping and performing R&d programmes.
In general, the people addressed should be selected according to a minimum degree of expertise in the field. 511 K. Blind/Technological forecasting
Again in contrast to traditional science and technology foresight exercises representatives from companies, especially those involved in regulatory affairs
An important general limitation of the Delphi method is the well-known fact that sudden science and technology breakthroughs often have not been foreseen by the majority of main stream oriented experts,
Especially the use of science and technology indicators to detect future challenges for and fields of regulations is developed not yet.
but also researchers, to be involved in the regulatory process. Based on the few existing experiences with surveys, it can be concluded that this methodology allows the identification of very specific future regulatory issues.
which allow at least the identification of stakeholders in science and technology working both in research institutes
and assessment of regulatory foresight methodologies Methodology Type Data requirements Strengths Limitations Indicators Quantitative also providing qualitative information Adequate science
who also cannot be identified by the use of science and technology indicators. The use of Delphi studies for regulatory foresight is faced with the similar strengths
and weaknesses of using this approach to identify future trends in science and technology. In addition
since not only experts in science and technology, possible users and consumers, but also members of public organisations, e g. regulatory bodies, have to be addressed.
if rather specific commercial applications of new sciences and technologies already exist. For shaping regimes of intellectual property rights,
9 B. R. Martin, Foresight in science and technology, Technol. Anal. Strateg. Manag. 7 (2)( 1995) 139 168.10 K. Blind, K. Cuhls, H. Grupp, Current foresight activities in Central europe, Technol.
The Delphi method, Rand Corporation, Santa monica, 1967.17 J. Irvine, B. R. Martin, Foresight in Science, Picking the Winners, London, Dover, 1984.18 P. Swann:
Handbook of Quantitative Science and Technology research, Kluwer Academic Publishers, Dordrecht (The netherlands), 2004.21 K. Blind, The Economics of Standards Theory, Evidence, Policy, Edward Elgar, Cheltenham
Ein Rückblick auf 30 Jahre Delphi-Expertenbefragungen, Physica Verlag, Heidelberg, 1998.43 National Institute of Science and Technology policy (NISTEP:
45 National Institute of Science and Technology policy (NISTEP; Science and Technology agency (1997: The Sixth Technology Forecast Survey Future technology in Japan toward The Year 2025, No. 52, NISTEP Report, Tokyo,(1993.
46 K. Cuhls, K. Blind, H. Grupp, Delphi'98 Umfrage. Zukunft nachgefragt, Studie zur globalen Entwicklung von Wissenschaft und Technik, Karlsruhe, 1998.47 K. Cuhls, T. Kuwahara, Outlook for Japanese and German Future technology
, Comparing Technology Forecast Surveys, Physica-Verlag, Heidelberg, 1994.48 Science and Technology foresight Center (NISTEP), The Seventh Technoloy Forecast Future technology in Japan toward the Year 2030, No. 72
Tilo Propp b a Department of Science, Technology, Health and Policy Studies, University of Twente, Enschede, The netherlands b Department of Innovation and Environmental sciences, University of Utrecht, Utrecht
accepted 1 february 2008 Abstract Roadmapping serves both short and long term (strategic) alignment in science and technology (S&t.
Our tool can be applied in strategic management of research andr&dat the level of science-to-industry networks.
For new and emerging fields of science and technology (S&t) where architectural (radical innovations might occur 1,
However, in an age of strategic science and high-investment projects decision makers need to identify possible and promising directions and options and influence technology emergence in advance.
Noes have to combinevertical'or bottom-up management of a portfolio of research projects withhorizontal'stimulation of science-to-industry innovation chains.
The Technology assessment Programme is part of the Science to Industry work package and the Ethical and Societal Aspect package,
and 2. exploring strategies for specific actor groups (SMES and researchers. At both intra-organizational (department-level) and inter-organizational levels in technology and industry, roadmapping has become a fashionable alignment tool.
In contrast, analyses of assessment practices of researchers and start-ups (who constitute the larger part of Frontiers) seemrare.
Scientists undertake assessments all the time; these assessments are functioning if not always characterised by breadth of focus (a broader view of the field) and depth of vision (i e. possible applications in the long term.
and looks at sociotechhnica paths as emerging as outcomes of actor alignments within and across multilevels. 13 Researchers working with the concept of socio-technical paths have recently taken up the notion of emerging irreversibilities.
In this dotted bubble, researchers attempt to develop and bridge the technology hurdle of integrating these proof-of-principle devices
MPM-1) the technical dimension of the MPM was based on desk research as a map to be used for the Frontiers network to aid strategy articulation in research and science-to-industry linkages,
Looking at specifics of innovation chains addresses the management challenge 2, development and maintenance of science-toinduustr links through stimulation of innovation chains.
As possible participants we identified (1) researchers in microfluidics, microfabrication and nanotechnology tools for cell analysis and (2) start-up companies and small-and medium-sized enterprises (SMES) relating to specific cell analysis techniques and lab-on-a-chip technology.
the workshop participants recognized the difficulty of researchers in public institutions getting credit in developing integrated platforms.
which can in themselves be turned into innovations. 23 This also a general issue in relation to the current situation of strategic science and application oriented research. 532 D. K. R. Robinson, T. Propp/Technological forecasting
Manag. 11 (4)( 1999) 493 525.11 R. N. Kostoff, R. R. Schaller, Science and Technology roadmaps, IEEE Trans.
Change 71 (1 2)( 2004) 161 185.23 G. Spinardi, R. Williams, The Governance Challenges of Breakthrough Science and Technology, in:
Developing an Integrated Policy Approach to Science, Technology, Risk and the Environment, Ashgate, Aldershot, 2005, pp. 45 66.24 S. K. Kassicieh, S. T. Walsh
Improving Distributed intelligence in Complex Innovation systems, Final Report of the Advanced Science and Technology policy Planning Network (ASTPP.
18 july September 2006) Number 3 4. 49 M. Callon, J. Law, A. Rip, Mapping the dynamics of science and technology, The Macmillan Press Ltd.
Electrophoresis-Based Chemical analysis System on Chip, Science 261 (1993)( 5123). 53 H. Andersson, A. Van den berg, Microfluidic devices for cellomics:
, Science 309 (2005. 58 J. Voldman, M. L. Gray, M. Toner, M. A. Schmidt, A microfabrication-based dynamic array cytometer, Anal.
A further master's degree focused on an interdisciplinary study of the space sector combining science, technology policy and innovation studies with a final thesis focusing on cosmonautics research in the former Soviet union with field research undertaken at the Cosmonaut Training Centre (Star City) and the Institute of Biomedical Problems, Moscow.
He worked in South africa on the dynamics of social development projects and science-and-technology-in-society issues and at Twente University,
'The diversity of the above areas suggests that foresight process impacts should be interpreted through the lenses of epistemology, sociology, political science, management science and organisational theory.
Certain developments have led to undesired effects and to a decreasing trust in science, scientists and decision-makers.
The alignment of actors goes beyond the usual actors in previous times (i e. government, industry and scientists.
foresight can help break down some of the barriers between science and society both crucial developments if the emerging knowledge societies are to cope with social, environmental and intellectual complexity.
interdepartmental and interdisciplinary space needed for forward thinking on science-based issues. Impacts were grouped 11 See for example 2, 3, 8, 15 17.
In terms of ultimate impacts, the exercise influenced research agendas in the science base and in industry and influenced the shape and course of government policy.
and extensive media promotion that raised the profile of science, technology and innovation on the national agenda.
Efforts were made to bridge numerous divides between the public private sector, between political parties, between scientific disciplines and between generations.
Foundations and Frameworks, Edward Elgar, 2003.12 H. Nowotny, P. Scott, M. Gibbons, Rethinking Science. Knowledge and the Public in an Age of Uncertainty, Polity Press, Cambridge, 2001.13 A. Guimaraes Pereira, S. Funtowicz, Quality assurance by extended peer review:
) 539 557 24 B. Latour, Science in Action: How to Follow Scientists and Engineers Through Society, Open University Press, Milton Keynes,
1987.25 B. Latour, Reassembling the Social: An Introduction to Actor-Network-theory, Oxford university Press, Oxford, 2005.26 A k. Baker, Chapter 9:
She is currently a freelance research and innovation policy analyst and a part-time Phd researcher at PREST.
Since 1996 she held the position of Director of the Science and Technology policy Studies Unit at ATLANTIS Research organisation (Greece)
A methodological experiment Attila Havas Institute of Economics, Hungarian Academy of Sciences, Budaörsi út 45.
changing science society links and societal demands towards universities; demographic changes,massification'of higher education, and studentconsumerrism'technological development (offering new opportunities,
as the broadest socioeconomic context for universities, with its own science, technology and innovation (STI) policy tools,
training the future generation of researchers, engineers, managers (including R&d managers), experts, and policy-makers (among many other fields, for STI policies);
In other words, the links between science and technology are far from being (uni-)linear. Contrary to the widespread belief that technologies are, in essence, applied sciences,
a number of scientific disciplines evolved from the puzzles why certain technologies work as they do 22.12 This list is far from being exhaustive:
training of future generations of researchers is understood to have overriding importance among the other benefits of basic science,
a huge variety can be observed among the EU (and OECD) members both in terms of theirpool'of researchers,
i e. the number of researchers per 1000 labour force. Second, both employment and financial data, that is, spending on R&d activities by research performing sectors, suggest a great diversity in terms of theweight'of these sectors.
and the Academies of Sciences in a number of Central and Eastern European countries. 19 For a more detailed description of public research centres, especially on the variety of players in this sector, e g. in terms of organisational forms and changing ownership (public,
and as the training of the future generation of researchers. 565 A. Havas/Technological forecasting & Social Change 75 (2008) 558 582 The most important driving forces can be derived by considering the increasingly intense global competition in research activities;
and in the meantime a fierce competition for talents (Phd students and researchers) among universities, as well as between universities and other research actors.
Second, new types of currentlyunthinkable'research players might also Fig. 2. The distribution of researchers by R&d performing sectors (FTE, most recent years.
of which are briefly summarised below. 1. Intensifying international mobility of postgraduate students and researchers. Currently, postgraduate courses offered by US universities are particularly attractive for foreign students,
including those from the EU. Nearly 60%of science and engineering doctoral students coming from EU countries have firm plans to stay in the US upon the completion of their studies,
NGOS and patient groups as research players. 24 These policy initiatives are criticised heavily by researchers on various grounds.
Besides conventional academic researchers, knowledge is produced by a wide variety of players, e g. think tanks, private research organisations, nonprofit organisations, government agencies, consultancy companies, market research organisations, patients'groups, various
some (minimal) research efforts to tackle social challenges stemming from the widening gaps between flourishing and laggard EU regions Mobility of researchers, university staff and students Two-way traffic:
Double success case Trends, driving forces Universities Largely unchanged universities Radically reformed universities The role/mission of universities The main emphasis is on teaching andbasic research'(science for the sake of science), not much interaction
and able to adapt to this new environment Mobility of researchers, competition for talents Only a fewworld-class'EU universities can attract talents from advanced Triad regions A large (r) number of EU universities become attractive for talents from advanced
but conducted in the rationale ofpure science':'the complexities of societal issues and competitiveness are addressed not;
putting emphasis only on enhancing competitiveness Mobility of researchers, competition for talents Same as in the Double success case A large (r) number of EU universities become attractive for talents from advanced Triad regions Conscious efforts on aone-way street'type
but conducted in the rationale ofpure science':'crosscutting'issues relevant to enhancing competitiveness are addressed not;
training of future generation of researchers is of overriding importance among the benefits of basic science,
e g. exploring the impacts of given polices on the mobility of researchers and students inside the EU or globally.
, The Future of Research actors in the European research area, Synthesis Paper, HLEG on The Future of Key Research actors in the European research area, 2006.28 A. Bonaccorsi, The Changing Role of Researchers in Europe, 2020, Contribution to the HLEG on The Future
M. Thorne, ed.,Foresight, OST, DTI, London, 1999.38 EC, Third European Report on Science & Technology indicators 2003:
Towards a Knowledge-Based Economy, Office for Official Publications of the European communities, Luxembourg, 2003.39 OECD, Main Science and Technology indicators, OECD, Paris, 2006.40 M. Thorne (Ed.),Universities
of Education and Research, Bonn, 2005.42 G. Dosi, P. Llerena, M. Sylos Labini, The relationships between science, technologies and their industrial exploitation:
Attila Havas (MA 1983, Phd 1997) is a Senior Research fellow at the Institute of Economics, Hungarian Academy of Sciences (e-mail:
Deep uncertainty characterizes many domains of decision-making in science and technology. In particular, under deep uncertainty, there is little agreement or consensus about system structure.
the Internet, science and technology databases, patent databases, newswires, and potentially also newsgroups or other online collaborative environments.
It extends and elaborates upon the procedures described by these authors for discovering new linkages of knowledge through use of a structured representation of science and technology,
Likewise, in terms of knowledge production, researchers form multi-disciplinary teams devoted to specific problems and specific contexts 12.
conforming to theories about the organization of science and technology. Without a theory of the data the technology analyst cannot distinguish between meaningful structure and possibly accidental corruption of the knowledge base.
which is shared between distributed communities of designers and researchers. This knowledge is stored in databases of science and technology.
New future-oriented technology analysis techniques, such as the approach suggested here, may contribute to the process and management of radical innovation 17,18.
The express purpose of these science and technology databases is to research specific existing technologies, and yet the biggest promise of these sources of information may be the diffuse and distributed information they contain about the current state of the knowledge of the community.
Unlike conventional, disciplinary researchers, these organizations do need not necessarily the database to gain access to individual pieces of information
but decentralized, knowledge of science and technology is something which can be tested through the use of machine learning techniques.
Previous researchers have identified a number of consequences of radical innovation for the poorly prepared firm or country:
Claim Claimant Data Scientific and technical knowledge consists of a set of interdependent claims Popper 31 Networks of knowledge can be structured readily from science
and technology databases using techniques such as hierarchical random graphs Knowledge claims are heterogenous in character Derrida 32 Networks built upon science
and is distributed therefore a characteristic of science Lakatos 34 Changes in network structure in this case are diffuse,
We suggest that innovation researchers incorporate this new concept into their theories and case studies. 6. Interpretations from the philosophy and sociology of science The hierarchical random graph is one possible model of science, technology and innovation data.
A more fundamental question is whether such a model is consistent with what is postulated about the sociology and epistemology of science.
Towards this end, this section examines features of the hierarchical random graph and relates these features to relevant work in the philosophy of science.
Seven features of the random graph model are problematic and therefore worthy of additional explanation.
The role of scientists, engineers, and innovators is to enhance the coherence of this network.
The progress of science is such that claims which bridge knowledge and increase coherence between related fields may be increasingly more difficult to formulate.
or deny selected ideas in the philosophy of science. Rather, by confronting observations with the context of discussion provided by philosophy,
The status of knowledge is a matter of prolonged and fundamental discussion in philosophy of science.
and it is the role of the scientist to absorb this knowledge according to his or her capabilities.
Semioticians such as Derrida 32 argue that a full accounting of science requires a registration of claims about both about the physical as well as social worlds.
Derrida's ideas informed Callon and others who developed actor network theory as a vehicle for research in science and technology 33.
Knowledge about science and technology may come in two forms. Explicit knowledge entails knowledge about specific claims.
the existence of the claim can be verified through recourse to knowledge bases of science and technology.
Polanyi's account of science and technology has technologists laboring at the interface of claims,
when applied to a network of science and technology information, is likely to be material as well as semiotic in character. 1147 S w. Cunningham/Technological forecasting
The alternative approach would be to expressly encode the configuration within the database of science and technology.
a hierarchical random graph, is a useful way for structuring diffuse knowledge bases of science and technology.
as well as presaging a significant reorganization of the science and technology database to better match technological progress.
of which may be monitored by means of science and technology databases. This technique (and other techniques like it) may see application in open innovation,
a conceptual basis for uncertainty management in model-based decision support, Integrated Assessment 4 (1)( 2003) 5 17.8 G. S. Altshuller, Creativity as an Exact Science
The Dynamics of Science and Research in Contemporary Societies, SAGE, London, 1994.13 B. Harrison, Industrial districts:
A Social and Behavioral Sciences Approach, Chapman & Hall, 2002.26 J. J. Garrett, AJAX: A New approach toweb Applications, 2005, Retrieved 15 may 2007, from http://www. adaptivepath. com/ideas/essays/archives/000385. php. 27 W3c (World wide web Consortium), Roadmap
Scott Cunningham received a Ph d. in Science, Technology and Innovation policy from the Science policy Research Unit.
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