we analysed demand issues by using data from consumer surveys and developing case studies on failed instances of product introduction
(10) Most users of audiovisual content regularly consume them on mobile devices (11) Speech is the predominant means to interact with data
A second observation is that it proved to be necesssar to engage with practitioners early on in the process of data gathering
An assessment of this qualitative data was coupled with more quantitatiiv data (budgets, number of employees etc.
An assessment of this qualitative data was coupled with more quantitative data (budgets, number of employees etc. to identify similarities
So much data was collected during these studies than it could not all be reported in one paper,
however, we will only report on data related to the two primary research questions: firstly, what is defined as program success,
Results The definition of success Overall the studies provide a rich array of insights and observations-data on the most dynamic public foresight programs in the world.
In reviewing the collected data, there was relatively little program diversity seen from country to country.
The publicatiio trends were analyzed by using the medical databases of MEDLINE to present the potential trends of EID.
Future decisions regarding interventions should use all available information about the disease and possiibl interventions, together with current data from sensors and assays, health clinics, hospitals,
cheap No physical burden Continuous microbial monitoring system Table 2. Short term Medium term Long term Improving database of genome, proteome of causative microbe Need to have international/dome
Automated data collection and analysis Technology Lateral flow and other point of care devices, low cost Low cost tests of greater sensitivity, gene amplification Screening technologies
and analyse data National laboratory hierarchy accepted Acceptance of information collection processes Privacy concerns addressed Use of point of care
multi-agent diagnostic devices linked to automated data collection and analysis Biosecurity and emerging infectious diseases in Asia-pacific Science and Public policy February 2010 49 APEC diagnosis center,
Increased effort is needed to improve the automaate analysis of surveillance data to enable early detection of outbreaks.
The criteeri for this clustering are the correlations and similariitie in interest patterns for certain subsets of applications.
we identified the subsidized firms in the period 2000 2002 from the CTI database. We collected innovation data for the promoted firms similla to those already existing for a sample of innovating firms of The swiss Innovation Survey 2002 (Arvanitis et al.
2004). ) We estimated the propensity scores with respect to the likelihood of receiving a CTI subsidy. We then applied four different matching methods
the use of innovation data for the subsidized firms, collected by means of a survey;
Thirdly, we deal with the data sources; fourthly, we present some informmatio on the patterns of CTI promotion in the reference period.
Most studies use contemporraneou data on the states of subsidized and non-subsidized firms (as in this paper.
Database Our information sources were: a list of the firm projects that were subsidized by the CTI in the period 2000 2002;
and the data for firms that reported the introduction of innovations in the period 2000 2002 in The swiss Innovation Survey 2002.
The CTI database contained information on 634 subsiddize R&d projects that were finished between 1 january 2000 and 31 december 2002.
Hence, the sample we used for the study contained data on 199 firms (64.8%of the subsidized firms.
This additional information allowed us to estimate the propensity scores based on data for all 307 subsidized firms.
which a control group was constructed (KOF panel database). For the firms that finished their projects subsidiize by the CTI during the first half of the period 2000 2002,
CTI database, authors'calculations Table 3. Subsidized enterprises by scientific field 2000 2002 Scientific field Number of firms Percentage Construction technology 11 5. 5
CTI database, authors'calculations Impact of technology policy on innovation by firms Science and Public policy February 2010 69 firms which are subsidized not out
an economic analysis based on Swiss micro data. Small Business Economics, 19 (4), 321 340. Arvanitis, S, H Hollenstein, N Sydow and M Wörter 2007.
Matched-pair analysis based on business survey data to evaluate the policy of supporting the adoption of advannce manufacturing technologies by Swiss firms, KOF Working Paper No. 65, July 2002.
Characterizzin selection bias using experimental data. Econometrica, 66 (5), 1017 1098. Heckman, J J, R J Lalonde,
and analyse very large sets of data. Significant methodological and even philosophical tensions are arising as a result of this shift.
whenever there is a need to gather primary data from experts and other stakeholders. 4. Strategic foresight methodological approach This section will explore the main aspects of the strategic foresight methodological approach.
In this phase, tasks related to gathering and structuring data, and environment scanning are established frequently. This phase also produces the key information components,
and trends in intellecctua property rights (IPR) Mapping S&t national capacity according to data available in CNPQ/Lattes databases and Innovation Portal Expert panels to debate the following themes:
and international cooperation) S&t monitoring using text mining techniques applied to relevant international databases Delphi, involving around 1,
which was obtained in the first phase of the exercise (informatiio and data gathering), as discussed before.
and export the data. Available at<www. cgee. org. br>.>References Brummer, H. L. 2005)‘ A dynamic competitive analysis model for global mining firms',Doctor of commerce thesis, University of South africa.
Key data for expendditur by Central Government on the main S&t programs is shown in Table 3. Fig. 2 classifies China's main S&t programs,
based on data on national S&t programs provided in the China Statistical Yearbook on Science and Technology (2009).
unfortunately there is a lack of data), the 863 Program and the Key technologies Program, clearly identify specific‘missions
2009 China Statistical Yearbook on Science and Technology Data from 2008. Note: In order to simplify, some programs have been grouped into one‘bubble'.
'Thus, the‘Innofund+programs'includes Innofund, Spark, Torch, Agricultural S&t Transfer Fund, National Engineering research Centers (data from 2007) and the New National Products Program.
The Mega-engineering Projects is missing due to lack of data. Table 3. Allocations for S&t by Central Government in main S&t programs (in million RMB) Item 2001 2002 2003 2004 2005 2006 2007 2008
All data for programs, except data for 863 Program, are from National Bureau of Statistics,
*Data for 863 Program are from MOST (2009)( see Note 2), China Science and Technology indicators (2008) and from<http://www. sts. org. cn>accessed 20 may 2011.264.
One principal program, the Mega-engineering Projects is missing due to lack of data. However, though we do not know their exact size,
All data are from National Bureau of Statistics, MOST (see Note 2) and China Statistical Yearbook on Science and Technology (2009).
Yet, as shown by the statistical data in 1995, the sales of local SMES only accounted for 31%of the domestic market,
Even though they held a rich database of genetic resources, the ASS merely charged the cost of handling
Guidelines for Collecting and Interpreting Innovation Data, 3rd edn. Paris: OECD. Rogers, E. M. 1995) Diffusion of Innovations, 4th edn.
Related to this are issues around intellectual property regimes in different countries and restrictions on access to data for science.
The storage and accessing of large amounts of data that could be available to international scientists is another challenge.
commons including less developed countries Science is a global stabilising agent Greater mobility of researchers Internationally agreed data standards Global strategic research fund combining 2%of each countries public research
Better linkages to people and data: ICSU used its global and regional structures to establish
and maintain comprehensive databases of individuals and institutions working on different global challenges. They were made also openly available to the research communnit
and national governments were convinced of the importance investing in data infrastructure. The vision for a global open-access library for scientific data is being realised.
An evolving organisational structure for ICSU: With an expanded membership base (in terms of both countries and disciplines;
but the data is presented also in a visual roadmap structure. Secondly, in IPRM the long-term thinking is dependent on the subject under study.
ICT offers achievable data and easy-to-use tools for the people to decrease their ecological footprint
metering Consumer information systems for complex green data Intelligent housing solutions Intelligent transportation solutions Digitalized production processes Personalized footprint services Solutions based on cloud computing Distributed
for waste management and recycling Web 3. 0 in advanced identification and recognition technologies for waste management and recycling Data mining technologies 3d environments and
there will be different types of services that utilize data from ICT embedded in our everyday environment.
and handle complex data on environmental sustainabiilit (automatically) are entering the market. In industry, new manufacturing paradigms are evolving
%co-ordination or clustering of ongoing nationally funded research projects (59%.%generating multinational evaluation procedures (55%)(Matrix-Rambøll 2009.
4 5 6 7 Knowledge exchange Knowledge clustering Level of strategic approach to S&t cooperation Degree of networking Joint infrastructure investments No instruments no cooperation 0 1
which allowed advanced network analysis and supported novel research collaboration across research fields Foresight exercise is multi-disciplinary.
scenarios and other relevant data (by dedicating a pilot call to research on such future-oriented issues)
Towards this end foresight can facilitaat access to and co-ordination of different networks and databases of experts and other stakeholders.
'if one relies only on internal databases. Also the composition of the initial consortium may impact on the capacity to engage with wider networks.
building on diverse statistical and policy support databases and the plethora of documentation from different levels of research and innovation systems.
For example, ERAWATCH data show that two-thirds of 2009 national research prograamme relevant for the Joint Programming Initiative on Agriculture,
Food Security and Climate change have no openness to other EU Member States. 7. Platforms collecting data on foresight exercises can offer deeper insights into possible and desired futures of research priorities, e g.<
ERAWATCH is a platform collecting data on national research systems in the ERA, including policy documents and research programmes. 11.
NETWATCH collects data on transnational research collaboration in the ERA. 12. In Europe the following European and intergovernmennta mechanisms are in place:
%while in Lithuania over 50%of gross expenditure on r&d is performed by this sector (calculaation based on Eurostat data for 2009).
data and knowledge for linking various disciplines and for initiating new co-operations within the European research and innovaatio communities (with scientists from different disciplines and research areas, city representatives,
because databases from consortium partners were used, and the consortium did not reflect all disciplines involved. 34.
A set of examples of internet-based tools allowing for integration of data of all sorts in future-oriented technollog analysis can be found in Haegeman et al.
while the creative function enables the reassembly of issues or the creation of new emerging issues on the basis of the analysis and integratiio of scan data.
and classify data, analyse and understand relationships, and anticipate as well as discover emerging issues that could have a strategic impact on Singapore.
The exploratory scanning approach concentrates on assembling potential emerging issues from a wide variety of data from different signal sources
Automated text-mining tools as well as databases that allow for tagging and categorisation can help with clustering individual observations.
Thus, one may end up with different sets of individual observations that could be related to each other under certain headings such as:
The vast amount of data coming from these sources can be analysed in terms of potential signals of change,
The selection of key signals from the vast amount of data coming from the various sources is done by experts.
Clustering of signals: The long list of signals is clustered then, using potential emerging issues as a clusteriin mechanism.
but also video documentaries, reports and databases. A focused expert review supported by internet scanning has the advantage that it can use any available source and tool that is on the internet.
Currently text-mining is especially useful to identify networks and clusters of phrases within huge data sets but less useful for identifying new signals and issues.
Step 2 Clustering of weak signals. Step 3 Assessing the significance of clustered weak signals. Step 4 Framing the connected weak signals into clustered topics.
Database tools that are connected to search engines such as Google news Timeline, Google Insight, Web of Science, 9 or Gapminder10 are very helpful for this purpose.
However, online software tools for clustering Twitter tweets are necessary, especially for the processing and analysis phases,
Twitter could allow a continuing clustering of signals related to emerging issues. Policy-makers who were interviewed within the SESTI project noted the importance of methods that allow for identifying the connections, clustering of signals and the stakeholders behind them.
To obtain this information (micro-)blogs are becoming interesting tools with which to analyse which communities have taken up specific issues
Twitter was used also to obtain data for text-mining. However with downloading and processing data from Twitter one of the huge advantages of Twitter was lost:
the ability to trace how signals evolve over time. In general, however, the potential of Twitter to become a main tool for retrieving future-oriented information is high as colleagues,
and the other opportunity is to use them as fast expanding sources of structured informatiio by clustering them.
Clustering blog sites presents new challenges for information science (Agarwal et al. 2010) as no tools are yet available.
However, text-mining is useful in the processing phase as it identifies networks and clusters of concepts and phrases within huge data sets.
Table 3. Evaluation criteria for scanning approaches and methods Connections, clustering of weak signals and degree of relevance to a specific area Duration of weakness of signal, also associated with time at
or even create new emerging issues on the basis of the analysis and integration of scan data.
on one hand, may be focused on clustering and synthesis of scan data and, on the other hand, on human imagination and creativvity Within the SESTI project different text-mining techniques were used for this purpose as well as exercises which used participative web tools such as Wikipedia,
/clustering Medium Medium High Connections predefined through tagging. Also inputs about links from field experts and futurists.
Automatic clustering of keywords in text-mining. In focused expert review the primary signal contains a rich narrative that already relates many aspects of the emerging issues.
or meta descriptions Connections and clustering is made as reported in survey responses, literature and based on reviewers'expertise.
and clustering Cross-checking with results from recent foresight exercises Duration: observation time High Medium Medium As reported but also time series tracing possible in blogs, google etc.
as reported in literature Novelty High High High Cross-checking with scientific databases. Cross-checking with results from recent foresight exercises In focused expert review by tracing back on internet (e g. google timeline) As reported by survey respondents;
and credibility Medium Medium High Through discussion with peers In text-mining dependent on sources fed into database.
It is equally important to utilise automated tools for the clustering and network analysis of issues
In general, model-based forward-looking results are taken into account far more seriously by policy-makers than horizon scanning data
Collective wisdom based blog clustering',Information sciences, 180: 39 61. Boden, M.,Cagnin, C.,Carabias, V.,Haegeman, K. and Ko nno la, T. 2010)‘ Facing the future:
combining the flexibility of Wikis with the structure of databases',Bioinformatics, 26: 2210 1. Chilton,
and network analysis for prioritizing, clustering and combining issues. Furthermore, these methods provide support for traceability,
Yet, an inherent difficulty in this type of clustering which requires and fosters collective sense-making is that the number of possible combinations can be enormous.
and for the prioritization and clustering thereof is viable even in other contexts where there is a need to build shared understandings about the prospects of crosscutting coordination in support of systemic policy objectives.
They made use of different trend lines from historical data and identified longlasstin developments, sometimes in combinations of more than one line, with large impacts that were identified additionally.
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