Call for papers

Papers are invited on new indicators and approaches to support science, technology and innovation policies. The audience will include public policy researchers, economists, social scientists and statisticians, together with policy makers, government officials and other stakeholders with an interest in science, technology and innovation indicators.

Proposals must be in the form of a 500-word (maximum) abstract submitted by Friday, March 31, 2006. Submissions should be accompanied by a detailed résumé as well as a brief biographical note of no more than 40 words.

Selected papers will be presented and discussed in break-out sessions during the three-day Forum. Proceedings containing the plenary sessions and other selected papers will be published in a research volume.

We are soliciting policy-relevant papers with an emphasis on the following themes:

• Globalisation of research and development (R&D) activities and networks
• New understandings of the changing nature of science and innovation and their impacts
• Capturing the value of scientific research and innovation
• Human resources in science and technology (HRST) and global knowledge flows
• Building scientific knowledge capital
• Multidisciplinary science, technology and innovationfields including emerging technologies
• Shifting science, technology and innovation landscape: regions, players and issues
• New indicators for science and innovation policies

The abstracts must be submitted by Friday, March 31, 2006 by e-mail to bluesky@statcan.gc.ca

or by regular mail to:

Blue Sky Forum 2006
Attn: Forum Secretariat, Paper Review Committee
Statistics Canada
R.H. Coats Building, 7^th floor Section A
Ottawa, Ontario
Canada, K1A 0T6
Telephone: (613) 951-2880
Fax: (613) 951-9920

Globalisation of research and development (R&D) activities and networks

The nature of R&D performers has changed (e.g. dominance of R&D by large, diversified multinationals, and trend of outsourcing of R&D to "R&D Services" firms) and new ways of conducting R&D in collaborative environments are emerging. Yet, the structure of data collection is tied to models of R&D performance that are increasingly unrepresentative of the whole of the R&D enterprise and new forms of conducting R&D are not well captured in current measurement.

New understandings of the changing nature of science and innovation and their impacts

Science and innovation have increasingly become a collective endeavour and are more closely linked. Science has become more multidisciplinary in nature. Industrial innovation has taken new, non technological forms and a lot of successful innovation comes from better managing organisations. The challenge is to obtain measures that help with the understanding of the changing nature of science and innovation as well as their linkages and impacts, spanning across organisations and geographical locations.

Capturing the value of scientific research and innovation

The location where the value of research and innovation is created and captured is changing. Firms are increasingly relying on external sources of knowledge rather than in-house research, and research (including public research) is increasingly becoming commercialised via spin-off companies and the licensing of patented technologies. There is a need to develop indicators that capture the value of research and innovation and answer questions such as to whom is appropriating the returns from these activities.

Human resources in science and technology (HRST) and global knowledge flows

Looking at demand and supply of human resources for science and technology and their mismatch is a complex exercise and requires the availability of a large variety of good quality data. These range from demographic characteristics, statistics on education, training, employment, current and perspective compensations, as well as data on government spending on S&T related areas and on how the S&T labour market reacts to public policy. One of the major challenges is to develop measurement frameworks and indicators that take into account the mobility of human resources across sectors and geographical locations.

Building scientific knowledge capital

Knowledge capital has been described as a form of intangible asset, i.e. hard to measure. Indeed scientific education, scientific training, knowledge networks (among researchers, university-industry knowledge transfers, public-private partnerships), clustering of research and innovation activities, all contribute to the building of economies' scientific knowledge capital, responsible for scientific discoveries and innovation. Although hard to measure with traditional science, technology and innovation (STI) indicators, indicators of scientific knowledge could be developed borrowing from other areas.

Multidisciplinary science, technology and innovationfields including emerging technologies

In the 1990s the combination of continually falling computer prices with vastly improved performance has led to the ubiquity of computing and communication. The impacts of new information technologies are only now beginning to be understood. Similar developments could occur in biotechnology and nanotechnology, the engineering at the scale of atoms and molecules. Finally there are signs that energy technology is going to make a dramatic leap forward, with the promise of efficient fuel cells, carbon sequestration technology, new approaches to solar power and safer nuclear plants.

Shifting science technology and innovation landscape: regions, players and issues

While increasingly relying on networks across actors and geographical locations, science and innovation activities also tend to cluster in particular locations or around certain institutions (e.g. a leading university or a research lab of a multinational corporation). Geographical boundaries and traditional units of analysis might not be the best units to analyse the changing landscape in science, technology and innovation.

New indicators for science and innovation policies

There are only a few internationally comparable indicators that directly measure investment in scientific research and innovation. There is also a need to identify indicators of the types of science and innovation policies in use, their effectiveness, and their impacts and economic returns. Such indicators could help with the fine tuning science and innovation policy instruments, while designing a systematic measurement framework could address their development.