Везде
On Long-Term Prediction of Fundamental and Exploratory Research
Table of contents
Annotation Estimate Publication content
References Comments
Share
QR
Metrics
On Long-Term Prediction of Fundamental and Exploratory Research
Annotation
PII
S042473880004047-0-
DOI
10.31857/S042473880004047-0
Publication type
Article
Status
Published
Authors
Levan Mindeli 
Occupation: Scientific Director of ISS RAS
Affiliation: Institute for the Study of Science of the Russian Academy of Sciences (ISS RAS)
Address: Moscow, Russian Federation
Sergey Ostapyuk
Occupation: Leading Research Associate
Affiliation: Institute for the Study of Science of the Russian Academy of Sciences (ISS RAS)
Address: Russian Federation
Vyacheslav Fetisov
Occupation: Advisor to the Director of ISS RAS
Affiliation: Institute for the Study of Science of the Russian Academy of Sciences (ISS RAS)
Address: Russian Federation
Edition
Volume 55 Issue 1
Pages
56-67
Abstract

A basic precondition for the solution of the ambitious task — Russia entering the club of five largest economies in the worlds, set by the President of the Russian Federation, — is consolidation and joint actions of the participants in the strategic planning, ensuring the development of socio-economic and scientific-technological spheres of activity. The original threshold document determining the prospects for their development is the prediction of socio-economic and scientific-technological development, forecast of the progress in science, including the basic research. Prediction of fundamental and exploratory research (pilot-study) is the responsibility of the Russian Academy of Sciences. However, as evidenced by the analysis, forecasting procedure of these activities, in contrast to the socio-economic and scientific-technological development, is not legally regulated. Ways to eliminate this gap is the subject of the study. The work outlines the subject and steps in the procedure of long-term forecasting in the scientific and technical spheres. The analysis of normative and legal basis of the formation of aggregated long-term forecast models for fundamental and exploratory research defined terms and stages of such rules’ development for aggregate models, formulated the methodological features and requirements of these regulations, as well as the proposals for the development of its expertise tools and information support. The study laid the basis for preparing and taking the government decision on regulation of predicting fundamental and exploratory research providing RAS with the responsible status on predicting fundamental and pilot-studies. It is emphasized that the procedure and the development model specified matches the national forecasting model, certain decisions of the Government of the Russian Federation on the procedure of forecasting the socio-economic, scientific and technological development. At the same time, the model considers the differences in forecasting problems of development of fundamental and applied scientific types of research.

Keywords
fundamental and pilot-study, socio-economic and scientific-technological development, procedure and model of long-term forecasting, strategic planning, legislation, methodological and information provision, institute and rules of regulations
Received
14.03.2019
Date of publication
21.03.2019
Number of purchasers
98
Views
3279
Readers community rating
0.0 (0 votes)
Previous versions
S042473880004047-0-1 Дата внесения правок в статью - 14.02.2019
Cite   Download pdf

References

1. Belousov D.R., Frolov I.E. (2008). Long-Term Science and Technology. Forsyth, 3, 54—66 (in Russian).

2. Biktimirov M. R., Glebskii V.L., Dolgov B.V., Polikarpov S.A. (2015). Use of Information Technologies and Infrastructures for Scientific Information Aggregation. Experience in Canada, the Netherlands, Germany. Modeling and Analysis of Information Systems, 22, 1, 114—126 (in Russian).

3. Dushkin R.V. (2018). Why hybrid AI Systems of the Future. Economic Strategy, 6 (156), 84—93 (in Russian).

4. Ivanov V.V. (2012). Strategic Directions of Modernization: Innovation, Science, Education. M.: Nauka (in Russian).

5. Ivanova N.I. (2012). Industry Innovation Policy Tools. Moscow: IMEMO of RAS, 2016 (in Russian).

6. Knyazev Y. (2016). On the Role of Economics in Society and the Importance of Science in Economic Development. The Society and Economy, 3, 16 (in Russian).

7. Kudrin A. (2016). Strategic lessons. Polit.ru. Available at: http://polit.ru/article/2016/12/27/lessons/December 27 (accessed: December 2018, in Russian).

8. Litvak B.G. (1996). Expert Assessments and Decisions. Moscow: Patent (in Russian).

9. Makosko A.A., Abrosimov V.K. (2018). Prediction of the Development of Science as a Task the Weak Artificial Intelligence (Conceptual Approach). Innovation, 9 (239), 13—19 (in Russian).

10. Marcus G. (2017). Deep Learning: A Critical Appraisal. Cornell University Library. New York University. Available at: http;//arxiv.org/1801.00631 (accessed: December 2018).

11. Mindeli L., Chernykh S. (2014). Basic Science and Economic Growth on the Basis of Innovative Development. The Society and Economy, 9, 66—70 (in Russian).

12. Mindeli L., Ostapyuk S., Chernykh S. (2017). Long-Term Forecasting of the Development of Fundamental Science in Russia: Methodological Aspects. The society and economy, 10, 5—22 (in Russian).

13. Mindeli L., Ostapyuk S., Fetisov V. (2018). Global Trends and Challenges That Define the Scientific and Technological Development of Russia. Microeconomics, 5, 7—14 (in Russian).

14. Novikov, D.A., Chhartishvili A.G. (2002). Active Forecast. Moscow: IPU RAS (in Russian).

15. Ostapyuk S.F. (2007). State Forecasting System (Problems, Tasks, Principles of Organization and Operation). In: Bestuzhev-Lada I.V., Ageev A.I. et al. “Small Russian encyclopedia of foresight activities” Moscow: Institute of Economic Strategies, 251—255 (in Russian).

16. Pletnyov K.I., Lazarenko N.E. (2003). Expertise in Scientific and Technical Sphere: Methodology and Organization. Moscow: Publishing House RAGS (in Russian).

17. Russell S., Norvig P. (2006). Artificial Intelligence. A Modern Approach. Moscow: Williams (in Russian).

18. Science and Innovation Policy: Russia and the World, 2011—2012 (2013). Ivanova N.I., Ivanov V.V. (eds). Moscow: Nauka (in Russian).

19. Sidelnikov U.V., Minaev E.S. (2017). Technology Expert scenario forecasting. Moscow: MAI (in Russian).

20. Sokolov A.V. (2007). Forsyth: A Look into the Future. Forsyth, 1, 1, 8—15 (in Russian).

21. Zubova L.G., Mindeli L.E.,Motova M.A., Ostapyuk S.F., Starostin S.P. (2004). Methodological Aspects of the Development of Forecasting Scientific and Technological Development over the Long Term. Newsletter, 6, 31—74 (in Russian). Moscow: ZISN.

Comments

No posts found

Write a review
Translate