Journal of Information Management (정보관리연구)

Korea Institute of Science and Technology Information (한국과학기술정보연구원 과학기술정보센터)
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Identification of Emerging Research at the national level: Scientometric Approach using Scopus

국가적 차원의 유망연구영역 탐색: Scopus 데이터베이스를 이용한 과학계량학적 접근

  • 여운동 (한국과학기술정보연구원 계량정보연구팀) ;
  • 손은수 (한국과학기술정보연구원 계량정보연구팀) ;
  • 정의섭 (한국과학기술정보연구원 경인지원) ;
  • 이창환 (한국과학기술정보연구원 계량정보연구팀)
  • Published : 2008.09.30
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Abstract

In todays environment in which scientific technologies are changing very fast than ever, companies have to monitor and search emerging technologies to gain competitiveness. Actually many nations try to do that. Most of them use Dephi approach based on experts review as a searching method. But experts review has been criticised for probability of inclination and its derivative problems in the sense that it is accomplished only by expert's subjectivity. To overcome such problems, we used Scientometric Method for identifying emerging technology that had been done by Delphi as a rule. We made three particular efforts in order to improve the Quality of the result. Firstly, we selected one alternative database between SCI and Scopus hoping to see evenly-distributing results in wide fields on the front burner. Secondly we used Fractional citation counting in counting citation number in the stage of linear regression analysis. Lastly, we verified Scientometric result with experts opinions to minimize probable errors in a Scientometric research. As a result, we derived 290 emerging technologies from Scientometric analysis with Scopus Database, and visualized them on 2-dimension map with data mining system named KnowledgeMatrix which was developed by KISTI.

급속도로 변화하는 과학기술 환경 속에서 기업들은 현존하는 기술의 발전을 모니터링함과 동시에 새롭게 부상하는 유망기술을 찾아야만 경쟁력을 가질 수 있다. 각 국가에서는 경쟁적으로 유망연구 영역을 찾고 있는데, 대부분의 국가에서는 전문가 평가를 기반으로 한 델파이 방법으로 유망기술을 탐색하고 있다. 그러나 델파이와 같은 전문가방식은 기본적으로 전문가의 주관적 판단에 의지하기 때문에 편향성과 이에 따른 문제가 발생한다. 본 연구에서는 델파이 방법의 기술예측방법이 가지는 문제점을 개선하기 위해 과학계량학적 방법으로 유망연구영역을 탐색하였다. 탐색과정에서는 다음 3가지의 특별한 노력을 통해 과학계량학적 방법의 성능을 제고하고자 하였다. 첫째, 데이터베이스 선정에 있어서 공학 등 저널수가 적은 기술분야에서도 유망연구영역의 도출이 가능한가를 고려하였다. 둘째, 과학기술 전분야를 대상으로 하는 분석에서 과학기술분야별로 가지고 있는 인용수의 차이로 인해 발생하는 문제점을 해결하고자 부분인용계상(fractional citation counting)과 이동평균을 이용한 선형회귀분석을 도입하였다. 셋째, 과학계량학적 분석으로 나온 결과를 정성적으로 검증하여 과학계량학적 방법에 의한 오류를 최소화 하였다. 최종 290개의 유망연구영역을 선정하였으며, 각 영역은 기술의 네트워크상에서 가시화하였다. 본 연구에서는 Scopus 데이터베이스가 사용되었으며, 데이터마이닝과 가시화에는 한국과학기술정보연구원에서 개발한 KnowledgeMatrix가 사용되었다.

Keywords

References

  1. 정보통신연구진흥원. 2007. Raius를 통한 IT 미래유망기술 발굴. 대전: 동연구소.
  2. 한국화학공학회. 2005. 과학기술정책동향-과학기술부, NEWS & INFORMATION FOR CHEMICAL ENGINEERS, 23(5): 512-513.
  3. Aksnes D. W. 2003. “Characteristics of highly cited papers.” Research Evaluation, 12(3): 159-170. https://doi.org/10.3152/147154403781776645
  4. Bengisu, M. and R. Nekhili. 2006. “Forecasting emerging technologies with the aid of science and technology databases.” Technological Forecasting and Social Change, 73(7): 835-844. https://doi.org/10.1016/j.techfore.2005.09.001
  5. Bauin, S., B. Michelet, M. G. Schweighoffer and P. Vermeulin. 1991. “Using bibliometrics in strategic analysis: Understanding Chemical Reactions at CNRS.” Scientometrics, 22: 113-137. https://doi.org/10.1007/BF02019278
  6. Callon, M., J. P. Courtial, and F. Laville. 1991. “Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry” Scientometrics, 22(1): 155-205. https://doi.org/10.1007/BF02019280
  7. Case, D. O., and G. M. Higgins. 2000. “How can we investigate citation behavior? A study of reasons for citing literature in communication.” Journal of the American Society for Information Science, 51(7): 635-645. https://doi.org/10.1002/(SICI)1097-4571(2000)51:7<635::AID-ASI6>3.0.CO;2-H
  8. Chen, C. and S. Morris. 2003. “Visualizing evolving networks: Minimum spanning trees versus Pathfinder networks.” Proceedings of IEEE Symposium on Information Visualization, IEEE Computer Society Press, 67-74.
  9. Chubin D. E., and E. J. Hackett. 1990. “Peer review and the printed word.” In: Chubin DE, Hackett E.J. Peerless Science: Peer Review and U.S. Science Policy. Albany, NY: SUNY Press.
  10. COLE, J. R. 2000. “A short history of the use of citations as a measure of the impact of scientific and scholarly work.” In: B. CRONIN, H. B. ATKINS (Eds), The Web of Knowledge. A Festschrift in Honor of Eugene Garfield. Medford, NJ, USA, Information Today, 281–300.
  11. Corrocher, N., F. Malerba, and F. Montobbio. 2003. “The emergence of new technologies in the ICT field: main actors, geographical distribution, and knowledge sources.” Working Papers of Faculty of Economics Universit? degli Studi dell'Insubria, 37 Varese, Italy.
  12. Day, G. S. and P. J. H. Schoemaker. 2000. “A different game. In G. S. Day & P. J. H. Schoemaker(Eds.).” Wharton on Managing Emerging Technologies. New York: John Wiley & Sons.
  13. Egghe, L., and R. Rousseau. 1990. “Introduction to informetrics. Quantitative Methods in Library.” Documentation and Information Science. Amsterdam: Elsevier, 203–290.
  14. European Commission. 2001. Key Figures 2001. Special edition. Indicators for benchmarking of national research policies(Brussels).
  15. Garfield E. 1993. “Essays of an Information Scientist.” ISI Press, 15: 75-83.
  16. Glanzel, W., and H. Czerwon. 1996. “A new methodological approach to bibliographic coupling and its application to the national, regional and institutional lenel.” Scientometrics, 37: 195-221. https://doi.org/10.1007/BF02093621
  17. Hicks, D. 1987. “Limitations of co-citation analysis as a tools for science policy.” Social Studies of Science, 17: 295-316. https://doi.org/10.1177/030631287017002004
  18. Hung, S. C., and Y. Y. Chu. 2006. “Stimulating new industries from emerging technologies: challenges for the public sector.” Technovation, 26(1): 104-110. https://doi.org/10.1016/j.technovation.2004.07.018
  19. Kuusi, O. and M. Meyer. 2007. “Anticipating technological breakthroughs: Using bibliographic coupling to explore the nanotubes paradigm.” Scientometrics, 70(3): 759-777. https://doi.org/10.1007/s11192-007-0311-5
  20. Kessler, M. M. 1963. “Bibliographic coupling between scientific papers.” American Documentation, 14: 10-25. https://doi.org/10.1002/asi.5090140103
  21. Kostoff, R. N. 1994. “Assessing research impact: US. government retrospective and quantitative approaches.” Science and Public Policy, 2(1).
  22. Liu, M. 1993. “Progress in documentation: the complexities of citation practice: a review of citation studies.” Journal of Documentation, 49(4): 370-408. https://doi.org/10.1108/eb026920
  23. Martin, B. R. 1995. “Foresight in Science and Technology.” Technology Analysis & Strategic Management, 7(2): 139-168. https://doi.org/10.1080/09537329508524202
  24. Martin, B. R., and J. Irvine. 1983. “Assessing basic research. Some partial indicators of scientific progress in radio astronomy.” Research Policy, 12: 61-90. https://doi.org/10.1016/0048-7333(83)90005-7
  25. Miranda Santo, M., G. Massari Coelho, D. M. dos Santos, and L. Fellows Filho. 2006. “Text mining as a valuable tool in foresight exercises: a study on nanotechnology.” Technological Forecasting & Social Change, 1013–1027.
  26. Moed, H. F. 2005. Citation analysis in research evaluation. New York: Springer.
  27. Morris, S. A. 2005. Unified mathematical treatment of complex cascaded bipartite networks: The case of collections of journal papers, Ph.D. diss., University of Oklahoma.
  28. NISTEP, Japanese website. .
  29. Norris, M., and C. Oppenheim. 2007. “Comparing alternatives to the Web of Science for coverage of the social sciences' literature.” Journal of Informetrics, 1-9.
  30. Okuwada, K. 2008. “Elements of Convertging Technologies.” CACCI Journal, 1: 1-6.
  31. Park, H. W., C. W. Lee and W. D. Yeo. 2007. “Development of Information Model to Identify Emerging Technologies.” Jornal of Information Management, 38(4): 1-21.
  32. Porter, A. L., D. Roessner, X. Y. Jin & N. C. Newman. 2002. “Measuring national emerging technology capabilities.” Science and Technology Policy, 29(3): 189-200.
  33. Salton, G. 1989. Automatic text processing: the transformation, analysis, and retrieval of information by computer. Reading: Addison-Wesley.
  34. Salton G., and M. J. McGill 1983, Introduction to Modern Information Retrieval, McGraw-Hill, New York
  35. Schvaneveldt, R. W., F. T. Durso and D. W. Dearholt. 1989. “Network structures in proximity data.” The psychology of learning and motivation: Advances in research and theory, Academic Press, San Diego, Calif., 24: 249-284. https://doi.org/10.1016/S0079-7421(08)60539-3
  36. Small, H. 1973. “Co-citation in the scientific literature: a new measure of the relationship between two documents.” Journal of the American Society for Information Science, 24(4): 265–269. https://doi.org/10.1002/asi.4630240406
  37. Small, H. 1982. “Citation context analysis.” Progress in Communication, 3: 287-310.
  38. Small, H. 1997. “Update on Science Mapping: Creating Large Document Spaces.” Scientometrics, 38(2): 275-293. https://doi.org/10.1007/BF02457414
  39. Small H. 2003. “Paradigms, citations and maps of science: a personal history.” Journal of the American Society for Information Science and Technology, 54(5): 394-399. https://doi.org/10.1002/asi.10225
  40. Small, H., and E. Sweeney. 1985. “Clustering the Science Citation Index Using Co-Citations I. A Comparison of Methods.” Scientometrics, 7: 391-409. https://doi.org/10.1007/BF02017157
  41. Tijssen R. J. W., M. S. Visser and T. N. van Leeuwen. 2002. “Benchmarking international scientific excellence: are highly cited research papers an appropriate frame of reference?” Scientometrics, 54(3): 381-397. https://doi.org/10.1023/A:1016082432660
  42. TUBITAK. 2004. Vision 2023 Technology Foresight Delphi Survey Final Report.
  43. Wheatley, K. K. and D. Wilemon. 1999. “From Emerging Technology to Competitive Advantage.” in Portland International Conference on the Management of Engineering and Technology (PICMET).
  44. Whittaker, J. 1989. “Creativity and conformity in science: Titles, keywords and co-word Analysis.” Social Studies of Science, 19: 473-496. https://doi.org/10.1177/030631289019003004
  45. Wouters, P. 1999; The citation culture. Unpublished doctoral thesis, University of Amsterdam. [cited 2006.4.25]. .