General properties of the evolution of research fields: a scientometric study of human microbiome, evolutionary robotics and astrobiology
- 4 Downloads
How do research fields evolve? This study confronts this question here by developing an inductive analysis based on emerging research fields of human microbiome, evolutionary robotics and astrobiology (also called exobiology). Data analysis considers papers associated with subject areas of authors from starting years to 2017 per each research field under study. Findings suggest some empirical properties of the evolution of research fields: the first property states that the evolution of a research field is driven by few disciplines (3–5) that generate more than 80% of documents (concentration of scientific production); the second property states that the evolution of research fields is path-dependent of critical disciplines: they can be parent disciplines that have originated the research field or new disciplines emerged during the evolution of science; the third property states that the evolution of research fields can be also due to a new discipline originated from a process of specialization within applied or basic sciences and/or convergence between disciplines. Finally, the fourth property states that the evolution of specific research fields can be due to both applied and basic sciences. These results here can explain and generalize some characteristics of the evolution of scientific fields in the dynamics of science. Overall, then, this study begins the process of clarifying and generalizing, as far as possible, the general properties of the evolution of research fields to lay a foundation for the development of sophisticated theories of the evolution of science.
KeywordsResearch fields Evolution of science Dynamics of science Convergence in science Applied sciences Basic sciences Human microbiome Evolutionary robotics Astrobiology Exobiology
JEL ClassificationA19 C00 I23 L30
The research in this paper was conducted while the author was a visiting scholar of the Center for Social Dynamics and Complexity at the Arizona State University funded by CNR - National Research Council of Italy and The National Endowment for the Humanities (Research Grant No. 0003005-2016). I thank the fruitful suggestions and comments by Ken Aiello, Sara I. Walker and seminar participants at the Beyond-Center for Fundamental Concepts in Science (Arizona State University in Tempe, USA). Older versions of this paper circulated as working papers. The author declares that he has no relevant or material financial interests that relate to the research discussed in this paper. Usual disclaimer applies.
- Coccia, M. (2016a). Radical innovations as drivers of breakthroughs: characteristics and properties of the management of technology leading to superior organisational performance in the discovery process of R&D labs. Technology Analysis & Strategic Management, 28(4), 381–395. https://doi.org/10.1080/09537325.2015.1095287.CrossRefGoogle Scholar
- Coccia, M. (2017). The source and nature of general purpose technologies for supporting next K-waves: Global leadership and the case study of the U.S. Navy’s Mobile User Objective System. Technological Forecasting and Social Change, 116(March), 331–339. https://doi.org/10.1016/j.techfore.2016.05.019.CrossRefGoogle Scholar
- Crane, D. (1972). Invisible colleges: Diffusion of knowledge in scientific communities. Chicago, IL: University of Chicago Press.Google Scholar
- David, P. A. (1994). Positive feedbacks and research productivity in science: Reopening another black box. In O. Granstrand (Ed.), Economics of technology. Amsterdam: Elsevier Science.Google Scholar
- De Solla Price, D. J. (1986). Little science, big science… and beyond. Columbia University Press, New York, Ch. 3.Google Scholar
- Dogan, M., & Pahre, R. (1990). Creative marginality: Innovation at the intersections of social sciences. Boulder, CO: Westview Press.Google Scholar
- Floreano, D., Husbands, P., & Nolfi, S. (2008). Evolutionary Robotics. In B. Siciliano & O. Khatib (Eds.), Springer handbook of robotics. Berlin: Springer.Google Scholar
- Freedman, P. (1960). The principles of scientific research (First edition 1949). London: Pergamon Press.Google Scholar
- Gibbons, M., Limoges, C., Nowotny, H., Schwatzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary society. London: Sage Publications.Google Scholar
- International Journal of Astrobiology. (2018). https://www.cambridge.org/core/journals/international-journal-of-astrobiology. Accessed May 2018.
- Klein, J. T. (1996). Crossing boundaries. Knowledge, disciplinarities and interdisciplinarities. Charlottesville, VA: University Press of Virginia.Google Scholar
- Kuhn, T. S. (1962). The structure of scientific revolutions (2nd enlarged ed.). Chicago, IL: The University of Chicago Press.Google Scholar
- Latour, B. (1987). Science in action. Cambridge, MA: Harvard University Press.Google Scholar
- Latour, B., & Woolgar, S. (1979). Laboratory life: The social construction of scientific facts. London and Beverly Hills: Sage.Google Scholar
- Levin, S. G., & Stephan, P. E. (1991). Research productivity over the life cycle: Evidence for academic scientists. American Economic Review, 81(1), 114–132.Google Scholar
- NASA. (2018a). Astrobiology at NASA-Life in the Universe. https://astrobiology.nasa.gov/about/history-of-astrobiology/.
- NASA. (2018b). NASA Astrobiology Institute (NAI). https://nai.nasa.gov/about/. Accessed July 2018.
- NASA. (2018c). Exobiology. https://astrobiology.nasa.gov/research/astrobiology-at-nasa/exobiology/. Accessed July 2018.
- Pan, R. K., Kaski, K., & Fortunato, S. (2012). World citation and collaboration networks: Uncovering the role of geography in science. Scientific Reports, 2(902), 1–7.Google Scholar
- Rucker, R. B. (1980). Towards robot consciousness. Speculations in Science and Technology, 3(2), 205–217.Google Scholar
- Scopus. (2018). https://www.scopus.com/search/form.uri?zone=TopNavBar&origin=sbrowse&display=basic. Accessed December 2018.
- Small, A. W. (1905). General sociology. Chicago, IL: University of Chicago.Google Scholar
- Stephan, P. E. (1996). The economics of science. Journal of Economic Literature, 34(3), 1199–1235.Google Scholar
- Stephan, P. E., & Levin, S. G. (1992). How science is done; Why science is done. In P. Stephan & S. Levin (Eds.), Striking the Mother Lode in science: The importance of age, place and time, Chapter 2 (pp. 11–24). New York, NY: Oxford University Press.Google Scholar
- Storer, N. W. (1967). The hard sciences and the soft: Some sociological observations. Bulletin of the Medical Library Association, 55(1), 75–84.Google Scholar
- Storer, N. W. (1970). The internationality of science and the nationality of scientists. International Social Science Journal, 22(1), 80–93.Google Scholar
- The American Microbiome Institute. (2015). http://www.microbiomeinstitute.org/humanmicrobiome. Accessed, 20 April, 2018.
- Wagner, C. (2008). The new invisible college: Science for development. Washington DC: Brookings Institution Press.Google Scholar