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Promoting scientodiversity inspired by biodiversity

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Abstract

Diversity of science (variety in and balance among research subjects) is often regarded as a key driver of innovation, but it is typically understood by means of heuristics, given the lack of precise formulations such as those found in biodiversity studies. From the policy perspective, a standard methodology for characterization of diversity of science is needed to enable the efficient management and breeding of diverse research responsive to socio-economic demands. We investigated the distribution of research subjects in a bibliographic database to develop a framework of diversity of science analogous to that of biodiversity. Our analysis of the distribution of research subjects among countries suggests that diversity of science has similar statistical characteristics as biodiversity. We find that number of research subjects follows log-normal distribution for almost all countries and indicates linear dependency on research budget in log–log plot. We also identify an inflection point in the subject–budget relationship curve. The results may validate the adoption of sophisticated concepts and techniques from biodiversity work in “scientodiversity” studies.

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References

  • Abbasi, A., Altmann, J., & Hossain, L. (2011). Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures. Journal of Informetrics, 5(4), 594–607. doi:10.1016/j.joi.2011.05.007.

    Article  Google Scholar 

  • Aydinoglu, A. U., Allard, S., & Mitchell, C. (2015). Measuring diversity in disciplinary collaboration in research teams: An ecological perspective. doi:10.1093/reseval/rvv028.

  • Barjak, F. (2006). Team diversity and research collaboration in life sciences teams: Does a combination of research cultures pay off? University of Applied Sciences Northwestern Switzerland, Series A: Discussion Paper, W02. Retrieved from http://netreact-eu.org/documents/DPW2006-02_TeamDiversity_Barjak_Franz.pdf.

  • Börner, K. (2010). Atlas of science: Visualizing what we know. Cambridge: The MIT Press.

    Google Scholar 

  • Bosman, J., van Mourik, I., Rasch, M., Sieverts, E., & Verhoeff, H. (2006). Scopus reviewed and compared. Utrecht: Utrecht University Library.

    Google Scholar 

  • Carley, S., & Porter, A. L. (2012). A forward diversity index. Scientometrics, 90, 407–427. doi:10.1007/s11192-011-0528-1.

    Article  Google Scholar 

  • Chaminade, C., & Plechero, M. (2014). Do regions make a difference? Regional innovation systems and global innovation networks in the ICT industry. European Planning Studies, 23(2), 215–237. doi:10.1080/09654313.2013.861806.

    Article  Google Scholar 

  • Confraria, H., & Godinho, M. M. (2014). The impact of African science: A bibliometric analysis. Scientometrics, 102(2), 1241–1268. doi:10.1007/s11192-014-1463-8.

    Article  Google Scholar 

  • Confraria, H., Mira Godinho, M., & Wang, L. (2017). Determinants of citation impact: A comparative analysis of the Global South versus the Global North. Research Policy, 46(1), 265–279. doi:10.1016/j.respol.2016.11.004.

    Article  Google Scholar 

  • Gibbons, M. (1999). Science’s new social contract with society. Nature, 402, C81–C84.

    Article  Google Scholar 

  • Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary societies. Contemporary sociology. London: Sage.

    Google Scholar 

  • Hicks, D., & Katz, J. S. (2011). Equity and excellence in research funding. Minerva, 49(2), 137–151. doi:10.1007/s11024-011-9170-6.

    Article  Google Scholar 

  • Hubbell, S. P. (2001). The unified neutral theory of biodiversity and biogeography. Princeton: Princeton University Press.

    Google Scholar 

  • Igami, M., & Saka, A. (2016). Decreasing diversity in Japanese science, evidence from in-depth analyses of science maps. Scientometrics, 106(1), 383–403. doi:10.1007/s11192-015-1648-9.

    Article  Google Scholar 

  • Irie, H., & Tokita, K. (2012). Species–area relationship for power-law species abundance distribution. International Journal of Biomathematics, 5(3), 1260014. Retrieved from http://arxiv.org/abs/q-bio/0609012.

  • Kitai, T. (1993). Construction of JICST scientific technological classification 1993. Journal of Information Processing and Management, 35, 967–974.

    Article  Google Scholar 

  • Kuhn, T. S. (1970). The structure of scientific revolutions. Chicago: The University of Chicago Press. doi:10.1119/1.1969660.

    Google Scholar 

  • Lee, Y. N., Walsh, J. P., & Wang, J. (2015). Creativity in scientific teams: Unpacking novelty and impact. Research Policy, 44(3), 684–697. doi:10.1016/j.respol.2014.10.007.

    Article  Google Scholar 

  • Leydesdorff, L., Carley, S., & Rafols, I. (2013a). Global maps of science based on the new web-of-science categories. Scientometrics, 94, 589–593. doi:10.1007/s11192-012-0784-8.

    Article  Google Scholar 

  • Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations. Journal of Informetrics, 5, 87–100. doi:10.1016/j.joi.2010.09.002.

    Article  Google Scholar 

  • Leydesdorff, L., Rafols, I., & Chen, C. (2013b). Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations. Journal of the American Society for Information Science and Technology, 64, 2573–2586. doi:10.1002/asi.

    Article  Google Scholar 

  • Limpert, E., Stahel, W. A., & Abbt, M. (2001). Log-normal distributions across the sciences: Keys and clues. BioScience, 51(5), 341–352.

    Article  Google Scholar 

  • Lund Declaration. (2009). Europe must focus on the grand challenges of our time. In Swedish Presidency Research Conference in Lund. New Times New Solutions. Lund. Retrieved from http://www.vr.se/download/18.7dac901212646d84fd38000336/.

  • MacArthur, R. H., & Wilson, E. O. (1967). The theory of island biogeography. Princeton: Princeton University Press. doi:10.2307/1796430.

    Google Scholar 

  • Malerba, F. (2002). Sectoral systems of innovation and production. Research Policy, 31, 247–264.

    Article  Google Scholar 

  • May, R. M. (1972). Will a large complex system be stable? Nature, 238, 413–414.

    Article  Google Scholar 

  • May, R. M. (1975). Patterns of species abundance and diversity. In M. L. Cody & J. M. Diamond (Eds.), Ecology and evolution of communities (pp. 81–120). Cambridge: The Belknap Press.

    Google Scholar 

  • May, R. M. (1999). Unanswered questions in ecology. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 354(1392), 1951–1959. doi:10.1098/rstb.1999.0534.

    Article  Google Scholar 

  • Merton, R. K. (1973). The Normative Structure of Science. In N. Storer (Ed.), The sociology of sciene: Theoretical and empirical investigations (pp. 267–278). Chicago: The University Chicago Press.

    Google Scholar 

  • Mitesser, O., Heinz, M., Havemann, F., & Gläser, J. (2008). Measuring diversity of research by extracting latent themes from bipartite networks of papers and references. In H. Kretschmer & F. Havemann (Eds.), Proceedings of WIS 2008, 6th international conference on webometrics, informetrics and scientometrics & ninth COLLNET meeting. Berlin.

  • Mougi, A., & Kondoh, M. (2012). Diversity of interaction types and ecological community stability. Science, 337(6092), 349–351. doi:10.1126/science.1220529.

    Article  MATH  MathSciNet  Google Scholar 

  • Mugabushaka, A. M., Kyriakou, A., & Papazoglou, T. (2016). Bibliometric indicators of interdisciplinarity: The potential of the Leinster–Cobbold diversity indices to study disciplinary diversity. Scientometrics, 107(2), 593–607. doi:10.1007/s11192-016-1865-x.

    Article  Google Scholar 

  • Nelson, R. (Ed.). (1993). National innovation systems: A comparative analysis. Oxford: Oxford University Press.

    Google Scholar 

  • Newman, M. E. J. (2005). Power laws, Pareto distributions and Zipf’s law. Contemporary Physics, 46(5), 323–351. doi:10.1016/j.cities.2012.03.001.

    Article  Google Scholar 

  • OECD. (2016). OECD Science, Technology and Industry Outlook. OECD. https://doi.org/10.1787/23129638.

  • Paine, R. T. (1995). A conversation on refining the concept of keystone species. Conservation Biology, 9(4), 962–964. doi:10.1046/j.1523-1739.1995.09040962.x.

    Article  Google Scholar 

  • Pan, R. K., Sinha, S., Kaski, K., & Saramäki, J. (2012). The evolution of interdisciplinarity in physics research. Scientific Reports, 2, 1–8. doi:10.1038/srep00551.

    Google Scholar 

  • Power, M. E., Tilman, D., Estes, J. A., Menge, B. A., Bond, W. J., Mills, L. S., et al. (1996). Challenges in the quest for keystones. BioScience, 46(8), 609–620. doi:10.2307/1312990.

    Article  Google Scholar 

  • Preston, F. W. (1962). The canonical distribution of commonness and rarity: Part I. Ecology, 43(2), 185–215.

    Article  Google Scholar 

  • Preston, F. W. (1980). Noncanonical distributions of commonness and rarity. Ecology, 61(1), 88–97.

    Article  Google Scholar 

  • Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience. Scientometrics, 82(2), 263–287. doi:10.1007/s11192-009-0041-y.

    Article  Google Scholar 

  • Rosenberg, N. (1996). Uncertainty and technological change. In G. W. R. Landau & T. Taylor (Eds.), The mosaic of economic growth (pp. 334–353). Stanford: Stanford University Press.

    Google Scholar 

  • Sakagami, Y. (1989). JICST science and technology classification. The Journal of Information Science and Technology Association, 39(11), 497–502.

    Google Scholar 

  • Schmidt, M., Glaser, J., Havemann, F., & Heinze, M. (2006). A methodological study for measuring the diversity of science. In Proceedings international workshop on webometrics, informetrics and scientometrics & seventh COLLNET meeting. Nancy.

  • Shibayama, S. (2011). Distribution of academic research funds: A case of Japanese national research grant. Scientometrics, 88(1), 43–60. doi:10.1007/s11192-011-0392-z.

    Article  MathSciNet  Google Scholar 

  • Shimada, Y., Tsukada, N., & Suzuki, J. (2017). Promoting diversity in science in Japan through mission-oriented research grants. Scientometrics, 110(3), 1415–1435. doi:10.1007/s11192-016-2224-7.

    Article  Google Scholar 

  • Stirling, A. (2007). A general framework for analysing diversity in science, technology and society. Journal of the Royal Society, Interface, 4(15), 707–719. doi:10.1098/rsif.2007.0213.

    Article  Google Scholar 

  • The World Bank. (2017). World Development Indicators. Retrieved from http://data.worldbank.org/data-catalog/world-development-indicators.

  • Trajtenberg, M., Henderson, R., & Jaffe, A. (1997). University versus corporate patents: A window on the basicness of invention. Economics of Innovation and New Technology. doi:10.1080/10438599700000006.

    Google Scholar 

  • Uzzi, B., Mukherjee, S., Stringer, M., & Jones, B. (2013). Atypical combinations and scientific impact. Science, 342, 468–472. doi:10.1126/science.1240474.

    Article  Google Scholar 

  • Van Noorden, R. (2015). Interdisciplinary research by the numbers. Nature, 525, 306–307.

    Article  Google Scholar 

  • Voutilainen, A., & Kangasniemi, M. (2015). Applying the ecological Shannon’s diversity index to measure research collaboration based on coauthorship: A pilot study. Journal of Scientometric Research, 4, 172–177. doi:10.4103/2320-0057.174866.

    Article  Google Scholar 

  • Wagner, S. C. (2010). Keystone species. Nature Education Knowledge, 3(10), 51. doi:10.1007/978-3-642-58001-7_11.

    Google Scholar 

  • Wagner, C. S., Roessner, J. D., Bobb, K., Klein, J. T., Boyack, K. W., Keyton, J., et al. (2011). Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. Journal of Informetrics, 5(1), 14–26. doi:10.1016/j.joi.2010.06.004.

    Article  Google Scholar 

  • Williams, K. Y., & O’Reilly, C. A. (1998). Demography and diversity in organizations: A review of 40 years of research. Research in Organizational Behavior, 20, 77–140.

    Google Scholar 

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Correspondence to Yoshi-aki Shimada.

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Shimada, Ya., Suzuki, J. Promoting scientodiversity inspired by biodiversity. Scientometrics 113, 1463–1479 (2017). https://doi.org/10.1007/s11192-017-2545-1

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