Abstract
Diversification and fragmentation of scientific exploration brings an increasing need for integration, for example through interdisciplinary research. The field of nanoscience and nanotechnology appears to exhibit strong interdisciplinary characteristics. Our objective was to explore the structure of the field and ascertain how different research areas within this field reflect interdisciplinarity through citation patterns. The complex relations between the citing and cited articles were examined through schematic visualization. Examination of WOS categories assigned to journals shows the scatter of nano studies across a wide range of research topics. We identified four distinctive groups of categories each showing some detectable shared characteristics. Three alternative measures of similarity were employed to delineate these groups. These distinct groups enabled us to assess interdisciplinarity within the groups and relationships between the groups. Some measurable levels of interdisciplinarity exist in all groups. However, one of the groups indicated that certain categories of both citing as well as cited articles aggregate mostly in the framework of physics, chemistry, and materials. This may suggest that the nanosciences show characteristics of a distinct discipline. The similarity in citing articles is most evident inside the respective groups, though, some subgroups within larger groups are also related to each other through the similarity of cited articles.
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References
Adams, J., Jackson, L., & Marshal, S. (2007). Bibliometric analysis of interdisciplinary research. Report to the higher education funding council for England. Leeds: Evidence Ltd.
Bartol, T., & Stopar, K. (2015). Nano language and distribution of article title terms according to power laws. Scientometrics, 103(2), 435–451.
Bassecoulard, E., Lelu, A., & Zitt, M. (2007). Mapping nanosciences by citation flows: A preliminary study. Scientometrics, 70(3), 859–880.
Batagelj, V., Mrvar, A. (2012). Pajek. Programs for large networks analysis. http://pajek.imfm.si/doku.php?id=pajek. Accessed 25 June 2012.
Bordons, M., Morillo, F., & Gómez, I. (2004). Analysis of cross-disciplinary research through bibliometric tools. In H. F. Moed, W. Glänzel, & U. Schmoch (Eds.), Handbook of quantitative science and technology research (pp. 437–456). Dordrecht: Kluwer.
Boyack, K. W., Klavans, R., & Börner, K. (2005). Mapping the backbone of science. Scientometrics, 64(3), 351–374.
Braun, T., Schubert, A., & Zsindely, S. (1997). Nanoscience and nanotechnology on the balance. Scientometrics, 38(2), 321–325.
Committee on Facilitating Interdisciplinary Research, & National Academy of Sciences. (2004). Facilitating Interdisciplinary Research. Washington, DC: National Academies Press.
de Nooy, W., Mrvar, A., & Batagelj, V. (2011). Exploratory social network analysis with Pajek (2nd ed.). Cambridge: University Press.
Grieneisen, M. L., & Zhang, M. (2011). Nanoscience and nanotechnology: Evolving definitions and growing footprint on the scientific landscape. Small (Weinheim an der Bergstrasse, Germany), 7(20), 2836–2839.
Hill, M. O., & Gauch, H. G. (1980). Detrended correspondence analysis: An improved ordination technique. Vegetatio, 42(1–3), 47–58.
Igami, M. & Okazaki, T. (2007). Capturing nanotechnology’s current state of development via analysis of patents. STI Working paper 2007/4. Paris, OECD.
Janssens, F., Zhang, L., De Moor, B., & Glänzel, W. (2009). Hybrid clustering for validation and improvement of subject-classification schemes. Information Processing and Management, 45(6), 683–702.
Klavans, R., & Boyack, K. W. (2006). Identifying a better measure of relatedness for mapping science. Journal of the American Society for Information Science and Technology, 57(2), 251–263.
Leydesdorff, L. (2008). The delineation of nanoscience and nanotechnology in terms of journals and patents: A most recent update. Scientometrics, 76(1), 159–167.
Leydesdorff, L., & Rafols, I. (2009). A global map of science based on the ISI subject categories. Journal of the American Society for Information Science and Technology, 60(2), 348–362.
Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations. Journal of Informetrics, 5(1), 87–100.
Leydesdorff, L., & Zhou, P. (2007). Nanotechnology as a field of science: Its delineation in terms of journals and patents. Scientometrics, 70(3), 693–713.
Maghrebi, M., Abbasi, A., Amiri, S., Monsefi, R., & Harati, A. (2011). A collective and abridged lexical query for delineation of nanotechnology publications. Scientometrics, 86, 15–25.
Meyer, M., & Persson, O. (1998). Nanotechnology—interdisciplinarity, patterns of collaboration and differences in application. Scientometrics, 42(2), 195–205.
Mogoutov, A., & Kahane, B. (2007). Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking. Research, 36, 893–903.
Morillo, F., Bordons, M., & Gómez, I. (2001). An approach to interdisciplinarity through bibliometric indicators. Scientometrics, 51(1), 203–222.
Moya-Anegon, F., Vargas-Quesada, B., Herrero-Solana, V., Chinchilla-Rodríguez, Z., Corera-Álvarez, E., & Munoz-Fernández, F. J. (2004). A new technique for building maps of large scientific domains based on the cocitation of classes and categories. Scientometrics, 61(1), 129–145.
Noyons, E. C. M. (2001). Bibliometric mapping of science in a science policy context. Scientometrics, 50(1), 83–98.
Noyons, E. C. M., Buter, R. K., van Raan, A. F .J., Schmoch, U., Heinze, T., Hinze, S. & Rangnow, R. (2003). Mapping excellence in science and technology across Europe: Nanoscience and Nanotechnology. Final report of project EC-PPN CT-2002-0001 to the European Commission. Leiden: Leiden University.
Oksanen, J., Guillaume Blanchet, F., Kindt, R., Legendre, P., Minchin, P.R., & O’Hara et al. (2015). Package ‘vegan’. http://cran.r-project.org/web/packages/vegan/vegan.pdf. Accessed 12 January 2015.
Persson, O. (2010). Bibexcel—a toolbox for bibliometricians. Inforsk, Umeå university. http://www8.umu.se/inforsk/Bibexcel/. Accessed 11 June 2012.
Porter, A. L., & Rafols, I. (2009). Is science becoming more interdisciplinary? Measuring and mapping six research fields over time. Scientometrics, 81(3), 719–745.
Porter, A. L., & Youtie, J. (2009). How interdisciplinary is nanotechnology? Journal of Nanoparticle Research, 11(5), 1023–1041.
Porter, A. L., Youtie, J., Shapira, P., & Schoeneck, D. J. (2008). Refining search terms for nanotechnology. Journal of Nanoparticle Research, 10(5), 715–728.
R Development Core Team (2012). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. http://www.R-project.org. Accessed 15 June 2012.
Rafols, I., & Meyer, M. (2007). How cross-disciplinary is bionanotechnology? Explorations in the specialty of molecular motors. Scientometrics, 70(3), 633–650.
Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience. Scientometrics, 82(2), 263–287.
Rao, C. R. (1982). Diversity and dissimilarity coefficients: A unified approach. Theoretical Population Biology, 21, 24–43.
Roco, M. C. (2002). Coherence and divergence of megatrends in science and engineering. Journal of Nanoparticle Research, 4(1–2), 9–19.
Schummer, J. (2004). Multidisciplinarity, inetrdisciplinarity, and patterns of research collaboration in nanoscience and nanotechnology. Scientometrics, 59(3), 425–465.
Stirling, A. (1994). Diversity and ignorance in electricity supply investment: Addressing the solution rather than the problem. Energy Policy, 22, 195–216.
Stirling, A. (2007). A general framework for analysing diversity in science, technology and society. Journal of the Royal Socety Interface, 4, 707–719.
Ter Braak, C. J. F. (1986). Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis. Ecology, 67(5), 1167–1179.
van Eck, N. J., & Waltman, L. (2009). How to normalize cooccurrence data? An analysis of some well-known similarity measures. Journal of the American Society for Information Science and Technology, 60(8), 1635–1651.
van Leeuwen, T., & Tijssen, R. (2000). Interdisciplinary dynamics of modern science: Analysis of cross-disciplinary citation flows. Research Evaluation, 9, 183–187.
Wagner, C. S., Roessner, J. D., Bobb, K., Thompson Klein, J., 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, 165, 14–26.
Warris, C. (2004). Nanotechnology benchmarking project. Canberra: Australian Academy of Science.
Zhang, L., Liu, X., Janssens, F., Liang, L., & Glänzel, W. (2010). Subject clustering analysis base on ISI category classification. Journal of Informetrics, 4, 185–193.
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This work was partially supported by the Slovenian Research Agency (ARRS) Research Programme P4-0085 (D).
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Stopar, K., Drobne, D., Eler, K. et al. Citation analysis and mapping of nanoscience and nanotechnology: identifying the scope and interdisciplinarity of research. Scientometrics 106, 563–581 (2016). https://doi.org/10.1007/s11192-015-1797-x
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DOI: https://doi.org/10.1007/s11192-015-1797-x