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Reflections on and a short review of the science of team science

Author

Listed:
  • Yuxian Liu

    (Tongji University
    Tongji University
    Yunnan University)

  • Yishan Wu

    (Chinese Academy of Science and Technology for Development)

  • Sandra Rousseau

    (KU Leuven)

  • Ronald Rousseau

    (KU Leuven
    University of Antwerp)

Abstract

We provide a short overview of the science of team science (SciTS). Starting from the notion of a scientific team, we move to interdisciplinary studies and finally the Science of Team Science itself. We describe the main areas of research in this field. As co-authorship networks may grow over time, which can lead to a future “global brain”, understanding how teams work and what leads to their failure or success is of the utmost importance. A thorough study of team science in all its aspects needs a collaborative, interdisciplinary and international approach. Such an approach will result in reaching the main objective of SciTS, namely to use science to transform the ways researchers do science and to enhance their effectiveness.

Suggested Citation

  • Yuxian Liu & Yishan Wu & Sandra Rousseau & Ronald Rousseau, 2020. "Reflections on and a short review of the science of team science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 937-950, November.
    • Handle: RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03513-6
    DOI: 10.1007/s11192-020-03513-6
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    References listed on IDEAS

    as
    1. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
    2. Yi Bu & Ying Ding & Xingkun Liang & Dakota S. Murray, 2018. "Understanding persistent scientific collaboration," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(3), pages 438-448, March.
    3. Kara L. Hall, 2017. "What makes teams tick," Nature, Nature, vol. 551(7682), pages 562-563, November.
    4. Walsh, John P. & Lee, You-Na & Tang, Li, 2019. "Pathogenic organization in science: Division of labor and retractions," Research Policy, Elsevier, vol. 48(2), pages 444-461.
    5. Arif Khan & Nazim Choudhury & Shahadat Uddin, 2019. "Few research fields play major role in interdisciplinary grant success," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 237-246, April.
    6. David Asai, 2019. "To learn inclusion skills, make it personal," Nature, Nature, vol. 565(7741), pages 537-537, January.
    7. Fernanda Morillo & María Bordons & Isabel Gómez, 2001. "An approach to interdisciplinarity through bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 51(1), pages 203-222, April.
    8. Lindell Bromham & Russell Dinnage & Xia Hua, 2016. "Interdisciplinary research has consistently lower funding success," Nature, Nature, vol. 534(7609), pages 684-687, June.
    9. Tibor Braun & András Schubert, 2003. "A quantitative view on the coming of age of interdisciplinarity in the sciences 1980-1999," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(1), pages 183-189, September.
    10. Raf Guns & Linda Sīle & Joshua Eykens & Frederik T. Verleysen & Tim C. E. Engels, 2018. "A comparison of cognitive and organizational classification of publications in the social sciences and humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1093-1111, August.
    11. Rennie, D. & Yank, V., 1998. "If authors became contributors, everyone would gain, especially the reader," American Journal of Public Health, American Public Health Association, vol. 88(5), pages 828-830.
    12. Wagner, Caroline S. & Roessner, J. David & Bobb, Kamau & Klein, Julie Thompson & Boyack, Kevin W. & Keyton, Joann & Rafols, Ismael & Börner, Katy, 2011. "Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature," Journal of Informetrics, Elsevier, vol. 5(1), pages 14-26.
    13. Jesús Rey-Rocha & Belén Garzón-García & M. José Martín-Sempere, 2006. "Scientists' performance and consolidation of research teams in Biology and Biomedicine at the Spanish Council for Scientific Research," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(2), pages 183-212, November.
    14. Wesley S. Ward & Lisa M. Given, 2019. "Assessing intercultural communication: Testing technology tools for information sharing in multinational research teams," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(4), pages 338-350, April.
    15. Cummings, Jonathon N. & Kiesler, Sara, 2007. "Coordination costs and project outcomes in multi-university collaborations," Research Policy, Elsevier, vol. 36(10), pages 1620-1634, December.
    16. Reindert K Buter & Ed C M Noyons & Anthony F J van Raan, 2010. "Identification of converging research areas using publication and citation data," Research Evaluation, Oxford University Press, vol. 19(1), pages 19-27, March.
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    Cited by:

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    2. Liu, Meijun & Jaiswal, Ajay & Bu, Yi & Min, Chao & Yang, Sijie & Liu, Zhibo & Acuña, Daniel & Ding, Ying, 2022. "Team formation and team impact: The balance between team freshness and repeat collaboration," Journal of Informetrics, Elsevier, vol. 16(4).
    3. Zhe Cheng & Yihuan Zou & Yueyang Zheng, 2024. "A method for identifying different types of university research teams," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    4. Hamid Bouabid & Hind Achachi, 2022. "Size of science team at university and internal co-publications: science policy implications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6993-7013, December.
    5. Ruinan Li & Raf Guns & Tim C. E. Engels & Lin Zhang & Ying Huang, 2023. "Tracking the featured topics of the International Science of Team Science conference series and their evolution during 2010–2019," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2447-2469, April.
    6. Ma, Guoshuai & Yuhua, Qian & Zhang, Yayu & Yan, Hongren & Cheng, Honghong & Hu, Zhiguo, 2022. "The recognition of kernel research team," Journal of Informetrics, Elsevier, vol. 16(4).

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