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A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science

Author

Listed:
  • Zhichao Ba

    (Wuhan University)

  • Yujie Cao

    (Wuhan University)

  • Jin Mao

    (Wuhan University)

  • Gang Li

    (Wuhan University)

Abstract

As a driver in modern science, interdisciplinary research has attracted a lot of attention. Major foci are laid on exploring the relations of multiple involved disciplines as well as the knowledge structure in interdisciplinary field. However, there is still a lack of decomposing the knowledge structure of interdisciplinary field to investigate how knowledge from relevant disciplines is integrated in the field. This study proposes an approach to investigating knowledge integration relationships between two research fields from a perspective of hierarchy. Medical Informatics (MI) and its most relevant field of Computer Science (CS) are chosen in the case study. This study decomposed each keyword network of the two fields into four layers by using the K-core method, then quantified the knowledge integration relationships between different layers of the two fields together. The results present that the MI basic layer shows the strongest knowledge integration with CS, followed by the middle layer, with the detail layer the weakest. And all MI layers have the greatest breadth and strength of knowledge integration with the CS middle layer, followed by the CS marginal layer and detail layer, but with the CS basic layer the weakest. A time series analysis shows that the integration of new CS knowledge into MI is a gradual process without explosive growth and the path of knowledge integration between the two fields were identified. The proposed approach could be applied to deeply understanding the integration of one discipline knowledge by an interdisciplinary field.

Suggested Citation

  • Zhichao Ba & Yujie Cao & Jin Mao & Gang Li, 2019. "A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1455-1486, June.
    • Handle: RePEc:spr:scient:v:119:y:2019:i:3:d:10.1007_s11192-019-03103-1
    DOI: 10.1007/s11192-019-03103-1
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    as
    1. Kavitha Karunan & Hiran H. Lathabai & Thara Prabhakaran, 2017. "Discovering interdisciplinary interactions between two research fields using citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 335-367, October.
    2. Jiming Hu & Yin Zhang, 2017. "Discovering the interdisciplinary nature of Big Data research through social network analysis and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 91-109, July.
    3. Peter van den Besselaar & Gaston Heimeriks, 2006. "Mapping research topics using word-reference co-occurrences: A method and an exploratory case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 377-393, September.
    4. Mario Karlovčec & Dunja Mladenić, 2015. "Interdisciplinarity of scientific fields and its evolution based on graph of project collaboration and co-authoring," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 433-454, January.
    5. Leah G. Nichols, 2014. "A topic model approach to measuring interdisciplinarity at the National Science Foundation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 741-754, September.
    6. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    7. Ruobing Chi & Jonathan Young, 2013. "The interdisciplinary structure of research on intercultural relations: a co-citation network analysis study," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 147-171, July.
    8. Leydesdorff, Loet & Rafols, Ismael, 2011. "Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations," Journal of Informetrics, Elsevier, vol. 5(1), pages 87-100.
    9. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    10. 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.
    11. Pei-Chun Lee & Hsin-Ning Su & Te-Yi Chan, 2010. "Assessment of ontology-based knowledge network formation by Vector-Space Model," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 689-703, December.
    12. 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.
    13. Finn Valentin & Maria Theresa Norn & Lars Alkaersig, 2016. "Orientations and outcome of interdisciplinary research: the case of research behaviour in translational medical science," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 67-90, January.
    14. Thed N. van Leeuwen & Henk F. Moed, 2005. "Characteristics of journal impact factors: The effects of uncitedness and citation distribution on the understanding of journal impact factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(2), pages 357-371, April.
    15. Lu Xiao & Guo Chen & Jianjun Sun & Shuguang Han & Chengzhi Zhang, 2016. "Exploring the topic hierarchy of digital library research in China using keyword networks: a K-core decomposition approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1085-1101, September.
    16. Min Song & Su Yeon Kim, 2013. "Detecting the knowledge structure of bioinformatics by mining full-text collections," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 183-201, July.
    17. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    18. Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
    19. Graeme Hirst, 1978. "Discipline impact factors: A method for determining core journal lists," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(4), pages 171-172, July.
    20. Kun Dong & Haiyun Xu & Rui Luo & Ling Wei & Shu Fang, 2018. "An integrated method for interdisciplinary topic identification and prediction: a case study on information science and library science," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 849-868, May.
    21. Diana Lucio‐Arias & Loet Leydesdorff, 2008. "Main‐path analysis and path‐dependent transitions in HistCite™‐based historiograms," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(12), pages 1948-1962, October.
    22. Alan L. Porter & Alex S. Cohen & J. David Roessner & Marty Perreault, 2007. "Measuring researcher interdisciplinarity," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(1), pages 117-147, July.
    23. Anke Piepenbrink & Elkin Nurmammadov, 2015. "Topics in the literature of transition economies and emerging markets," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2107-2130, March.
    24. Keeheon Lee & Hyojung Jung & Min Song, 2016. "Subject–method topic network analysis in communication studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1761-1787, December.
    25. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    26. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    27. Xiaoguang Wang & Qikai Cheng & Wei Lu, 2014. "Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1253-1271, November.
    28. Haiyun Xu & Ting Guo & Zenghui Yue & Lijie Ru & Shu Fang, 2016. "Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 583-601, February.
    29. Lili Wang & Ad Notten & Alexandru Surpatean, 2013. "Interdisciplinarity of nano research fields: a keyword mining approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 877-892, March.
    30. Wei Lu & Yong Huang & Yi Bu & Qikai Cheng, 2018. "Functional structure identification of scientific documents in computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 463-486, April.
    31. Joachim Schummer, 2004. "Multidisciplinarity, interdisciplinarity, and patterns of research collaboration in nanoscience and nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 425-465, March.
    32. Gao-Yong Liu & Ji-Ming Hu & Hui-Ling Wang, 2012. "A co-word analysis of digital library field in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 203-217, April.
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    6. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
    7. Hoang-Son Pham & Bram Vancraeynest & Hanne Poelmans & Sadia Vancauwenbergh & Amr Ali-Eldin, 2023. "Identifying interdisciplinary research in research projects," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5521-5544, October.
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