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Network Based Methodology for Characterizing Interdisciplinary Expertise in Emerging Research

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Complex Networks & Their Applications XII (COMPLEX NETWORKS 2023)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1142))

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Abstract

Funding agencies and researchers are placing increasing emphasis on interdisciplinary research (IDR) to promote innovation and to address complex real-world problems. Understanding characteristics of IDR early (as soon as projects get funded), can formatively shape a research community at portfolio, project, and individual investigator levels. This involves surfacing the interacting components and the context that manifest IDR. We present a network-based methodology to model and analyze IDR, and apply it to a three-year portfolio of awards in the Research on Emerging Technologies for Teaching and Learning program. Our IDR analysis features two network-based metrics (1) diversity of expertise and (2) intensity of inter-expertise collaboration. It reveals the organization of the 116 expertise areas that form the “building blocks” for IDR in this community, while also highlighting potential for knowledge integration, specifically within “hotspot” topics. It also reveals gaps in IDR potential. Applying our network-based methodology for understanding IDR could enable other research domains and communities to conduct early and rapid analyses of the emerging IDR profile in their network, and could inform formative efforts to strengthen IDR.

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Notes

  1. 1.

    https://www.nsf.gov/pubs/2020/nsf20612/nsf20612.htm.

  2. 2.

    https://www.nsf.gov/awardsearch/.

  3. 3.

    https://circls.org/project-tag-map.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. 2021159.

Author information

Authors and Affiliations

  1. Digital Promise Global, Berkeley, CA, USA

    Aditi Mallavarapu & Jeremy Roschelle

  2. University of Pittsburgh, Pittsburgh, PA, USA

    Erin Walker & Cassandra Kelley

  3. SRI International, Menlo Park, CA, USA

    Shari Gardner

  4. National Museum of Mathematics, New York, NY, USA

    Stephen Uzzo

Authors
  1. Aditi Mallavarapu
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  2. Erin Walker
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  3. Cassandra Kelley
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  4. Shari Gardner
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  5. Jeremy Roschelle
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  6. Stephen Uzzo
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Corresponding author

Correspondence to Aditi Mallavarapu .

Editor information

Editors and Affiliations

  1. University of Burgundy, Dijon Cedex, France

    Hocine Cherifi

  2. Thomas J. Watson College of Engineering and Applied Science, Binghamton University, Binghamton, NY, USA

    Luis M. Rocha

  3. IUT Lumière - Université Lyon 2, University of Lyon, Bron, France

    Chantal Cherifi

  4. Department of Economics, Yildiz Technical University, Istanbul, Türkiye

    Murat Donduran

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Mallavarapu, A., Walker, E., Kelley, C., Gardner, S., Roschelle, J., Uzzo, S. (2024). Network Based Methodology for Characterizing Interdisciplinary Expertise in Emerging Research. In: Cherifi, H., Rocha, L.M., Cherifi, C., Donduran, M. (eds) Complex Networks & Their Applications XII. COMPLEX NETWORKS 2023. Studies in Computational Intelligence, vol 1142. Springer, Cham. https://doi.org/10.1007/978-3-031-53499-7_10

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  • DOI: https://doi.org/10.1007/978-3-031-53499-7_10

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  • Print ISBN: 978-3-031-53498-0

  • Online ISBN: 978-3-031-53499-7

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