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Visualizing big science projects

Nature Reviews Physics volume 3, pages 753–761 (2021)Cite this article

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Abstract

The number, size and complexity of ‘big science’ projects are growing — as are the size, complexity and value of the data sets and software services they produce. In this context, big data gives a new way to analyse, understand, manage and communicate the inner workings of collaborations that often involve thousands of experts, thousands of scholarly publications, hundreds of new instruments and petabytes of data. We compare the evolving geospatial and topical impact of big science projects in physics, astronomy and biomedical sciences. A total of 13,893 publications and 1,139 grants by 21,945 authors cited more than 333,722 times are analysed and visualized to help characterize the distinct phases of big science projects, document increasing internationalization and densification of collaboration networks, and reveal the increase in interdisciplinary impact over time. All data sets and visual analytics workflows are freely available on GitHub in support of future big science studies.

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Fig. 1: The data compilation, analysis and visualization workflow.
Fig. 2: Number of publications, citations, authors and author affiliations for six big science projects.
Fig. 3: Geodistributed collaboration network of institutions for ATLAS.
Fig. 4: Citations breakdown by disciplines and subdisciplines.

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Code availability

Data details and code77,78 are available at https://bigscience.github.io.

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Acknowledgements

The authors thank the interviewed experts for their time and expert input. T. Schwander gave guidance for compiling the INSPIRE data sets. B. W. Herr II implemented the interactive science maps. T. N. Theriault compiled references and provided professional copy-editing support. This work is funded by the NSF under grants NRT-1735095, AISL-1713567 and DMS-1839167 and the Precision Health Initiative as part of Indiana University’s Grand Challenges programme. In addition, this material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-19-1-0391. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

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Authors and Affiliations

  1. Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Katy Börner & Staša Milojević

  2. Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA

    Filipi Nascimento Silva

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  1. Katy Börner
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  3. Staša Milojević
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Contributions

S.M. led the literature review, K.B. led the expert survey and science mapping effort and F.N.S. led the data analysis and visualization. All authors contributed equally to the write-up of other article parts.

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Correspondence to Katy Börner.

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Nature Reviews Physics thanks Junming Huang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

Council for Chemical Research. Chemical R&D Powers the US Innovation Engine: https://scimaps.org/map/5/6

Human Cell Atlas. Publications: https://www.humancellatlas.org/publications

Human Genome Project Information Archive, 1990–2003: landmark HGP papers: https://web.ornl.gov/sci/techresources/Human_Genome/project/journals.shtml

INSPIRE: https://inspirehep.net

National Institutes of Health. NIH Research Portfolio Online Reporting Tools (RePORT): https://reporter.nih.gov/

National Science Foundation. BaBar award search results: https://www.nsf.gov/awardsearch/simpleSearchResult?queryText=babar

National Science Foundation. IceCube award search results: https://www.nsf.gov/awardsearch/simpleSearchResult?queryText=icecube

National Science Foundation. LIGO award search results: https://www.nsf.gov/awardsearch/simpleSearchResult?queryText=ligo

National Institutes of Health. NIH RePORTER search results (I): https://reporter.nih.gov/search/bC3_awAf4U6Hl7zF9rQEZQ/projects?shared=true

National Institutes of Health. NIH RePORTER search results (II): https://reporter.nih.gov/search/BwnasVXfbUiGwaac353HGw/projects?shared=true

NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) Initiative: https://datascience.nih.gov/strides

Nominatim. Home page: https://nominatim.org

Vera C. Rubin Observatory. Rubin Observatory System & LSST survey key numbers: https://www.lsst.org/scientists/keynumbers

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Börner, K., Silva, F.N. & Milojević, S. Visualizing big science projects. Nat Rev Phys 3, 753–761 (2021). https://doi.org/10.1038/s42254-021-00374-7

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