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SiSOB Data Extraction and Codification: A tool to analyse scientific careers

Author

Listed:
  • Geuna, Aldo

  • Kataishi, Rodrigo

  • Toselli, Manuel

  • Guzmán, Eduardo
  • Lawson, Cornelia

  • Fernandez-Zubieta, Ana

  • Barros, Beatriz

    (University of Turin)

Abstract

This paper describes the methodology and software tool used to build a database on the careers and productivity of academics, using public information available on the Internet, and provides a first analysis of the data collected for a sample of 360 US scientists funded by the National Institute of Health (NIH) and 291 UK scientists funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The tool’s structured outputs can be used for either econometric research or data representation for policy analysis. The methodology and software tool is validated for a sample of US and UK biomedical scientists, but can be applied to any countries where scientists’ CVs are available in English. We provide an overview of the motivations for constructing the database, and the data crawling and data mining techniques used to transform webpage - based information and CV information into a relational database. We describe the database and the effectiveness of our algorithms a nd provide suggestions for further improvements. The software developed is released under free software GNU General Public License ; the aim is for it to be available to the community of social scientists and economists interested in analysing scientific production and scientific careers, who it is hoped will develop this tool further.

Suggested Citation

  • Geuna, Aldo & Kataishi, Rodrigo & Toselli, Manuel & Guzmán, Eduardo & Lawson, Cornelia & Fernandez-Zubieta, Ana & Barros, Beatriz, 2015. "SiSOB Data Extraction and Codification: A tool to analyse scientific careers," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201506, University of Turin.
    • Handle: RePEc:uto:dipeco:201506
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    Citations

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    Cited by:

    1. Loet Leydesdorff & Gaston Heimeriks & Daniele Rotolo, 2016. "Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 741-748, March.
    2. Stapleton, Lee & Sorrell, Steve & Schwanen, Tim, 2016. "Estimating direct rebound effects for personal automotive travel in Great Britain," Energy Economics, Elsevier, vol. 54(C), pages 313-325.
    3. Valentina Tartari & Francesco Di Lorenzo & Benjamin A. Campbell, 2020. "“Another roof, another proof”: the impact of mobility on individual productivity in science," The Journal of Technology Transfer, Springer, vol. 45(1), pages 276-303, February.
    4. Stephane Lhuillery & Julio Raffo & Intan Hamdan-Livramento, 2016. "Measuring creativity: Learning from innovation measurement," WIPO Economic Research Working Papers 31, World Intellectual Property Organization - Economics and Statistics Division.
    5. Magnus Gulbrandsen & Taran Thune, 2017. "The effects of non-academic work experience on external interaction and research performance," The Journal of Technology Transfer, Springer, vol. 42(4), pages 795-813, August.
    6. Cornelia Lawson & Aldo Geuna & Rodrigo Kataishi & Manuel Toselli & Ana Fernández-Zubieta, 2015. "International Careers of Researchers in Biomedical Sciences: A Comparison of the US and the UK," SPRU Working Paper Series 2015-09, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Beatriz Barros & Ana Fernández-Zubieta & Raul Fidalgo-Merino & Francisco Triguero, 2018. "Scientific knowledge percolation process and social impact: A case study on the biotechnology and microbiology perceptions on Twitter," Science and Public Policy, Oxford University Press, vol. 45(6), pages 804-814.
    8. Paulo Lopes Henriques & Carla Curado & Mírian Oliveira & Antônio Carlos Gastaud Maçada, 2019. "Publishing? You can count on knowledge, experience, and expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1301-1324, May.
    9. Claartje J Vinkenburg & Sara Connolly & Stefan Fuchs & Channah Herschberg & Brigitte Schels, 2020. "Mapping career patterns in research: A sequence analysis of career histories of ERC applicants," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-19, July.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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