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Data Combination for Problem-Solving: A Case of an Open Data Exchange Platform

Author

Listed:
  • Teruaki Hayashi

    (The University of Tokyo)

  • Hiroki Sakaji

    (The University of Tokyo)

  • Hiroyasu Matsushima

    (Shiga University)

  • Yoshiaki Fukami

    (Keio University
    Keio University)

  • Takumi Shimizu

    (Keio University)

  • Yukio Ohsawa

    (The University of Tokyo)

Abstract

In recent years, rather than enclosing data within a single organization, exchanging and combining data from different domains has become an emerging practice. Many studies have discussed the economic and utility value of data and data exchange, but the characteristics of data that contribute to problem-solving through data combination have not been fully understood. In big data and interdisciplinary data combinations, large-scale data with many variables are expected to be used, and value is expected to be created by combining data as much as possible. In this study, we conducted three experiments to investigate the characteristics of data, focusing on the relationships between data combinations and variables in each dataset, using empirical data shared by the local government. The results indicate that even datasets that have a few variables are frequently used to propose solutions for problem-solving. Moreover, we found that even if the datasets in the solution do not have common variables, there are some well-established solutions to these problems. The findings of this study shed light on the mechanisms behind data combination for solving problems involving multiple datasets and variables.

Suggested Citation

  • Teruaki Hayashi & Hiroki Sakaji & Hiroyasu Matsushima & Yoshiaki Fukami & Takumi Shimizu & Yukio Ohsawa, 2021. "Data Combination for Problem-Solving: A Case of an Open Data Exchange Platform," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 521-534, November.
    • Handle: RePEc:spr:trosos:v:15:y:2021:i:2:d:10.1007_s12626-021-00083-8
    DOI: 10.1007/s12626-021-00083-8
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    References listed on IDEAS

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    1. Markus Spiekermann, 2019. "Data Marketplaces: Trends and Monetisation of Data Goods," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 54(4), pages 208-216, July.
    2. Ridder, Geert & Moffitt, Robert, 2007. "The Econometrics of Data Combination," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 75, Elsevier.
    3. Max Boisot & Agustí Canals, 2004. "Data, information and knowledge: have we got it right?," Journal of Evolutionary Economics, Springer, vol. 14(1), pages 43-67, January.
    4. Yoon, Hyungwook & Zo, Hangjung & Ciganek, Andrew P., 2011. "Does XBRL adoption reduce information asymmetry?," Journal of Business Research, Elsevier, vol. 64(2), pages 157-163, February.
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