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

Teruaki Hayashi (), Hiroki Sakaji, Hiroyasu Matsushima, Yoshiaki Fukami, Takumi Shimizu and Yukio Ohsawa
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Teruaki Hayashi: The University of Tokyo
Hiroki Sakaji: The University of Tokyo
Hiroyasu Matsushima: Shiga University
Yoshiaki Fukami: Keio University
Takumi Shimizu: Keio University
Yukio Ohsawa: The University of Tokyo

The Review of Socionetwork Strategies, 2021, vol. 15, issue 2, 521-534

Abstract: 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.

Keywords: Data combination; Data exchange; Data ecosystem; Open data; Data platform (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s12626-021-00083-8

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