Incentive or Disincentive for Disclosure of Research Data? A Large-Scale Empirical Analysis and Implications for Open Science Policy

Author Name KWON Seokbeom (University of Tokyo) / MOTOHASHI Kazuyuki (Faculty Fellow, RIETI)
Creation Date/NO. June 2020 20-E-058
Research Project Digitalization and Innovation Ecosystem: A Holistic approach
Download / Links


The incentive for scientists to disclose their research data hinges on the extent to which data disclosure brings academic credit (the credit effect) compared to the dissipation of academic credit through intensified scientific competition (the competition effect). In this study, we examine the net effect on the academic credit received by research publications of data-providing researchers publicly disclosing research data. To accomplish this, we compared the citation impact of scientific journal articles that disclosed original data with those that did not.

An analysis of metadata of over 310,000 Web of Science (WoS)-indexed journal articles published in 2010 shows that in the early period after publication, more citations accrued to articles that disclosed original data than to those that did not. However, this difference faded over time and the pattern was later reversed. Additional analysis shows that the credit effect dominates for data-disclosing research published in journals with higher scholarly reputations, whereas the competition effect dominates for research published in journals with lower scholarly reputations. This study contributes to on-going policy discussion concerning the need for institutional measures to promote open science and the disclosure of research data by scientists.

Published: Kwon, Seokbeom, and Kazuyuki Motohashi, 2021. "Incentive or disincentive for research data disclosure? A large-scale empirical analysis and implications for open science policy," International Journal of Information Management, Volume 60, 102371.