A Research data Sharing Game
- Published
- Accepted
- Subject Areas
- Science Policy, Statistics
- Keywords
- open data, data sharing, research data, game theory, simulation model
- Copyright
- © 2014 Pronk et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2014. A Research data Sharing Game. PeerJ PrePrints 2:e599v1 https://doi.org/10.7287/peerj.preprints.599v1
Abstract
While reusing research data has evident benefits for the scientific community as a whole, decisions to archive and share these data are primarily made by individual researchers. For individuals, it is less obvious that the benefits of sharing data outweigh the associated costs, i.e. time and money. In this sense the problem of data sharing resembles a typical game in interactive decision theory, more commonly known as game theory. Within this framework we analyse in this paper how different measures to promote sharing and reuse of research data affect sharing and not sharing individuals. We find that the scientific community can benefit from top-down policies to enhance sharing data even when the act of sharing itself implies a cost. Namely, if (almost) everyone shares, many individuals can gain a higher efficiency as datasets can be reused. Additionally, measures to ensure better data retrieval and quality can compensate for sharing costs by enabling reuse. Nevertheless, an individual researcher who decides not to share omits the costs of sharing. Assuming that the natural tendency will be to use a strategy that will lead to maximisation of individual efficiency it is seen that, as more individuals decide not to share, there is a point at which average efficiency for both sharing and non-sharing researchers becomes lower than was originally the case and scientific community efficiency steadily drops. With this in mind, we conclude that the key to motivate the researcher to share data lies in reducing the costs associated with sharing, or even better, turning it into a benefit.
Author Comment
This preprint will be submitted to PeerJ for review.