Abstract

Among the frequently stated benefits of sharing research data are time efficiency or increased productivity. The assumption is that reuse or secondary use of research data saves researchers time in not having to produce data for a publication themselves. This can make science more efficient and productive. However, if there is no reuse, time costs in making data available for reuse will have been made with no return on this investment. In this paper a mathematical model is used to calculate the break-even point for time spent sharing in a scientific community, versus time gain by reuse. This is done for several scenarios; from simple to complex datasets to share and reuse, and at different sharing rates. The results indicate that sharing research data can indeed cause an efficiency revenue for the scientific community. However, this is not a given in all modeled scenarios. The scientific community with the lowest reuse needed to reach a break-even point is one that has few sharing researchers and low time investments for sharing and reuse. This suggests it would be beneficial to have a critical selection of datasets that are worth the effort to prepare for reuse in other scientific studies. In addition, stimulating reuse of datasets in itself would be beneficial to increase efficiency in scientific communities.

Highlights

  • Sharing research data is generally regarded as yielding benefits for the scientific community, society as a whole, and as having potential benefits for the researchers that share their data (e.g. Ascoli, 2007; Kim, 2013; Pitt & Tang, 2013)

  • We focus on the question how much reuse is needed in a scientific community to compensate for the investment of making data available for sharing

  • The break-even point in terms of time efficiency is in each subplot indicated by a black vertical line that intersects the x-axis at zero net added productivity

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Summary

Introduction

Sharing research data is generally regarded as yielding benefits for the scientific community, society as a whole, and as having potential benefits for the researchers that share their data (e.g. Ascoli, 2007; Kim, 2013; Pitt & Tang, 2013). One of the specific benefits of shared data for the scientific community is more efficient or productive science When research data are shared, they become available for reuse. This may be time-efficient for a reuser because the often time consuming task of data collection or generation is omitted. Researchers who have the option to reuse data rather than having to produce it, have net more time to produce scientific products or to start other scientific inquiries, leading to increased productivity in science. For a whole community the reuse and combining of data can bring about great efficiency leaps in terms of understanding complex systems such as in brain research (Koslow, 2002) and biodiversity (Enke et al, 2012). The secondary use of the shared data in such individual cases can be very helpful for both scientific community and individual reusers

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