To Move Towards A More Open Science, We Must Free The Data | National Center for Ecological Analysis and Synthesis (NCEAS), University of California
ab1630's bookmarks 2018-08-05
"Open science can be incorporated into every step of the scientific process and emphasizes data sharing. Making data publicly available facilitates their reuse by scientists, such as in synthesis research, and can thus have a much greater impact than data that are limited to the creator's initial analysis or intention. With billions of dollars dedicated each year to support scientific research, there is a growing push from funders to increase the impact and prestige of the money they award by requiring or encouraging data sharing. Particularly, when scientists receive public funds, their data are considered a public good and therefore carry an expectation of public accessibility. Additionally, new tools are emerging that make data annotation and sharing easier to incorporate into the research process. However, while tools and protocols are changing to improve data sharing among researchers, colleagues and I found little data are currently made public in practice. In an article published in PLOS One, our team of scientists tested compliance with funder-imposed data-sharing requirements among projects in the environmental sciences over a twenty-year period. We were able to collect data from only 26 percent of the funded projects. As scientists, we believe everyone in the scientific community can play a role in increasing data publication and sharing, and it is our responsibility to do so to improve the efficiency of research. In our analysis, data availability did differ based on the project’s field of study, influenced by factors such as the time required to prepare data, whether a field has established data collection protocols and standardized methods, the sensitivity of data, and the ease of their interpretation. Nonetheless, we assert that a fundamental obstacle facing data sharing is the absence of a professional reward structure, such as the recognition that data citations are as valuable as paper citations. This discrepancy de-incentivizes the time spent formatting, annotating, and preparing data to be shared...."