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Moderator: Vinodh Ilangovan, Postdoctoral Researcher, Max Planck Institute for Biophysical Chemistry and member of the eLife Early-Career Advisory Group.
Speakers: Girija Goyal, co-founder of ReFigure; Lawrence Rajendran, Professor, University of Zurich and CEO of ScienceMatters; and Courtney Soderberg, Statistical and Methodological Consultant, Open Science Framework.
It can take months or years to publish an article in an academic journal. This can make it difficult for researchers to demonstrate their productivity early in their careers. To address this problem, a number of new ways to share small units of work rapidly have been developed.
A journal article generally consists of a research story constructed from many separate experimental findings and procedures. A minimal unit is one of these – for example, the data that supports one result, a figure, or a protocol. Many platforms and services have been set up to make it easier to share individual units, including those represented by the webinar panellists – ReFigure, ScienceMatters and the Open Science Framework. Importantly, these platforms and services contain features that allow work to be properly cited, and so enable researchers to receive formal credit.
Moving away from traditional journal articles provides opportunities for researchers to communicate their work in other formats. Courtney Soderberg has seen an increase in the popularity of video protocols, where researchers film themselves as they set up a particular technique. She thinks they complement written protocols well: “Having a video may provide details that you didn’t think of to write down”.
Sharing the results of experiments that did not work is often cited as something that is valuable to the scientific community. But how do you decide what to make available to other researchers? If you’ve made a technical mistake while performing the experiment, is that work still worth sharing? Girija Goyal points out that it is not always possible to be certain that deviating from the experimental protocol has introduced an error: “We think about that when we don’t get the result we expected, which I think introduces a bias”. To be of most help to other researchers, Lawrence Rajendran suggests keeping reproducibility in mind when deciding what to share: “we need to make sure we can reproduce [a result] in the lab before we publish – even if it is a minimal unit that we want to publish”.
Some researchers hesitate to share their unpublished data for fear of being scooped (for example, because other researchers analyse the data first). If this is a concern, you could focus on sharing only some types of data. “About 50–80% of your data is not going to make it to a traditional publication,” says Goyal. This includes reproduced data, negative data and experiments that didn’t lead anywhere. Sharing these data provides other researchers with potentially useful information without necessarily revealing any of your future research plans. But if you’re not comfortable sharing any data before you’ve finished working on a project, it is still better to share it after you have published your findings than to not share it at all.
Many of the actions that researchers can take to share their work outside of journal articles fall under the banner of open science practices. Support for these actions is growing: Soderberg has seen more and more hiring committees asking for evidence of open science practices – for example, sharing data – from job applicants. A number of funders also prefer to see preprints rather than papers “in press” included in grant applications. The best way to support the sharing of minimal units of productivity (in all their forms) is for researchers to make them an integral part of how they communicate research. After all, as Rajendran put it at the end of the webinar, it’s not enough only to complain about the system – we also all need to participate in making the change happen.
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