NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
QUEST Center for Transforming Biomedical Research, Berlin Institute of Health (BIH), Berlin, Germany.
Clin Sci (Lond). 2020 Oct 30;134(20):2729-2739. doi: 10.1042/CS20201125.
Statistically significant findings are more likely to be published than non-significant or null findings, leaving scientists and healthcare personnel to make decisions based on distorted scientific evidence. Continuously expanding ´file drawers' of unpublished data from well-designed experiments waste resources creates problems for researchers, the scientific community and the public. There is limited awareness of the negative impact that publication bias and selective reporting have on the scientific literature. Alternative publication formats have recently been introduced that make it easier to publish research that is difficult to publish in traditional peer reviewed journals. These include micropublications, data repositories, data journals, preprints, publishing platforms, and journals focusing on null or neutral results. While these alternative formats have the potential to reduce publication bias, many scientists are unaware that these formats exist and don't know how to use them. Our open source file drawer data liberation effort (fiddle) tool (RRID:SCR_017327 available at: http://s-quest.bihealth.org/fiddle/) is a match-making Shiny app designed to help biomedical researchers to identify the most appropriate publication format for their data. Users can search for a publication format that meets their needs, compare and contrast different publication formats, and find links to publishing platforms. This tool will assist scientists in getting otherwise inaccessible, hidden data out of the file drawer into the scientific community and literature. We briefly highlight essential details that should be included to ensure reporting quality, which will allow others to use and benefit from research published in these new formats.
有统计学意义的发现比无统计学意义或无效的发现更有可能被发表,这使得科学家和医疗保健人员只能根据扭曲的科学证据做出决策。不断扩大未发表数据的“档案抽屉”,这些数据来自精心设计的实验,浪费了资源,给研究人员、科学界和公众带来了问题。人们对发表偏倚和选择性报告对科学文献的负面影响认识有限。最近引入了替代发表格式,使难以在传统同行评审期刊上发表的研究更容易发表。这些替代格式包括微型出版物、数据存储库、数据期刊、预印本、发表平台以及专注于无效或中性结果的期刊。虽然这些替代格式有可能减少发表偏倚,但许多科学家不知道这些格式的存在,也不知道如何使用它们。我们的开源档案抽屉数据解放工作(fiddle)工具(RRID:SCR_017327,可在:http://s-quest.bihealth.org/fiddle/ 获取)是一个匹配的 Shiny 应用程序,旨在帮助生物医学研究人员为他们的数据确定最合适的发表格式。用户可以搜索符合他们需求的发表格式,比较和对比不同的发表格式,并找到发表平台的链接。该工具将帮助科学家将原本无法获取的、隐藏的数据从档案抽屉中解放出来,纳入科学界和文献中。我们简要强调了确保报告质量所需包含的基本细节,这将允许其他人使用和受益于以这些新格式发表的研究。