A medical journal is to make the publication of raw data a condition of article acceptance after an investigation by its editor found that many authors failed to provide the information on request – and that there were serious issues with much of the data that were shared by researchers.
Tsuyoshi Miyakawa, a professor of genetics at Japan’s Fujita Health University and editor-in-chief of Molecular Brain, warns that periodicals’ failure to require submitting authors to share their data could be contributing to the reproducibility “crisis” in science and may even be leading to research fraud going unnoticed.
He started asking for raw data after finding in some submissions “amazingly beautiful results to the extent that I could not believe it”, and ultimately made the request to the authors of 41 suspect papers, out of the 180 submissions handled between early 2017 and September 2019. In more than half these cases – 21 – the manuscripts were withdrawn without raw data being provided and, of the remaining 20 papers for which data were submitted, the information was “insufficient” in 19 cases, Professor Miyakawa says. In seven cases the raw data did not match the results in the article, and in two Professor Miyakawa identified evidence of image duplication and “inappropriate cuts and pastes”.
Hence only one of the 41 passed muster for review and publication. However, this was not the end for many of the 40 withdrawn or rejected manuscripts – 14 were later published in other journals, writes Professor Miyakawa in a Molecular Brain editorial. Of these, 12 were published in journals that require or recommend that authors provide raw data upon request from readers.
Professor Miyakawa sent emails or letters requesting the data again – and got no response in 10 cases. In the 11th case, the author provided raw data for one sample per condition, and in the 12th the author declined to share the data because they said they included “some other novel information”.
In his editorial, Professor Miyakawa says that some authors were perhaps unwilling to gather all the raw data or, as happened in the case outlined above, wanted to base further publications on them. But, he adds, in at least some cases, he “cannot help thinking that the data did not exist from the beginning”.
While his own survey leans towards research from east Asia, “the lack of willingness to supply data can be found worldwide”, Professor Miyakawa told Times Higher Education.
“Employment, promotions and research funding are mostly determined by publications in academic journals, and so the temptation in researchers to cheat must be huge in general,” he said.
Given concern about the lack of reproducibility of experiments in some scientific fields – and the key role that sharing data plays in this issue – Professor Miyakawa proposes in his editorial “that sharing raw data publicly [should be] a necessary condition for a study to be considered scientifically sound, unless the authors have acceptable reasons not to do so”, for example, when the data contains personally confidential information.
“An absence of raw data means the absence of science,” Professor Miyakawa told THE.
Molecular Brain will begin requiring datasets on which conclusions of articles rely to be deposited in repositories or in the main paper or additional supporting files, in machine-readable format, from 1 March.
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