No raw data, no science: another possible source of the reproducibility crisis

Abstract A reproducibility crisis is a situation where many scientific studies cannot be reproduced. Inappropriate practices of science, such as HARKing, p-hacking, and selective reporting of positive results, have been suggested as causes of irreproducibility. In this editorial, I propose that a la...

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Main Author: Tsuyoshi Miyakawa
Format: Article
Language:English
Published: BMC 2020-02-01
Series:Molecular Brain
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13041-020-0552-2
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spelling doaj-b92e595093b64f3faa4aefc615a9d6cd2020-11-25T02:27:39ZengBMCMolecular Brain1756-66062020-02-011311610.1186/s13041-020-0552-2No raw data, no science: another possible source of the reproducibility crisisTsuyoshi Miyakawa0Division of Systems Medical Science, Institute for Comprehensive Medical Science, Fujita Health UniversityAbstract A reproducibility crisis is a situation where many scientific studies cannot be reproduced. Inappropriate practices of science, such as HARKing, p-hacking, and selective reporting of positive results, have been suggested as causes of irreproducibility. In this editorial, I propose that a lack of raw data or data fabrication is another possible cause of irreproducibility. As an Editor-in-Chief of Molecular Brain, I have handled 180 manuscripts since early 2017 and have made 41 editorial decisions categorized as “Revise before review,” requesting that the authors provide raw data. Surprisingly, among those 41 manuscripts, 21 were withdrawn without providing raw data, indicating that requiring raw data drove away more than half of the manuscripts. I rejected 19 out of the remaining 20 manuscripts because of insufficient raw data. Thus, more than 97% of the 41 manuscripts did not present the raw data supporting their results when requested by an editor, suggesting a possibility that the raw data did not exist from the beginning, at least in some portions of these cases. Considering that any scientific study should be based on raw data, and that data storage space should no longer be a challenge, journals, in principle, should try to have their authors publicize raw data in a public database or journal site upon the publication of the paper to increase reproducibility of the published results and to increase public trust in science.http://link.springer.com/article/10.1186/s13041-020-0552-2Raw dataData fabricationOpen dataOpen scienceMisconductReproducibility
collection DOAJ
language English
format Article
sources DOAJ
author Tsuyoshi Miyakawa
spellingShingle Tsuyoshi Miyakawa
No raw data, no science: another possible source of the reproducibility crisis
Molecular Brain
Raw data
Data fabrication
Open data
Open science
Misconduct
Reproducibility
author_facet Tsuyoshi Miyakawa
author_sort Tsuyoshi Miyakawa
title No raw data, no science: another possible source of the reproducibility crisis
title_short No raw data, no science: another possible source of the reproducibility crisis
title_full No raw data, no science: another possible source of the reproducibility crisis
title_fullStr No raw data, no science: another possible source of the reproducibility crisis
title_full_unstemmed No raw data, no science: another possible source of the reproducibility crisis
title_sort no raw data, no science: another possible source of the reproducibility crisis
publisher BMC
series Molecular Brain
issn 1756-6606
publishDate 2020-02-01
description Abstract A reproducibility crisis is a situation where many scientific studies cannot be reproduced. Inappropriate practices of science, such as HARKing, p-hacking, and selective reporting of positive results, have been suggested as causes of irreproducibility. In this editorial, I propose that a lack of raw data or data fabrication is another possible cause of irreproducibility. As an Editor-in-Chief of Molecular Brain, I have handled 180 manuscripts since early 2017 and have made 41 editorial decisions categorized as “Revise before review,” requesting that the authors provide raw data. Surprisingly, among those 41 manuscripts, 21 were withdrawn without providing raw data, indicating that requiring raw data drove away more than half of the manuscripts. I rejected 19 out of the remaining 20 manuscripts because of insufficient raw data. Thus, more than 97% of the 41 manuscripts did not present the raw data supporting their results when requested by an editor, suggesting a possibility that the raw data did not exist from the beginning, at least in some portions of these cases. Considering that any scientific study should be based on raw data, and that data storage space should no longer be a challenge, journals, in principle, should try to have their authors publicize raw data in a public database or journal site upon the publication of the paper to increase reproducibility of the published results and to increase public trust in science.
topic Raw data
Data fabrication
Open data
Open science
Misconduct
Reproducibility
url http://link.springer.com/article/10.1186/s13041-020-0552-2
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