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      Knowledge and Attitudes Among Life Scientists Toward Reproducibility Within Journal Articles: A Research Survey

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          Abstract

          We constructed a survey to understand how authors and scientists view the issues around reproducibility, focusing on interactive elements such as interactive figures embedded within online publications, as a solution for enabling the reproducibility of experiments. We report the views of 251 researchers, comprising authors who have published in eLIFE Sciences, and those who work at the Norwich Biosciences Institutes (NBI). The survey also outlines to what extent researchers are occupied with reproducing experiments themselves. Currently, there is an increasing range of tools that attempt to address the production of reproducible research by making code, data, and analyses available to the community for reuse. We wanted to collect information about attitudes around the consumer end of the spectrum, where life scientists interact with research outputs to interpret scientific results. Static plots and figures within articles are a central part of this interpretation, and therefore we asked respondents to consider various features for an interactive figure within a research article that would allow them to better understand and reproduce a published analysis. The majority (91%) of respondents reported that when authors describe their research methodology (methods and analyses) in detail, published research can become more reproducible. The respondents believe that having interactive figures in published papers is a beneficial element to themselves, the papers they read as well as to their readers. Whilst interactive figures are one potential solution for consuming the results of research more effectively to enable reproducibility, we also review the equally pressing technical and cultural demands on researchers that need to be addressed to achieve greater success in reproducibility in the life sciences.

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          Most cited references117

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          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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            Standards for reporting qualitative research: a synthesis of recommendations.

            Standards for reporting exist for many types of quantitative research, but currently none exist for the broad spectrum of qualitative research. The purpose of the present study was to formulate and define standards for reporting qualitative research while preserving the requisite flexibility to accommodate various paradigms, approaches, and methods.
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              Is Open Access

              The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update

              Abstract Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.

                Author and article information

                Contributors
                Journal
                Front Res Metr Anal
                Front Res Metr Anal
                Front. Res. Metr. Anal.
                Frontiers in Research Metrics and Analytics
                Frontiers Media S.A.
                2504-0537
                29 June 2021
                2021
                : 6
                : 678554
                Affiliations
                [ 1 ]Earlham Institute, Norwich, United Kingdom
                [ 2 ]School of Biological Sciences, University of East Anglia, Norwich, United Kingdom
                Author notes

                Edited by: Hamid R. Jamali, Charles Sturt University, Australia

                Reviewed by: Tom Crick, Swansea University, United Kingdom

                Iman Tahamtan, The University of Tennessee, United States

                *Correspondence: Evanthia Kaimaklioti Samota, evanthia.samota@ 123456earlham.ac.uk

                This article was submitted to Scholarly Communication, a section of the journal Frontiers in Research Metrics and Analytics

                Article
                678554
                10.3389/frma.2021.678554
                8276979
                34268467
                ca9e2f40-43f8-415f-b52a-9efec05a1b44
                Copyright © 2021 Samota and Davey.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 March 2021
                : 18 May 2021
                Funding
                Funded by: Biotechnology and Biological Sciences Research Council 10.13039/501100000268
                Award ID: BB/M017176/1 BB/CCG1720/1 BBS/E/T/000PR9817 BBS/E/T/000PR9783
                Categories
                Research Metrics and Analytics
                Original Research

                reproducibility in life sciences,replication of experiments,reproducibility of computational experiments,interactive figures,reproducibility,reproducibility metrics,open science,reproducibility survey in life sciences

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