IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1007128.html
   My bibliography  Save this article

Open collaborative writing with Manubot

Author

Listed:
  • Daniel S Himmelstein
  • Vincent Rubinetti
  • David R Slochower
  • Dongbo Hu
  • Venkat S Malladi
  • Casey S Greene
  • Anthony Gitter

Abstract

Open, collaborative research is a powerful paradigm that can immensely strengthen the scientific process by integrating broad and diverse expertise. However, traditional research and multi-author writing processes break down at scale. We present new software named Manubot, available at https://manubot.org, to address the challenges of open scholarly writing. Manubot adopts the contribution workflow used by many large-scale open source software projects to enable collaborative authoring of scholarly manuscripts. With Manubot, manuscripts are written in Markdown and stored in a Git repository to precisely track changes over time. By hosting manuscript repositories publicly, such as on GitHub, multiple authors can simultaneously propose and review changes. A cloud service automatically evaluates proposed changes to catch errors. Publication with Manubot is continuous: When a manuscript’s source changes, the rendered outputs are rebuilt and republished to a web page. Manubot automates bibliographic tasks by implementing citation by identifier, where users cite persistent identifiers (e.g. DOIs, PubMed IDs, ISBNs, URLs), whose metadata is then retrieved and converted to a user-specified style. Manubot modernizes publishing to align with the ideals of open science by making it transparent, reproducible, immediate, versioned, collaborative, and free of charge.Author summary: Traditionally, scholarly manuscripts have been written in private by a predefined team of collaborators. But now the internet enables realtime open science, where project communication occurs online in a public venue and anyone is able to contribute. Dispersed teams of online contributors require new tools to jointly prepare manuscripts. Existing tools fail to scale beyond tens of authors and struggle to support iterative refinement of proposed changes. Therefore, we created a system called Manubot for writing manuscripts based on collaborative version control. Manubot adopts the workflow from open source software development, which has enabled hundreds of contributors to simultaneously develop complex codebases such as Python and Linux, and applies it to open collaborative writing. Manubot also addresses other shortcomings of current publishing tools. Specifically, all changes to a manuscript are tracked, enabling transparency and better attribution of credit. Manubot automates many tasks, including creating the bibliography and deploying the manuscript as a webpage. Manubot webpages preserve old versions and provide a simple yet interactive interface for reading. As such, Manubot is a suitable foundation for next-generation preprints. Manuscript readers have ample opportunity to not only provide public peer review but also to contribute improvements, before and after journal publication.

Suggested Citation

  • Daniel S Himmelstein & Vincent Rubinetti & David R Slochower & Dongbo Hu & Venkat S Malladi & Casey S Greene & Anthony Gitter, 2019. "Open collaborative writing with Manubot," PLOS Computational Biology, Public Library of Science, vol. 15(6), pages 1-21, June.
  • Handle: RePEc:plo:pcbi00:1007128
    DOI: 10.1371/journal.pcbi.1007128
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007128
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1007128&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1007128?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jeffrey M. Perkel, 2018. "Data visualization tools drive interactivity and reproducibility in online publishing," Nature, Nature, vol. 554(7690), pages 133-134, February.
    2. Chris Woolston, 2015. "Fruit-fly paper has 1,000 authors," Nature, Nature, vol. 521(7552), pages 263-263, May.
    3. Darrel C. Ince & Leslie Hatton & John Graham-Cumming, 2012. "The case for open computer programs," Nature, Nature, vol. 482(7386), pages 485-488, February.
    4. Simon Oxenham, 2016. "Legal confusion threatens to slow data science," Nature, Nature, vol. 536(7614), pages 16-17, August.
    5. Douglas Heaven, 2019. "Bitcoin for the biological literature," Nature, Nature, vol. 566(7742), pages 141-142, February.
    6. Andrew Silver, 2017. "Collaborative software development made easy," Nature, Nature, vol. 550(7674), pages 143-144, October.
    7. Ewen Callaway & Davide Castelvecchi & David Cyranoski & Elizabeth Gibney & Heidi Ledford & Jane J. Lee & Lauren Morello & Nicky Phillips & Quirin Schiermeier & Jeff Tollefson & Richard Van Noorden & A, 2017. "2017 in news: The science events that shaped the year," Nature, Nature, vol. 552(7685), pages 304-307, December.
    8. Jeffrey M. Perkel, 2014. "Scientific writing: the online cooperative," Nature, Nature, vol. 514(7520), pages 127-128, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christian Heise & Joshua M. Pearce, 2020. "From Open Access to Open Science: The Path From Scientific Reality to Open Scientific Communication," SAGE Open, , vol. 10(2), pages 21582440209, May.
    2. Hunter, Kevin & Sreepathi, Sarat & DeCarolis, Joseph F., 2013. "Modeling for insight using Tools for Energy Model Optimization and Analysis (Temoa)," Energy Economics, Elsevier, vol. 40(C), pages 339-349.
    3. Kushal Kolar & Daniel Dondorp & Jordi Cornelis Zwiggelaar & Jørgen Høyer & Marios Chatzigeorgiou, 2021. "Mesmerize is a dynamically adaptable user-friendly analysis platform for 2D and 3D calcium imaging data," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    4. Colliard, Jean-Edouard & Hurlin, Christophe & Pérignon, Christophe, 2019. "Reproducibility Certification in Economics Research," HEC Research Papers Series 1345, HEC Paris.
    5. Stefan Pauliuk & Niko Heeren, 2020. "ODYM—An open software framework for studying dynamic material systems: Principles, implementation, and data structures," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 446-458, June.
    6. Anne E Thessen & Paul Bogdan & David J Patterson & Theresa M Casey & César Hinojo-Hinojo & Orlando de Lange & Melissa A Haendel, 2021. "From Reductionism to Reintegration: Solving society’s most pressing problems requires building bridges between data types across the life sciences," PLOS Biology, Public Library of Science, vol. 19(3), pages 1-12, March.
    7. Alsudais, Abdulkareem, 2021. "In-code citation practices in open research software libraries," Journal of Informetrics, Elsevier, vol. 15(2).
    8. Fabio Pesari & Giovanni Lagioia & Annarita Paiano, 2023. "Client‐side energy and GHGs assessment of advertising and tracking in the news websites," Journal of Industrial Ecology, Yale University, vol. 27(2), pages 548-561, April.
    9. Marc-Oliver Gewaltig & Robert Cannon, 2014. "Current Practice in Software Development for Computational Neuroscience and How to Improve It," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-9, January.
    10. Teresa Riso & Carla Morrone, 2023. "To Align Technological Advancement and Ethical Conduct: An Analysis of the Relationship between Digital Technologies and Sustainable Decision-Making Processes," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    11. Whan Shin, 2022. "Evenly Is Even Better? Digital Competitiveness and the Quality of Medical Research," Sustainability, MDPI, vol. 14(17), pages 1-16, September.
    12. Whan Shin & Byungchul Choi, 2022. "Digital Competency, Innovative Medical Research, and Institutional Environment: A Global Context," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    13. Niccolo Pescetelli, 2021. "A Brief Taxonomy of Hybrid Intelligence," Forecasting, MDPI, vol. 3(3), pages 1-11, September.
    14. Paul J McMurdie & Susan Holmes, 2013. "phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-11, April.
    15. DeCarolis, Joseph F. & Hunter, Kevin & Sreepathi, Sarat, 2012. "The case for repeatable analysis with energy economy optimization models," Energy Economics, Elsevier, vol. 34(6), pages 1845-1853.
    16. J. Israel Martínez-López & Samantha Barrón-González & Alejandro Martínez López, 2019. "Which Are the Tools Available for Scholars? A Review of Assisting Software for Authors during Peer Reviewing Process," Publications, MDPI, vol. 7(3), pages 1-28, September.
    17. Li, Kai & Yan, Erjia, 2018. "Co-mention network of R packages: Scientific impact and clustering structure," Journal of Informetrics, Elsevier, vol. 12(1), pages 87-100.
    18. David Lovell & Vera Pawlowsky-Glahn & Juan José Egozcue & Samuel Marguerat & Jürg Bähler, 2015. "Proportionality: A Valid Alternative to Correlation for Relative Data," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-12, March.
    19. Bistline, John E.T. & Merrick, James H., 2020. "Parameterizing open-source energy models: Statistical learning to estimate unknown power plant attributes," Applied Energy, Elsevier, vol. 269(C).
    20. van der Linden, Aart & de Olde, Evelien M. & Mostert, Pim F. & de Boer, Imke J.M., 2020. "A review of European models to assess the sustainability performance of livestock production systems," Agricultural Systems, Elsevier, vol. 182(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1007128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.