1,721,107 research outputs found
The Turing Way: A handbook for reproducible, ethical and collaborative research
No full textThe Turing Way is an open source community-driven guide to reproducible, ethical, inclusive and collaborative data science. The Turing Way book is collaboratively developed by its diverse community of researchers, learners, educators, and other stakeholders.
The Turing Way project is openly developed and any and all questions, comments and recommendations are welcome at our github repository: https://github.com/alan-turing-institute/the-turing-way. In 2020, the project underwent a major overhaul categorising chapters into 5 guides on reproducible research, project design, collaboration, communication and ethical research. Additionally, we added a community handbook to document all the practices designed and implemented towards the development of the project and community.
This release in 2021 includes additional chapters developed by our contributors across five guides and the community handbook. In addition, all the project documents from the project are provided as they appear on The Turing Way GitHub repository including the Zenodo metadata: https://github.com/alan-turing-institute/the-turing-way.
Release log
v1.0.1: Zenodo metadata information and additional chapters
v1.0.0: Five guide expansion of The Turing Way with a community handbook
v0.0.4: Continuous integration chapter merged to master.
v0.0.3: Reproducible environments chapter merged to master.
v0.0.2: Version control chapter merged to master.
v0.0.1: Reproducibility chapter merged to master.
Full Changelog: https://github.com/alan-turing-institute/the-turing-way/compare/v1.0.0...v1.0.1 (Previous release: https://github.com/alan-turing-institute/the-turing-way/compare/v0.0.3...v1.0.0)This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
Illustrations from the Turing Way book dashes
No full textIllustrations created by Scriberia as part of the Turing Way book dashes in Manchester on 17 May 2019 and London on 28 May 2019. They depict a variety of content of the handbook as well as book sprint activities and the Turing Way community in general. All illustrations are provided as .jpg and .svg files.
More information on the book dashes can be found at https://github.com/alan-turing-institute/the-turing-way/tree/master/workshops/book-dash
When using any of the images, please credit it with
"This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence."
We encourage the use and re-use of these images as much as possible. This includes remixing the images, for example changing the colours or merging them together with additional (openly licensed) images. If you create something that others may benefit from, we encourage you to get in touch with the Turing Way team who can update this repository with the images you create.This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
Illustrations from The Turing Way: Shared under CC-BY 4.0 for reuse
No full textIllustrations created by Scriberia as part of the Turing Way book dashes and illustration sprints in 2019 (two events in person), 2020 (one event in-person and one online), 2021 (two online), 2022 (Turing-Crick partnership project hybrid sprint, one Book Dash online). They depict a variety of content of the five guides in The Turing Way as well as data science and the community activities of The Turing Way in general. More information on the book dashes can be found at https://the-turing-way.netlify.app/community-handbook/bookdash.html.
When using any of the images, please include the following attribution with the specific DOI as listed on the particular Zenodo page:
This illustration is created by Scriberia with The Turing Way community. Used under a CC-BY 4.0 licence. DOI: 10.5281/zenodo.3332807
You can cite all versions by using the DOI 10.5281/zenodo.3332807. This DOI represents all versions, and will always resolve to the latest one.
Please note that these images are shared here in the original format and size. We use smaller files in The Turing Way guides that you can find in our GitHub repository: https://github.com/alan-turing-institute/the-turing-way/tree/main/book/website/figures.
Individual illustrations are provided as .jpg files and zipped archives of the files are given in .jpg and .pdf (named starting with zz- to keep them at the bottom of the list).
The most recent release have been made in June 2022 with the following zipped archives:
zz-Latest-TheTuringWay-Scriberia-2022-Jun-allJPG-English-text.zip <-- Latest JPG release
zz-Latest-TheTuringWay-Scriberia-2022-Jun-allJPG-without-text.zip <-- Latest JPG release without any text (for reuse purpose)
zz-Latest-TheTuringWay-Scriberia-2022-Jun-allPDF-English-text.zip <-- Latest PDF release
zz-Latest-TheTuringWay-Scriberia-2022-Jun-allPDF-without-text.zip <-- Latest PDF release without any text (for reuse purpose)
Images from the previous Book Dash from May 2019 - November 2021 are shared in the following zipped archives:
zz-TheTuringWay-previous-Scriberia-2022-Jun-AllJPG-English-text.zip
zz-TheTuringWay-previous-Scriberia-2022-Jun-AllPDF-English-text.zip
zz-TheTuringWay-previous-Scriberia-2022-Jun-allJPGs-without-text.zip
zz-TheTuringWay-previous-Scriberia-2022-Jun-allPDFs-without-text.zip
From the previous Book Dashes, we have also released SVG files when available:
zz-TheTuringWay-Scriberia-2019-20-SVG-where-available.zip.
Translating and editing for reusing Images: Zipped archives's names ending with '-without-text.zip' are provided for the latest release that can be translated into languages that you would like to use them in. We encourage the use and re-use of these images as much as possible. This includes remixing the images, for example changing the colours, translating text or merging them together with additional (openly licensed) images. If you create something that others may benefit from, we encourage you to contribute your image back to The Turing Way. Please get in touch with the team members by emailing [email protected] who can help you update this repository with the images you create.
If you'd like to change the colours of the image to align with other elements of your presentation, Turing Way community member Alex Chan has written a guide for changing the dominant colour in an image which we hope is helpful.This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
The Turing Way Book Dash: Onboarding Call
No full text<p><i>The Turing Way</i> <a href="https://the-turing-way.netlify.app/community-handbook/bookdash">Book Dash events</a> are a less intense version of <a href="https://en.wikipedia.org/wiki/Book_sprint">Book Sprints</a>, where participants collaboratively work on <i>The Turing Way</i> book synchronously to develop new chapters and review/edit existing ones to make them more accessible, comprehensive and up-to-date. They also contribute to enhancing the project by improving the ways we work in the community and take the lead on accomplishing different tasks or sub-projects.</p><p>This material is being used for the November 2023 Book Dash as onboarding materials for participants.</p>
The Turing Way: A Handbook for Reproducible Data Science
No full textPoster presentation of the Turing Way at the 2019 Open Science Fair.
Abstract:
The Turing Way is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible data science is "too easy not to do" (https://the-turing-way.netlify.com). It includes training material on topics such as version control and analysis testing, and will build upon Alan Turing Institute case studies and workshops. The project also demonstrates open and transparent project management and communication with future users, as it is openly developed at our GitHub repository: https://github.com/alan-turing-institute/the-turing-way. All resources associated with workshops we have delivered, as well as how to organise a Book Dash (a one-day book sprint), are also openly available.
Reproducible research is necessary to ensure that scientific work can be trusted. Funders and publishers are beginning to require that publications include access to the underlying data and the analysis code. The goal is to ensure that all results can be independently verified and built upon in future work, which is sometimes easier said than done. Sharing these research outputs means understanding data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers and data scientists.
This poster will present an overview of the handbook so far and show Open Science Fair participants how they can contribute their knowledge to make it even better going forwards or how to open up their own projects to a wider contributor community. This poster relates to the overall theme of the conference, as the Turing Way provides the tools to improve research habits in a self-contained handbook. It will also ensure that PhD students, postdocs, PIs and funding teams know which parts of the "responsibility of reproducibility" they can affect, and what they should do to nudge research and data science to being more efficient, effective and understandable
The Turing Way: A Handbook for Reproducible Data Science
No full text<p>Reproducible research is necessary to ensure that scientific work can be trusted. Funders and publishers are beginning to require that publications include access to the underlying data and the analysis code. The goal is to ensure that all results can be independently verified and built upon in future work. This is sometimes easier said than done.</p>
<p>Sharing these research outputs means understanding data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers and data scientists.<em> </em><em>The Turing Way</em> is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible data science is "too easy not to do".</p>
<p>It will include training material on version control, analysis testing, and open and transparent communication with future users, and build on Turing Institute case studies and workshops.</p>
<p>This project is openly developed and any and all questions, comments and recommendations are welcome at our github repository: <a href="https://github.com/alan-turing-institute/the-turing-way">https://github.com/alan-turing-institute/the-turing-way</a>.</p>
<p><strong>Release log</strong></p>
<ul>
<li><strong>v0.0.4:</strong> Continuous integration chapter merged to master.</li>
<li><strong>v0.0.3:</strong> Reproducible environments chapter merged to master.</li>
<li><strong>v0.0.2:</strong> Version control chapter merged to master.</li>
<li><strong>v0.0.1: </strong>Reproducibility chapter merged to master.</li>
</ul>This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
The Turing Way: A Handbook for Reproducible Data Science
No full text<p>Reproducible research is necessary to ensure that scientific work can be trusted. Funders and publishers are beginning to require that publications include access to the underlying data and the analysis code. The goal is to ensure that all results can be independently verified and built upon in future work. This is sometimes easier said than done.</p>
<p>Sharing these research outputs means understanding data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers and data scientists.<em> </em><em>The Turing Way</em> is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible data science is "too easy not to do".</p>
<p>It will include training material on version control, analysis testing, and open and transparent communication with future users, and build on Turing Institute case studies and workshops.</p>
<p>This project is openly developed and any and all questions, comments and recommendations are welcome at our github repository: https://github.com/alan-turing-institute/the-turing-way.</p>
<p><strong>Release log</strong></p>
<ul>
<li><strong>v0.0.2:</strong> Version control chapter merged to master.</li>
<li><strong>v0.0.1: </strong>Reproducibility chapter merged to master.</li>
</ul>This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
The Turing Way: A Handbook for Reproducible Data Science
No full text<p>Reproducible research is necessary to ensure that scientific work can be trusted. Funders and publishers are beginning to require that publications include access to the underlying data and the analysis code. The goal is to ensure that all results can be independently verified and built upon in future work. This is sometimes easier said than done.</p>
<p>Sharing these research outputs means understanding data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers and data scientists.<em> </em><em>The Turing Way</em> is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible data science is "too easy not to do".</p>
<p>It will include training material on version control, analysis testing, and open and transparent communication with future users, and build on Turing Institute case studies and workshops.</p>
<p>This project is openly developed and any and all questions, comments and recommendations are welcome at our github repository: https://github.com/alan-turing-institute/the-turing-way.</p>
<p><strong>Release log</strong></p>
<p><strong>v0.0.3:</strong> Reproducible environments chapter merged to master.</p>
<p><strong>v0.0.2:</strong> Version control chapter merged to master.</p>
<p><strong>v0.0.1: </strong>Reproducibility chapter merged to master.</p>
<p> </p>This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
The Turing Way: A Handbook for Reproducible Data Science
No full text<p>Reproducible research is necessary to ensure that scientific work can be trusted. Funders and publishers are beginning to require that publications include access to the underlying data and the analysis code. The goal is to ensure that all results can be independently verified and built upon in future work. This is sometimes easier said than done.</p>
<p>Sharing these research outputs means understanding data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers and data scientists.<em> </em><em>The Turing Way</em> is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible data science is "too easy not to do".</p>
<p>It will include training material on version control, analysis testing, and open and transparent communication with future users, and build on Turing Institute case studies and workshops.</p>
<p>This project is openly developed and any and all questions, comments and recommendations are welcome at our github repository: https://github.com/alan-turing-institute/the-turing-way.</p>
<p><strong>Release log</strong></p>
<ul>
<li><strong>v0.0.1: </strong>Reproducibility chapter merged to master.</li>
</ul>This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1
The Turing Way Book Dash - November 2020
No full textThe introduction talk presented at The Turing Way Book Dash, 09-13 November 2020, online
- …
