Welcome — The Turing Way

“The Turing Way is an open source community-driven guide to reproducible, ethical, inclusive and collaborative data science.

Our goal is to provide all the information that data scientists in academia, industry, government and in the third sector need at the start of their projects to ensure that they are easy to reproduce and reuse at the end.

The book started as a guide for reproducibility, covering version control, testing, and continuous integration. But technical skills are just one aspect of making data science research “open for all”.

In February 2020, The Turing Way expanded to a series of books covering reproducible research, project design, communication, collaboration, and ethical research.”

A Community Handbook for Open Data Science

“The Turing Way started in December 2018 and has quickly evolved into a collaborative, inclusive and international endeavor with the aim of uncovering gold standards to ensure reproducible, ethical, inclusive and collaborative data science. How did this happen? I think two ingredients were central to The Turing Way‘s success: extraordinary community building and a clear enticing vision….

Anyone can contribute is a central theme. And not only that: anyone can bring ideas to the table. And folks are doing just that. At the time of writing this post 168 people have contributed. So on average the project has gained 9 new contributors every month since it’s initiation….”

Open Entomology: Tips and Tools for Better Reproducibility in Your Research

“Many tools are available to make our work more reproducible, and I outline several in more detail in my paper, “A Guide and Toolbox to Replicability and Open Science in Entomology,” published in May in the open-access Journal of Insect Science. The article is part of a special “Open Entomology” group of papers published in the journal. I cowrote it with my advisor, Brian Aukema, Ph.D., of the University of Minnesota because there does not seem to be much open science communication targeted at the entomology community.

Open science practices and tools exist to make it easier for other people to pick up our work and see how we did it, which has the side effect of being beneficial to us individually! There is a common adage uttered in many statistics courses that captures this sentiment: “Your most important collaborator is you 6 months from now, and past you doesn’t answer emails.” At the start of my graduate work, I can’t tell you how many times I had to spend a few hours reacquainting myself with old data or analyses. If I had been aware of the open science movement and all the tools and practices available to me, I could have saved myself many headaches. Below are a few ways you can save yourself a headache, while simultaneously making your work more open and reproducible….

 

Recommendations to enhance rigor and reproducibility in biomedical research | GigaScience | Oxford Academic

Abstract:  Biomedical research depends increasingly on computational tools, but mechanisms ensuring open data, open software, and reproducibility are variably enforced by academic institutions, funders, and publishers. Publications may present software for which source code or documentation are or become unavailable; this compromises the role of peer review in evaluating technical strength and scientific contribution. Incomplete ancillary information for an academic software package may bias or limit subsequent work. We provide 8 recommendations to improve reproducibility, transparency, and rigor in computational biology—precisely the values that should be emphasized in life science curricula. Our recommendations for improving software availability, usability, and archival stability aim to foster a sustainable data science ecosystem in life science research.

 

When you are making plans to publish research, you need to plan for data sharing: Climacteric: Vol 0, No 0

Abstract:  Open data is another step on the pathway of strengthening medical research. Allowing access to data facilitates testing the reproducibility of research findings. It also allows for the testing of new hypotheses, the incorporation of individual level data into meta-analyses and the development of very large data sets in which to develop and test new algorithms. There are now many data repositories that researchers can use to share their protocols, syntax and data. There are strategies both for managing what other researchers do with publically available data and for rewarding researchers who share their data. There is a strong ethical argument for making data publically available and research participants are generally supportive of this approach.

 

When you are making plans to publish research, you need to plan for data sharing: Climacteric: Vol 0, No 0

Abstract:  Open data is another step on the pathway of strengthening medical research. Allowing access to data facilitates testing the reproducibility of research findings. It also allows for the testing of new hypotheses, the incorporation of individual level data into meta-analyses and the development of very large data sets in which to develop and test new algorithms. There are now many data repositories that researchers can use to share their protocols, syntax and data. There are strategies both for managing what other researchers do with publically available data and for rewarding researchers who share their data. There is a strong ethical argument for making data publically available and research participants are generally supportive of this approach.

 

Connecting Data, Tools and People Across Europe: ELIXIR’s Response to the COVID-19 Pandemic – PubMed

Abstract:  ELIXIR, the European research infrastructure for life science data, provides open access to data, tools and workflows in the response to the COVID-19 pandemic. ELIXIR’s 23 nodes have reacted swiftly to support researchers in their combined efforts against the pandemic setting out three joint priorities: 1. Connecting national COVID-19 data platforms to create federated European COVID-19 Data Spaces; 2. Fostering good data management to make COVID-19 data open, FAIR and reusable over the long term; 3. Providing open tools, workflows and computational resources to drive reproducible and collaborative science. ELIXIR’s strategy is based on the support given by our national nodes – collectively spanning over 200 institutes – to research projects and on partnering with community initiatives to drive development and adoption of good data practice and community driven standards. ELIXIR Nodes provide support activities locally and internationally, from provisioning compute capabilities to helping collect viral sequence data from hospitals. Some Nodes have prioritised access to their national cloud and compute facilities for all COVID-19 research projects, while others have developed tools to search, access and share all data related to the pandemic in a national healthcare setting.

 

Guide and Toolbox to Replicability and Open Science in Entomology | Journal of Insect Science | Oxford Academic

Abstract:  The ability to replicate scientific experiments is a cornerstone of the scientific method. Sharing ideas, workflows, data, and protocols facilitates testing the generalizability of results, increases the speed that science progresses, and enhances quality control of published work. Fields of science such as medicine, the social sciences, and the physical sciences have embraced practices designed to increase replicability. Granting agencies, for example, may require data management plans and journals may require data and code availability statements along with the deposition of data and code in publicly available repositories. While many tools commonly used in replicable workflows such as distributed version control systems (e.g., ‘git’) or script programming languages for data cleaning and analysis may have a steep learning curve, their adoption can increase individual efficiency and facilitate collaborations both within entomology and across disciplines. The open science movement is developing within the discipline of entomology, but practitioners of these concepts or those desiring to work more collaboratively across disciplines may be unsure where or how to embrace these initiatives. This article is meant to introduce some of the tools entomologists can incorporate into their workflows to increase the replicability and openness of their work. We describe these tools and others, recommend additional resources for learning more about these tools, and discuss the benefits to both individuals and the scientific community and potential drawbacks associated with implementing a replicable workflow.

 

Registered Reports: Genre Evolution and the Research Article – Ashley Rose Mehlenbacher, 2019

Abstract:  The research article is a staple genre in the economy of scientific research, and although research articles have received considerable treatment in genre scholarship, little attention has been given to the important development of Registered Reports. Registered Reports are an emerging, hybrid genre that proceeds through a two-stage model of peer review. This article charts the emergence of Registered Reports and explores how this new form intervenes in the evolution of the research article genre by replacing the central topoi of novelty with methodological rigor. Specifically, I investigate this discursive and publishing phenomenon by describing current conversations about challenges in replicating research studies, the rhetorical exigence those conversations create, and how Registered Reports respond to this exigence. Then, to better understand this emerging form, I present an empirical study of the genre itself by closely examining four articles published under the Registered Report model from the journal Royal Society Open Science and then investigating the genre hybridity by examining 32 protocols (Stage 1 Registered Reports) and 77 completed (Stage 2 Registered Reports) from a range of journals in the life and psychological sciences. Findings from this study suggest Registered Reports mark a notable intervention in the research article genre for life and psychological sciences, centering the reporting of science in serious methodological debates.