GSoC 2021 project idea 15.1: The Turing Way: A how-to guide to data science

The Turing Way is an open-source, community-led and collaboratively developed “book project” on making data research accessible for a wider research community (https://the-turing-way.netlify.com). We bring together individuals from diverse fields and expertise to develop practices and learning resources that can make data research accessible and easy to understand. Our community members are researchers, engineers, data librarians, industry professionals, and experts in various domains, at all levels of seniority, from all around the world. They collaborate in the project to develop chapters by compiling best practices, tools and recommendations used by the researchers and data science communities worldwide.

Technical details

All questions, comments, recommendations and discussions are facilitated through an online GitHub repository (GitHub - alan-turing-institute/the-turing-way: Host repository for The Turing Way: a how to guide for reproducible data science). The online book with multiple guides is hosted as a Jupyter Book (https://github.com/jupyter/jupyter-book/) at https://the-turing-way.netlify.com. Jupyter Book formats markdown files and Jupyter notebooks as static HTML making them easy to read. When a notebook is included in the book, the static page includes a link to an interactive version of the notebook via Binder (https://mybinder.readthedocs.io). Additional styling of the front end is possible by providing a CSS file that handles it across the entire book.

GSoC project plan

Since the project’s launch in 2019, about 250 contributors have so far co-authored more than 140 subchapters and community documents on reproducible research, communication, collaboration, project design and ethics. As the number of chapters continues to increase, it is important for us to offer appropriate ways for our readers to discover relevant and desired content in the book based on their topics of interest and skill levels. A GSoC contributor will help us in developing such a feature in the project that provides an enhanced filtering or search functionality in the book. Based on their interest and availability, they will have the possibility to contribute to the development of Python scripts and GitHub actions to enhance the project workflow, chapter development, community engagement and the overall interactivity in the book. They will be provided with appropriate guidance and the opportunity to work in a positive working environment. They will be fairly acknowledged for their contributions to the project.

Expected outcome

  1. An enhanced version of The Turing Way’s online book by providing an advanced filtering or search feature that will allow our readers to navigate through the book and find the information they are looking for.
  2. Upstream contribution of newly developed features to the Jupyter Book project will be a plus and supported by the mentors.

Required skills

  1. Python programming skills (intermediate to advanced)
  2. Basic web-development skill required to work with Jupyter Book
  3. Experience working in distributed communities, using git and GitHub

Optional skills

  • Interactive visualisation of small datasets
  • Experience collaborating on data science or quantitative research projects at any level
  • JavaScript skills (for front end development)

Possible mentors

Tags: TuringWay, handbook, Javascript, Python, Jupyter

Hello, my name is Kush Kothari, I’m a web developer who is experienced in React (JS) in the frontend and Node with Express in the backend. I’m also fluent in Python and have worked on projects in Flask for web development. I see this project as an excellent match for me as apart for my skills matching the ones required for this project, I see this as a nice opportunity to further explore data science, a field that I’ve already started exploring independently.

Hence, I’m super excited about this project and wish to start contributing to it as soon as possible. Could someone give a brief guide to what things/issues I can start working on?

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Hi Kush, and welcome! I’m going to tag @martinagvilas and ping the other two mentors. Ping me or @arnab1896 if you don’t get a reply in a couple of days. /Malin, org admin

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Thank you for the quick response, I did get in touch with the lead mentor.

Hi @martinagvilas, @arnab1896 and @malin
I am Daniela Cialfi, a cognitive-behavioural economist, a postdoctoral researcher at the University of CHIETI-PESCARA (ITALY) and former visiting postdoc at Simons Institute for the Theory of the Computing (UC Berkeley).

Since my postdoctoral research project, I am very interested in this topics. I’m fluent in Python and Javascript (also I have experience in collaborating on data science or quantitative research projects at any level and experience in the interactive visualisation of small datasets) . I see this project as an excellent match for me as apart for my skills matching the ones required for this project. I see this as a nice opportunity to further explore data science, a field that I’ve already started exploring independently.

Hence, I’m super excited about this project and wish to start contributing to it as soon as possible. Could someone give a brief guide to what things/issues I can start working on?

Daniela

Hi @kkothari2001 and @Athene-ai! We are very excited to read you are interested in the project.

We are welcoming GSoC candidates to connect with us and explore their ideas and plans to work on The Turing Way online book in this GitHub issue.

There you will find all the information you need to get you started. You can also connect with us via slack using this link. We have specific channels to work on these topics.

Looking forward to hearing from you :rocket:

1 Like

It’s great @martinagvilas !

Daniela

Hi,

I am Wang Jiarui and interested in this project. But the slack link seems expired. Do you mind providing the invitation link again? Or tell me the channel name so that I can join you.

Thanks!

Jiarui

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