---
title: "Contributor Pathways"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

(pd-persona-contributors)=
# Contributor Pathways

In this subchapter, we have developed personas in order to understand how new members might experience their first interactions with an online project and what "pathways" they are likely to take to get further involved as contributors.

The interactions with the project followed by the sustained engagements in a project can be understood in the following different phases of community membership:

1. Discovery - How they first hear about the project or group.
2. First Contact - How they first engage with the project or group, their initial interaction.
3. Participation - How they first participate or contribute.
4. Sustained Participation - How their contribution or involvement can continue.
5. Networked Participation - How they may network within the community.
6. Leadership - How they may take on some additional responsibility on the project, or begin to lead.

The examples provided below include personas for _The Turing Way_ contributors and users based on their initial engagements with the project as a reader, learner, resource developer, reviewer and maintainer.
These personas are created based on GitHub skills and willingness of the community members to contribute to the project.

For each persona, we highlight how their involvement with _The Turing Way_ can improve and enrich the project and community.
This document is meant to suggest ways you might interact with, learn from, and contribute to _The Turing Way_.
We hope that one of these personas resonates with you and motivates you to get involved!

## Contributor personas

1. Sam, someone who has no GitHub experience
2. Alia, someone who has a lot of GitHub experience
3. Amal, someone who knows they want to contribute and does
4. Noor, someone who doesn't know they want to contribute, but does
5. Robin, someone who can only contribute outside of their normal working hours

### 1. Sam, a PhD student with no GitHub experience

Sam is a PhD student in biology at University College London.
They are learning how to code in Python, but have not yet had any training in version control or GitHub.
They're interested in learning how to use open notebooks such as Jupyter to do their analysis so that they can easily share their work for critique with their very busy supervisor.

1. **Discovery** - Sam hears about _The Turing Way_ Book Dash events through an email from the department's Open Science Champion.
2. **First Contact** - Sam checks out the GitHub repository to learn more about the project and see what skills are needed that they may be able to contribute.
3. **Participation** - They attend the London Book Dash, accepted for their enthusiasm to learn how to make their PhD research reproducible. They participate in the discussions, read existing chapters, and scroll through issues to see where they can contribute.
4. **Sustained Participation** - After gaining experience with GitHub through submitting pull requests and issues during the Book Dash, Sam is empowered to continue contributing to the online discussion and suggesting topics for the book, as well as editing and reviewing existing chapters by applying them to his research.
5. **Networked Participation** - They encourage some of their fellow PhD students to read _The Turing Way_ and start using GitHub.
6. **Leadership** - Sam submits one of their research projects as a case study for _The Turing Way_.

###  2. Alia, a researcher with Git/GitHub experience and book topic expertise

Alia is a postdoc in Morocco who programs in R.
They are passionate about open data and using data for good, but also understand it can be more complex than that.
They attend data science meetups in the city but are interested in finding a community working towards improving how research is conducted.
They have experience with GitHub and contributing to open projects.

1. **Discovery** - Alia first hears about _The Turing Way_ via X (formerly Twitter) ([#TuringWay](https://twitter.com/search?q=%23TuringWay&src=typed_query)).
2. **First Contact** - They land on the project's README and look for the contributing guidelines to see where their skills can be applied.
3. **Participation** - They find an issue asking for help on writing the Credit for Reproducible Research chapter and add a few paragraphs on how to properly cite research software.
4. **Sustained Participation** - After constructive feedback and collaboration with _The Turing Way_ team, Alia follows the community on social media and attend the online Collaboration Cafe.
5. **Networked Participation** - They invite other friends and colleagues from the Rstats community to get involved, who have expertise on some of the book topics.
6. **Leadership** - Alia volunteers to write the chapter on "Scoping a data project for RSEs" that they found requested in the [Book Skeleton](https://github.com/the-turing-way/the-turing-way/blob/main/book_skeleton.md).

### 3. Amal, a PhD supervisor who is an expert in an aspect of reproducible research

Amal is a PhD supervisor who is an expert in running risk assessments for projects using reproducible research.
They are always looking for opportunities to share their expertise, particularly with students, as they think the consistent application of best practice is important.
They are very keen to collaborate with people and to volunteer their time for collaboration projects.
They like seeing their work make an impact and are keen to know about the eventual result of their collaborations.

1. **Discovery** - Amal finds out about _The Turing Way_ book from the X feed of experts in reproducible research who they follow.
2. **First Contact** - Amal navigates to the GitHub repository and reads the content there over a couple of days. While reading, they make notes on areas they could add to from their research.
3. **Participation** - They compile their work into a chapter format and submit it to the repo.
4. **Sustained Participation** - Amal checks back frequently to look at feedback on their chapter and respond to it. In their spare time, they make suggestions and edits on other chapters.
5. **Networked Participation** - Amal directs students to their chapter in the _The Turing Way_ when they ask about risk assessments in reproducible research, and begins to direct students to other chapters as part of their teaching.
6. **Leadership** - Amal promotes _The Turing Way_  at their institution, suggesting to other academics that they get involved with its creation and adopt it as best practice.

###  4. Noor, a PhD student who is trying to finish their dissertation

Noor is a final-year PhD student who has their dissertation deadline coming up.
They are feeling the pressure of needing to write up the results of their research but finding it easy to procrastinate.
They are confident that their research has taught them some particular considerations for reproducible environments, but they are slightly intimidated by the expertise of other people in their field, and they are considering their future after their PhD.

1. **Discovery** - Noor comes across _The Turing Way_ when they're surfing X while trying to write up their research.
2. **First Contact** - They read the chapter that's relevant to their research and then continue working on their dissertation.
3. **Participation** - Later, Noor returns to _The Turing Way_ and makes some suggestions and edits to that chapter.
4. **Sustained Participation** - They return to the repo periodically to read feedback on their commits and make additional comments, restricted to the one chapter they feel they know about.
5. **Networked Participation** - Noor tweets a link to _The Turing Way_ during a conversation about reproducible research and retweets a response from another expert which leads to a longer conversation.
6. **Leadership** - After submitting their PhD, and unsure what they want to do next, Noor volunteers to coordinate further research into the chapter by reaching out to experts in the space.

### 5. Robin, a Data Scientist in industry

Robin is a Data Scientist working at the Co-operative Bank in Lahore.
They have lots of meetings throughout the workday, so are looking for ways to make their workflow more efficient and sustainable.
They attend online webinars and watch videos on Youtube in their spare time to learn more about reproducibility and collaboration.

1. **Discovery** - Robin attended the [Women in Data Science webinar hosted by IBM Code Bristol](https://www.bigmarker.com/ibm-developer-uki/Women-in-Data-Science-IBM-Code-Bristol?bmid=2581093331c4), where they heard Malvika Sharan's talk *The Turing Way: A community built on a culture of collaboration*.
2. **First Contact** - Robin was so inspired by the talk that they followed the [Turing Way on X](https://twitter.com/turingway) and starred the [GitHub repository](https://github.com/the-turing-way/the-turing-way), to come back and learn more when they had time.
3. **Participation** - When they find time at the weekend, Robin reads the chapter on Continuous Integration to pick up some tips and tricks - however they see that there isn't yet information on using GitHub Actions. Robyn would like to know more about this topic, so reads tutorials on how to incorporate them into their workflow and opens a [WIP] pull request to add a subsection to the chapter based on what they learn.
4. **Sustained Participation** - As their contributions are made outside of working hours, the process of learning, writing the subsection and iterating on feedback from _The Turing Way_ team moves at a [relatively] slower pace than someone who can contribute during working hours. Robin appreciates the assistance and communication from the team through the pull request conversation.
5. **Networked Participation** - Robin mentions _The Turing Way_ and what she learned about using GitHub Actions during one of her team's stand-ups, promoting their use to her colleagues.
6. **Leadership** - Robin gives a lightning talk at a London tech event about GitHub Actions and her contributions to _The Turing Way_. She praises the inclusiveness of the project and invites more industry experts to check out the resource and open issues on topics that they can contribute to or would like to learn more about.

If the personas described here do not reflect your experience, and if getting involved with The Turing Way or using its resource are challenging in any way for you, please open an issue or get in contact on our [Slack channel](https://theturingway.slack.com/) letting us know what your persona or pathway might look like!
This process will not only help the _The Turing Way_ team members in getting you onboarded, but we will be able to improve the community documents including the [README](https://github.com/the-turing-way/the-turing-way/blob/main/README.md) and [Contributing Guidelines](#ch-contributing) to make it more relatable and usable for the wider community.

## Reference:

- This file has remixed and reused material from the [Open Leadership Framework GitHub repository](https://github.com/mozilla/open-leadership-framework/blob/master/personas.md) shared at the [Mozilla Open Leadership training](https://mozilla.github.io/open-leadership-training-series/articles/building-communities-of-contributors/bring-on-contributors-using-personas-and-pathways/), License: [CC-BY-SA](https://creativecommons.org/licenses/by/4.0/).
