Ways of Working in Data Science Without Borders

Data Science Without Borders (DSWB) is an international initiative, funded by the Wellcome Trust and led by the African Population and Health Research Centre (APHRC).

This handbook provides ways and working to facilitate collaboration and co-development approaches in DSWB. Resources in this handbook have been centralised in collaboration with the members of our community through their contributions to the Open Science and Capacity Building Working Group meetings.

Project Overview¶

Details about the DSWB project and its consortia can be found on our website: https://dswb.africa/.

Without duplicating the resources available on our website, we provide an overview of DSWB below.

Vision: Making African Data Findable, Accessible, Interoperable, & Reusable.

Objectives: The three main objectives of this project are to: 1) strengthen data systems in Pathfinder countries, 2) develop a sustainable environment for collaborative and replicable AI/ML platforms, and 3) create a user-friendly (low- and no-code) platform for AI and Machine Learning (AI/ML) tools.

Mission: We are Committed to Strengthening Data Systems, Fostering Collaboration, & Building Capacity.

The impact of inequality in data availability and access is evident, particularly in resource-limited settings like many African nations. The DSWB project aims to foster a collaborative environment that empowers African nations to harness the full potential of AI/ML for improving health outcomes. This African institution-led initiative will leverage artificial intelligence and machine learning (AI/ML) to bridge existing gaps in data accessibility, infrastructure, and expertise.

Ways of Working in DSWB¶

In collaboration with our community members, we co-develop, centralise and build a shared understanding of our ways of working, aiming to engage all community members through inclusive, equitable, and thoughtful approaches.

With a goal to enable respectful collaboration, practices described across this handbook will enable our community members to engage in the co-development of the DSWB projects, share and utilise resources effectively, and contribute to the positive impact.

In all our work, we aim to apply open practices to ensure that all members have clarity, opportunities and pathways to lead initiatives and receive recognition in line with the project goals.

Who is this handbook for?¶

This handbook on ways pf working is for all members contributing to DSWB from across the Pathfinder Countries, Technical Partners and their networks. Find details about our partners under “who we are”.

Pathfinder Institutions¶

The Data Science Without Borders (DSWB) project is an initiative designed to address these challenges by supporting the development of advanced data science pipelines in three African countries:

• Armauer Hansen Research Institute (AHRI) in Ethiopia 🇪🇹
• Institute for Health Research, Epidemiological Surveillance (IRESSEF) in Senegal 🇸🇳
• Douala General Hospital (DGH) in Cameroon 🇨🇲

Technical Partners¶

Technical Partners in DSWB (listed below) provide technical support such as in tools or platform development, community engagement, identification of priority use cases, prototype development, data handling and provision of guidance for effective policy engagement.

• The London School of Hygiene & Tropical Medicine (LSHTM)
• Committee on Data of the International Science Council (CODATA)
• OSPO Now
• Makerere AI
• Africa CDC

Working Groups Operationalise Ways of Working¶

Working Groups within DSWB provide structured spaces for engagement and collaboration around shared data science interests, fostering Communities of Practice.

DSWB currently hosts the following working groups:

1. Open Science and Capacity Building Working Group
2. Platform Development and Data Harmonisation Working Group
3. Students Working Group

More information about each working group is available on our website under “What We Do”.

These Working Groups enable members to communicate their work, exchange ideas, discuss data and AI skills, identify collaboration opportunities, build shared resources, and embed open and collaborative approaches into their work.

Working Groups are key channels through which DSWB’s ways of working are disseminated and operationalised.

Contributing to this Handbook¶

All of the text in this guide is to help DSWB members engage with DSWB and each other’s work, ultimately contributing to the development of collaborative tools, practices and methods. DSWB members are encouraged to read, share, and contribute their insights to enhance this handbook.

Documentation for the Ways of Working is developed on our GitHub Organisation (aphrc-dswb) under the Open Science and Capacity Building Working Group repository: aphrc-dswb/dswb-open-science-capacity-wg.

Every thoughtful contribution, however large or small, will empower the DSWB community to develop standard practices, fostering a supportive culture. Please read contributing guideline and Code of Conduct to start contributing via our GitHub repository.

Collaboration with The Turing Way¶

We also connect, centralise and share knowledge from other community-driven resources. An important project is The Turing Way, a collaborator in our efforts to provide DSWB members with access to well-documented and maintained best practices, avoiding duplication within this handbook.

DSWB members actively collaborate with The Turing Way to curate and share relevant data science practices, which are referenced and recommended in various documents throughout this handbook. Furthermore, to directly address the DSWB community’s needs, our members contribute to The Turing Way by documenting and openly sharing practices and examples derived from our work.

Please follow the style guide and related processes described in The Turing Way Community Handbook to contribute to, maintain and improve resources within this book.

Read more about our collaboration with The Turing Way: The Turing Way Collaboration.

Maintainers¶

This handbook has been set up by Malvika Sharan and maintained by Precious Onyewuchi from the OSPO Now team to support the work DSWB community. Please reach out to them via email or Discord, or open an issue to share references or ideas related to the development of this project.

♻️ License¶

This work is licensed under the MIT license (code) and Creative Commons Attribution 4.0 International license (for documentation). You are free to share and adapt the material for any purpose, even commercially. as long as you provide attribution (give appropriate credit, provide a link to the license, and indicate if changes were made) in any reasonable manner, but not in any way that suggests the licensor endorses you or your use and with no additional restrictions.

🤝 Acknowledgement¶

1. The Github repository for this handbook uses the template created by Malvika Sharan and members of The Turing Way team, shared under CC-BY 4.0 for reuse: https://github.com/the-turing-way/reproducible-project-template.
2. The book is implemented using Jupyter Book, attributed to the Executable Books Community. (2020). Jupyter Book (v0.10). Zenodo. Executable Books Community (2020).
3. The Turing Way resources are attributed to The Turing Way Community. (2025). The Turing Way: A handbook for reproducible, ethical and collaborative research (1.2.3). Zenodo. The Turing Way Community (2025)