Skip to content

Latest commit

 

History

History
68 lines (39 loc) · 5.6 KB

README.md

File metadata and controls

68 lines (39 loc) · 5.6 KB
Raw

Open Science and Capacity Building Working Group - Data Science Without Borders

Data Science Without Borders project hosts an Open Science and Capacity Building Working Group for researchers in African countries.

Background

Data Science Without Borders (DSWB) is an international initiative, funded by the Wellcome Trust and led by the African Population and Health Research Center (APHRC). This project has three overarching objectives: to strengthen data systems in Pathfinder countries, to create a sustainable environment for collaborative AI/ML platforms, and to create a user-friendly platform for AI and Machine Learning (AI/ML) tools. The impact of inequality in data availability and access is evident, particularly in resource-limited settings like many African nations. This African institution-led initiative will leverage artificial intelligence and machine learning (AI/ML) to bridge existing gaps in data accessibility, infrastructure, and expertise. It aims to foster a collaborative environment that empowers African nations to harness the full potential of AI/ML for improving health outcomes.

The DSWB research consortium will be working closely with three Pathfinder Institutions, namely the Armauer Hansen Research Institute (AHRI), the Institute for Health Research, Epidemiological Surveillance (IRESSEF), and the Training and Douala General Hospital (DGH) based in the Pathfinder countries (Ethiopia, Senegal and Cameroon respectively). London School of Hygiene & Tropical Medicine (LSHTM) and the Committee on Data of the International Science Council (CODATA) will collaborate as delivery partners providing support in platform development. The Africa CDC will provide key technical oversight for the project, supporting country engagement, identification of priority use cases and provision of guidance for effective policy engagement.

A Working Group hosted by this project in 2024-2025 is the Open Science and Capacity Building Working Group.

This repository centralised all resources relevant to this Working group (WG).

Goals of the Open Science and Capacity Building Working Group

DSWB can only achieve its ambitious goals if it is delivered by health and AI/ML experts working together.

This WG will ensure that everyone in the DSWB partnership network understands - to the extent that they need to – best practices such as open science, computational reproducibility, data sharing practices, AI standards, project management, cross-team collaboration and technical translation skills, and responsible research and innovation practices.

Connection with The Turing Way and other Open Science communities

The WG will support the knowledge-building and adoption of open science practices and approaches in DSWB through active connections with existing open science communities and projects.

The Turing Way will be used as a primary reference for curating and sharing practices, as well as identifying gaps where resources can be developed by the DSWB members in collaboration with other interested practitioners.

Community managers and trainers in this working group will be onboarded to become active contributors to The Turing Way, acting as a bidirectional conduit to implement best practices for reproducible, ethical, inclusive and collaborative data science. They will support DSWB community members in the documentation and sharing of best practices via The Turing Way making it useful for their contexts.

The chair of this working group is Malvika Sharan, working as a consultant on the project.

Primary deliverables

  • D1. Engagement with Communities of Practice (CoP) for data science initiatives involved in DSWB.
  • D2. Contribute to the development of standard operating procedures (SOPs) and ways of working for the collaborators and stakeholders, drawing examples and resources from open science communities and projects.
  • D3. Develop a context-specific roadmap to support the adoption of The Turing Way and develop relevant resources, infrastructure and community to involve researchers from Pathfinder countries in DSWB efforts.

Goals

  • The Short-term goal of this WG is to build a shared understanding of open science and reproducibility in data science and AI among all members of the DSWB partners
  • The long-term goal is to build capacity for the DSWB partners and their networks to extend the impact of open science and reproducibility practices in advancing the impact of data science and AI

In due course, we will provide a roadmap for the WG on this repository.

Contributing

  • Guidelines: Contribution Guidelines for contributors will be developed in due course
  • Code of Conduct: Code of Conduct will be adopted in agreement with the DSWB members

Maintainers

This repository has been set up and maintained by Malvika Sharan to support the work of WG under DSWB.

Please create 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

This repository uses the template created by Malvika and members of The Turing Way team, shared under CC-BY 4.0 for reuse: https://github.com/alan-turing-institute/reproducible-project-template.