The project aims to develop the capacity of MH prize winners to use open-source platform for data sharing.  The goal is to enable data scientists to share their project progress (e.g., code, datasets, documentation) on open-source platforms (e.g., GitHub, Kaggle, Zenodo) under licenses that allow free use, modification, and distribution (e.g., MIT, Apache 2.0, CC-BY for data). This promotes transparency, collaboration, and reproducibility in data science. The Consultant will work closely with MHDP-Africa Project team and will be responsible to the MHDP-Africa Project Lead at APHRC. The consultant will lead the development and capacity building of MH data prize winners on use and application of open sources; design and implement a user authentication module for an open-source application.

Scope of Work

• The consultant is expected to conduct need assessments of prize winners on knowledge and skills about open source and report. Assess the needs of data scientists for publishing (e.g., platforms, formats, licenses).
• Select and configure appropriate open-source platforms (e.g., GitHub for code, Zenodo for datasets, Jupyter for notebooks).
• Develop guidelines and templates for publishing code, datasets, and progress reports.
• The consultant is expected to develop a training plan, content and strategy to promote use of open-source platform and data sharing principles (PLE) in the MHDP – Africa project.
• Train data scientists on open-source publishing best practices (e.g., version control, metadata, licensing). Assist through training and hands-on development in the creation of a GitHub organization and repository for sharing analysis and metadata created by the grantees.
• Provide expertise in open-source software development and platforms such as GitHub. This include provision of ad hoc consultancy services as the Client may request which may include ad-hoc video calls or asynchronous conversations over email, or other online platforms, with the mental health data prize grantees.
• Support grantees publishing data and metadata to increase the findability of mental health datasets. E.g. For each project pilot, the workflow and refine based on feedback.
• Discuss questions or strategies about open source to foster an environment of open data and software sharing.
• Prepare a write-up on good practices for open-source platform capacity building and use based on project experiences that can be made publicly available through APHRC or related blog platforms (in French/English/Arabic).
• Regularly monitor, evaluate and report country-specific MH researchers progress of developing and using the open-source platform.
• Participate in regular project meetings and update progress and inform the mechanisms to monitor ongoing feedback throughout the project lifecycle
• Outline and ensure ethical consideration data use, protection and sharing.
• Submit monthly project progress report to the MHDP project team.

Deliverables

 Inception Report

• Conduct and prepare a report on the need’s assessment i.e. develop questionnaire and assess open access skills, gaps and experience of data scientists’ involvement in MH research open-source use.
• Prepare the training materials and submit.
• Provide training to support and upskill members and upskilling team members.
• Support the team on OS development
• Prepare and submit a report
• Pilot implementation of the workflow, regularly monitor and provide feedback
• Lead communication around Open source.
• Final report including outcomes, refined workflow and user guide.

Responsibilities of the APHRC MHDP – Project Team

• Provide relevant project background documents.
• Liaise and assist in communicating with and mobilizing key
• Handle all logistical
• Closely work with the consultant on the development, implementation, and evaluation of the Open-source capacity building program and data sharing.

Timeframe

The consultancy is expected to be completed in 3 months, spread over 1st July 2025 – 30th September 2025.

Qualifications and Experience

The ideal consultant will demonstrate a proven track record in designing and implementing open-source data science publishing workflows. The assignment requires a high level of technical specialization, strong community credibility. The selected candidate or firm must meet the following qualifications:

• Proven expertise in open-source data science workflows: Demonstrated experience in developing and implementing efficient, reproducible publishing pipelines using platforms such as GitHub, Zenodo, and Kaggle. A portfolio highlighting successful collaborations with major research institutions is essential.
• Specialized software development skills: Advanced knowledge of software development, with the ability to create scalable, license-compliant publishing systems. Experience using tools like Python, Jupyter Notebooks, and Docker is required.
• Capacity building experience: Prior involvement in training data scientists on open-source licensing (e.g., MIT, CC-BY) and data science tools. The ability to build rapport and trust with trainees is crucial, as evidenced by positive client feedback and high satisfaction scores from similar engagements (e.g., MHDP project).
• Rapid deployment capability: Due to the project’s tight timeline, the consultant must be able to commence immediately and leverage pre-existing templates, frameworks, and expertise to deliver quickly and efficiently without compromising quality.
• Open-source community engagement: A strong reputation in the open-source ecosystem, including direct contributions to widely recognized platforms and demonstrated adherence to open-source principles, is required. This ensures outputs will be credible, trusted, and widely adopted.
• Ethical and legal data handling: Deep understanding of data privacy, ethics, and legal standards in open-source contexts to ensure sensitive data is managed responsibly, minimizing potential legal and reputational risks.