To accomplish this, the DS-I Africa Initiative aims to contribute to the development of the necessary expertise among African scientists, and to establish networks of African investigators.
The vision of DS-I Africa is to create and support a robust pan-continental network of data scientists and technologies that will be equipped to apply advanced data science skills to transform health.
- DS-I Africa is an NIH Common Fund Initiative
Contributing Institutes, Centres and Offices
- Fogarty International Center
- National Cancer Institute
- National Human Genome Research Institute
- National Institute of Allergy and Infectious Diseases
- National Institute of Biomedical Imaging and Bioengineering
- National Institute of Child Health and Human Development
- National Institute of Dental and Craniofacial Research
- National Institute of Environmental Health Sciences
- National Institute of Mental Health
- National Library of Medicine
- Office of Data Science Strategy
- Office of Strategic Coordination (Common Fund)
To advance Data Science and related innovations in Africa to create an ecosystem that can begin to provide local solutions to countries’ most immediate public health problems through advances in research.
Create a pan continental network with broad academic, public, private and industry partnerships.
Enhance Data Science capacity through training toward developing a new generation of interdisciplinary African Data Scientists..
Develop new data collection and analytic systems, applications, and tools with attention to usages that are population-relevant, affordable, acceptable, and scalable.
Advances in policy surrounding ethical issues
Facilitate resource access to the global scientific community. Resources may include medical image repositories to be used as a basis for machine learning.
Establish recognized regional and continental DS Centres of Excellence.
Enable new interdisciplinary collaborations and new scientific knowledge.
Demonstration of the feasibility of advanced DS to improve health in Africa
On this page you will find a list of consortium projects. The consortium consists of a data science platform and coordinating center, seven research hubs, seven data science research training programs and four projects focused on studying the ethical, legal and social implications of data science research.
On this page, you will find the list of Working groups, links to the minutes of their meetings and other documentation about the establishment of the working group and its purpose and function.
Training & Education Working Group
Data Management Working Group
Partnerships & Outreach Working Group
- Create networking opportunities with potential partners.
- Provide a forum for consortium members to discuss the challenges to partnerships and strategies for effective collaboration.
Data Governance Working Group
Latest News & Events
Comp Science HR Code
Comp Science HR Code
World Science Day
World Science Day
Third Meeting of the DS-I Africa Consortium
We are pleased to announce the 3rd DS-I Africa Consortium Meeting. The Meeting will be held in Kigali, Rwanda at The Kigali Serena Hotel.
REDCap Africa Symposium 2023
The annual REDCap Africa Symposium is an event where REDCap administrators and users from Africa gather for technical discussions, use case demonstrations and networking opportunities. Key note speakers for 2023 include REDCap inventor Prof Paul…
DS-I Africa REDCap Workshop
We are pleased to announce the DS-I Africa REDCap Workshop 17-18 October 2023, Cape Town South Africa.
This workshop is intended to provide some intensive REDCap training for REDCap Users who design and…
Data Science for Health in Africa 3rd Virtual Networking Exchange
The DS-I Africa Coordinating Center and NIH staff are organizing a Virtual Networking Exchange event that will allow DS-I Africa projects and other data science and health organizations in Africa to:
- share information about their…
DS-I Africa Steering Committee
Principal investigators, project and data managers from each grant and NIH program staff constitute the Steering Committee membership. Participants are bound by policies and procedures developed by the Steering Committee.
Adoption of such policies and procedures requires a majority vote, each funded project has one vote. The Steering Committee chair and co chair are elected by majority vote, and together with the Coordinating Centre prepares meeting agendas and fulfills all related administrative and management tasks.
Chair: Prof. Chenfeng Xiong
Co-Chair: Dr Joyce Nakatumba-Nabende
TBAResources & Outputs
Documents - to followMeeting Frequency
Online - monthly
In-person - Bi-annually rotating to various member countries
- Community Engagement & Health Information
- Data scientist video series
- Data Science Community Toolkit