UZIMA-DS Research Hub
Utilizing Health Information for Meaningful Impact in East Africa through Data Science
The UZIMA-DS (UtiliZe health Information for Meaningful impact in East Africa through Data Science) Hub aims to create a scalable and sustainable platform to apply novel approaches to data assimilation and advanced artificial intelligence/machine learning-based methods to serve as early warning systems to critical health issues impacting Africans in two domains: maternal, new-born and child health and mental health.
UZIMA-DS brings together method experts in statistics, computer science, and informatics, healthdomain experts and practitioners, and partnerships with key stakeholders to not only improve the quality, efficiency, and relevance of multidisciplinary data science in health research, but also its transparency, reproducibility, and dissemination for sustainable impact in Africa. Thus, helping ensure current and future generations of Africans can achieve uzima (health/well-being in Swahili). Learn more about UZIMA-DS Here.
Data Management and Access Core (DMAC)
The Data Innovation team plays a vital role in supporting the data infrastructure needs of the UZIMA-DS project. Operating within a cloud-first, open-source environment, the UZIMA-DS architecture undergoes continuous iteration, incorporating emerging data algorithms, best practices, and standards. Our work involves facilitating and supporting effective data management and analysis using FAIR (Findable, Accessible, Interoperable, Reusable) principlesWe ensure that all data required by researchers undergoes processing and cleaning through high-quality data pipelines and is then organised within a data model optimised for analysis. Additionally, the DIO team provides essential training and support to researchers on accessing cloud resources and utilizing tools effectively while ensuring compliance with Kenyan Data Protection laws and serves as the primary contact with the Office of the Data Protection Commissioner.
Sustainable Cloud Operations for Research (SCORE)
SCORE introduces a practical framework that helps research teams in low- and middle-income countries (LMICs) design and manage cost-efficient, high-performance, and environmentally sustainable cloud data pipelines. Our guidelines address the real-world challenges of limited budgets, technical capacity, and connectivity common in LMIC research settings.
Using a three-phase model, Assessment, Selection, and Optimization, SCORE guides health research teams in designing the right data pipelines, controlling costs, optimizing performance and minimizing carbon emissions. This provides a clear pathway to adopt cloud technologies responsibly, advancing both scientific innovation and environmental sustainability across global health research.
Read the full report here: Sustainable Cloud Operations for Research Report.pdf
Too long? Here's an infographic cheat sheet that sums it up: SCORE Infographic Cheat Sheet.png
