Data & Data Support
The eLwazi Data Support WG supports DS-I Africa research hubs and other eLwazi users to share their data through the eLwazi platform to enable greater data reuse across the consortium and larger research community. The WG defines data sharing and reuse requirements following shared policy and consent, focusing on making data FAIR (findable, accessible, interoperable and reusable). Data are made discoverable/findable and accessible via a fit-for-purpose data catalogue, which provides metadata search and summary. Similarly, data are made interoperable and reusable by identifying suitable data standards or models for application across the consortium and facilitating data harmonisation and integration efforts within and across DS-I Africa.
The eLwazi Catalogue is an essential component of the platform, providing searchable metadata for datasets generated and used by the DS-I Africa consortium and external organisations/projects across the African continent. The catalogue FAIRifies the data science datasets in the following way:
- Findable - through search and filter options
- Accessible - coded to DUO (Data Use Ontology) conditions and restrictions
- Interoperable - standardised and harmonised to the eLwazi metadata model
- Reusable - clickable connections from datasets connect researchers to dataset providers
The catalogue serves the following purposes:
- Centralised Repository: To provide a single platform where researchers, healthcare professionals, and policymakers can explore various African health-related data.
- Data Categorisation: To organise projects based on the data types they involve, making it easier for users to find datasets that align with their specific data needs, i.e. Geospatial; Demographic and Health; Omics and Image data.
- Regional Focus: To highlight projects that are specific to certain regions within Africa, thereby encouraging localised solutions and research.
- Interdisciplinary Collaboration: By listing projects that involve different data types, the catalogue aims to foster interdisciplinary research and applications in healthcare.
- Transparency and Accessibility: To make health-related data more discoverable, accessible and transparent, thereby accelerating research and applications in healthcare.
- Institutional Support: To acknowledge and leverage the support from reputable institutions like the National Institutes of Health for credibility and resource allocation.
- Feedback Mechanism: The platform also has a feedback section, demonstrating its aim to continually evolve based on user input and needs.