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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 Data Support WG facilitates the FAIRification of datasets with DS-I Africa, making the data Findable, Accessible, Interoperable and Reusable (FAIR), through workshops, training, tutorials and practical exercises/implementations. The WG centres the application of FAIR principles through the establishment of FAIR goals, assessment of FAIR gaps and determination of opportunities for FAIRification. Consideration for ethical and responsible data sharing is a key focus. Some of the commonly employed resources in the application of FAIR principles are summarised below:

  1. FAIR Cookbook
    The FAIR Cookbook is an online, open and live resource for the Life Sciences with examples and recipes that help you to make and keep data FAIR. The resource can be accessed here. Recipes provide you with the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges, to achieve and improve FAIRness. Each recipe tells you the audience type, reading time, level of difficulty, and the level of FAIR maturity it allows you to reach.
  2. ELIXIR Research Data Management (RDMkit)
    The ELIXIR Research Data Management Kit (RDMkit) has been designed to guide life scientists in their efforts to better manage their research data following the FAIR Principles. It is based on the various steps of the data lifecycle, although not all the steps will be relevant to everyone. The RDMkit can be accessed here. One of the key resources within the RDMkit is the FAIRplus Dataset Maturity (DSM) Model, used to assess dataset maturity according to FAIR goals.
  3. Data Use Ontology (DUO)
    The Data Use Ontology (DUO) is a GA4GH-developed standard which provides a standard set of terms or consent codes that can be used to tag datasets with use permissions, aiding researchers in discovering data and facilitating DAC decisions in the data access process. The standard allows data to be tagged with consistently defined, computer-readable use permissions and optional modifiers, enables tagged data to be more easily discoverable and accessible, and streamlines the process of identifying appropriate uses and users of data. DUO can be explored via the Ontology Lookup Service. For more information on DUO, see the presentation from the eLwazi Data Jamboree 2023.