A framework to standardize Machine Learning in Life Sciences (2023-24)

Through this project, we will continue building on the DOME recommendations, expanding them in scope, while also creating a concrete framework to increase adoption and overall impact of the DOME recommendations, looking both within ELIXIR and beyond.

The project will engage in the following three complementary activities:

  1. Implement a framework around the DOME recommendations, including a registry to capture DOME-related information from existing and future literature, and a low-barrier software tool that will allow for the easy creation of DOME annotation by the wider community.
  2. Review and connect the DOME recommendations in light of the particular needs, requirements and expectations of relevant ELIXIR communities, thus establishing a pathway towards adoption. 
  3. Create a clear engagement plan to stakeholders beyond ELIXIR, linking to relevant global efforts and initiatives, including the RDA ML interest groups, the NIH AI activities and efforts in Industry (such as the Pistoia Alliance).