Resources in Model-driven Life Sciences Data Management

This page aims at providing an access point to resources to MDE concepts and tools applied to Life Sciences Data Management.

What is "Model-Driven Data Management" in the context of Life Sciences?

In the context of Life Sciences, data management issues are mostly concerned with data integration. Adapting model-driven approaches to Life Sciences Data Management aims at providing smart solutions for the following reasons:

  1. Metadata, which allows data description and comparison, is central to data integration and standardization efforts have been engaged to acheive consistent metadata implementation.
  2. Model-driven concepts and tools, based on Model-Driven Engineering (notably, models processing operators), are well suited to acheive complex data integration in Life Sciences.
  3. Domain standards, which refer to the current knowledge in Life Sciences, could serve as reusable models in a Model-Driven approach to interoperability.

Click on the thumbnail below to see the characteristics of the particular area.