Systematic Mapping of Arbitrary Scientific Tasks into Modular VAILabs Workflows

Establish systematic methodologies for mapping arbitrary scientific tasks into the VAILabs modular workflow architecture, including criteria for decomposition into modules, selection of plugins, and composition of iterative loops, to support truly general-purpose AI-assisted research environments.

Background

The paper introduces VAILabs, a modular, domain-agnostic platform for implementing Virtual Laboratory workflows across diverse scientific disciplines. While the authors demonstrate feasibility with three use cases, they explicitly note that generalizing the approach remains challenging.

In the discussion, the authors state that mapping arbitrary scientific tasks into a modular structure is still a work in progress, highlighting the need for systematic methodologies to consistently translate diverse research activities into compatible, reusable workflow components.