JFAB’s data management ecosystem enables the generation of FAIR-compliant, standardized datasets.

JFAB’s data management pipeline

How it works:

JFAB leverages a digital stack specifically optimized to eliminate data silos for the entire research ecosystem. 

1. Bench scientists use Superhuman Docs and TeselaGen for metadata entry and design management. At the same time, AI agents work autonomously to generate metadata about experiments.
2. Raw data is then captured by Ganymede, which delivers insights back into the Superhuman Docs interface.
3. Data is backed up in the Lawrence Berkeley National Laboratory (Berkeley Lab) Google Cloud.
4. Beyond the bench, Ganymede serves as a data bridge, disseminating standardized information to Bioenergy.org, U.S. Department of Energy data lakehouses and autonomous agents for high-level modeling.

All data is FAIR (findable, accessible, interoperable, reusable) compliant, enabling a seamless and machine-readable flow of “clean” information that serves the diverse needs of individual bench researchers, data scientists, and autonomous agents.