This Pathways to Enable Open-Source Ecosystems (POSE) project enables automation in laboratory science workflows. Laboratory automation increases the precision and efficiency of science experiments, enabling the collection of large data sets and automating feedback loops. However, scientific experiments are highly varied and require deep domain expertise and specialized equipment. There are no one-size fits all approach to establishing a self-driving lab. This project addresses this opportunity by advancing RepLab, an Open-Source Ecosystem (OSE) for open-source laboratory automation. RepLab will support scientists in adopting automation in their workflows to increase their efficiency and accelerate their progress while training a generation of scientists with new skills. This ecosystem will vet open-source laboratory automation technologies by testing, benchmarking, and validating their performance and reliability. This solution will lower the barrier to replicating the technologies by conducting design for distributed production and supply chain assessments. Enabling automation in laboratory science workflows will foster U.S. innovation and accelerate technology development and translation by supporting industry and small businesses in establishing competitive science workflows. This POSE project establishes an OSE for laboratory automation. The team will validate and support open-source infrastructure that underpins self-driving labs, enabling scientists to close the loo