datalab: Decentralized materials research data management, curation & dissemination for accelerated discovery

This presentation was given at the Physical Sciences Data Infrastructure (PSDI) Materials Community Workshop, 16 - 17 June 2025 at the Royce Hub, Manchester, UK. Abstract The primary barrier to widespread adoption of AI-accelerated materials science is the availability and quality of data. Researchers lack frictionless tooling and have limited incentive to record their data in such a way that is immediately amenable for machine learning, whether by them or by others. This talk introduces the open-source datalab materials data management platform. datalab is a open-source data management platform that can be customized and adopted by materials research groups to allow for straightforward provenance tracking of samples, devices and raw data. It integrates with the broad open-source community of file format parsers (from the datatractor initiative and other popular packages) to allow for data normalization and simple analysis in the browser for many characterisation techniques (XRD, NMR, Raman, electrochemistry, etc). This platform provides the traditional benefits of having a digital system of record (e.g., an electronic lab notebook), whilst also enabling programmatic re-use of data across a research group via its API, with the aim to allow end user programming. By providing labs with control over their data platform, they can develop their own AI-driven developments, as well as selectively sharing and collaborating with others on shared workflows and samples. This talk will summarize the ongoing developments of datalab, including the integration of AI-based agents, and motivate future use cases of a federation of such datalab deployments.