Project Summary This proposal aims to continue the development of XNAT. XNAT is an imaging informatics platform designed to facilitate common management and productivity tasks for imaging and associated data. We will develop the next generation of XNAT technology to support the ongoing evolution of imaging research. Development will focus on modernizing and expanding the current system. In Aim 1, we will implement platform components, in including a new archive file management system and database interface, a streamlined image annotation interface, a module to support integrations with cloud applications, and a set of software development kits (SDKs) to support development of tools that interact with XNAT data and services. In Aim 2, we will implement two innovative new capabilities that build on the services developed in Aim 1. The XNAT Workspaces module will link Jupyter Notebooks with XNAT, creating a computing environment that enables users to mount specified data sets in their Notebooks, share and clone Notebooks, save Notebooks to version control systems, and publish them as static dashboard. XNAT Workspaces will be linked to XNAT Container Service and high-performance computing and cloud computing resources to enable scalable computation. The XNAT Machine Learning (ML) Studio will provide an integrated application for data science teams to build and annotate data sets, train and validate ML models, and publish their models as deployable applications. ML Studio will implement quality control, logging, and provenance tracking to help users avoid the pitfalls that often plague machine learning efforts. For both Aim 1 and 2, all capabilities will be developed and evaluated in the context of real world scientific programs that are actively using the XNAT platform. In Aim 3, we will provide extensive support to the XNAT community, including developer workshops and hackathons, online documentation, discussion forums, and the XNAT Academy training platform. These activities will be targeted at both XNAT users and developers. Together these aims represent a major advance in imaging informatics that is unique in the field and will greatly benefit an extraordinarily broad research portfolio.