The ability to detect and unambiguously follow all moving entities in a state space is important in many domains both in defense (e.g., air surveillance, maritime situational awareness, and ground moving target indication) and the civil sphere (e.g., astronomy, biology, epidemiology, and dispersion modeling). However, tracking and state estimation researchers and practitioners have difficulties recreating state-of-the-art algorithms to benchmark their own work. Furthermore, system developers need to assess which algorithms meet operational requirements objectively and exhaustively rather than driven by intuition or individual preference. We have, therefore, set up a collaborative initiative to create an open-source framework for production, demonstration, and evaluation of tracking and state estimation algorithms. Stone Soup is designed to be a (MIT– licensed) software framework for researchers and practitioners to test, verify, and benchmark a variety of multisensor and multiobject state estimation algorithms. The initiative is supported by four defense laboratories (Defence Research and Development Canada, Defence Science and Technology Laboratory, Defence Science and Technology Group, and Naval Research Laboratory), who are contributing to the development effort for the framework through the Technical Cooperation Program. The tracking and state estimation community will derive significant benefits from this work, including access to repositories of verified and validated tracking and state estimation algorithms, a framework for the evaluation of multiple algorithms, standardization of interfaces, and access to challenging data sets.