m+m: movement + meaning is developing a software framework that, broadly speaking, enables researchers to construct meaningful semantic models of movement data. The acquisition, processing, and rendering of movement data can be local or distributed, real-time or off-line. Examples of systems that can be built with m+m as the internal communication middleware include those for the semantic interpretation of human movement data, machine-learning models for movement recognition and movement analytics, the representation of semantic properties of movement data in virtual characters, and the mapping of movement data as a controller for online navigation, collaboration, distributed performance.

Key features of the m+m middleware are small footprint in terms of computational resources, portability between different platforms, and high performance regarding low latency and high bandwidth.