This contribution is about an information management and storage system for modeling the environment of autonomous systems. The three pillars of the system consist of prior knowledge, environment model and sensory information. The main pillar is the environment model, which supplies the autonomous system with relevant information about its current environment. For this purpose, an abstract representation of the real world is created, where instances with attributes and relations serve as virtual substitutes of entities (persons and objects) of the real world. The environment model is created based on sensory information about the real world. The gathered sensory information is typically uncertain in a stochastic sense and is represented in the environment model by means of Degree-of-Belief (DoB) distributions. The prior knowledge contains all relevant background knowledge (e.g., concepts organized in ontologies) for creating and maintaining the environment model. The concept of the three pillar information system has previously been published. Therefore this contribution focuses on further central properties of the system. Furthermore, the development status and possible applications as well as evaluation scenarios are discussed
