ABSTRACT
Existing theories and data models for simulating processes focus on representing the state of the represented system at a moment in time. The future pattern of global temperature from a global climate change model or the distribution of humans in an agent-based simulation of disease spread, for example, only provides information about the status of the attributes of the system at each step of the simulation, attributes such as temperature or agent health at a particular location. Information about the processes defined in the model is typically not expressed or represented in any form. In utilising a process-oriented data model, we gain the advantage of being able to query, analyse and visualise processes.
