Information processing plays an important role in such systems, as recorded information requires various types of processing in order to be presented to an end user in an easy to understand format. The various concepts involved in MyRoR are captured through the model in the following picture. The information captured by MyRoR is processed along 8 context types: activity, availability, emotional, environmental, mental., social, spatial and temporal, corresponding to various aspects of one’s lifestyle.
The Information model constantly evolves as new input information is added to the system, as new correlations generate new types of information and as new presentation models (e.g., models that arrange information in a certain way, such as story-based) are created. Given the variety of information collected, the possibilities of creating high-level concepts are immense. One of the dangers of such systems is to automate too much, both in terms of collecting as well as processing information without any involvement of end users. As argued in , successful technologies should involve end users in all stages, including in making sense of collected information. Within such systems, the user is examiner, explainer, producer and consumer of processed data (i.e., forming a closed loop involving the person and the data modelling and processing systems). MyRoR uses a rule-based engine to provide information processing at various abstraction levels and for different purposes.
For providing more engaging and easier to understand correlations and processing, I created a story-inspired framework, that include information modelling, automatic story creation and multimedia visualizations. More information on this framework can be found here.