Changes and anomalies in multi-modal data are detected, collected and abstracted into understandable and actionable formats utilizing, for example, color, intensity, icons and texture creating a rendition of current and developing situations and events. Changes and anomalies in multi-modal sensor data are detected, aggregated, abstracted and filtered using case-based reasoning providing a tractable data dimensionality. From this collection of data situations are recognized and presented in a means so as to assist a user in accessing an environment and formulate the basis a recommended course of action.