1. A dynamic event detection architecture configured as one or more hypernodes and comprising: (a) a hardware workflow engine that runs one or more workflows employed for processing input data by facilitating logic and state manipulation of the input data based on requirements of a specified task; (b) a semantic database defined by an ontological model that is related to the specified task and which includes a meaning, rules, and data elements based on the ontological model; (c) a hyperfragmenter system that processes the input data in real-time, in a workflow, to produce fragments of input data that are self-contained and discrete; (d) a hyperasset file system joined with the semantic database such that both operate automatically, the hyperasset file system enabling the fragments of input data to be stored and retrieved based on specified criteria; (e) a plurality of distributed experts that use an application program interface to facilitate review of the fragments of input data by the distributed experts at any point in the workflow and to provide additional information to the fragments of input data; (f) a plurality of event definitions used by a first rule-based language engine to define events based on the fragments of input data in the workflow or based on relationships defined in the semantic database; (g) a plurality of situation definitions used by a second rule-based engine to define complex situations to create situational rules; and (h) a filtration system that applies the situational rules to the workflow to determines if an output of the workflow requires further analysis.