... the notion that information within a given enterprise (system model) has significant meaning (structure) and is understandable to its internal and external entities.

Transcription is the application of syntactical structure and validation used to produce a storage structure and visual representation of the information in the new format.
OmPrompt's automated mapping uses self-learning ontology-based semantic recognition and is deployed in two ways: firstly to create syntactical structures from sample messages and secondly to validate live messages based on those same structures.
The creation of syntactical structure in the syntax ontology has three steps:
1) the analysis of message samples provided by the client to produce a syntax structure.
2) the data profiling of message samples to produce a representation of the message at segment and element level. Validation is built into the syntax ontology based on expected values, which forms the basis of the automated mapping process.
3) a defined syntax structure.
OmPrompt holds a library containing the syntax of all known message standards and all other message formats that the system has previously processed.
Data-profiled messages are parsed against the library to define a syntax structure. New message format structures are derived from the samples provided. The system validates that both library message structure and data values are compliant before deriving the syntax structure for the sample messages.
The outbound syntax ontology creates syntactical structures in the same way as the inbound and applies the same methods.
