Data Transformation Processes
Reaction masks convert a new meaning which someone might have into a number of existing meanings. In simple words: A reaction mask describes how to transform an information object, which matches the definition of a human or API, into a structured representation of the given object.
The process of applying such a variable meaning and its reaction mask to a specific object is called derivatization, or simply 'transformation'. The transformation is done automatically (when data is processed through Phorio) and is usually independent of manual input from users. However, users can adjust variables and reaction masks to reflect their own meanings of a definition. A variable must have at least one reaction mask but may also feature additional reaction masks.
Example transformation
Example of a reaction mask
A warehouse building located at a given coordinate (represented by the string 'highbay warehouse / 49.902214,8.612074') would transform using the variable high-bay warehouse and its associated reaction mask into the following constants:
--- reaction mask [start] ---
> status: existing
> frame material: steel
> structural form: rack-supported building
> primary use: warehouse
> window type: no windows
--- reaction mask [end] ---
and would generate a highly structured, derivated object from the initial string:
> status: existing
> frame material: steel
> structural form: rack-supported building
> primary use: warehouse
> window type: no windows
> latitude: 49.902214
> longitude: 8.612074
> city: Weiterstadt
> state: Hesse
> country: Germany
. . .
Needless to say, the system will learn over time from changes, corrections, reactions, and the evolution of definitions and reaction masks. As a result, this can lead to the creation of new reaction masks and/or new variable codes based on gained knowledge.
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