As a capability of live organisms, languages are best understood in terms of communication.
That understanding is of particular interest for enterprises immersed in digital environments inhabited by hybrids with deep learning capabilities.
- Languages begin with the need of direct (here) and immediate (now) communication. While there is no time for explanations, messages must convey some meaning, if only to distinguish friends from foes. Hence the use of signs pointing to categories of objects or phenomena. That’s the language lexical layer linking instantly observations (data) to information (bottom right).
- Rules governing the combination of signs follow soon because more has to be communicated about circumstances and what is to be done with. That’s the language syntactic layer linking observations (data) to current information (top right).
- The breakthrough comes with symbolic representation: once
disentangled from immediate circumstances, communications can encompass whatever is deemed relevant in contexts and concerns;
That’s the language semantic layer that weave together information and knowledge (top left). - The cognitive ability to “manipulate” symbolic representations (aka models) independently of circumstances opens the door to any kind of constructions. That’s the language pragmatic layer meant to put knowledge to actual use (bottom left).
That functional taxonomy can be usefully applied to the digital transformation of enterprise architectures, the first layer aligned with data, the second and third with information, and the fourth with knowledge.
FURTHER READING
- Modeling Paradigm
- The Pagoda Blueprint
- Digital Transformation & Homeostasis
- Views, Models, & Architectures
- EA: Maps & Territories
- EA: Work Units & Workflows
- Ontologies & Enterprise Architecture
- Ontologies as Productive Assets
- Models Transformation & Agile Development
- Agile Architectures: Versatility meets Plasticity