The Knowledge Network model

The Knowledge Network model defines the following five elements and their interrelationships. ·   knowledge ·   information ·   task /decision ·   learning ·   context   The basic purpose of this conceptual model is to clarify the key entities that constitute the “knowledge network”; in other words the entities that interact in developing and using knowledge within an enterprise. As such the model provides the baseline in formulating the meta-models for the KBOS knowledge networking platform and solutions.
The model distinguishes between the information and knowledge domains. In the information domain data represent facts and becomes information when embedded in a context of relevance to a task or learning activity. The extraction of information from data can be undertaken efficiently by computers.  In the knowledge domain, knowledge is a property of agents (people or computer systems) predisposing them to act in particular way in circumstances defined by the context.  New knowledge is generated through learning. Learning is mainly associated with people and mental processes, even though machine learning is equally applicable when it becomes available.   Both tacit and explicit knowledge are addressed in the model. A task may be performed using explicit and tacit knowledge. If the activity can be performed using explicit knowledge it means that has been automated.  If an activity is performed by a person then information will trigger different mental processes involving reasoning and learning and possibly communication with an expert or team members.

<<                                                                                                                                                    >>