Table 2

Individual and general knowledge

General knowledge

Individual knowledge


Example

Explicit general propositions, rules, algorithms, guidelines and formal theories for recognizing faces of people (e.g., a formal theory of human face recognition).

The implicit knowledge used to recognize and the explicit knowledge (e.g., textual description) that would allow recognizing the face of a specific person.

Complexity

Very lean, abstract, symbolic.

Varies from rich to lean.

Acquisition

Identical to acquisition of explicit knowledge.

Identical to acquisition of both implicit and explicit knowledge.

Representation Transferability

Very structured, highly transferable, explicitly as general propositions, rules and guidelines.

Varies from unstructured to less structured. Transferable in both implicit and explicit form.

Context retention Applicability

Does not retain context.

Easy applicable to generic problems, difficult to apply to specific problem instances (e.g., recognition of the face of a specific person).

Retains context.

Well applicable to specific problem instances, especially if context retention is high.

Processing mechanisms

Logic reasoning.

Pattern recognition, feature selection, associative recall, case-based reasoning.


Pantazi et al. BMC Medical Informatics and Decision Making 2004 4:19   doi:10.1186/1472-6947-4-19

Open Data