GI2Vis Challenges and definitions:

1. How can we best capture results of explicit learning processes visually?
An equivalent:
How can we best visualize explicit (declarative) knowledge?

2. How can we best visualize tacit knowledge?
An equivalent:
How can we best capture results of implicit learning processes visually?

3. How can we best visualize blended explicit and tacit knowledge learned in parallel and influenced each other?
An equivalent:
How can we best capture results of parallel explicit and implicit learning processes visually?

B. Kovalerchuk, CWU

Working definitions:

Tacit knowledge is an unspoken, implicit, unstated knowledge.
Knowledge is a result of learning from data, actions, etc.
Subscript 1 will be used to specify knowledge learned from "atomic" (basic, elementary) data, actions, etc. -- knowledge₁.
Data, actions, etc are "atomic" if their internal structure is not considered.
Thus, if we want to be specific
Knowledge₁ is a result of learning from ("atomic") data, actions, etc;
Knowledge₂ is a result of learning from Knowledge_1;;
Knowledge₃ is a result of learning from Knowledge₂ ;
Knowledge₄ is a result of learning from Knowledge₃.
General:
Knowledge_i+1 is a result of learning from Knowledge_i.
Knowledge₁ serves as data for Knowledge₂.
Knowledge₂ serves as data for Knowledge₃.
Knowledge₃ serves as data for Knowledge₄.
General:
Knowledge_i serves as data for Knowledge_i+1.
For uniformity we can use Knowledge₀ notation for atomic data, actions, etc.
Different tasks may have their own knowledge hierarchies. Thus, Knowledge₁ for task 1 can be Knowledge₂ task 2,
    Knowledge₁,task1 = Knowledge_2,task2

The distinction between procedural (including tacit knowledge-BK) and declarative knowledge maps roughly onto the distinction between the explicit and implicit knowledge [Ron Sun 2001, http://www.hcrc.ed.ac.uk/cogsci2001/pdf-files/abs4.pdf].

Three learning models are under development:

• "top-down" -- learning first explicit knowledge and then implicit knowledge on the basis of the former.
• "bottom-up" -- learning first implicit (tacit) knowledge and then explicit knowledge,
• "parallel" --- learning implicit and explicit knowledge in parallel.

The bottom-up and parallel directions has been largely ignored in work on cognitive architectures [Ron Sun, 2001, http://www.hcrc.ed.ac.uk/cogsci2001/pdf-files/abs4.pdf]