Abstract:

Organisational, legal and financial issues may require professional expertise which is large scale and complex. The difficulty of teaching such expertise can be assisted through the use of an eGanges application, which provides a visualisation of the expert knowledge. This visualisation guides the management of the complexity of the operation of the knowledge, namely its implicit four-valued logic and combinatorics.
To illustrate this assistance, an eGanges application, called AML & CTF is described and demonstrated. The AML & CTF application is used in teaching an area of law, the Australian Anti-Money Laundering and Counter-Terrorism Financing Act 2006, which requires large scale and complex administration. At the same time the application covers a combination of organisational, legal and financial issues.

eGanges implements a designed epistemology which includes the visualisation of an hierarchical decision River graphic to guide the user through the complex knowledge. The user is interrogated at each point in the River knowledge and the answers of the user are processed by the sorting of an automated four-valued logic. There are three alternative answers, as well as no answer which gives a choice of four alternative logic values. Thus, the large number of questions and possible answers creates massive combinatorics implicit in the expertise. The eGanges automation of this combinatorics makes it a superexpert aid that assists learning and the application of expert knowledge beyond ordinary human capacity. It is part of the new genre of the beauty of data visualisation that blends the language of the eye and the language of the mind to compress massive data to relative and significant understanding.

Keywords:

Knowledge visualisation, expert systems, designed epistemology.