Abstract
Combining a knowledge acquisition methodology with a powerful data model we present an approach to the acquisition, maintenance and browsing of scientific medical hypertext. The hypergraph-based data model supports the consistent treatment of cyclic data structures, the nesting of complex object and provides an elegant way of path declaration to represent time-dependent medical processes or large hypertext tours. It encourages a stepwise schema design and therefore supports a spiral-shaped acquisition process. We formally define view mechanisms on the basis of a rule-based query and modification language. The views enable a context-sensitive presentation of medical knowledge according to the informational needs of the physician.
Our approach has been applied to the implementation of an authoring and tutoring environment for a computer-based hypermedia reference book for cerebrovascular diseases (NeuroN). During the acquisition process the expressive power and flexibility of the representational formats have been evaluated.
Keywords
Knowledge-based Medical Systems - Hypertext - Knowledge Acquisition - Graph-based Data Model
