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In the field of Knowledge Engineering, dissatisfaction with the rapid-prototyping approach has led to a number of more principled methodologies for the construction of knowledgebased systems. Instead of immediately implementing the gathered and interpreted knowledge in a given implementation formalism according to the rapid-prototyping approach, many such methodologies centre around the notion of a conceptual model: an abstract, implementation independent description of the relevant problem solving expertise. A conceptual model should describe the task which is solved by the system and the knowledge which is required by it. Although such conceptual models have often been formulated in an informal way, recent years have seen the advent of formal and operational languages to describe such conceptual models more precisely, and operationally as a means for model evaluation. In this paper, we study a number of such formal and operational languages for specifying conceptual mode...

Provision of automated support for planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system, and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by applicable protocols. This paper presents a synthesis of research carried out at Stanford University to model the therapy-planning task, and to demonstrate a component-based architecture for building protocol-based decision-support systems. We have constructed general-purpose software components that (1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans; (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts; (3) perform time-oriented queries on a timeoriented patient database; and (4) allow acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and by computers. We have implemented these components in a computer system known as EON. Each of the components has been developed and evaluated independently. We have evaluated the integration of the components as a composite architecture by implementing T-HELPER, a computer-based patient-record system that uses EON to offer advice regarding the management of patients who have AIDS. A test of the reuse of the software components in a different clinical domain demonstrated rapid development of a prototype application to support protocol-based care of patients who have breast cancer.

The software and knowledge engineering literature defines maintenance strategies for seven main types of knowledge: words; sentences; behavioural knowledge; and meta-knowledge. Meta-knowledge divides into problem solving methods; quality knowledge; fix knowledge; social knowl- 5 edge; and processing activities. There are five main ways in which these seven knowledge types are processed: acquire; operationalise; fault; fix; and preserve. We review systems that contribute to these 7 5 = 35 types of knowledge maintenance. 1 Introduction 10 A general trend in the twentieth century is an increasing level of doubt about the things we speak or write or try to enter into programs. Popper argues that all knowledge is an hypothesis since nothing can ever be ultimately proved; Submitted to the Knowledge Engineering Review page 2 of 73 our currently believed ideas are merely those that have survive active attempts to refute them [89]. Knowledge representation theorists stress that KBs are...

Metalevel tools can support the software development process by automating the design of task- and application-specific tools. Dash is a metalevel tool that allows developers to generate domain-specific knowledge-acquisition tools from domain ontologies. Domain specialists use the knowledge-acquisition tools generated by dash to instantiate the concepts and relationships defined in the domain ontologies. The output of the knowledge-acquisition tools is a collection of instances that constitute the knowledge base for a knowledge-based system.

patterns developed by different developers can be different. The number of abstract patterns seems unbounded; practioners keep inventing new one. Practioners don't reuse each others' supposedly reusable abstractions. When we actually experiment with supposedly reusable patterns and productivity, (e.g. the Corbridge study) we see evidence to support the counter-intuitive conclusion that well-formed mature supposedly reusable patterns are less productive than no pattern at all. So, what is the appropriate use of the reuse patterns offered by (e.g.) GOF, GOV, Fowler, KADS, etc? We make two suggestions. Firstly, we should monitor OO patterns for -type problems. Secondly, we not use them as objective canonical versions of truth, but as an assistant in analysis and design. Monitoring Potential Problems with Patterns Reuse We hope we have, at the very least, motivated the need for experimentation to test if patterns are indeed reusable. This section describes a series of suc...

Situated cognition is not a mere philosophical concern: it has pragmatic implications for current practice in knowledge acquisition. Tools must move from being design-focused to being maintenance-focused. Reuse-based approaches (e.g. using problem solving methods) will fail unless the reused descriptions can be extensively modified to suit the new situation. Knowledge engineers must model not only descriptions of expert knowledge, but also the environment in which a knowledge base will perform. Descriptions of knowledge must be constantly re-evaluated. This re-evaluation process has implications for assessing representations 1.

input args: (D-SUBSTANCE-CONCEPT D-SUBSTANCE-CONCEPT) predicate: (LAMBDA (X Y) (OR (EQUAL (SLOT-VALUE X (QUOTE NAME)) (SLOT-VALUE Y (QUOTE NAME))) (MEMBER (SLOT-VALUE Y (QUOTE NAME)) (SUBSTANCE-SPECIALIZATIONS (SLOT-VALUE X (QUOTE NAME)))))) name: LESS-ABSTRACT input args: (D-SUBSTANCE-CONCEPT D-SUBSTANCE-CONCEPT) predicate: (LAMBDA (X Y) (OR (EQUAL (SLOT-VALUE X (QUOTE NAME)) (SLOT-VALUE Y (QUOTE NAME))) (MEMBER (SLOT-VALUE X (QUOTE NAME)) (SUBSTANCE-SPECIALIZATIONS (SLOT-VALUE Y (QUOTE NAME)))))) name: ROOT-SPECIALIZATION input args: (D-MEMORY-ROOT D-PROPERTY) output args: (LIST-OF D-MEMORY-NODE) truth table: ROOT-SPECIALIZATION-RELATION indexing relation: T name: NODE-SPECIALIZATION input args: (D-MEMORY-NODE D-VALUE) output args: (LIST-OF D-MEMORY-NODE) truth table: NODE-SPECIALIZATION-RELATION indexing relation: T name: VALUE-SPECIALIZATION input args: (D-VALUE) output args: (LIST-OF D-VALUE) truth table: VALUE-SPECIALIZATION-RELATION name: INDEXING input args: (D-MEMORY-NODE) out...

The work reported in this thesis is motivated by the belief that knowledge-based systems (KBS) research needs to focus more on users ’ needs and cater for the various decision situations in which users will find themselves. To build individual systems that cater for all the activities that may be needed is not feasible or desirable. The problems associated with capturing knowledge are well known and the ability to capture knowledge once and access and manipulate the knowledge in multiple ways is highly desirable. It adds value to the original knowledge and offers all the benefits associated with the reuse of resources. Thus, the problem becomes one of knowledge reuse. The research question pursued in this thesis is “can knowledge captured for one purpose, such as consultation, be reused to support a wide range of alternative purposes, such as critquing or tutoring, allowing the user to answer different types of questions according to their current circumstances”? Further, this question was to be answered in a situated cognition, dynamic knowledge framework. The system developed in this thesis is based on the Multiple Classification Ripple Down Rule (MCRDR) knowledge acquisition and representation technique. MCRDR is a form of casedbased

: A good methodology should be an accurate description of sound software engineering (SE) practice. Without empirically-supported method-ologies, we run the risk of using potentially inaccurate prescriptions of the software engineering process. We reject arguments that SE is unmeasurable. Related fields, such as knowledge acquisition, routinely perform repeatable experiments on specification development and maintenance. A sample of these results are presented here. For a devotee of the OO approach such as ourselves, these empirical results are very counterintuitive. They motivate our call for a thorough empirical investigations of all the truisms of objectoriented (OO) SE such as: (i) OO is better than functional decomposition; (ii) OO promotes re-use; (iii) OO programs are easier to maintain and have fewer errors than alternative approaches; and (iv) OO is currently our best technique for SE. As a starting point for these investigations, we include designs for several experiments. Man...