In Silico Hypothesis Discovery - Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare - page 128

Optional Feedback Cycle(s)

1 2 3 4

System
Implementation and
Refinement

Knowledge
Acquisition (KA)

Knowledge
Representation (KR)

Verification and
Validation

Intelligent
Agent

Fig. 8.5 Overview of the Knowledge Engineering ( KE ) process, consisting of knowledge acquisi-
tion ( KA ), knowledge representation ( KR ), system implementation and refi nement, and the verifi -
cation and validation of those systems (numbered per the steps enumerated in Sect. 8.2.1 ). Of note,
there is an optional feedback mechanism from the verifi cation and validation results back to the
initial KA component, which helps to inform subsequent KA activities and the refi nement of exist-
ing knowledge bases

With regards to the fi nal step of the KE process (verifi cation and valida-
tion), the reference standards used to evaluate the performance of an intelligent
agent can include expert performance measures, requirements acquired before
designing the knowledge-based system and/or requirements that were realized
upon implementation of the knowledge-based system. In this context, verifi ca-
tion is the process of ensuring that the knowledge-based system meets the initial
requirements of the potential end-user community. In comparison, validation
is the process of ensuring that the knowledge-based system meets the realized
requirements of the end-user community once a knowledge-based system has
been implemented [ 23 ].

8.2.2 Theoretical Frameworks for KE

Underlying the KE process is a set of theories concerning the ability to acquire and
represent knowledge in a computable format, which is known as the physical sym-
bol hypothesis. First proposed by Newell and Simon [ 24 ], and expanded upon by
Compton and Jansen [ 25 ], the physical symbol hypothesis argues that knowledge
consists of both symbols of reality, and relationships between those symbols. This
defi nition of knowledge thus allows for the creation of “physical symbol systems”
(e.g., conceptual knowledge collections), which are defi ned as:

…a set of entities, called symbols, which are physical patterns that can occur as compo-
nents of another type of entity called an expression (or symbol structure). Thus, a symbol
structure is composed of a number of instances (or tokens) of symbols related in some
physical way (such as one token being next to another). At any instant of time the system
will contain a collection of these symbol structures. [ 26 ]