10.11.1 Purpose
A concept model is used to organize the business vocabulary needed to consistently and thoroughly communicate the knowledge of a domain.
10.11.2 Description
A concept model starts with a glossary, which typically focuses on the core noun concepts of a domain. Concept models put a premium on high-quality, design independent definitions that are free of data or implementation biases. Concept models also emphasize rich vocabulary.
A concept model identifies the correct choice of terms to use in communications, including all business analysis information. It is especially important where high precision and subtle distinctions need to be made.
Concept models can be effective where:
- the enterprise seeks to organize, retain, build-on, manage, and communicate core knowledge,
- the initiative needs to capture large numbers of business rules,
- there is resistance from stakeholders about the perceived technical nature of data models, class diagrams, or data element nomenclature and definition,
- innovative solutions are sought when re-engineering business processes or other aspects of business capability, and
- the enterprise faces regulatory or compliance challenges.
A concept model differs from a data model. The goal of a concept model is to support the expression of natural language statements, and supply their semantics. Concept models are not intended to unify, codify, and simplify data.
Therefore the vocabulary included in a concept model is far richer, as suits knowledge-intensive domains. Concept models are often rendered graphically.
10.11.3 Elements
.1 Noun Concepts
The most basic concepts in a concept model are the noun concepts of the domain, which are simply “givens” for the space.
.2 Verb Concepts
Verb concepts provide basic structural connections between noun concepts. These verb concepts are given standard wordings, so they can be referenced unambiguously. These wordings by themselves are not necessarily sentences; rather, they are the building blocks of sentences (such as business rule statements). Sometimes verb concepts are derived, inferred, or computed by definitional rules. This is how new knowledge or information is built up from more basic facts.
.3 Other Connections
Since concept models must support rich meaning (semantics), other types of standard connections are used besides verb concepts.
These include but are not limited to:
- categorizations,
- classifications,
- partitive (whole-part) connections, and
- roles.
10.11.4 Usage Considerations
.1 Strengths
- Provide a business-friendly way to communicate with stakeholders about precise meanings and subtle distinctions.
- Is independent of data design biases and the often limited business vocabulary coverage of data models.
- Proves highly useful for white-collar, knowledge-rich, decision-laden business processes.
- Helps ensure that large numbers of business rules and complex decision tables are free of ambiguity and fit together cohesively.
.2 Limitations
- May set expectations too high about how much integration based on business semantics can be achieved on relatively short notice.
- Requires a specialized skill set based on the ability to think abstractly and nonprocedurally about know-how and knowledge.
- The knowledge-and-rule focus may be foreign to stakeholders.
- Requires tooling to actively support real-time use of standard business terminology in writing business rules, requirements, and other forms of business communication.
