A conceptual model
is a representation of a system that uses concepts and ideas to form said representation.Conceptual modeling
is used across many fields, ranging from the sciences to socioeconomics to software development.
When using a conceptual model
to represent abstract ideas, it's important to distinguish between a model of a concept versus a model that is conceptual. That is to say, a model is intrinsically a thing unto itself, but that model also contains a concept of what that model represents -- what a model is, as opposed to what a model represents.
Without diving too deep into the philosophical, recognizing these differences between the model itself and what it represents is critical to understanding the proper use of conceptual models
in the first place. It should come as no surprise, then, that conceptual models
are often used as an abstract representation of real world objects.
Throughout this article we'll explore what conceptual models
are, how they are most commonly implemented, as well as a few advantages and disadvantages of using conceptual models
in the realm of software development, so let's get to it!
As touched on above, conceptual modeling
is used as a way to describe physical or social aspects of the world in an abstract way. For example, in the realm of software development, a conceptual model
may be used to represent the relationships of entities within a database. Whether written down via text or diagrammed visually, such a conceptual model
can easily represent abstract concepts of the relationships between objects in the system, such as Users
and their relationship to Accounts
.
In fact, conceptual models
within a typical software development life cycle are often referred to as domain models
. A domain model
is a type of conceptual model
that incorporates representations of both behavior and data at the same time. As illustrated above, this often represents database entities, using simple diagramming techniques to illustrate 1-to-1
, 1-to-many
, and many-to-many
relationships within the system.
Overall, a conceptual model
should fulfill four fundamental objectives:
Applying these objectives to our example data model above, we can ascertain that a conceptual data model
should capture the key business entities (a person, place, concept, event, or thing about which the organization wants to collect data), as well as the relationships between these entities.
Due to the broad spectrum of concepts and inherent abstractness that it can represent, conceptual modeling
is used in a wide range of projects, across dozens of fields. Within the realm of software development, as we illustrated above, conceptual modeling
is most commonly used as a form of data modeling
; representing abstract business entities and the relationships therein.
The rise of rapid application development
represents another very common implementation of conceptual modeling
, which uses abstract models to represent development processes that are rapidly changing and being iterated upon. Furthermore, within each phase of rapid application development
, conceptual models
are typically used to communicate sub-concepts as well.
Even fundamental modeling practices are, by their very nature, forms of conceptual models
. One such example is the Unified Modeling Language
, which was created in the mid-90s, and is a general purpose modeling language that attempts to provide a standard method to visualize system design.
Throughout all the various implementations of conceptual models
, a few best practices have emerged. A conceptual model
should:
In spite of the name, conceptual models
are not merely conceptual, they are frequently put to use in real-world scenarios. The Federal Emergency Management Agency
(FEMA
) used conceptual modeling
to develop Emergency Response Management
systems, as have other vital institutions including the U.S. Missile Defense Agency
and the National Institute of Standards and Technology
.
Since conceptual models
are merely representations of abstract concepts and their respective relationships, the potential advantages of implementing a conceptual model
are many, but largely depend on your own ability to devise a strong model in the first place. Generally speaking, the primary advantages of a conceptual model
include:
conceptual model
can help ensure that there are fewer surprises down the road, where entities or relationships might otherwise have been neglected or forgotten.conceptual model
can be used as a way to define project scope, which assists with time management and scheduling.conceptual model
. Conceptual models
serve as a great jumping-off point from which more concrete models can be created, such as logical data models
and the like.Conceptual models
serve as a great tool by providing a high-level understanding of a system throughout the software development life cycle. This can be particularly beneficial for managers and executives, who may not be dealing directly with coding or implementation, but require a solid understanding of the system and the relationships therein.Since a conceptual model
is so abstract, and thus, is only as useful as you make it, there can be a few disadvantages or caveats to watch out for when implementing your own conceptual model
:
conceptual models
can (and should) be adaptive, proper creation and maintenance of a conceptual model
requires a fundamental and robust understanding of the project, along with all associated entities and relationships.conceptual model
may lead to massive time waste and potential sunk costs, where development and planning have largely gone astray of what was actually necessary in the first place.conceptual modeling
is used to represent such abstract entities and their relationships, it's possible to create clashes between various components. In this case, a clash simply indicates that one component may conflict with another component, somewhere down the line. This may be seen when design
or coding
clash with deployment
, as the initial assumptions of scaling during design
and coding
were proven wrong when actual deployment
occurred.conceptual models
are not inherently ill-suited for large applications, it can be challenging to develop and maintain a proper conceptual model
for particularly complex projects, as the number of potential issues, or clashes
, will grow exponentially as the system size increases.