Conceptual model
Semantics is fundamentally a study of concepts, the meaning that thinking beings give to various elements of their experience.
The value of a conceptual model is usually directly proportional to how well it corresponds to a past, present, future, actual or potential state of affairs.
[3] In artificial intelligence, conceptual models and conceptual graphs are used for building expert systems and knowledge-based systems; here the analysts are concerned to represent expert opinion on what is true not their own ideas on what is true.
Conceptual modeling is the activity of formally describing some aspects of the physical and social world around us for the purposes of understanding and communication.
[4] A conceptual model's primary objective is to convey the fundamental principles and basic functionality of the system which it represents.
[5] The conceptual model plays an important role in the overall system development life cycle.
Figure 1[6] below, depicts the role of the conceptual model in a typical system development scheme.
Those weak links in the system design and development process can be traced to improper execution of the fundamental objectives of conceptual modeling.
Entity-relationship diagrams, which are a product of executing the ERM technique, are normally used to represent database models and information systems.
More specifically, the EPC is made up of events which define what state a process is in or the rules by which it operates.
The EPC technique can be applied to business practices such as resource planning, process improvement, and logistics.
JEFFF is intended to focus more on the higher level development planning that precedes a project's initialization.
The JAD process calls for a series of workshops in which the participants work to identify, define, and generally map a successful project from conception to completion.
To alleviate this issue, and shed some light on what to consider when selecting an appropriate conceptual modeling technique, the framework proposed by Gemino and Wand will be discussed in the following text.
However, before evaluating the effectiveness of a conceptual modeling technique for a particular application, an important concept must be understood; Comparing conceptual models by way of specifically focusing on their graphical or top level representations is shortsighted.
Gemino and Wand make a good point when arguing that the emphasis should be placed on a conceptual modeling language when choosing an appropriate technique.
The presentation method for selection purposes would focus on the technique's ability to represent the model at the intended level of depth and detail.
The conceptual model language task will further allow an appropriate technique to be chosen.
Gemino and Wand go on to expand the affected variable content of their proposed framework by considering the focus of observation and the criterion for comparison.
The criterion for comparison would weigh the ability of the conceptual modeling technique to be efficient or effective.
[13] This is to say that it explains the answers to fundamental questions such as whether matter and mind are one or two substances; or whether or not humans have free will.
This enables a pragmatic modelling but reduces the flexibility, as only the predefined semantic concepts can be used.
Akin to entity-relationship models, custom categories or sketches can be directly translated into database schemas.
A scientific model represents empirical objects, phenomena, and physical processes in a logical way.
The aim of these attempts is to construct a formal system that will not produce theoretical consequences that are contrary to what is found in reality.
Predictions or other statements drawn from such a formal system mirror or map the real world only insofar as these scientific models are true.
A nonparametric model has a distribution function without parameters, such as in bootstrapping, and is only loosely confined by assumptions.
The economic model is a simplified framework designed to illustrate complex processes, often but not always using mathematical techniques.
Entity–relationship models have had wide application in the building of information systems intended to support activities involving objects and events in the real world.
