Operational definition

Defining a concept in terms of specific, replicable actions or procedures

In his managerial and statistical writings, W. Edwards Deming placed great importance on the value of using operational definitions in all agreements in business. As he said:

"An operational definition is a procedure agreed upon for translation of a concept into measurement of some kind." – W. Edwards Deming
"There is no true value of any characteristic, state, or condition that is defined in terms of measurement or observation. Change of procedure for measurement (change of operational definition) or observation produces a new number." – W. Edwards Deming

Many times, issues are related to persistence and clarity of use of variables, functions, and so forth. Also, systems dependence is an issue. In brief, length (as a standard) has matter as its definitional basis. What pray tell can be used when standards are to be computationally framed?

One referenced project pulled together fluid experts, including some who were expert in the numeric modeling related to computational fluid dynamics, in a team with computer scientists. Essentially, it turned out that the computer guys did not know enough to weigh in as much as they would have liked. Thus, their role, to their chagrin, many times was "mere" programmer.

Some knowledge-based engineering projects experienced similarly that there is a trade-off between trying to teach programming to a domain expert versus getting a programmer to understand the intricacies of a domain. That, of course, depends upon the domain. In short, any team member has to decide which side of the coin to spend one's time.

In advanced modeling, with the requisite computational support such as knowledge-based engineering, mappings must be maintained between a real-world object, its abstracted counterparts as defined by the domain and its experts, and the computer models. Mismatches between domain models and their computational mirrors can raise issues apropos this topic. Techniques that allow the flexible modeling required for many hard problems must resolve issues of identity, type, etc. which then lead to methods, such as duck typing. Many domains, with a numerics focus, use limit theory, of various sorts, to overcome the duck test necessity with varying degrees of success. Yet, with that, issues still remain as representational frameworks bear heavily on what we can know.

Of these, indentation hardness itself leads to many operational definitions, the most important of which are:

In all these, a process is defined for loading the indenter, measuring the resulting indentation, and calculating a hardness number. Each of these three sequences of measurement operations produces numbers that are consistent with our subjective idea of hardness. The harder the material to our informal perception, the greater the number it will achieve on our respective hardness scales. Furthermore, experimental results obtained using these measurement methods has shown that the hardness number can be used to predict the stress required to permanently deform steel, a characteristic that fits in well with our idea of resistance to permanent deformation. However, there is not always a simple relationship between the various hardness scales. Vickers and Rockwell hardness numbers exhibit qualitatively different behaviour when used to describe some materials and phenomena.