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{Whatever objects you are studying - e.g. people, artifacts or processes - usually your first target will be to describe the object(s). For presenting this description scientists often use a model. A model is thus a theoretical image of the object, in other words, a conceptual structure that is isomorphic with the object.
The principal reason for making a model of the object is that it helps analyzing data obtained from the object and finding the answer to the researcher's problem. A scientific model need not enumerate all the properties of every object that is being studied. On the contrary, you will normally want to take into account only the "interesting" properties, i.e. those that are related to the purpose of your study.
Limiting the amount of data becomes especially important when the study concerns not one singular object but a class of objects. Without effective delimitation the amount of data would expand too much. Instead, if you can restrict your view to just the essential measurements, attributes and properties of the object, it will help you to manage a large material and unearth the answers to your questions.
A model is an excellent means to present those patterns or characteristics which are common to several or all cases in the material of study. Because these patterns are invariable from case to case, they are often called invariances. In research these are invaluable because they can often be generalized, i.e. we can assume that they are true not only for the cases that have been studied, but elsewhere (in certain limits) as well. That is why they can often be used for predicting the future development of the object of study, or of other similar objects.
Because the model is made to be an image of the object of study, its indispensable material will be observations and measurements from the object of study. Sometimes - but not very often - no other material is available to help you in constructing a model because very little or nothing is known about the object in advance. In such a situation of exploratory research you have to collect all the substance for the model by meticulously examining the objects. Often it will be laborious, because much material will have to be collected and in the beginning you do not quite well know which data are important and which are not.
Fortunately, today the normal situation at the outset of a novel research project is that you already know quite a lot about your object, and in the best case there are already published research reports where you can find models that have been used successfully by earlier researchers in the field. At least you will find vocabulary and instruments - such as concepts, definitions, and methods of measurement - for building a new variant of model that serves your purposes. This quite usual approach of study is discussed elsewhere under the title Research on the Basis of Earlier Theory.
| Theory consists of... |
...models which consist of... |
...concepts and... |
| ...relations between concepts, | ||
| and there must also be a few empirical definitions. | ||
The researcher has complete freedom to select the modelling language in such a way that it clearly conveys the essential features of the objects. In sciences, several types of model languages are used. A researcher familiar with fine arts may notice that more than one of these scientific presentation languages have some resemblance with some genres of artistic presentation. This is not astonishing, as one cardinal goal of art is "to disclose what is invisible", in other words, to express an invariance behind conventional, visible things.
When selecting the most suitable modelling language, the researcher should remember that models are needed in several different phases of the project. When gathering empirical data by observation and measurement the model must be able to handle individual cases, but in the analysis phase a conceptual model which is also generalizable can be more effective. Finally, presenting the findings of analysis so that they can be applied to practice may require a straightforward presentation that can be understood by the layman users. It can be difficult to find a single language of presentation which would meet all these requirements. Sometimes it is possible to use different styles of presentation in the successive phases of a research project.}
Usual scientific model languages include,
In addition to the above types, researchers invent new model types all the time. This is quite permissible if the researcher's aim is to give the reader a clear picture of the object of the study. The researcher must, however, make sure that his audience has a chance to understand the language of the model. When necessary, the researcher may explain the unusual symbols.
{In the following the above mentioned types of models are discussed, including some remarks on the presentation of four sometimes problematic dimensions of models: time, variation between cases, the degree of uncertainty, and the normative aspect, if there is one.}
Is the model informative or normative? Informative study means an attempt to unearth, and perhaps explain, the actual state of the object at the time of its inspection. An informative research project (upper diagram on the right) includes no attempt to change this state of things. Indeed, the researcher often tries hard to avoid disturbing the object in any way, because it could modify the activity of the object and spoil the possibility of getting an authentic picture of the object. The findings of an informative study are intended to enlarge our knowledge about the object, its theory; they shall not be used to practical purposes, at least immediately.
As a contrast, normative study and model (lower figure) purports to discover ways to improve the object or similar later objects, by pointing out possible improvements for the object of study. Note that normative models are also extensively used by designers. A designer starts his work in the world of concepts, making there conceptual plans and projects for new products.
Beside developing new products, normative models are often used for improving activities, such as the material and monetary flows of a business, or any existing procedure of work.
There is no fundamental difference between informative and normative models. Many informative models can be made normative simply by adding an evaluative dimension, such as 'capacity', 'durability' or 'price'. When this is not feasible, you might consider making two or more models, one of which represents the preferable alternative.}
A problem with scientific models is often the abundance of detail, which makes the model too large and difficult to grasp. One remedy to this problem is hypermedia presentation. The basic model then includes only the most important general structures and a number of links to the detailed texts or other material which are placed in separate files. Gaines and Shaw have published a WWW page on these questions.
Describing the object with words of a natural language must be the most usual type of a scientific model. Historically, it was probably poetry and novel writing that served as prototypes for this method. Now, it is popular e.g. in history and behavioural sciences. Given the fact that adjectives are the cornerstone of verbal description, this type of study often goes by the name of "qualitative" research.
Verbal presentation is so illustrative and versatile that it is often used in the final study report when the original, for example mathematical model needs to be clarified and explained. It is especially suitable for presenting comparison or evolution of objects, causal relationships and other explanations of processes.
The dimension of time, which appears in dynamic invariances, can easily be presented verbally with phrases like "grow up", "evolve", "the trend is that..." etc.
Variation can be presented verbally: "Objects were generally like this, but some were..." - "As a contrast, a small minority think that"... etc. Also for uncertainty or probable error there are words: "approximately", "usually" etc. If such phrases seem too vague it is always possible to insert more exact complementary models like percentages or tables.
{Normative written language presentation is usual in the early phases of designing a new product. It takes shape as a written list of requirements, examples of which can be found in the chapters on Design Driver and on Product Concept.}
An icon model gives a pictorial representation of the object.
The object is usually presented as a two dimensional projection; the
scale and the colours are often changed, the less interesting details are
omitted, and the presentation concentrates on those details or attributes
of the object that are interesting -- these are often such static invariances that are common to all or most of the
objects which were studied.
Today we have excellent instruments, like cameras and video recorders, to facilitate the task of making pictures. However, photographs and recordings made with these machines often include a great amount of detail, thus hiding the theoretically more interesting features of the objects. Therefore, in research projects, the method of drawing is often preferred. On the left is depicted a coffee pot and some static invariances (circles etc.) that seem to govern its shape (Gunzenhäuser p. 203).
When selecting the method of presentation, one possibility is to adopt the
drawing methods of designers. This includes views and sections from
one or more directions drawn to a scale. However, such methods are
designed for the manufacture of objects. For the purposes of
research it can be more rewarding to develop a method of
depicting which emphasizes exactly those features of the objects which
are interesting. This can be accomplished, for example, by an ink
drawing in perspective where the not essential details are simply omitted.
In some fields of study, there are standard methods of depiction. Below on the left, there is an example of a usual archaeological method of presenting pottery in such a way that one picture portrays both outward and inward decoration and also the cross section.
The dimension of time, for example the historical evolution of a type of product, is not quite easy to be presented on two-dimensional medias like paper, because two dimensions of the image are already reserved for presenting the physical shape. A usual solution is to make a series of pictures like the succession of car models in Raymond Loewy's book Industrial Design, above. (See the complete series.)
Another solution, made possible by modern medias of information, is the animated picture of TV or computer.
Uncertainty. An advantage of the method of drawing by hand is that if something is not known exactly you can draw it in thin, dotted or blurred lines, without giving the wrong idea of precision. An example is the picture (on the left) of an ancient pot: the shape of the missing handle is not known and in the picture it is presented in dotted lines.
Variation between objects can sometimes be presented by superimposing several images. In the diagram on the right, Sture Balgård shows several cross-sections of old buildings in Härnösand. He has also added into the same model an invariance which he has found existing in the objects: they follow uniform proportions of width and height (the red line) with just a few exceptions.
{Normative icon models that are used in the development of new products take the shape of drawings and three-dimensional mock-ups. In the beginning these are often blurred sketches, from which the initial ambiguity gets gradually expelled during the design process. On the right here, we have an example of a sketch in which the exact form of the design is not clear yet. (From Keiski, 1996, p.136; the project produced eventually a new type of kitchen.) Later on the product development project proceeds to prototypes and their evaluation. These operations make use of more and more realistic illustrations, mock-ups, virtual prototypes and interactive models described in Presenting the Draft and Prototype.}
The placing of the elements in a topological model reflects the structure of the object. This model can be used for conceptual structures as well as for presenting holistic classifications of objects.
An example is on the right, where Shackel has analyzed the concept of usability of products. The model he has used is a logical tree.
Holistic models consist of physical events or specimens, like people or products. This presentation is particularly suitable for taxonomies, i.e. classifications. On the right is an example of a taxonomy of home furniture. Logical tree is perfect to its presentation, if each individual and every class belongs to no more than one superior class.
However, if a case, an individual or a class belongs to more than one class, a Venn diagram (on the left) might be a better presentation. Here, you can read from the model that you can place the dining table either to the living room or kitchen. (John Venn, 1834-1923, an English logician.)
The researcher should consider if the sizes of the symbols describing the elements should carry any meaning: for instance, does a big box in a picture denote that the class is numerous? Moreover, the shapes of symbols which in a typical Venn diagram mean nothing: should they?
It is up to the researcher to provide the reader with instructions as to
how to read the diagram, i.e. with an explanation of the symbolism in the
presentation.
How should you place the elements of a
topological model?
A meaning
can be assigned not only to the relative placing of the elements
but also to the lines or arrows connecting the elements: their width, colour
etc. Such options allow you to show simultaneously several different types of
relations between the elements of the model. For example the above
chart of a person's movements in a house can be amplified by adding the
direction of the motion (see figure on the left).
Moreover, influences and causal relationships are often presented
with arrows in a topological model. Examples.
A common problem with scientific models is that abundance of detail makes the model too large and difficult to grasp. One remedy to this problem is hypermedia presentation, for which topological models are well suited. The basic model includes then only the most important general structures and a number of links to the detailed texts or other material which are placed in separate files. Gaines and Shaw give many examples of such multi-layered structures.
The dimension of time, which appears in dynamic invariances, can easily be presented by letting the horizontal axis of the model indicate time. In this way you can present quite complex chains of events, for example the progress of work or circulation of information. On the right is a model of production process; elsewhere is shown a model of a research project.
Variation, subjective or objective, is not quite easy to show in a topological model. You might, for example, try varying the style or colour of the elements.
Uncertainty is also difficult because topological models usually give an undue impression of exactness. You could perhaps express uncertain relations with thin or dotted lines, for example.
Arithmetic models require that your data are measured with an arithmetic scale. There is a vast selection of mathematical models. You will often have great freedom when choosing the type of model; your data usually allows several alternatives and you should try to select the most illustrative one. For example, the traffic flow of the apartment shown above could be presented as an arithmetic table:
| The subject moved from | - the kitchen | - the living room | - the bathroom | - the lobby |
| to the kitchen: | . | 8 times | 9 times | 6 times |
| to the living room: | 7 times | . | 5 times | 5 times |
| to the bathroom: | 10 times | 5 times | . | 2 times |
| to the lobby: | 7 times | 4 times | 2 times | . |
Other common mathematical presentations include equations and diagrams.
If a model is constructed with a computerized programming language,
nothing prevents it from being extremely complicated if necessary for
simulating a complicated object of research. A single model may thus
combine arithmetic and Boolean calculations, time bound events and
conditional branches of processes; even random variation. In addition to
making such a large model for the computer, you often want to present a
simpler and more illustrative one, for example a topological one.
Sometimes you could consider dividing the original, clumsy model in
pieces. Example.
The dimension of time which appears in dynamic invariances, presents no problem in mathematical models because these are invariably capable of including several independent dimensions.
The same goes for subjective variation.
Objective variation and uncertainty. Mathematical models easily exaggerate the clarity and definition so that it by far exceeds the factual exactness of the empirical registration of facts. There are, however, arithmetical methods of expressing the precision, or the lack of it, in data. They include concepts like the error of measurement, moreover variation and significance of the measurements. There are also some graphical methods of presentation.
(Normative arithmetic models are often equations or graphs where one or more of the variables is evaluative, for example 'cost'. They often allow finding the optimum or the best one of alternatives. An example is the diagram on the right which helps finding an optimum for wall isolation. Their use is discussed on the page Theory of Design. }
Usually, the researcher assembles his model "on an empty table" using the elements offered by the modelling language he has chosen. But sometimes he may happen to find, in another environment, an invariant structure which logically resembles the object of study. The other, foreign structure or object can then perhaps be directly used as a model. Analogy refers thus to the procedure of transferring a model (i.e. copying and adjusting it) from a "system" to another. Analogy does not necessitate any specific language of modelling, on the contrary it allows importing models in any language of modelling.
Examples of analogous models used in research:
The method of analogy is easy to use, but it has serious drawbacks. It is difficult to present the uncertainty of the model or the variation between cases, and it stays unclear how generally valid the model is. Analogous presentation is, even at its best, relatively nebulous and is is often advisable, once you have found a suitable model, to define it anew with the help of concepts that relate to your object of study and not to the original setting of the model (by using empirical or nominal definitions).
Remember that the essence that you want to import into your project is only the invariance that the analogous model is expressing. Beside this invariance, the imported model usually contains much detail that relates to its original environment, which you have to clean out. You can then either replace the details with new ones describing your own object of study, or leave out the not interesting particulars definitely, thus enhancing the generality of your final model.
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September 15, 2005. Original location:
http://www2.uiah.fi/projects/metodi
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