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Representation of something that simplifies some aspects of the full situation in order to improve comprehension and reasoning.

The concept of a model is key to all forms of architecture, and this is no less true of information architecture.

Various Car Models

In the pictures above various "Car Models" are shown. These take a variety of forms, each focused on different elements of "carness". A model is a success if it accurately and succinctly describes the "important" features, the content of the best models depend not on the thing being modeled but on what you want to do with it. So a if you are purchasing a new radio a schematic diagram of the electrics may be perfect, when you are fitting it you might want to know the physical layout of the wiring, and if you are working out how the vehicle behaves when thrown from an airplane both are completely irrelevant.

When working on more abstract models this is a crucial distinction. Often as an information architect you will mediate between subject experts and software developers, in this case both sides are liable to disagree with your model. Experts will claim "that's not how it really works", so we have to make them realise that it is not important to capture every single detail. Developers will, in contrast, claim that your model is too complex and has to be simplified, to them you have to explain why users require those extra features. Both groups need to understand that we want a model that is as simple as possible to get the job done, but no simpler.

As an Information Architect you will often be consolidating inconsistent descriptions from a range of stakeholders. Usually to create a consistent but incomplete description for the client. The temptation is to try and construct a logical data model too early. This should be left as late as possible, not only is there a good chance that one of the stakeholders will reveal unexpected complexities, but also you want to involve a data modeller who will be closely connected to the implementers.

Links to this page

The following pages link to here: Business Intelligence, Chaos Theory, Complexity, Data Model, Domain, Game Theory, Gathering Data, IA Best Practice, IA Rendition, Inference, Information Architecture, Pattern, Unified Modeling Language

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