Constructing models - simplified descriptions of the real world - is central to all areas of science. By identifying the relevant variables of a system, models help us to understand the world around us and its reaction to our actions.
Models can come in many forms, they can be a narrative in written form, an mathematical analysis, computational, or a mixture of those. Models of all kinds have in common though that identifying the relevant ingredients and understanding the limits of their applicability is of utmost importance for their usefulness.
In all cases one has to make a trade-off between generality and precision, limiting either predictability or applicability. The building of models - in areas of large data sets especially computational models - is a central ingredient to our understanding of nature. Models are where the scientific method can separate the wheat from the chaff, and where we construct tools that ideally can be used by a wide array of people.
At the Lightcone Institute we want to promote the basic knowledge of model building to improve application, prediction and communication of research results.
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Last Updated ( Sunday, 27 July 2008 )
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