Marcus,
Now here, I would argue that gravel is a very bad metaphor for base pairs. The salient properties of the elements of gravel is that the particles are more or less uniform in shape free to move with respect to one another , and not easily compressed and broken. Base pairs are of significantly different shapes, bind together importantly with each other and other substances, do not move freely with respect to one another, and can readily be crushed and broken. So, the argument would run, thinking of base pairs as gravel will lead to more errors than thinking of them as, say, dance partners in an elaborate contra-dance.
Nick .
Nicholas S. Thompson
Emeritus Professor of Psychology and Biology
Clark University
From: Friam [mailto:[hidden email]] On Behalf Of Marcus Daniels
Sent: Sunday, September 11, 2016 10:33 AM
To: The Friday Morning Applied Complexity Coffee Group <[hidden email]>
Subject: Re: [FRIAM] speaking of analytics - data mining
In anguish, the people invented an entire new profession - Data Mining - that essentially 'crushed' the data stores creating gravel composed of individual datums and put the result in a different, more malleable matrix — live gravel in cement and sand and water (before the matrix dries). From this new medium the people would pluck bits of gravel and place them next to each other an proclaim, "Look! Information!"
That’s a funny story, but it overlooks the fact that sometimes all there is, is bits of gravel. Like 3 billion base pairs of the human genome. There’s no “teenage clerk” that has looked at most of it in detail or has much of any intuition about what it does. Similarly, there’s no Rosetta stone for the nuances of why different whale species vocalize one way or another. It’s just a process of throwing ideas against the wall and see if they stick. Computers can do that more rapidly than humans can, at least. Data mining isn’t just for developers in industry that can’t figure out how to decompose tables or make indices.
There are many approaches to modeling information, database normalization is one of many. Information and category theory contribute other approaches.
Marcus
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