Christopher Alexander's 1965 essay (Part I & Part II and also Part I with all diagrams intact) has a great title, but deserves its status as a classic for its ideas. It argues that the elements of a city: the people, the buildings, the businesses, and their interrelations are not well represented by a mathematical tree structure but much better by a mathematical semi-lattice. The complex interrelations between these elements can be much better described by a structure that allows them to overlap.
Isn't this obvious? To me at least, only in hindsight. When I first read it I had one of those "Ah-Hah!" moments as the idea struck me. Of course it had to be that way, except I'd somehow never known it.
And to this day tree-patterned suburbs continue to be built around many urban cores, which suggests that it either isn't obvious to the planners either, or that Alexander was also correct in advancing the idea that people have a cognitive barrier to the representation of concepts in semi-lattice structures. Another cognitive problem to look out for I guess...
So, what has any of this got to do with information analysis? The lesson I get out of this is that I need to get the analytical framework right before I can hope to get anything useful out of my data, and any work I do based on the wrong framework is worse than useless.
And wider that that? That the systems that interest us most are richer and more complex that we find it easy to conceive. That seems like a good place to leave this first post.
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