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July 31, 2011

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Joey Carlisle

As somebody who has done a lot of statistics before, I found this very refreshing. This is a fantastic way to explain to somebody philosophically how one will be able to make sense of raw data and turn it into something that is meaningful.

Did I understand your article correctly?

efi

Nice essay on necessary technology for knowledge representation in a text resource based and NLP-ridden environment!

For digging deeper into the ideas discussed in your last paragraphs, I recommend reading about the Topic Maps standard.

Topic Maps aim to be a rather "pragmatic philosophical technology" as you call it. - And they are a bit different from what currently buzzes as the "Semantic Web". Especially interesting is their use of identifiers and their identity merging concept based on that identifiers. Also worth a glance should be the approach modelling of statements (with fixed semantics) entirely based on "topics" - digital proxys for real world entities, concepts and other constructs of thought and reality.

www.google.com/accounts/o8/id?id=AItOawnCYF4H7VHqH2Bl7SZt1Ev7rDFCr0Vx4f4

Great essay! Topic maps weren't the first effort to address the issues you raise but (personally biased as a topic map standard editor) I too would recommend reading about them. My blog, Another Word For It, http://tm.durusau.net focuses on topic maps and semantic diversity.

The one point about subjects that I would make explicit is that the ways we talk about subjects are also composed of subjects. That is if I am identified by name = "Patrick Durusau", then "name" is just as much a subject as the subject we are trying to identify. That realization makes it easier to create mappings between formats/data structures (which are composed of subjects). Or more bluntly, no format or data structure is final or universal.

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