For my JungleDragon project I was facing an enormous information architecture challenge. Starting out with a classic tagging model for content classification, I had strong desires to overcome some of the drawbacks of such a folksonomy:

• Tags have no/weak relationships with each other since they are just user-invented text labels. This means that it is not possible to use tags to position content in a hierarchical tree
• Tags have no meaning or rich context other than the label itself. If I tag something as "Africa" the system does not know that this is a continent. If it would know this it could for example display Africa on a globe. 
• Due to the flexible nature of tagging, they introduce data quality problems: tags not used or not used correctly, misspellings, synonyms, etc.

I needed to bring the worlds of folksonomy and taxonomy together. To combine the strengths of both, whilst minimizing their cons. If this is not difficult enough already, I needed the added strength of a taxonomy structure to be loosely coupled to the community software (ImageDragon).

A challenge so it is. But I managed to do all of the above, and in this article I am explaining you how. Given the length of the article, I have published it as a PDF:

Download Tagonomy: Taxonomy meets Folksonomy

Solving this challenge and writing this article has been a lot of work. I hope you will find the interest and patience to absorb it. I am convinced that the solution beholds a lot of power as I will show you over time. For now, enjoy, and don't forget to rate and comment back here. It keeps me going in writing more articles.

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