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In the exercise, I describe an AS-IS model (in the spirit of the old Business Process Re-engineering techniques) that uses the RDF and metadata paradigm. However, it is our opinion that this paradigm will never extend beyond the acquisition of algorithmic and structured context. It is a mere matter of category. As the scholar Robert Rosen points out, there is a category error in thinking that structured and algorithmic context is fully representable of all natural contexts. Sometimes correspondences can be established and there will be utility, but it is not possible to predict when the correspondences will fail. The reason for this is simple. The world has a unstructured aspect that is not fully captured by formal models. These models depend on descriptive reduction to well defined and stationary structure.

Algorithmic context is context held completely within a formal model, even if the algorithms are part of distributed and so-called emergent computing. It can be far removed from the real world context that it is designed to reflect. To address the knowledge sciences issues, one must move from the representation of structured context and towards the representation of unstructured context.