What are Knowledge Attributes?

Consider a book, a traditional source of knowledge.

It has many physical attributes: its length, width, and other dimensions, its weight, type of binding, whether it has a removable jacket, whether it has a built-in bookmark, etc.

A book also has several data-level attributes: its size in words, the number of illustrations it contains, what writing system and fonts are used in it, whether it is in multiple volumes, other formats (audio, e-book, ...) in which it is available, etc.

A book has many more attributes at the information level: its title, names of authors, the publisher, year when it was published, edition, number of pages in it, its ISBN number, cover price and currency, its table of contents, etc.

Conventional knowledge management systems such as library and bookstore management systems as well as most KM solutions make good use of many of the above attributes. However, they barely touch the next level: attributes at the knowledge level.

Knowledge attributes of a book include its subject matter (a.k.a. topic), its intended readership, the background knowledge it assumes, how it is meant to be read or taught, how well it explains some concepts, how popular it is, what reviews it has received, how is it rated by particular user communities, how its matter is related to knowledge contained in other sources, etc.

Notice that some of the above knowledge attributes are often contained in the book in textual form such as in a preface or foreword, and as such aren't useful to systems. What we need are structured representations of knowledge attributes of which our library/bookstore/e-commerce/KM systems can make good use.

How else could it pick the right knowledge source to satisfy a user's knowledge need effectively? By counting hyperlinks? By launching Clusty the Clown? I for one don't think so.

Without knowledge attributes, KM will continue to barely touch the semantic or knowledge level.