The KM / IM Debate

I don’t really see any worthwhile debate – the buzz of turf-wars may keep the subjects in the headlines, but there is no definitional problem not already adequately sorted by the data > information > knowledge > wisdom stack. (Thanks to David Gurteen’s tweets prompting this post.)

Anyone with strong allegiance to any one part of the stack will widen (blur) their definitions into the adjacent layers, but anyone interested in the whole stack can see worthwhile (pragmatic and valuable) distinctions, each being a layer of patterning built on the previous layer.

• data – is about significant difference – bits and bytes being distinct from one another, at any level of granularity from fundamental physics upwards to whole books and libraries.
• information – is about the significance of those data differences, their semantics – what the patterns of data mean.
• knowledge – is about how that information is applied to add value, valuable patterns of use, applied information.
• wisdom – is about understanding (knowing, experiencing, appreciating) value and the fact that it depends on how the whole stack works, and the pragmatic need to balance interests and priorities across (two-way) interactions between all levels of the stack. A more “holistic” view, if that’s not a dirty word.

Personally, like anyone else who’s given the matter any thought I guess, the aims are always towards the higher level – wisdom – whatever our (current) level of activity as a practitioner. In my particular case as an engineer I started and worked for 20 years in the applied space – learning and using knowledge of how to apply information to specific ends. It’s all about “decision-support” of course – all worthwhile activities involve decisions, so that truism in itself doesn’t add much to any definitions. One of the things you learn – wisdom you gain – is that those practitioners in the data and information layers can, by inadvertent presumptions about decision-making and use-in-action, create constraints on usage in the knowledge layers. So for the last 12 years or so, I shifted my focus down a couple of layers to understand the presumptions and how (unnecessary) constraints can arise.

I have to say in the process, I’ve developed a huge respect for librarians. Anyone who thinks it’s “just” thorough record keeping – some clerical admin task – misses the need for good strategies and architectures for how data, meta-data, information and relations between these are organized. We benefit from some types of “constraint”. The more virtual our libraries become, the more we need to avoid librarianship becoming a dying art.

Ubiquitous, real-time, interactive connectivity is not necessarily entirely good in and of itself.