Mt. Everest - data to wisdom

We use the words “data”, “in­form­a­tion”, and “know­ledge” in in­form­at­ics-re­lated con­ver­sa­tions all the time. Do we know what we mean?

Some days, I don’t think so.

The field of Know­ledge Man­age­ment has defined these terms rig­or­ously. The gen­er­al view is that data is at the low­est level of the stack, with know­ledge at the top. As you go up the stack, you add con­text, ab­strac­tion, and syn­thes­is. And yet I fre­quently find that people have dif­fer­ent no­tions in their heads about what these terms really mean and how they are used. (In part be­cause when you read phrases like “con­text, ab­strac­tion and syn­thes­is”, you should think “what the hell does that mean?”) And even with rig­or­ous defin­i­tions, the terms over­lap and get con­fus­ing.

When people talk to each oth­er us­ing terms that are in­ter­preted dif­fer­ently by every­one in­volved, the con­ver­sa­tions are hope­less and the de­cisions are poor. (This drives me crazy. We do it all the time. One of the best things you can do in a com­plex dis­cus­sion is stop and say, “Let me make sure I un­der­stood you. Is this what you meant?”)

With “In­form­a­tion Li­fe­cycle Man­age­ment” (ILM), In­form­a­tion Ac­cess, and Or­gan­iz­a­tion­al Know­ledge all be­com­ing in­creas­ingly act­ive top­ics these days (and didn’t that hap­pen in the 80s too?), I looked around a bit to see if I could find use­ful defin­i­tions for these terms that were easi­er to ap­ply than the usu­al text­book ex­plan­a­tion.

I like real ex­amples that stick. I was quite happy to come across ex­amples in Wiki­pe­dia’s Data page that I think work wel, so I’m passing these along, with some ex­ten­sions.

Data:
The height of Mt. Everest. (Meas­ure­ments.)
In­form­a­tion:
A book on Mt. Everest geo­lo­gic­al char­ac­ter­ist­ics. A map of the Hi­m­alaya re­gion. (Col­lec­tions of meas­ure­ments and in­ter­pret­a­tions.)
Know­ledge:
A re­port con­tain­ing prac­tic­al in­form­a­tion on climb­ing Mt. Everest. Routes. Re­com­mend­a­tions. (Ana­lys­is and as­sess­ments.)
Wis­dom:
The in­stinct an ex­per­i­enced climb­ing guide uses, as­sess­ing weath­er, snow lines, and cli­ent con­di­tions in mak­ing a de­cision.

A book can con­tain as­pects of all of these. This is why dif­fer­en­ti­at­ing them can be so hard. (And let’s be real: some days you don’t need to dif­fer­en­ti­ate them. At every level of the stack - keep it if it’s use­ful. Get rid of it if it’s not. Make sure oth­ers can find and un­der­stand it.)

The ex­ten­sion in­to “wis­dom” is due in part to Steve Cleav­er, who found some ref­er­ence to this last year that I really liked – but then I lost. (Steve, if you ever read this, could you post the ref­er­ence in a com­ment?)

In NIBR, we have all kinds of chal­lenges with data, in­form­a­tion, know­ledge, and wis­dom. Chief among them:

  • Data: Keep­ing too much of it. Not keep­ing enough data about the data (metadata) to al­low us to con­tex­tu­al­ize it in­to know­ledge.
  • In­form­a­tion: Keep­ing too much of it - and yet not be­ing able to find it.
  • Know­ledge: Not cre­at­ing enough of it. Not cap­it­al­iz­ing on it. Con­fus­ing it with in­form­a­tion.
  • Wis­dom: Learn­ing how to re­cog­nize, cap­ture, share, and act on it.

We’re not alone… every sig­ni­fic­ant or­gan­iz­a­tion struggles with these. One could even say that the abil­ity to cap­ture and act on wis­dom is what defines an or­gan­iz­a­tion over time.

Who­ever gets this right wins.