|Research Blog - Customer Intelligence|
Just sneaked in under a year since last blog entry. It's also timely to review progress since the last entry. Briefly, I got confirmed in my PhD by the Committee. I am now going through Ethics approval and hope to start collecting data next month. I have a plan to finish this in two years, so I figure I'm about 3-6 months behind the ideal, which is about on target for most candidates.
More importantly, I have a much clearer view of what I want to do with my research, and how to get there. I also have a stronger grasp on this IS discipline and what it is about. (This my cue to start my rant.) It amazes me the things people research in this field - and what they leave alone. The concept of "information" for one. It seems to me that the "systems" side of things gets about 95% of the spotlight. People seem strangely reluctant to tackle "information". I regularly come into contact with researchers and gurus who state that "data and information are interchangable terms", or "information is data in context". Well, you'd expect that from a researcher who studies the work of SAP installers (ie interested in organisation, not content), but I even see it from the leading lights in my own sub-discipline of Information Quality (or Data Quality).
"Data" is to do with symbols. "Information" is to do with uncertainty. They are not the same thing.
Yes, "Information Science" (or what I think of as "Information Theory") has very little to do with "Information Systems". This must be quite a puzzle to people outside the field, perhaps arguing by analogy with "Chemistry" and "Chemical Engineering". But, I would be suprised if 10% of the people turning up to an IS conference could tell you anything at all about Information Theory. Engineers and economists are big on Information Theory, yet IS ignores it. This is a curious state of affairs, but I have a very crude explanation. Suppose you're interested in computers; if you're also interested in, and capable of handling, mathematical concepts, you do Computer Science. If you're not, you do Information Systems, and acquire a psychological or sociological reference discipline. I'm sure this does injustice to some researchers, but is probably broadly true. This situation impoverishes both fields. (I think that CS people are broadening their perspectives, especially the AI oriented researchers, via Cognitive Science.)