[Sigia-l] Re:Serious Discussion of IA Research?

[Patrick Debois]

I guess this discussion show some different angles on how people look 
upon IA.
-Is it a science which needs its proper research, or is more of an 
applied science (organizing things from other sciences)
-Is it only focusing on information as the essence or information in a 
broader perspective (organizing, making it work)

Let me make little comparison with a construction architect. He needs to 
be a versatile person to get the job well done:
-know things about design (what looks nice)
-know how to make things pratical (usability,~ findability)
-know things about human behaviour (should the kitchen be near the 
living room)
-know things about psychology (what colours depresses people, how to 
create effect of large rooms)
-know things about socially (are the neighbours going to complain about 
the large wall, can we see in the neighbours bed room ;-)
-know what building materials exist and how they relate (make it wood, 
plastic)
-know what things cost and making it a cost effective design (sure you 
want it in gold, but that would cost to much)
-guide constructor companies to making the correct decisions
-being a project manager to coordinate the whole process

The key-note here is to know a bit of everything, but still enough to be 
able to talk to each party as an equal partner. So this means other 
people usually now more about their field than we do. Does that mean we 
are absolete? No, because we help to get the balance in everything, And 
sure people will get mad about our advice (the system engineer going 
crazy about the resources needed for the UI).

But back to the original subject: How would you qualify about research 
in IA? Again how would you do it for Construction architecture? It also 
draws upon different domains and sometimes has to wait until concepts 
get through to people or products exist. Does that mean it lacks 
research? I tend to think that construction architecture is more about 
patterns, combining skills off different fields. Presenting that some 
patterns work and others don't (antipatterns) would be very usefull to 
the IA community especially focusing on Cases and lessons learned. 
Explaining these things also does not qualify for exact science but 
draws on exact sciences and non-exact.

In no other sector companies would re-organize their company more as in 
IT. It is not because of the changing technology, but because  things 
went bad. Because most people can only think limited in a few dimensions 
(f.i. cost, revenue but not about employee satisfaction). The answer is 
that as long as you keep a balance between different related things it 
would work, but still you need to find the correct balance. Think about, 
if you jump out of a building and people are holding a blanket to catch 
you, you would make sure they would pull at it in the correct way and 
with the correct strength.

Drawing the analogy with the corporate websites, how often do you see 
that people rebuilt because one of the "dimensions" was bad. (was it bad 
colours, bad servers, bad UI ..) So that's were IA comes in, in limiting 
the mistakes made and finding a balance between all the related areas to 
make things work.

As an engineer this is what attracts me to IA. Instead of only handling 
some dimensions (products, timeframe,technology) and hoping other 
aspects are under control (human behaviour, user specs), it makes clear 
that you need to read and know much more. He i even went to a course 
Emotional Intelligence as a techie ;-)

Must say i enjoyed this thread as first starter to this list ;-) And a 
big thanks to PeterV to initiating it. It shows once againg that there 
is no exact definition of IA.