A New View of Data
By: Hal Reid
| (Feb 08, 2006) |
Data are now the basic raw material that will drive
progress, innovation and profit. We need to thoroughly grasp the end
products that will be created from them.
An entire special
edition of Newsweek (December 2005/February 2006) was
dedicated to
the “Knowledge Revolution.” The message is that those with the most
knowledge will be the dominate players in business, politics and
science in this century. Newsweek proposes that “victory will
go to the
smartest” and there will no awards for being the dumbest or the less
smart.
Several efforts have been made to represent this view of data, showing
a path moving data as a raw material, transformed into knowledge and
ultimately into wisdom.
While I think this is a noble portrayal, it is limited and perhaps not
as well thought out as it might be. The path may be accurate for the
data themselves (data to knowledge), but it does not show data getting
to the point where there is a level of understanding to make decisions
or generate action.
Why? First, the achievement of wisdom is not a trivial undertaking. It
takes years, decades or a lifetime to achieve wisdom - and it is a fact
that very few of us are wise. So a predictive, repetitive flow cannot
be established to produce wisdom. Second, knowledge by itself is not an
end - possessing knowledge does not guarantee that you can do anything
with it. There are probably some classic examples of professors (maybe
you knew some at school) who certainly had the knowledge, but just
couldn’t apply it. So we can establish that wisdom is a sometimes thing
and knowledge alone is not enough.
Rather than knowledge or wisdom, a better end product would be
understanding. Understanding provides the means to act on knowledge and
therefore, create, innovate, build or establish.
Because of today’s rate of change and innovation, we all have a
pressing need to stay current. In order to remain viable in this new
world, we need a consistent, reliable, accurate and rapid process to
move data from raw material to understanding and perhaps, occasionally
into wisdom.
But even understanding may not be enough. We may need some predictive
modeling to help identify options. It is important to have answers to
questions such as, “what are the possible scenarios given what I know
now?” or “Are there probabilities I can weigh?” Without modeling, data
to understanding is not a complete process. All decisions at any level
have several possible outcomes and without considering them,
understanding is not complete.
Data, or rather the correct data, has become the new crude oil powering
the next information age. Certainly, we would all like to have an
endless supply of cheap Texas light sweet crude. But as our expectation
and demand for higher quality and more precise data rise, the tolerance
for anything less will be pretty low. This new intolerance level will
apply to decisions and actions as well. It will also have to include
appreciation for intuitively knowing when the data is wrong and making
decision based on “gut feel.”
It is obvious that understanding based on the wrong core data will
produce the wrong information. (The old “garbage in/garbage out”
model.) With the wrong knowledge and the wrong understanding,
ultimately the wrong decision will be made, and of course, wisdom will
never be achieved.
What is certainty is that with the speed of change and innovation
increasing, bad decisions will put you out of the race sooner. The new
business problem is, with things moving faster, it will now take less
time to win and even less time to lose, and the difference may be just
a one or a zero.
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| Trough Wittgenstein we know the certainty means idea+fact and idea+fact=visualization, i.e., the logic in the lived experience. The wisdom need this logic positivism. Thanks! |
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| Some well taken remarks but although concern over data quality is mentioned I feel a need, once again, to point out the general low level of knowledge of spatial data among all these users. Again and again I have encountered the "maps = truth" view of spatial data that can easily undermine the process discussed here. Although falling down is part of growing up, the ability to anticipate possible failure can be acquired in less painful ways! |
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| If we really want to compel a revolution in information sharing, stop assigning value to data. When something has value, there's reason to expect compensation for an exchange. Compensation requires contracts (express or implied) that further slow the exchange. If every public holder of content decided to treat data as a consumable like toilet paper and electricity, the barriers to exchange would fall away. Couple that with the fact (yes, fact) there is virtually no secondary market for data, unless you're adding value. And 99% of all public GIS programs are ill-equipped or legally prevented from doing so. Data should be valueless...not valuable. Only then will REAL information sharing take off. |
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