[Sigia-l] RE: Data vs. Information

Tue Jan 7 00:31:20 EST 2003

Okay,

Maybe I can add a bit more here. There's some marvellous discussions 
going on here and I think we need to look at a slightly bigger picture. 
Folks keep mentioning that knowledge continuum and then only 
concentrate on the first half of it (data -- information) but it's a 
continuum, after all, and I don't think you can have part of it without 
all of it. That means that knowledge -- wisdom -- enlightenment (or 
whatever name you put on that end) are also part of the picture. Just 
because we understand these less (and, as IAs,  are able to have 
increasingly less affect as one goes up the line) does not mean they 
must be ignored. I'm especially concerned with knowledge. That is, I 
would hope that the web-documents that might be created out of my work 
can help create knowledge in those who use them.

We might normally think that knowledge is gained by education. That is 
certainly the case, but as people leave behind formal education  they 
increasingly need to be re-educated as methods in their profession 
change. But too often, they don't go back to school or even enroll in 
continuing education. Part of my project is to try build a system that 
can allow them to more easily gain new knowledge by using resources 
that usually live separately (a CE course syllabus, a text-book, a 
practice manual). I hope to even be able to include something that 
tells the user that a course is being offered that contains the 
information they need to gain the new knowledge that they are seeking 
and that they should take that course.

Anyway, what this means to me in terms of this discussion is that data 
and information are certainly distinguishable. Perhaps the difficulty 
in this concept is that, since we are talking about a continuum, the 
*line* between data and information is not really distinguishable but 
when you move along closer to the 'knowledge' part of the continuum, 
then information is very much different from data (or from the flow of 
experience). In fact, this might be why, as i said in my previous post, 
I don't think Ed is mad. When I think of information as a 'wave' or 
'substance', I'm looking at rich information that is much closer to 
knowledge than it is to data. In that part of the continuum things get 
really slidey and you have to keep your wits (and in my case, all those 
library science concepts I'm now so grateful to have had driven into 
me) about you. At that point, empirical ('bit'-like) definitions are 
not as much help to me, I don't think.

Regards,
Phil
www.philiphall.ca

On Monday, January 6, 2003, at 08:06 PM, Thomas Vander Wal wrote:

> On 1/6/03 10:03 PM, "Boniface Lau" <boniface_lau at compuserve.com> wrote:
>
>>> -----Original Message-----
>>> From: sigia-l-admin at asis.org [mailto:sigia-l-admin at asis.org]On
>>> Behalf Of Thomas Vander Wal
>>
>> [...]
>>> Since most of us interact with these folks, if not where these hats
>>> it is good to know the difference so that we can intelligently
>>> converse with fields we need to embrace to do our jobs well.
>>
>> Looking down from the 64-thousand feet level, data and information are
>> clearly distinguishable. But as we descent closer and closer to the
>> ground level, the distinction becomes more and more difficult to
>> make.
>
> Because much of Usability, Information Architecture, and user-centered
> design relies on it depends and blurry lines do we avoid them?  No.  We
> learn and try to grasp the basic, like the distinction between data, 
> and
> information.  You may ask why?  Because we are crazy individuals that 
> care
> about the user and care about information being found and used.  To 
> throw
> out solid basic understanding because it is not a clear distinct line
>
> You also just proved the distinction between data and information.  
> From the
> 64k foot view we can see the difference between data and information.  
> We
> have enough data from the 64k view to create usable information and the
> difference is distinguishable.  When looking at the lower levels there 
> is
> less of a distinction, hence we are looking at data and not 
> information.  We
> are lacking enough data to make a pattern, context, discernable
> understanding of what we are looking at by being too close.  When we 
> have
> distinguishable patterns we have information and when we don't we have 
> data.
> When we can act on those distinguishable patterns that make up the
> information we have knowledge.  Providing proper information is the 
> key to
> commerce, this is why Amazon has been successful, they find the 
> patterns in
> their data that provides information to their users.
>
>>>
>>> The lines between data and information are blurred at best.
>>
>> Thus, trying to draw a clear line between the two is futile.
>
> The practice of drawing clear lines is anything but futile and it is 
> why
> most of us are Information Architects.  Drawing a clear line takes 
> many data
> points: the data, the user, the intended/expected use of the 
> information
> (once the line from data to information is crossed), the form of the 
> data,
> the form and medium and presentation of the data/information, etc all 
> play a
> role in drawing the line.  Understanding the finer points helps us
> understand when we have a product that is usable and findable.  We are
> Information Architects and not Data Architects (I have been a Data
> Architect/data modeler/data analyst whose role has been to find data 
> that
> builds information that is usable).  As IAs we work with full pieces of
> information and other times it is smaller chunks of information that 
> may be
> just a collection of data points to some.  We should now the 
> difference, if
> we charge clients we must know the difference as that is why we get 
> paid.
>
> At times we need to rely on the visualization of data points and take a
> higher level view to see the hundreds of data points as a line and see 
> the
> patterns that emerge.  The line becomes our information.   See
> http://www.fhwa.dot.gov/ohim/tvtw/02jultvt/figure1.htm, which shows a 
> line
> connecting the data points of the billions of miles of total vehicle 
> miles
> traveled in the U.S. From 1977 to present.  The individual data points 
> would
> not provide the information the line connecting the data points 
> provides.
> The line show dips in the increase of vehicle miles traveled at certain
> points.  The flattening of the line and dips occur at the Iranian 
> Crisis in
> 1979, a slight recession in 1982, the Gulf War in 1991, gas price 
> increase
> in 1999, and the beginning of an economic downturn in 2001.  Seeing the
> changes in the normal trend of the line lead us to look at what was
> happening in the world around the data points.  Seeing the data points 
> when
> combined with other data points auxiliary data provides enough clues 
> to see
> a pattern that becomes usable information.  We do not need to see the 
> line
> of data points if we have an algorithm that can use a predictive line 
> trend
> that will allow us to understand when there are variations to the 
> increasing
> trend and when the trend returns to its normal increase.  The visual 
> display
> of this information assists the user by providing enough information 
> to look
> for more information to describe what is happening.  To users who do 
> not
> understand what the line is describing the line is meaningless until 
> the
> user is told to look for the variations of the line, then describing
> possible causation events.
>
> All the best,
> Thomas
>
> -- 
> www.vanderwal.net
>
> The future is mine, not Microsoft's
>
>
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