It all starts with a question: What even is information?
My name’s Peter. This is Stacks & Facts.
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Maybe it feels like a simple question, but what actually *is* information?
Is it the YouTube video you watch to learn about music theory?
Is it the book you read in your free time, or the podcast you listen to on the bus to
work?
Or, are these simply a medium for something else?
As it happens, there’s no consensus across disciplines about what information actually
is, and even within the field of LIS there’s no single definition that people point to
(but there are lots of them -- link in the dooblydoo).
That’s due in no small part to the fact that how a mathematician thinks of information
can be wildly different from, say, a wildlife biologist, whose definition is different still
from a poet's, and so on, et cetera, ad nauseum, forever and ever amen.
But! If we’re going to talk about information science and the various information professions,
then we have to give this question some thought!
What *we think* information is and isn’t -- shapes how we study and interact with it,
so that’s what we’re looking at today.
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Let’s begin with one of the great philosophers of our time:
Today, me going to tell you about word called "information."
Right? Information. And information mean "news or facts about something."
Did you catch that?
“News or facts about something.”
Let’s see how this cookie crumbles:
... Okay, not this cookie. We're gonna see how this cookie fits into my face.
First, there’s the idea of truthfulness: information is factual.
If I tell you that this is a cookie, that’s information.
If I tell you it’s a cake, that’s *mis*-information…
Or at least, about this cookie (it may inform you about something
else, but within the context of this cookie, it's not relevant).
This leads to aboutness: Information tells us *about* something else.
If I just sat here and said “dog!
Magenta!
Charlie Hebdo!
Chrysanthemum!
Flummox!”
Or whatever, this wouldn’t be information, it would be noise: random fluctuations that obscure or
do not contain meaningful data.
Finally, we have thing-ness, and information *is* a thing -- albeit, perhaps intangible.
After all, news is a thing, and facts are things, right?
They're just separate from the newspapers and books that hold them.
And if we look at the roots of the word itself , we can see that this part of the
definition is:
BAKED IN.
the prefix “in-” means within, like in the brain or mind; and
“formare” means to create, or take shape, or… to form.
Now, let's go back to Cookie Monster for a second.
Today, me going to give you information about word "cookie."
Give me cookie please!
Oh thank you! Thankyouthankyouthankyouthankyou.
Right in my hand. Oh thank you.
That: cookie!
OMNOMNOMNOMNOMNOM [smacking of lips]
And now me give you information about cookie:
And the information is: cookie was delicious.
Give me other cookie please. Other cookie. Oh thank you thank you.
AAAHMNOMNOMNOM.
Now me give you MORE information:
Cookie was delicious and crunchy!
Now give me whole box please, whole box -- oh boy, OH BOY--
OMMMMMNOMNOMNOMNOMNOMNOM
[the faintest tinkling of laughter from little girl, barely audible over Cookie Monster's indulgent habit]
Oh, thank you very much, Tara.
Now, rest of information:
Cookies... Gone. Ah ha ha.
Thank you Tara! Give me hug. Oh thank you. [happy monster grunt]
When cookie monster tells us that cookies are delicious, crunchy, and (ultimately) gone,
it allows us to build in our own brains an idea of what those cookies are.
At this point, the *information* about cookies transforms into *knowledge* about cookies.
This knowledge, in turn, will shape our future encounters with -- and perceptions of -- cookies
as things.
This way of thinking about information follows what’s known as the Data-Information-Knowledge-Wisdom,
or DIKW, Pyramid.
The idea behind the DIKW pyramid is that concepts of things follow a path from least-processed
(data), to most-processed (wisdom).
It’s an easy rabbit hole to fall into, but the basic idea is that if information were
a cookie, then its ingredients would be the data that go into it, and how it tasted would
be the knowledge that derives from it.
As for wisdom, that would probably be more along the lines of, say,
whether or not a person decided the cookie tasted good or not.
But that's outside of the scope of LIS, so we're not gonna touch on that a whole lot.
So let's move on!
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Claude Shannon is one of the pioneers of information theory, a field of study separate from but
related to LIS that looks at the engineering around signaling -- sending ones and zeroes,
radio waves, beams of light, and all that jazz.
Shannon saw information as a thing to build systems around.
He worked at Bell Labs during World War II, and like many of his contemporaries, his research
initially revolved around wartime communications between entities, and the systems that
made this possible.
Those entities could be people, or they could be systems like radar or fire control.
In 1948, his article “A Mathematical Theory of Communication” was published, which laid
the groundwork for information theory as a field.
We can get an idea of how it framed information from its introduction:
In other words, information is a thing that conveys meaning about stuff (sound familiar?)
that gets transmitted as a message from one place to another.
When we think of it this way, information becomes somewhat defined by the fact that
it has a sender and a receiver, and is sent along a medium or channel -- whether that’s
electrons on a wire, or light through fiber optics, or radio waves through the air).
This medium may introduce interference or degradation to the message itself.
You could call this interference “noise” like I mentioned before, or “entropy,”
the word Shannon borrowed for it from physics.
Shannon’s model also has an encoder and a decoder.
These turn the information into something that can be sent on whatever medium (say,
zeroes and ones) and then decoded and understood by the recipient (say, words or coordinates).
So that’s Shannon’s idea of information: a thing to build systems around.
But there’s a much more elegant definition of information, that often gets attributed to him
-- although I haven't found a source for it; stand by, if I find one I'll let you know --
and at least philosophically, I think it contributes to our understanding:
"information," he supposedly said, “is the resolution of uncertainty.”
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Finally, let’s talk about Professor Robert Losee, out at UNC, Chapel Hill: In his search
for a definition that exists that can apply *regardless of* the discipline one looks at,
he gives us the idea of “Information from process.”
More specifically, information as *the characteristics* of a process’s output, that inform about
the process itself.
That process could be writing a book or baking cookies, calculating pi or looking at the
stars.
An interesting thing about this definition is that it pulls the definition away from
necessarily being human-sourced: Losee spends an entire page discussing how a kitten’s
purr, for example, can produce many different kinds of information, depending on the lens
through which one considers it.
Maybe there’s a place in LIS for this definition like this: it could give us the flexibility we need to
cross lines between computer science and psychology, education and digital media, or user experience
and social justice.
But to be clear, Losee’s idea is not as yet *the* information science definition.
Such a definition doesn’t exist -- and that’s okay!
Because LIS pulls from so many different fields, I think there’s something to be said for
having some wiggle room in how information is described.
My Chinese teachers always told me, “根據上下文找意思” which means “find
meaning according to context.”
And when we’re looking at Dr. Bates’s “world of recorded information produced
by human agency,” the context matters.
A lot!
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So that's just a few idea of what information is, but there are tons more out there.
If you want to see some of them, go into the dooblydoo, and you'll see a link to the entry on "information"
from the Encyclopedia of Information Science, written by our very own Dr. Bates -- who I mentioned last video.
Doctor Bates, you are getting so much coverage -- good on ya!
But I'm curious to see how y'all decide to define information for yourself,
the context of your studies, or your work, or your life more broadly?
Let me know in the comments below or shoot me a tweet - @StacksEtFacts - and let me know!
Cuz yeah, I'd like to find out.
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Thanks for watching, and until next time -- don’t forget to ask questions.
Alright... Bye!
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