What is information?
Really, what is it?
© Tefko Saracevic
1
As a phenomenon …
Answer:
WE DON’T KNOW!
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© Tefko Saracevic
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As a concept …



Well, we understand it intuitively quite well
We have a number of lexical definitions
We use it and nobody has to define it for us

it is a y’know concept

We easily adapt to various connotations
(differing senses) depending on the context

But formally, in a scientific sense, we really don’t
know what information is as a phenomenon,
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© Tefko Saracevic
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As a basic phenomenon


We don’t know what information is any more
than we know what is
energy
matter
gravity
life
knowledge
Basic phenomena in physics, biology,
philosophy …we don’t know what they are, BUT:
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© Tefko Saracevic
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So how do we study
them?

We study their

manifestations
behavior
(or behaviour if you are British)
effects
All scholarship, every science does this

e.g. we don’t know what gravity is, but we have
physical laws that describe its behavior and effects
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© Tefko Saracevic
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this slide doesn’t have to
do with the lecture topic
but I liked the picture,
so here it is
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© Tefko Saracevic
6
Information treated in
various disciplines

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
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physics – basic property as
energy, matter
biology – senses
neurophysiology – brain processes
psychology – behavior, perception
cognitive science – cognition
telecommunication, computer
science – signals, bits
philosophy – knowledge
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© Tefko Saracevic
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Information in
information
Again: intuitively
well understood, but formally not
science
well stated


Shannon: source-channel-destination


signals not content – not really applicable
Cognitive: changes in cognitive structures


Several viewpoints, models emerged
content processing & effects
Social: context, situation

information seeking, tasks
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© Tefko Saracevic
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Shannon's information
theory

Developed a general model for communication
systems, and a set of theoretical tools for
analyzing such systems, by measuring
information in terms of probabilities (numbers)
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© Tefko Saracevic
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Shannon … reducing
uncertainty

Defined information in terms of probabilities

developed measure of the information we get from
observing the occurrence of an event, BUT ignored
any particular features of the event


e.g. flipping a fair coin once will give us events h and t
each with probability 1/2, and thus a single flip of a coin
gives us - log2(1/2) = 1 bit (Binary digit) of information
(whether it comes up h or t)
Information measured in bits is the reduction in
uncertainty in the mind of the receiver

information (in bits) is the amount of uncertainty a
measure eliminates
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© Tefko Saracevic
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Shannon’s impact

Had great impact in treating of
digital information as signals

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e.g maximizing capacities of
channels; coding
Had disappointing impact
(despite many tries) where
information is connected with
meaning, context, humans,
values


the ideal to measure information in
human terms is elusive
but keep trying …
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© Tefko Saracevic
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Cognitive – basic idea:
K(S) + ΔI = K(S + ΔS) (Brookes)
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Information when operating on a knowledge
structure produces an effect whereby the
knowledge structure is changed
“Information is differences that make a
difference” (find who said it!)
Actually, it only states the problem –
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“unoperational” in information systems
involves cognitive, mental events only
constructivists rejected it
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© Tefko Saracevic
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Information
manifestations

Information as a process

what someone knows is changed when informed; “the action of
informing” (similar as Brookes)


refers to cognitive changes + process of doing it
Information as knowledge

knowledge communicated about x



(Buckland)
uncertainty removal a special case
refers to that which is being communicated - intangible
Information as a thing

data, documents with quality of imparting information - tangible

refers to potential information conveyed from objects
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© Tefko Saracevic
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Information
in information science
Three senses (from narrowest to broadest)
Information in terms of decision involving little or no
cognitive processing - Shannon
1.

signals, bits, straightforward data - computing, telecommunication, economics,
Information involving cognitive processing &
understanding - Brookes
2.

understanding, matching texts
Information also as related to context, situation, problemat-hand, process – Buckland to some extend
3.

users, use, tasks
For information science (including information retrieval):
third, broadest interpretation necessary
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© Tefko Saracevic
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What is in a book?
(for discussion in class)
Cover
page
of a
book:
What
is in
it?
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© Tefko Saracevic
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A
chapte
r in
that
book
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© Tefko Saracevic
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Here is
also a
cover
page of
a book:
What
is in
it?
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© Tefko Saracevic
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A
chapte
r in
that
book
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© Tefko Saracevic
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Adequacy?
None of the theories about
1452-1519
information are adequate to
cover fully information as a
phenomenon
 Each covers a bit or simply
describes manifestation
 Shannon’s theory is testable,
but reduces “information” to
signals only
 A scientific theory is one that
can be refuted – tested for
confirmation, rejection (Popper)
1564-1642
- they understood this
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© Tefko Saracevic
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So we went to study
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Human information behavior
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“how people need, seek, manage, give, and use
information in different contexts” (Pettigrew )
many models, theories, studies on a variety of aspects
extends to study of web behavior
Bibliometrics
 “the
study, or measurement, of texts and information”
(Norton)
 many studies and formal statements about structure &
patterns of literatures, citations, authors, journals,
texts …
 Bradford’s law, Lotka’s law
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© Tefko Saracevic
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to be continued …
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We cover these in other lectures and courses
and two 2005 books cover very nicely the topics of
theories of human information behavior
and
integration of information seeking and
information retrieval in context

highly recommended
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© Tefko Saracevic
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© Tefko Saracevic
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© Tefko Saracevic
p.s. there is code
in other slides
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