cs110_11_datainformationknowledgeunderstandingwisdom
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Overview
Data is just symbols
Information is data that are processed
to be useful; provides answers to
"who", "what", "where", and "when"questions
Knowledge is application of data and
information; answers "how" questions
Understanding is appreciation of why.
Wisdom is an evaluated understanding
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Data
Data is raw. It simply exists and has no
significance beyond its existence (in
and of itself). It can exist in any form,
usable or not. It does not have
meaning of itself.
In computer parlance, a spreadsheet
generally starts out by holding data.
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Information
Information is data that has been given
meaning by way of relational
connection. This "meaning" can be
useful, but does not have to be.
In computer parlance, a relational
database makes information from the
data stored within it.
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Knowledge
Knowledge is the appropriate
collection of information, such that it's
intent is to be useful.
Summaries of information in a
database for example. Or modeling
and simulation tools exercise some
type of stored knowledge.
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Understanding
The difference between knowledge andunderstanding is the difference between
"memorizing" and "learning.
Understanding is an interpolative and probabilistic
process. It is cognitive and analytical.
People who have understanding can undertake
useful actions because they can synthesize new
knowledge, or in some cases, at least new
information, from what is previously known (and
understood).
In computer parlance, AI systems possess
understanding.
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Wisdom
Wisdom is an extrapolative and non-
deterministic, non-probabilistic process. It
calls upon special types of human
programming (moral, ethical codes, etc.). Unlike the previous four levels, it asks
questions to which there is no (easily-
achievable) answer, and in some cases, to
which there can be no humanly-knownanswer period. i.e. judge between right and
wrong, good and bad.
Humans only possess wisdom.
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CS Example
A collection of student data
Data
Information
Knowledge
Understanding
Wisdom
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Data Organization
Unique characteristic (IDs)
Time
Location
Many Abstractions are used
Lists
Stacks Queues
Trees
Graphs
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New Data Challenges/Opportunities Big data
Unstructured data
social networking multimedia