What is Knowledge? Prof. Elaine Ferneley [email protected] [email protected]

What is Knowledge? What is Knowledge?

Prof. Elaine Ferneley Prof. Elaine Ferneley [email protected]@salford.ac.uk

mailto:[email protected]

Prof Elaine Ferneley

Data, Information, and KnowledgeData, Information, and Knowledge

Data: Unorganized and unprocessed facts; static; a set of discrete facts about events

Information: Aggregation of data that makes decision making easier

Knowledge is derived from information in the same way information is derived from data; it is a person’s range of information


Some ExamplesSome Examples

Data represents a fact or statement of event without relation to other things. Ex: It is raining.

Information embodies the understanding of a relationship of some sort, possibly cause and effect. Ex: The temperature dropped 15 degrees and then it started raining.

Knowledge represents a pattern that connects and generally provides a high level of predictability as to what is described or what will happen next. Ex: If the humidity is very high and the temperature drops substantially the

atmospheres is often unlikely to be able to hold the moisture so it rains.

Wisdom embodies more of an understanding of fundamental principles embodied within the knowledge that are essentially the basis for the knowledge being what it is. Wisdom is essentially systemic. Ex: It rains because it rains. And this encompasses an understanding of all the

interactions that happen between raining, evaporation, air currents, temperature gradients, changes, and raining.


KNOWLEDGE

INFORMATION

WISDOM

Nonalgorithmic(Heuristic)

Nonprogrammable

From Data Processing to Knowledge-based SystemsFrom Data Processing to Knowledge-based Systems

DATAAlgorithmic Programmable

The DIKW PyramidThe DIKW Pyramid


Definitions:Definitions: DataData, , Information, Knowledge, Information, Knowledge, Understanding and WisdomUnderstanding and Wisdom

Data is raw, it is a set of symbols, it has no meaning in itself

Quantitatively measured by: How much does it cost to capture and retrieve How quickly can it be entered and called up How much will the system hold

Qualitatively measured by timeliness, relevance, clarity:

Can we access it when we need it Is it what we need Can we make sense of it

In computing terms it can be structured as records of transactions usually stored in some sort of technology system


Definitions: Definitions: DataData, , InformationInformation, Knowledge, , Knowledge, Understanding and WisdomUnderstanding and Wisdom

Information is data that is processed to be useful Provides answers to the who, what, where and when type

questions given a meaning through a relational connector, often

regarded as a message Sender and receiver Changes the way the receiver perceives something – it

informs them (data that makes a difference) Receiver decides if it is information (e.g. Memo perceived as

information by sender but garbage by receiver)

Information moves through hard and soft networks Transform data into information by adding value in

various ways


Definitions: Definitions: DataData, , InformationInformation, Knowledge, , Knowledge, Understanding and WisdomUnderstanding and Wisdom

Quantitative information management measures e.g…. Connectivity (no. of email accounts, Lotus notes users) Transactions (no. of messages in a given period)

Qualitative information management measures Informativeness (did I learn something new) Usefulness (did I benefit from the information)

In computing terms a relational database makes information from the data stored within it


Definitions: Definitions: DataData, , Information, Information, KnowledgeKnowledge, , Understanding and WisdomUnderstanding and Wisdom

The application of data and information – answers the how questions

Collection of the appropriate information with the intent of making it useful By memorising information you amass knowledge e.g.

memorising for an exam – this is useful knowledge to pass the exam (e.g. 2*2=4)

BUT the memorising itself does not allow you to infer new knowledge (e.g.1267*342) – to solve this multiplication requires cognitive and analytical ability the is achieved at the next level – understanding

In computing terms many applications (e.g. modelling and simulation software) exercise some type of stored knowledge


Definitions: Definitions: DataData, , Information, Knowledge, Information, Knowledge,

UnderstandingUnderstanding and Wisdom and Wisdom

The appreciation of why The difference between learning and memorising

If you understand you can take existing knowledge and creating new knowledge, build upon currently held information and knowledge and develop new information and knowledge

In computing terms AI systems possess understanding in the sense that they are able to infer new information and knowledge from previously stored information and knowledge


Definitions: Definitions: DataData, , Information, Knowledge, Information, Knowledge,

Understanding and Understanding and WisdomWisdom

Evaluated understanding Essence of philosophical probing

Critically questions, particularly from a human perspective of morals and ethics

discerning what is right or wrong, good or bad A mix of experience, values, contextual

information, insight In computing terms may be unachievable

– can a computer have a soul??


A Sequential Process of KnowingA Sequential Process of Knowing

Understanding supports the transition from one stage to the next, it is not a separate level in its own right


Rate of Motion towards KnowledgeRate of Motion towards Knowledge

What is this (note the point when you realise what it is but do not say) I have a box. The box is 3' wide, 3' deep, and 6' high. The box is very heavy. When you move this box you usually find lots of dirt

underneath it. Junk has a real habit of collecting on top of this box. The box has a door on the front of it. When you open the door the light comes on. You usually find the box in the kitchen. It is colder inside the box than it is outside. There is a smaller compartment inside the box with ice in it. When I open the box it has food in it.


Rate of Motion towards KnowledgeRate of Motion towards Knowledge

It was a refrigerator At some point in the sequence you

connected with the pattern and understood

When the pattern connected the information became knowledge to you

If presented in a different order you would still have achieved knowledge but perhaps at a different rate


LearningLearning

Learning by experience: a function of time and talent

Learning by example: more efficient than learning by experience

Learning by sharing, education.

Learning by discovery: explore a problem area.

Prof Elaine Ferneley 15

From tacit to articulate knowledge From tacit to articulate knowledge

““We know more than we can tell.” We know more than we can tell.”

Michael Polanyi, 1966Michael Polanyi, 1966

TacitArticulated

High Low

MANUALHow to

play soccer

Codifiability

Prof Elaine Ferneley 1616

Knowledge is experience, Knowledge is experience, everything else is just everything else is just

information.information.-Albert Einstein-Albert Einstein

““We know more than we can tell.”We know more than we can tell.”


Explicit KnowledgeExplicit Knowledge

Mend a

broken legCalculate

tax

Make a cake

Raise a

n

invoiceBuild anengine

Service a boiler

Formal and systematic: easily communicated &

shared in product specifications, scientific formula or as computer programs;

Management of explicit knowledge: management of

processes and information

Are the activities to the right information or knowledge dependent ?


Tacit Knowledge ExamplesTacit Knowledge Examples

Work in

team

Get 100%in an

assignmentCo-ordinate colours

Ride a

bikeDesign apresentation

Arrange furniture

Highly personal: hard to formalise; difficult (but not

impossible)to articulate; often in the form of know

how.

Management of tacit knowledge is the management of people: how do you extract and

disseminate tacit knowledge.


Illustrations of the Different Types of Illustrations of the Different Types of Knowledge Knowledge

Know ‘that’

Know ‘how’


Knowledge As An Attribute of ExpertiseKnowledge As An Attribute of Expertise

An expert in a specialized area masters the requisite knowledge

The unique performance of a knowledgeable expert is clearly noticeable in decision-making quality

Knowledgeable experts are more selective in the information they acquire

Experts are beneficiaries of the knowledge that comes from experience


Expertise, Experience & UnderstandingExpertise, Experience & Understanding

Experience – rules of thumb: What e.g. gardener might have

Understanding – general knowledge:What a biology graduate might have

Expertise – E + U in harmonyWhat an expert has


Expertise, Experience & Understanding 2Expertise, Experience & Understanding 2


ReasoningReasoningandand

ThinkingThinkingandand

Generating KnowledgeGenerating Knowledge


Expert’s Reasoning MethodsExpert’s Reasoning Methods

Reasoning by analogy: relating one concept to another Formal reasoning: using deductive or inductive methods (see next slide) Case-based reasoning: reasoning from relevant past cases


Deductive and inductive reasoningDeductive and inductive reasoning

Deductive reasoning: exact reasoning. It deals with exact facts and exact facts and exact conclusionsexact conclusions

Inductive reasoning: reasoning from a set of facts or individual cases to a general general conclusionconclusion

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What is Knowledge? Prof. Elaine Ferneley [email protected] [email protected]