ptit481 km unit 1
TRANSCRIPT
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Course Deliveries
Discussions
Inputs
Clarifications Check What I Know (CWIK)
Clarifications
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UNIT 1 OBJECTIVES
Understand key terms
Create a platform for KM
Importance of KM Emergence of KM
Objectives of KM
KM Domain &U
ses Knowledge Economy
Knowledge Engineering & Knowledge Ontology.
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Introduction to Knowledge
ManagementKey terms
Information
Tangible raw data. Can be copied.
Knowledge
Intangible. Requires learning & practice.
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Knowledge Management
Knowledge is:
Knowing
WHYWHAT
WHEN
HOW
WHERE
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Knowledge Management
Y KM?
70 80 % what employees know is hidden.
Knowledge has become the key
differentiating factor.
It is the most sought after resource / asset.
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EMERGENCE
1996 Worlds top 5 heart surgeons
24% decrease in mortality rates
KM is a collaborative learning
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Definition
Knowledge Management refers to the
processes and/or tools an organization uses to
collect, analyze, store, and disseminate its
intellectual capital.
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Knowledge Cycle
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Sources of Knowledge
Employees
Products
Customers
Suppliers
Competitors
Government
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Objectives of KM
Create knowledge repositories
a) External knowledge (competitive intelligence,
market data, surveys, etc.)b) Structured internal knowledge (reports,
marketing materials, etc.)
c) Informal internal knowledge (discussiondatabases of know how)
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Improve knowledge access through
a) Technical expert referral
b) Expert networks used for staffing based on
individual competencies
c) Turnkey video conferencing to foster easy
access to distributed experts.
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Enhance the knowledge environment
a) Change organizational norms and values
related to knowledge in order to
encourage knowledge use and knowledge
sharing
b) Customers rating of organisations expertise
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Manage knowledge as an asset
a) Attempt to measure the contribution of
knowledge to bottom line success
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Knowledge Economy
An Economy where the growth of GDP is
altered based on the changes in the
knowledge based industries.
Ex: India IT industry falls GDP falls.
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Knowledge Engineering
Knowledge engineering (KE) was defined in
1983 by Edward Feigenbaum, and Pamela
McCorduck
KE is an engineering discipline that involves
integrating knowledge into engineering
systems in order to solve complex problems
normally requiring a high level ofhumanexpertise.
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Knowledge Engineering - Scope
artificial intelligence
databases,
data mining, expert systems,
decision support systems and
geographic information systems.
cognitive science and
socio-cognitive engineering
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Knowledge engineering principles
Knowledge engineers acknowledge that there aredifferent types of knowledge, and that the rightapproach and technique should be used for theknowledge required.
Knowledge engineers acknowledge that there aredifferent types of experts and expertise, suchthat methods should be chosen appropriately.
Knowledge engineers recognize that there aredifferent ways of representing knowledge, whichcan aid the acquisition, validation and re-use ofknowledge.
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Knowledge engineering principles
Knowledge engineers recognize that there are
different ways of using knowledge, so that the
acquisition process can be guided by the project
aims (goal-oriented).
Knowledge engineers use structured methods to
increase the efficiency of the acquisition process.
Knowledge Engineering is the process of elicitingKnowledge for many purpose be it Expert system
or AI development
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Views of knowledge engineering
Transfer View This is the traditional view. In
this view, the assumption is to apply
conventional knowledge engineering
techniques to transfer human knowledge into
artificial intelligence systems.
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Knowledge Intensive Organizations
Employs Highly skilled staff, knowledge
workers
Dealing with uncertainty Requires people who are problem solvers
Follows best practices to attract & retain
talents Knowledge seen as an asset
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Competence & Knowledge
Competence is the underlying characteristics
of a person to perform a job
Knowledge forms the basis for the underlying
characteristics of a person to perform a task
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Types of Knowledge
Domain knowledge: Knowledge about the
objective realities in the domain ofinterest
(Objects, relations, events, states, causalrelations, etc. that are obtained in
some domains)
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Problem-solving knowledge: Knowledge about
how to use the domain knowledge to achieve
various goals. This knowledge is often in the
form of a problem-solving method (PSM) that
can help achieve the goals in a different
domain.
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Knowledge Ontology
The term ontology is usually defined as aformal description of the knowledge in adomain / in a generic model.
First, ontology can refer to a full descriptionof all the knowledge, so that it can berepresented and used within a computersystem.
Second, ontology can refer to a genericmodel that applies to a class of domains.
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Elements of Knowledge Ontology
(1) a set of knowledge objects
(2) a set of relations that form associations
(relationships) between the knowledge objects
(3) a set of axioms that provides rules and
constraints for the relationships (e.g. if A is next
to B, then B is next to A). The ontology described
here will make use of the first two elements, butnot include any axioms, which requires more
development.
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Y Ontology in Personal Knowledge
First, it can help to integrate and coordinate
the use of the Personal Knowledge Techniques
for more efficient acquisition of knowledge
and facilitation of self-help.
Second, the ontology can provide a common
underlying language that aids users to
understand the information available to them(e.g. from other users) and aids researchers to
compare knowledge from different users.
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Third, the ontology can help the user when
searching for, and being presented with,
advice from the system. This is achieved by
using the ontology to provide key words and
semantic tags with which to code theinformation for searching.
Fourth, the ontology provides a structured set
of categories that can be used to analyse theknowledge captured from users.
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Fifth, as multiple users make use of the
Personal Knowledge Methodology, the
ontology can develop to be a reflection of thecommonalities between these users lay
psychological theories.
Sixth, the ontology can be a contribution tothe ongoing development of ontology within
knowledge engineering.
Finally, a longer-term goal would be to
develop multiple versions of the ontology
appropriate to different populations .