????

????

????

????

??

Join

t Adv

ance

d S

tude

nt S

choo

lS

aint

-Pet

ersb

urg,

200

8

Dudorov D.V., Jin HaiN

an

Pro

fess

or:

Gav

rilo

va T

.A.

SOFTWARE D

ECISIO

N FOR

KNOWLEDGE M

ANAGEMENT

Contents

�In

trod

uctio

n�

Bas

ic a

ppro

ache

s�

His

tory

of K

M�

Way

s of

get

ting

know

ledg

e�

Kno

wle

dge

Man

agem

ent S

yste

m�

Ont

olog

y�

Our

sof

twar

e de

cisi

on�

Per

spec

tives

�C

oncl

usio

n

What is Knowledge?

�K

now

ledg

e is

nei

ther

dat

a no

r in

form

atio

n, th

ough

it is

re

late

d to

bot

h, a

nd th

e di

ffere

nces

bet

wee

n th

ese

term

s ar

e of

ten

a m

atte

r of

deg

ree.

�

Dat

a, in

form

atio

n an

d kn

owle

dge

are

not i

nter

chan

geab

le

conc

epts

. �

Kno

wle

dge

is a

flui

d m

ix o

f fra

med

exp

erie

nce,

val

ues,

co

ntex

tual

info

rmat

ion,

and

exp

ert i

nsig

ht th

at p

rovi

des

a fr

amew

ork

for

eval

uatin

g an

d in

corp

orat

ing

new

ex

perie

nces

and

info

rmat

ion.

It o

rigin

ates

and

is a

pplie

d in

th

e m

inds

of k

now

ers.

In o

rgan

izat

ions

, it o

ften

beco

mes

em

bedd

ed n

ot o

nly

in d

ocum

ents

or

repo

sito

ries

but a

lso

in o

rgan

izat

iona

l rou

tines

, pro

cess

es, p

ract

ices

and

nor

ms.

What is Knowledge M

anagement?

The

leve

ragi

ng o

f col

lect

ive

wis

dom

to in

crea

se

resp

onsi

vene

ss a

nd in

nova

tion.

Kno

wle

dge

Man

agem

ent i

s in

tend

ed to

allo

w o

rgan

isat

ions

to

prot

ect a

nd d

evel

op th

eir

know

ledg

e re

sour

ce.

Kno

wle

dge

Man

agem

ent i

s a

man

agem

ent d

isci

plin

e th

at

focu

ses

on e

nhan

cing

kno

wle

dge

prod

uctio

n, in

tegr

atio

n an

d us

e in

org

aniz

atio

ns.

A c

ycle

of k

now

ledg

e cr

eatio

n, in

tegr

atio

n an

d di

ssem

inat

ion.

Objective of KM:

RIGHTinform

ation

RIGHTperson

the MOST

APPROPRIATEdecision

(just in time)

KM

Cognitive science

Expert systems

AI and KBMS

Computer-supported

collaborative work

Library and

inform

ation science

Technical writing

Document

management

Decision support

systems

Semantic networks

Simulation

Organizational science

Disciplines and Technologies:

KM theory models:

Polaniy’s

model

Knowledge (+ how)

Inform

ation (+ context)

Data

Wisdom

(+ when)

Tacit

knowledge

Explicit

knowledge

what is in

our heads

what we have

codified

DIKW

model

�R

educ

tions

in s

taffi

ng c

reat

e a

need

to r

epla

ce in

form

al

know

ledg

e w

ith fo

rmal

met

hods

.

�C

ompe

titiv

e pr

essu

res

redu

ce th

e si

ze o

f the

wor

k fo

rce

that

hol

ds

valu

able

bus

ines

s kn

owle

dge.

�T

he a

mou

nt o

f tim

e av

aila

ble

to e

xper

ienc

e an

d ac

quire

kn

owle

dge

has

dim

inis

hed.

�T

here

is a

nee

d to

man

age

incr

easi

ng c

ompl

exity

as

smal

l ope

ratin

g co

mpa

nies

are

tran

s-na

tiona

l so

urci

ng o

pera

tions

.

�M

ost o

f our

wor

k is

info

rmat

ion

base

d.

�P

rodu

cts

and

serv

ices

are

incr

easi

ngly

co

mpl

ex, e

ndow

ing

them

with

a s

igni

fican

t inf

orm

atio

n co

mpo

nent

.

Why do w

e need KM ?

A c

ompa

ny's

inte

llect

ual c

apita

l rep

rese

nts

its a

bilit

y to

cha

nge

in

the

face

of a

dver

sity

. Dev

elop

new

pro

duct

s. C

ut r

esea

rch

and

deve

lop

time.

Pro

vide

qua

lity

cust

omer

ser

vice

. Sha

re k

now

ledg

e w

ith e

mpl

oyee

s, p

artn

ers

and

cust

omer

s.

Real-life exam

ple

Compan

y: O

RBITAL Software

Knowledge

Mission

Competition

Perfomance

Change

What are we trying to accomplish?

How do we gain a

competitive edge?

How do we deliver the results?

How do we cope

with change?

management

dim

ensions

History of KM:

The beginning

The dawn of KM

Future

P. Druckerand P. Strassmann-

importance of inform

ation and explicit

knowledge as organizational resources

C. Argyris, C. Bartlett and

D. Leonard-Barton of Harvard Business School

examined various facets of managing knowledge

P. Senge–“learning organization”

1970s~

:Chaparral Steel company -

effective

knowledge management strategy

knowledge management

entered the lexicon

R. Acksyn, D. McCracken -

Knowledge M

anagement

System (KMS)

1995:Leonard-Barton-“W

ellsprings

of Knowledge —

Building and

Sustaining Sources of Innovation”

1989: The International KM Network

(IKMN)

1991: T. Stewart –

"Brainpower"

(KM was introduced in press)

1970s:E. Rogers (Stanford), T. Allen

(MIT) -how knowledge is

produced, used, and diffused within

organizations

KM as a business

Non-software

Magazines, books

TV

Radio

Conferences

Software

Expert systems

Portals

Search engines

Forums

FAQs

Ways of getting Knowledge:

KM System

KM System

--refers

refers

totoa

a

system

system

for

formanaging

managingknowledge

knowledge inin

organizations

organizations, , supporting

supportingcreation

creation, ,

capture

capture, , storage

storageand

andissemination

issemination

of

ofinform

ation

inform

ation..

�D

ocum

ent b

ased

�O

ntol

ogy

base

d

�B

ased

on

AI t

echn

olog

ies

�In

crea

sing

ly s

ocia

l com

putin

g to

olsE

xper

tK

now

ledg

e ba

se

Use

rs

Env

ironm

ent

Kn

ow

led

ge

Act

ion

Res

po

nse

Info

rmat

ion

Act

ion

Res

po

nse

Info

rmat

ion

Kn

ow

led

ge

Act

ion

Act

ion

KM System

Sha

ring

of v

alua

ble

orga

niza

tiona

l inf

orm

atio

n.

Can

avo

id r

e-in

vent

ing

the

whe

el, r

educ

ing

redu

ndan

t wor

k.

May

red

uce

trai

ning

tim

e fo

r ne

w e

mpl

oyee

s

Ret

entio

n of

Inte

llect

ual P

rope

rty

afte

r th

e em

ploy

ee le

aves

if s

uch

know

ledg

e ca

n be

cod

ified

.

Ben

efitsofKM System

s:

Digital studen

ts

By

age

21, t

he a

vera

ge c

olle

gest

uden

t will

hav

e sp

ent:

10,0

00 h

ours

vid

eo g

ames

200,

000

emai

ls20

,000

hou

rs T

V10

,000

hou

rs c

ell p

hone

Und

er 5

,000

hou

rs r

eadi

ng (

!)

Cam

pus Web

Portals

28%

of i

nstit

utio

ns h

ave

web

-bas

ed c

ampu

s po

rtal

s (2

1% in

200

2)(2

003

Nat

ion

al S

urv

ey o

f IT

in U

S H

igh

er E

du

cati

on

)

Relev

ant Techniques to KM

-Kno

wle

dge

Eng

inee

ring

-Dat

a M

inin

g, In

form

atio

n E

xtra

ctio

n-O

ntol

ogy

-XM

L, X

ML

Sch

ema

-Kno

wle

dge

and

Ent

erpr

ise

Mod

ellin

g-B

usin

ess

Pro

cess

Mod

ellin

g-C

apab

ility

, Goa

l Mod

ellin

g,

-Use

r M

odel

ling

and

Pro

filin

g-C

ase

Bas

ed R

easo

ning

-Pla

nnin

g-W

orkf

low

Sys

tem

s

Ontology

In p

hilo

sop

hy

of

anci

ent

tim

e:O

ntol

ogy

isth

ebr

anch

of p

hilo

soph

y th

atst

udie

sth

e na

ture

of E

xist

ence

.

No

wad

ays:

In c

ompu

ter

scie

nce,

onto

logy

defin

es th

e ba

sic

term

s an

d re

latio

ns

com

pris

ing

the

stru

ctur

ed v

ocab

ular

y of

a to

pic

area

.It

is a

n ex

plic

it S

peci

ficat

ion

of a

Con

cept

ualis

atio

nor

a h

iera

rchi

cally

st

ruct

ured

set

of t

erm

s fo

r de

scrib

ing

a do

mai

n th

at c

an b

e us

edas

a

skel

etal

foun

datio

n fo

r a

know

ledg

e ba

se”.The New

Old Conception…

Why do we need Ontology ?

Knowledge

engineering

and management

User

modelling

Multimediasearch

and retrieval

Query

processing

Agent-based

computing

Semantic Web

E-commerce

How to Present Ontology ?

Ontology Research

�C

AK

E/V

ITA

(Rus

sia)

�O

ntoE

dit

(Ger

man

y)�

KA

ON

(Ger

man

y)�

Apo

llo(U

nite

d K

ingd

om)

�W

ebO

nto

(Uni

ted

Kin

gdom

)�

OilE

d(U

nite

d K

ingd

om)

�P

RO

TE

GE

(Uni

ted

Sta

tes)

�H

ozo

OE

-M

izog

uchi

Too

l(J

apan

)

and Software

KnowledgePortal

Not

a s

earc

h en

gine

for

data

or

info

rmat

ion

but f

or K

now

ledg

e

+

Ontology-based KP by Using KAON

THE W

ORKFLOW

of the system

Dev

elopmen

tUtilizing

Dev

eloping Process

Analyzing…

Dev

eloping Process

Vocabulary construction…

Dev

eloping Process

Concept definition…

Dev

eloping Process

Relationsh

ip and

property…

Dev

eloping Process

Ontology design…

Ontology-based

Knowledge Portal

by U

sing KAON

Ont

olog

y-ba

sed

Kno

wle

dge

Por

tal

ente

r

Persp

ectives

The

cur

rent

cap

abili

ty o

f mac

hine

inte

llige

nce

will

con

tinue

to b

e a

valu

able

res

ourc

e fo

r th

e fu

ture

.

Tec

hnol

ogy

will

cle

arly

bec

ome

mor

e he

lpfu

l in

deal

ing

with

info

rmat

ion

over

load

.

Wha

t abo

ut e

mpl

oyee

s?

Conclusion

�K

M -

seek

s to

und

erst

and

the

way

in w

hich

kno

wle

dge

is c

reat

ed, u

sed

and

shar

ed w

ithin

org

aniz

atio

ns.

�2

mod

els

in K

M th

eory

: DIK

W a

nd P

olan

iy’s

.

�B

oth,

pos

itive

and

neg

ativ

e, p

ersp

ectiv

es o

f KM

de

velo

pmen

t ava

ilabl

e.

Link

s us

ed

�A

BC

: An

Intr

oduc

tion

to K

now

ledg

e M

anag

emen

t (K

M)

(ww

w.c

io.c

om)

�W

ikip

edia

(ww

w.w

ikip

edia

.com

)

�K

now

ledg

e P

raxi

s (w

ww

.med

ia-a

cces

s.co

m)

�K

now

ledg

eM

anag

emen

t—E

mer

ging

Per

spec

tives

(ww

w.s

yste

ms-

thin

king

.org

)

�K

M p

asta

ndfu

ture

-Cha

ngin

gth

eru

les

ofth

ega

me

(ww

w.k

mw

orld

.com

)

End

of s

lides

Tha

nk y

ou fo

r lis

teni

ng!