Knowledge Management & Semantic Web

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University of Crete

HY566
-
Semantic Web

CS566


Semantic Web

Computer Science Department
-

UoC

Heraklion
5 June
, 2003

Παπαγγελής Μάνος
,
Κοφφινά Ιωάννα
,
Κοκκινίδης Γιώργος

Knowledge Management

& Semantic Web

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

2

Overview


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic Web


Knowledge Representation


Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

3

Contents


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic Web


Knowledge Representation


Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

4

What is Knowledge Management (KM)


There is
no universal definition

of KM


K
M
could be defined as

the process through which
organizations
generate value

from their intellectual
and knowledge
-
based assets


KM is often
facilitated by IT


Not

all information is valuable


Two categories of knowledge


Explicit
-

Anything that can be documented, archived
and codified, often with the help of IT


Tacit
-

T
he know
-
how contained in people's heads

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

5

Technologies that support current KM Systems


K
nowledge repositories


E
xpertise access tools


E
-
learning applications


D
iscussion and chat technologies


S
ynchronous interaction tools


S
earch and data mining tools.

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

6

KM System Weaknesses


Searching Information


Word keywords

don’t express the
semantics


Extracting Information


Agents

are
not able

to

extract knowledge from textual
representations

and
to

integrate information

spread over
different sources


Maintaining


Sustaining
weakly structured

text sources is
difficult

and
time
-
consuming


Such collections
cannot be

easily
consistent
,
correct

and
up
-
to
-
date


Automating Document Generation


Adaptive Websites

that enable dynamic reconfiguration
based on user profiles require
machine

accessible
representation

of the
semi
-
structured data

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

7

Contents


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic Web


Knowledge Representation


Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

8

Ontology
-
based KM systems


Methodology for developing
ontology
-
based KM

systems


Ontologies can help
formalize the knowledge shared by a group of
people
, in contexts where knowledge has to be
modeled
,
structured

and
interlinked


Distinction between
knowledge process

and
knowledge meta
-
process


Two orthogonal Processes
with Feedback Loops


Knowledge Process


Knowledge Meta
-
process

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

9

The Knowledge Process (1/4)


Knowledge Creation


Knowledge Import


Knowledge Capture


Knowledge Retrieval
and Access


Knowledge Use

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

10

The Knowledge Process (2/4)


Knowledge Creation


Computer
-
accessible knowledge moves between
formal

and
informal


In order to have knowledge in the middle of the two
extremes the idea is to
embed the structure of
knowledge items

into
document templates

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

11

The Knowledge Process (3/4)


Knowledge Import


Importing knowledge into KM system has the
same

or
more importance

than creating it


For imported knowledge,
accurate access

to
relevant items plays an even
more important

role
than

for
homemade knowledge


Knowledge Capture


Knowledge capturing refers to
the way

that
knowledge items
,
their essential contents

and
their interlinks

are
accessed

(OntoAnnotate)

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

12

The Knowledge Process (4/4)


Knowledge Retrieval and Access


Typically through a conventional GUI


Ontology

can be used
to derive
further

views of the knowledge

(e.g. Navigation)
and
additional links

and
descriptions


Knowledge Use


It is
not the knowledge itself

that is of most
interest,
but the derivations made from it


No single knowledge item

can be useful,
but
the overall picture

derived the total analysis

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

13

The Knowledge Meta
-
Process (1/3)


Feasibility Study


Kickoff phase


Refinement Phase


Evaluation Phase


Maintenance Phase

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

14

The Knowledge Meta
-
Process (2/3)


Feasibility Study


Identification

of problems and opportunity
areas


Selection

of the most promising focus area
and target solution


Kick off phase


Requirement specification


Analysis of input sources


Development of
baseline taxonomy

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

15

The Knowledge Meta
-
Process (3/3)


Refinement phase


Concept Elicitation with domain experts


Development of baseline taxonomy


Conceptualization and Formalization


Evaluation Phase


Revision and Expansion
based on feedback


Analysis of
usage patterns


Analysis of
competency questions


Maintenance Phase


Management of organizational maintenance
process

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

16

Contents


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic
Web


Knowledge Representation


Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

17

A Framework for KM on the SW

1.
Knowledge Capturing

2.
Knowledge Repository

3.
Knowledge Processing

4.
Knowledge Sharing

5.
Using of Knowledge

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

18

Knowledge Capturing


Knowledge can be collected from various
sources and in
different formats


Four Types of Knowledge Sources


Expert knowledge


Legacy Systems


Metadata Repositories


Documents


Need for Knowledge Capturing Tools

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

19

Knowledge Repository


Use of Relational Databases


Efficient
storing


Efficient Access to
RDF metadata


It is an RDF Repository like RDFSuite or RDF
Gateway

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

20

Knowledge Process


Efficient manipulation of the stored
knowledge


Graph
-
based

processing for knowledge
represented in the form of rules


E.g Deriving a dependency graph

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

21

Knowledge Sharing


Knowledge Integration

of different sources
(Knowledge Base) and its utilization


Realized by
searching for rules

that satisfy
the query conditions


Searching is realized as an inferencing
process


Ground assertions (
RDF triples
) and domain
axioms are used for deriving
new assertions

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

22

Using of Knowledge


Finding appropriate documents is essential,
but the
derivation

made of them
adds value

to
KM applications


Composition of documents


Use of
conditional statements


Conditional Statements leads to efficient
searching for knowledge


Precondition
-
Action

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

23

Proposed KM Framework

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

24

Contents


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic Web


Knowledge Representation

ƒ
Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

25

Knowledge Representation


Knowledge should be expressed by explicit
semantics in order to be understood by
automated tools


Select
schemas

and express knowledge
through them


Knowledge
sharing,merging

and
retrieval

are
possible if the categories used in the
knowledge representation are connected by
semantic links, expressed in ontologies


University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

26

Elements of Knowledge
Representation


Ontologies and Knowledge Bases


Ontologies

are catalogues of
categories

with their
associated complete or partial formal definitions of
necessary and sufficient
conditions


A
knowledge base

is composed of one ontology (or
several interconnected ontologies) plus additional
statements using these ontologies


Ontology Servers


Permit Web users to modify the ontology part of the
KB


Knowledge within Web Documents


Permit the insertion of knowledge inside HTML
documents


University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

27

Challenges of Semantic Web


Scale

of information


The information found on the Web is orders of magnitude
larger than any traditional single knowledge
-
base


Change

rate


Information is updated frequently


Lack of
referential integrity


Links may be broken and information may not be found


Distributed
authority


Trust of knowledge is not standard because data are
obtained through different users


Variable
quality

of knowledge


Knowledge may differ in quality and should not be treated
the same

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

28

Challenges of Semantic Web (cont.)


Unpredictable use

of knowledge


Knowledge base should be task
-
independent


Multiple knowledge
sources


Knowledge is not provided by a single source


Diversity of
content


The focus of interest is wider


Linking
, not copying


The size of information forbid the copy of data


Robust inferencing


The degrees of incompleteness and unsoundness
must be functions of the available resources


Answers could be approximate

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

29

Ontology


Processing and sharing of knowledge between
programs in the Web


Definitions


Representation of a shared conceptualization of a
particular domain


A consensual and formal specification of a vocabulary
used to describe a specific domain


A set of axioms designed to account for the intended
meaning of a vocabulary


An ontology provides


A
vocabulary

for representing and communicating
knowledge about some topic


A
set of relationships

that hold among the terms in
that vocabulary

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

30

Ontology Driven KR


Knowledge sharing and reuse


Enable machine
-
based communication


Reusable descriptions between different
services


No more keyword
-
based approach…


…but
syntactic
-

and
semantic
-
based discovery
of knowledge


Hierarchical

description of important concepts
and definition of their properties (attribute
-
value mechanism)

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

31

Languages for KR

1.
XML


2.
RDF / RDF Schema


3.
DAML+OIL


4.
OWL

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

32

Contents


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic Web


Knowledge Representation


Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

33

On
-
To
-
Knowledge


On
-
To
-
Knowledge was a European project
that built an
ontology
-
based tool environment

to speed up knowledge management


Results aimed were


Toolset

for semantic information processing
and user access


OIL
, an ontology
-
based inference layer on
top of the Web


Associated Methodology


Validation

by industrial case studies

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

34

On
-
To
-
Knowledge Architecture

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

35

On
-
To
-
Knowledge Technical
Architecture

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

36

Tools Used


RDFferret


Combines full text searching with RDF quering


OntoShare


Storage of the information in an ontology and
querying, browsing and searching that ontology


Spectacle


Organizes the presentation (ontology
-
driven) of
information and offers an exploration context


OntoEdit


Inspect, browse, codify and modify ontologies

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

37

Tools Used (cont.)


Ontology Middleware Module (OMM)


Deals with ontology versioning, security (user
profiles and groups), meta
-
information and ontology
lookup and access via a number of protocols (Http,
RMI, EJB, CORBA and SOAP)


LINRO


Offers reasoning tasks for description logics,
including realization and retrieval


Sesame


Persistent storage of RDF data and schema
information and online querying of that information

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

38

Tools Used (cont.)


CORPORUM toolset


OntoExtract and OntoWrapper


Information Extraction and ontology generation


Interpretation of natural language texts is done
automatically


Extraction of specific information from free text
based on business rules defined by the user


Extracted information is represented in
RDF(S)/DAML+OIL and is submitted to the Sesame
Data Repository

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

39

Contents


Introduction to Knowledge Management


Knowledge Management Weaknesses


Knowledge Management for Semantic Web


Ontology
-
based KM systems


A Framework for KM on the Semantic Web


Knowledge Representation


Knowledge Management System Example


Conclusion Remarks

University of Crete

HY566
-
Semantic Web

Spring‘
0
3

Knowledge Management & Semantic Web

40

Conclusion Remarks


Current Knowledge Management technologies
need to be revised


There are some architectures of Knowledge
Management Systems for Semantic Web but
there are only few KM applications available


Knowledge Representation has to meet the
challenges that Semantic Web poses


On
-
to
-
knowledge proposes a fine architecture
on which KM systems for SW can be based