Knowledge Management

(1)

Knowledge Management

INF5100 Autumn 2006

INF5100 Knowledge Management

-Outline

Background

Knowledge Management (KM)

What is knowledge

KM Processes

Knowledge Management Systems and Knowledge Bases

Ontologies

What is an ontology

Types of ontologies

Use of ontologies in KM

Ad-Hoc InfoWare (Example application)

Ad-Hoc InfoWare and Approach

Ontology Based Update

(2)

-October 2006 3

Application Domain:

Rescue and Emergency Applications

Participants from different organizations

paramedics, police, fire,…

Rescue Site Leader, Team Leaders

Dynamic environment

movement and activity on site

personnel arriving and leaving

Sparse Mobile Adhoc Networks

minimal infrastructure, few nodes

heterogeneity, limited resources (battery, bandwidth)

a lot of movement; frequent disconnections;

delay tolerance

(3)

-October 2006 5

Knowledge Management (KM) in Sparse

MANETs

Definition for KM:

”…the tools, techniques and processes for the most

effective management of an organization’s

intellectual assets”

(Davies et al 2003).

Adapted to information sharing in Sparse

MANETs:

… effective management of the intellectual

assets (information resources) available for

sharing in a Sparse MANET

-Knowledge Management (KM) in Sparse

MANETs

Information sharing and content integration not

solved sufficiently in middleware for SMANETs

today.

KM offer solutions, but these do not consider

challenges posed by SMANETs

Beneficial for dynamic environments (e.g. rescue

operations) to combine middleware infrastructure

provided by SMANET with KM solutions

KM solutions may be valuable contribution to

(4)

-October 2006 7

Problem Statement

Network wide information sharing in rescue

operations

Avoid information overflow

Cross organizational administration Information not static, frequent updates Only partial view of available information

Three main tasks

Establish who needs what information Enable vocabulary sharing & mapping Efficient metadata management

Outline

Background

Knowledge Management (KM)

What is knowledge

KM Processes

Ontologies

What is an ontology

Types of ontologies

Ad-Hoc InfoWare (Example application)

(5)

-October 2006 9

What is Knowledge Management?

Started in the 80s, Management Theory

with the notion that all knowledge can be formalized

the goal was to automatize production processes

Multidisciplinary: political science, communication

studies, IT, management sciences,…

Knowledge central – seen as part of an organization's

competence

Central questions in KM:

what is knowledge in the production process

how can the knowledge flow be improved

-What is Knowledge Management?

”…the tools, techniques and processes for

the most effective management of an

organization’s intellectual assets

” (Davies et

al 2003)

“… a dynamic, continuous organizational

phenomenon of interdependent processes

with varying scopes and changing

(6)

INF5100 Knowledge Management -October 2006 11

Outline

Background

Knowledge Management (KM)

What is knowledge KM Processes

Ontologies

What is an ontology Types of ontologies Use of ontologies in KM

Ad-Hoc InfoWare (Example application)

Ad-Hoc InfoWare and Approach Ontology Based Update

Rescue Ontology Example

Knowledge - Complementary Definition

(Gardner95):

KNOWING

what

information is needed

how

information must be processed

why

which information is needed

where

information can be found

to achieve a specific result

(7)

-October 2006 13

Perspectives on Knowledge

Source: Alavi/Leidner 2001, p.111

-Hierarchical View of Knowledge –

Common in IT

Data:

raw numbers and facts - symbols not yet interpreted

Information:

interpreted data - data which has been assigned a meaning Always linked to specific situation, has only limited validity

Knowledge:

personalized information

enables people to act and to deal intelligently with all the

available information sources. (action component)

Whole set of insights, experiences and procedures considered

correct and true, guide people’s thoughts, behavior and communication.

Always applicable in several situations, valid over a relatively

(8)

-October 2006 15

Types of Knowledge –

The most common taxonomy

Explicit: facts, in documents, models, pictures

articulated, codified, and communicated in symbolic form and/or natural language

Tacit: implicit, a mental model, skills

rooted in action, experience and involvement in a specific context

cognitive elements: mental models: mental maps, beliefs,

paradigms, view-points

technical elements: concrete know-how, crafts, skills – apply to

specific context, e.g. knowledge of the best way to approach a customer.

Individual: is created by and exists in the individual

Social/Collective: is created by and inherent in the collective actions of a group

Outline

Background

Knowledge Management (KM)

What is knowledge KM Processes

Ontologies

Ad-Hoc InfoWare (Example application)

(9)

-October 2006 17

Knowledge Management Processes

Creating knowledge

develop new - or replace existing - content within an organization’s knowledge

socialization, combination, externalization, internalization

Storing/retrieving knowledge

storage, organization, and retrieval of knowledge

Transferring and Sharing knowledge

communicating and sharing knowledge

Applying knowledge

integrate and make good use of knowledge in the organization

-Knowledge Management Processes

- Role of IT

(10)

-October 2006 19

Knowledge Storage/Retrieval –

Organizational Memory

Knowledge in various forms

e.g., documentation, structured information in databases, knowledge stored in expert systems, organizational procedures and processes

Semantic memory

: general, explicit and articulated

knowledge

e.g., organizational archives of annual reports

Episodic memory

: context-specific and situated

knowledge

e.g. specific circumstances of organizational decisions and their outcomes, place and time

Knowledge Storage/Retrieval –

Role of IT

Enhancement and expansion of semantic

and episodic organizational memory

Increase speed of access to organizational

memory

Effective tools: Query languages, multimedia

databases, DBMSs

Groupware: enable creation and sharing of

(11)

-October 2006 21

Knowledge Sharing (KS) and Transfer

Sharing vs. Transfer:

Transfer: focus, a clear objective, unidirectional Sharing: can be unintentionally, multiple directionally,

without a specific objective

may occur

between and among individuals within and among teams

among organizational units among organizations

KM Systems for KS:

repositories – databases of knowledge (knowledge bases) networks –facilitate communications among team members

or groups of individuals

-Knowledge Sharing (KS) and Transfer

Knowledge about where the knowledge is – often as

important as the original knowledge itself

Sharing this kind of metadata important

E.g. corporate directories: who knows what in

organization

Knowledge transfer is driven by communication

processes and information flows

Forms of knowledge transfer: informal/formal,

personal/impersonal

Knowledge transfer to locations where it is needed and

can be used is important

(12)

Outline

Background

Knowledge Management (KM)

What is knowledge KM Processes

Knowledge Management Systems and Knowledge Bases

Ontologies

Ad-Hoc InfoWare (Example application)

Rescue Ontology Example

Knowledge Management Systems (KMS)

IT-based systems developed to support and

enhance all KM processes

Three common applications:

the coding and sharing of best practices

the creation of corporate knowledge directories the creation of knowledge networks

Requirements

must provide ontologies

must provide search capabilities

often provide filter capabilities (filters can be computer-based or human-computer-based)

provide opportunities for collaboration and use of expertise

(13)

-October 2006 25

KMS and Knowledge Bases

Two main components of KMSs: knowledge

bases and ontologies

A knowledge base is a database

Usually domain dependent

Information may need to be abstracted,

synthesized, or integrated with other information

(e.g. in best practices databases)

Ontologies provide shared vocabulary and

facilitates reusability

-Outline

Background

Knowledge Management (KM)

Ontologies

What is an ontology

Types of ontologies Use of ontologies in KM

Ad-Hoc InfoWare (Example application)

(14)

-October 2006 27

What is an Ontology

The term ontology can mean different things

glossaries & data dictionaries

thesauri & taxonomies

schemas & data models

formal ontologies & inference

Many definitions… the most commonly used:

“An ontology is an explicit specification

of a conceptualization.” (Gruber)

What is an Ontology

Basically a model of some part of the world

(Universe of Discourse)

Defines a common vocabulary for sharing

information in a domain

Specifies terms for classes/concepts and

relations between these

informal text or using formal language (e.g.

(15)

-October 2006 29

Ontology Modelling & Implementation

Can be modelled using different knowledge

modelling techniques and implemented in various

kinds of languages

Heavyweight ontologies:

AI based languages (framebased, first order logic): e.g., Ontolingua, LOOM

Ontology mark-up languages: RDF(S), DAML + OIL, OWL

Only Lightweight ontologies :

Techniques from software engineering & databases: UML, ER, SQL-scripts

Not as expressive

-Outline

Background

Knowledge Management (KM)

What is knowledge

KM Processes

Ontologies

What is an ontology

Types of ontologies

Ad-Hoc InfoWare (Example application)

(16)

-October 2006 31

Types of Ontologies

We will look at two categorizations

These are based on

the richness of the internal structure

Lightweight ontologies

Heavyweight ontologies (ontology proper)

the subject of their conceptualization

Lightweight Ontologies

Catalogs:

controlled vocabulary – a finite list of terms.

Glossary:

list of terms and meaning as natural language statements. Not

machine processable.

Thesaurus:

a networked collection of controlled vocabulary terms

synonym relationship. No explicit hierarchy.

Informal is-a hierarchies:

not strict subclass

(17)

-October 2006 33

Heavyweight Ontologies

Formal is-a

strict subclass hierarchies, necessary for exploiting inheritance

Formal instance relationships (formal is-a)

includes domain instances

Frames

ontology includes classes with property information. All subclasses inherit properties.

Value restrictions

More expressive ontologies, can place restrictions on values that can fill a property.

Expressing general logical constraints

the most expressive, first order logic.

-Lightweight vs. Heavyweight Ontologies

(18)

-October 2006 35

Types of Ontologies Based on the Subject

of the Conceptualization

Top-level ontologies

aka Upper-level ontologies, general concepts, existing

ontologies link root terms to these (e.g. Cyc, SUMO)

Domain ontologies

Reusable in a specific domain (KM, medical, law,

engineering, chemistry etc. )

E.g., UMLS (medical)

Application ontologies

application dependent, often extend & specialize

vocabulary of a domain

Outline

Background

Knowledge Management (KM)

Ontologies

What is an ontology Types of ontologies

Use of ontologies in KM

Ad-Hoc InfoWare (Example application)

(19)

-October 2006 37

Use of Ontologies in KM

Knowledge representation

Offer a way to cope with heterogeneous

representations of resources

Give shared and common understanding of a

domain

Can be communicated between people and

application systems

-Information Sharing and Integration

Interoperability problem

have to make the different systems and domains

understand each other

Structural heterogeneity

data structures, schema

solutions from domain of distributed databases

Semantic heterogeneity

meaning of content

(20)

-October 2006 39

Ontologies in Information Integration

As solution to semantic heterogeneity problem:

explicitly describe semantics of information sources language for translation

3 General approaches: (Wache et. al 2001)

Single: global ontology with shared semantics

Multiple: need mapping between (each pair of) ontologies (inter-ontology mapping)

Hybrid: multiple ontologies are built on top of or linked to a shared vocabulary of basic terms (may function like a bridge or a translation)

Single, Multiple, and Hybrid

Ontology Approaches

single ontology approach hybrid ontology approach global ontology multiple ontology approach local

ontology ontologylocal local ontology local ontology local ontology local ontology shared vocabulary Or Top-level ontology

(21)

Outline

Background

Knowledge Management (KM)

Ontologies

Ad-Hoc InfoWare (Example application)

Ad-Hoc InfoWare and Approach

Ontology Based Update Rescue Ontology Example

-Ad-Hoc InfoWare

Simplify application development for Sparse MANETS

Configurable MW services

scalable protocols and services

Tradeoff

between abstraction and awareness of location, resources, context,... between non-functional requirements, e.g. performance vs. security and

availability

Separation of mechanisms and policies Coordination of knowledge management and resource management

Integration of information

Information, data, meta-data, resources Context awareness

Resource and QoS aware data placement

(22)

Ad-Hoc InfoWare

– Architecture Overview

Watchdogs Watchdogs Manager Watchdogs Execution Envir. Resource Manager Replic. Mgnt Proposal Unit Resource Monitor Adjac. Monitor Local Monitor Resource Avail. Distributed Event Notification Service Delivery State Mgnt Availability & Scaling Storage Mgnt

Security and Privacy Manager

Authentication Access Control Key Management Encryption

Knowledge Manager

Semantic Meta-data & Ontology Framework Query Mgnt XML/RDF parser Profile & Context Mgnt LDD SDDD Data Dict. Manager

Knowledge Management (KM)

in Ad-Hoc InfoWare

Manage knowledge sharing and integration

in a Sparse MANET

Adds layer of knowledge

Services that allow relating metadata

descriptions to semantic context.

Only give tools (not decide usage & content)

Share information about where to find

(23)

-October 2006 45

Related to KM Elements

Hierarchical view of knowledge

Explicit knowledge

Focused KM processes: Storage/Retrieval and

Transfer ( or Knowledge Sharing)

Not addressing learning aspect (knowledge creation)

Use of ontologies

Domain ontologies, e.g. medical, police, fire

Upper level ontology/ shared vocabulary (similar to Hybrid approach)

Ontology based update

Metadata enriched with terms/concepts from ontologies

Only ontology use (development etc not during rescue operation)

-The Knowledge Manager

Distributed Event Notification System Watchdogs Resource Management

Security and Privacy Management

Data Dictionary Mgnt.

Semantic Metadata &

Ontology Framework XML Parser

Profile & Context Mgnt

Query Mgnt Knowledge Manager LDD SDDD UNDERSTANDING INFORMATION OVERLOAD EXCHANGE RETRIEVAL AVAILABILITY

(24)

-October 2006 47

Three Types of Metadata

Information structure and content description

metadata

Data Dictionary Management

Content, formats, data types etc

Semantic metadata

Semantic Metadata and Ontology Framework

Relations between concepts,

e.g. is-a, hasPart, hasResource, hasDeviceType

Profile and context metadata

Profile and Context Management

User profile, device profile

Context: location, time, situation

Profiles and Context

Profiles

What, who

Device type, resources, groups etc (for device profile)

User preferences, roles, personalia etc (for user profile).

Fairly static information

Context

Where, when, why

location, time, situation (e.g. rescue operation)

Dynamic information (network nodes moving)

Used in different meanings (the term

context

)

time, location and situation for a device or user

(25)

INF5100 Knowledge Management -October 2006 49 SDDD – linking level (Instance) (Link) LDD – metadata Semantic/ topical Context Information layer Conceptual Implementation Ontology layer

SDDD = Semantic Linked Distributed Data Dictionary. LDD = Local Data Dictionary.

Three-layered Approach

-Outline

Background

Knowledge Management (KM)

Ontologies

Ad-Hoc InfoWare (Example application)

Ontology Based Update

(26)

-October 2006 51

Approach to Ontology Based Update

Ontologies to represent

rescue operation context model

profiles for user, device and information

Update priorities

information types

rescue operation roles

Operational structure and organization

Issues of Dynamic Update

Dynamicity and limited resources

unstable availability

Frequent updates

increased communication needs

consistency issues

Need efficient metadata management to achieve

ontology based update in this environment

(27)

-October 2006 53

Kinds of Dynamic Update

- Overview

Between Entities Metadata or Data Change or Append (Vertical) Local update Different level data dictionaries Metadata Both (Horizontal) Metadata Exchange SDDDs Metadata Append (Horizontal) Ontology Based

SDDDs & KBs Both Both

SDDD = Semantic Linked Distributed Data Dictionary. KB = Knowledge Base.

-Outline

Background

Knowledge Management (KM)

Ontologies

Ad-Hoc InfoWare (Example application)

(28)

-October 2006 55

Example of Organization and Structure in

Rescue Operations

(29)

-October 2006 57

Upper Ontology for All Profiles

-Information Profile

and

Example

(30)

User

Profile

Example of DB Schema

Information Profile:

pr:InformationProfile(pr:IPId, pr:item)

pr:InformationItem(pr:IId, pr:subject, pr:priority)

pr:InformationPriority(pr:IPrId,...)

UserProfile:

pr:UserProfile(pr:UPId, pr:person, pr:role)

pr:RescueOperationRole(pr:RORId, pr:RORoleType, pr:reportsTo, pr:responsibility, pr:isMemberOf, pr:hasUpdatePriority)