INTELLIGENT CONTENT
MANAGEMENT SYSTEM
IST-2001-32429 ICONS
dr Bartosz Nowicki
dr Witold Staniszkis
Rodan Systems S.A.
The ICONS consortium
Presentation Outline
•
•
•
•
•
What is knowledge management?
Where are we now?
ICONS - a possibility to get even further!
What do we want to achieve?
Presentation of Rodan Systems S.A.
2
Knowledge Management
a set of compound activities aiming at
increasing an organisation’s effectiveness
and efficiency on the way of better
exploitation of information resources
Remedy for:
• bad decisions caused by lack of pertinent
information
• insufficient reuse
• information chaos
• overwhelming communication
3
Knowledge Management Life Cycle
Knowledge
Production
Knowledge
Claims
•Interaction
•Data/Info acquisition
•New knowledge claims
•Initial codification
Knowledge
Validation
Organisational
Knowledge
•Knowledge claim peer review
•Application of validation criteria
•Weighting of value in practice
•Formal knowledge codification
Knowledge
Integration
•Sharing and transfer
•Teaching and training
•Implementing new knowledge
•Production of knowledge artifacts
Experiential feedback loop
Knowledge Management Consortium International 2001
4
Where are we now?
Authors'Association
Polish Press Agency
8
Ministry of Economy
9
Road Inspection
10
Exchange Commission
11
SANPLAST Portal
12
ICONS - a possibility to get even
further!
ICONS formal information
• Rodan Systems - co-ordinator, initiator, project management,
architecture, prototype development, procedural knowledge
• University of Dauphine - distributed content repository
• University of Ulster - knowledge management paradigms
• Centro Informazioni Economiche a Sociali – Datalog inference engine
• SchmumbergerSema Belgium - the NAS Best Practices Portal
• IPI PAN - tools, standards, methods, user interface
• InfoVide - ICONS deployment methodology
• Budget: > 3 million EURO; founded 1,9
• Duration: 24 months; effort 350 man-months
14
Current project status
•
•
•
•
•
•
Started 1st January 2002
No slippage now!
First consortium meeting
First project review - positive
7 complete and 4 draft reports
Publications
– 2 book chapters
– 11 papers
– 13 presentations
• A number of working prototypes of specific functionality
• Sound integration platform of OfficeObjects® Portal
15
What do we want to achieve?
‘Simple ideas are hard to implement,
complex ideas are impossible to implement’
Prof. Witold Litwin, ACM fellow
on the first ICONS project meeting
Warsaw, Poland, 2002
Project goals
• Developing a stable prototype
• Supporting uniform, knowledge-based access to
– distributed information resources available in the form of web
pages,
– pre-existing heterogeneous databases, as well as
– legacy information processing systems.
• Managing knowledge base comprising
– meta-information representing the domain ontology of various
nature (structural, procedural, declarative, knowledge maps)
– multimedia content
18
Project plans
• Development of knowledge representation techniques and
methodologies for a multimedia content repository
• Development of user interface design and management tools
• Design and implementation of efficient algorithms for management of
large distributed multimedia content repositories
• Development of an analysis and design methodology for large,
knowledge-based content repository systems
• Integration of relevant research result and standards in a coherent
ICONS architecture and development of stable prototype
• Demonstration of the viability of the ICONS prototype in a real
application environment of “NAS Best Practices Portal”
• Starting point for development - OfficeObjects® Portal platform
19
ICONS: areas of interest, existing
solutions, points of attack
• Integration of
heterogeneous resources
• Intelligent agentsBusiness
Intelligence
Systems
Data
Bases
Web Pages
Legacy
Information
Systems
• An advanced
Conceptual
trees
Semantic
nets
Document
Management
Knowledge
Representation
Inference
Hyper-tekst
Semantic Data
Models
XML
RDF
Knowledge
Management
System
Process
graphs
Files
Electronic
signature
Knowledge
AutenthicationEngineering
• Knowledge engineeering aids
• Business process metrics
• Intelligent workload
assignment algorithms
Time
representation
nets
Search
Information
Integration
graphic interface
Encription
for knowledge
represenation
• Intelligent
Security
personalisation
facitlties
Access
Control
Text
Knowledge
maps
SDM nets
Files
• A formal knowledge
represenation language
• An Inference Engine
Properties
• A time
modelling
Knowledge
Semantic • Navigation
maps in semantic nets
Workflow
Management
Discussion
Forums
Version
control
Repository
Collaboration
HSM
Internet
Intranet
DBMS
Message • Scalable distributed ICONS
Exchange architecture
20
• Load balancing algorithms
• Intelligent information integrator
Knowledge access
Full text search
Attribute based
search
Content Repository
I
I
I
I
I
I
I
I
I
I
Navigational search
Categoristaion
based
(knowledge
maps)
Link based
21
Structural knowledge navigation
22
Procedural knowledge and
intelligent workflow management
•
•
•
•
•
•
•
•
•
•
WfMC compliant
advanced time modelling
intelligent workflow participant assignment
intelligent flow control
personalised „to do” list
knowledge creation processes
process monitoring
workflow distribution
process definition an important part of domain ontology
process instances important for optimisation
23
Selection of the best performer
positions
J
J
J
J
J
J
J
J
roles
J
J
J
J
J
J
J
Workflow engine assigns a task taking
into account positions competencies
and the task specifics, current load,
availability
time constraints
availability
load balancing
J
J
J
J
authorisation
J
J
final decision
L
24
“To do” list - a single access point to
delegated tasks
25
Load balancing
employee 1
employee 2
employee 3
employee 4
task under execution
waiting tasks
rescheduled task
26
Declarative knowledge
•
•
•
•
Support in solving difficult tasks
Disjunctive Datalog rules
Easy validation
Efficiency issues (application of main memory databases)
col(X,red) or col(X,green) or
col(X,blue) :-state(X)
:- border(X,Y), col(X,C), col(Y,C)
27
Scalability
Efficiency must be preserved regardless of increasing:
number of users
volume of data
amount of processes
variety of services provided
•
•
•
•
Data Access Performance
Scalability to Pbytes
High-Availability 7/24
Load Balancing
28
Typical Network Multicomputer /
Grid computer
Client
Server
Network
segments
Scalable distributed data structures (SDDS) - an
approach to efficient data access
29
Integration
Intelligent, web services based agents
a software entity that carries
out some set of operations
on behalf of a user or
another program with some
degree of independence or
autonomy, and in so doing,
employing some knowledge
or representation of the
user’s goals or desires
30
Human/Computer Interaction (HCI) Technologies
HCI
Personalisation
Engine
Electronic
Form
Manager
Electronic
Form
Manager
Knowledge
MapGraph
Manager
Content
Presentation
Manager
Structural
Knowledge
Graph Manager
Distributed
Architecture
Technologies
Process Graph
Manager
Structural
Knowledge
Graph Manager
Load Balancing
Algorithms
Knowledge Management Technologies
Ontology
Model
Manager
Structural
Knowledge
Navigator
Content
Categorisation
Engine
Datalog
Inference
Engine
Intelligent
Workflow
Manager
Semi-structured
Content
Integrator
Intelligent Agent
Development
Environment
Distribution
Optimisation
Algorithms
Scalable
Distributed
Data Structure
Content Management Technologies
Content
Repository
Manager
Content
Semantic Model
Manager
Workflow
Manager
Hierarchical
Storage
Manager
External
Content
Integrator
Role
Manager
Content Schema
Definition
Environment
Distributed
Workflow
Communication
Development Technologies
Object
Relational
DBMS
Main
Memory
DBMS
- exists, to be selected
Full Text
Search
Engine
Web
Application
Server
- exists, to be expanded
J2EE
Development
Environment
Security
Environment
- to be developed
Operating
System
ICONS project focus boarders
31
Content
XML/
Knowledge
Presentation
Level
Model
DHTML
Definition
Page
Process
Map
(WfMC)
Inference
Knowledge
Map
Rule
Definition
(DTD, RDF)
Information Object Mapper (XSL, SVG)
Content Structure Mapper
HTTP/ WebDav
Server
Inference Rule Mapper
Content
Disjunctive Datalog
Management
Inference Engine
Framework
Knowledge
Manipulation
Level
Content Base
(XML)
Ontology Base
Knowledge
(RDM)
Extractor/
Associator
Hierarchical Storage Manager
Integration
Level
Pre-existing, heterogeneous databases
Multi-source Information Mapper
Legacy Information Processing Systems
Web Information sources
I
C
O
N
S
A
R
C
H
I
T
E
C
T
U
R
E
32
ICONS - a platform for knowledge
intensive applications
Standard
functional
area 1
Standard
functional
area 2
Specific
functional
area 1
Specific
functional
area 2
ICONS
INTELLIGENT CONTENT MANAGEMENT SYSTEM
Heterogeneous
databases
Legacy Systems
Web sources
33
ICONS Methodology
•
•
•
•
•
•
•
•
•
•
Overall lifecycle
Modelling guidelines
Parametrisation guidelines
Guidelines for technical development of specific functional areas
Standard solutions
Strategy alignment
Best practice focus
Hardware / software infrastructure preparation
Social issues
Project management
Necessary for smooth implementation, deployment and
maintenance of a concrete ICONS based application
34
The NAS Best Practices Portal
•
•
•
•
To validate and give proof of concept for ICONS
To address social and economic objectives of EU
To gather basic information on ISP, SAPARD and PHARE projects
To allow more effective founding thanks to identified good practices
35