Semantic Web:Semantic Web:The Future Starts TodayThe Future Starts Today

“Industrial Ontologies” Group

http://www.cs.jyu.fi/ai/OntoGroup/index.html

Agora Center, University of Jyväskylä, 23 May 2003

Industrial Ontologies GroupIndustrial Ontologies Group

““Industrial Ontologies” Group: Industrial Ontologies” Group: Our HistoryOur History

• 1978-1984 – We took part in development of the first in USSR Industrial Natural Language Processing System “DESTA”, which included semantic analysis and ontologiesontologies;

• 1985-1989 - We took part in development of the first in USSR Industrial Automated Natural Language Programming System “ALISA”, which Enabled Semantic AnnotationEnabled Semantic Annotation, DiscoveryDiscovery and IntegrationIntegration of software components (prototype of today's Semantic Web ServicesSemantic Web Services concept);

““Industrial Ontologies” Group: Industrial Ontologies” Group: Our HistoryOur History

• 1990-1993 – under name of Metaintelligence Lab. we were piloting concept of a Metasemantic Network (triplet-based (meta-)knowledge representation model) – prototype of today’s RDF-based knowledge representation in Semantic WebSemantic Web;

• 1994-2000 – various projects with industrial partners, e.g. MetaAtom – “Semantic Diagnostics of Ukrainian Nuclear Power Stations based on Metaknowledge”; MetaHuman – industrial medical diagnostics expert system based on Metaknowledge”; Jeweler – metamodelling and control of industrial processes, etc.; got several research grants from Finnish Academy;

““Industrial Ontologies” Group: Industrial Ontologies” Group: Our HistoryOur History

• 2000-2001 – we have created branches in Vrije Universiteit Amsterdam (heart of Semantic Web activities in Europe) where now working 5 our former team members, in Jyvaskyla University (several tens of researchers) and established research groups in Kharkov (Ukraine) on Data Mining, Educational Ontologies, Telemedicine, etc.

• 2001-2003 – we took part in MultiMeetMobile Tekes Project, in InBCT Tekes Project in Tempus EU Compact Project in (or in cooperation with) University of Jyvaskyla where we further promote Semantic Semantic WebWeb concepts.

Industrial Ontologies Group:Industrial Ontologies Group:Important ObjectiveImportant Objective

• For us there are no doubts about the possibilities, which Semantic Web opens for industry.

• that is why one important objective of our activities is to study appropriate industrial cases, collect arguments, launch industrial projects and develop prototypes for the industrial companies to not only believe together with us but also benefit from the Semantic Web.

Why and Where Semantic Web ?Why and Where Semantic Web ?

WWW

Business

Knowledge Management

more then 3,000,000,000 web-pages “Information” burst ICT needs comprehensive resource management technology

Needs for integration of businesses Web Services for e-Business Standardization and Interoperability problems

Consolidate and reuse experience Standardize knowledge sharing technology Needs for the intelligent tools to use human’s knowledge

Approach: Semantic WebApproach: Semantic Web

“The Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes,

but for automation, integration and reuse

of data across various applications”

http://www.w3.org/sw/

The Semantic Web is an initiative with the goal of extending the current Web and facilitating Web automation, universally accessible web resources, and the 'Web of Trust', providing a universally accessible platform that allows data to be shared and processed by automated tools as well as by people.

Word-Wide Correlated ActivitiesWord-Wide Correlated Activities

Semantic Web

Grid Computing

Web Services

Agentcities

Agentcities is a global, collaborative effort to construct an open network of on-line systems

hosting diverse agent based services.

WWW is more and more used for application to application communication.The programmatic interfaces made available are referred to as Web services.

The goal of the Web Services Activity is to develop a set of technologies in order to bring Web services to their full potential

FIPA

FIPA is a non-profit organisation aimed at producing standards for the interoperation

of heterogeneous software agents.

Semantic Web is an extension of the currentweb in which information is given well-definedmeaning, better enabling computers and people

to work in cooperation

Wide-area distributed computing, or "grid” technologies, provide the foundation to a number of large-scale efforts

utilizing the global Internet to build distributed computing and communications infrastructures.

Semantic Web: New “Users” Semantic Web: New “Users”

SemanticAnnotations

Ontologies Logical Support

Languages Tools Applications /Services

Web content

UsersCreatorsWWWandBeyond

SemanticWeb

Semantic Webcontent

UsersSemanticWeb andBeyond

Creators

applications

agents

Semantic Web: Resource IntegrationSemantic Web: Resource Integration

Shared ontology

Web resources / services / DBs / etc.

Semantic annotation

Semantic Web: What to Annotate ?Semantic Web: What to Annotate ?

Web resources / services / DBs / etc.

Shared ontology

Web users (profiles,

preferences)

Web access devices

Web agents / applications

External world resources

Smart machines and devices

Ontologies: the foundation of Semantic WebOntologies: the foundation of Semantic Web

Document

Location

Subject

name

is-a

uri

comment __Thing__

is-a

Report

Web-page

Access Rights

Author

http://www.ontogroup.net

is-a

\\AgServ\vagan\InBCT_1.doc

V. Terziyan

Author

O. Kononenko

Author

uriLocation

draft

comment

public

Home page

comment

3.1: analysis

Subject

Instance-of Instance-of

Query 1: get all documents from location X, but not web-pagesQuery 2: get documents related to Y, with more then one author, one of which is TerziyanQuery 3: are there web-pages of Z with “private” access related to documents with subject S?

Related to

Related to

Access rights

#doc1 #doc2

Ontologies are key enabling technology for the Semantic Web

“..explicit specification of conceptualization..”

Ontology is formal and rich way to provide shared and common understanding of a domain, that can be used by people and machines

Semantic Webname

public

private

Semantic Web: InteroperabilitySemantic Web: InteroperabilityOntology A: Documents Ontology B: Research

A commitment to a common ontology is a guarantee of aconsistency and thus possibility of data (and knowledge) sharing

Common (shared) ontology

Ontology C: Services

System 1System 2

\\AgServ\vagan\InBCT_1.doc

V. Terziyan

A:Report

A:Location3.1: analysis

A:Subject

A:Author

Instance-ofSemantic Web

A:name

Co-operative Work in WebCo-operative Work in Web

WWW

Co-operative Work in Semantic WebCo-operative Work in Semantic Web

WWW

Semantic Web

Semantic Web is not Only ...Semantic Web is not Only ...

… but Alsobut Also ...

Industrial Ontologies GroupSamples of our Research:

“Applications of Semantic Web”

Web Resource/Service Integration:Web Resource/Service Integration:Server-Based Transaction MonitorServer-Based Transaction Monitor

Server Client

Server

Webresource /

service

Webresource /

service

Transaction Service

TMTM

wireless

Web Resource/Service Integration:Web Resource/Service Integration:Mobile Client-Base Transaction Mobile Client-Base Transaction

MonitorMonitor

ServerClient

Server

Webresource /

service

TM

Webresource /

service

wireless

wireless

The conceptual scheme The conceptual scheme of the ontology-based of the ontology-based

transaction transaction management with management with multiple e-servicesmultiple e-services

Transaction data

Service 1 ********

Service 2 ********

…

Service s ********

Services data

Transaction monitor

Client 1

…

Service 1 ********

Service 2 ********

…

Service s ********

Services data

Transaction monitor

Client r

Parameter 1

Parameter 2

…

Parameter n

Recent value

Recent value

…

Recent value

Transaction data

Parameter 1

Parameter 2

…

Parameter n

Recent value

Recent value

…

Recent value

Service atomic action ontologies

Parameter 1

Parameter 2

…

Parameter n

Parameter ontologies

Ontologies

Name 1

Name 2

…

Name n

Default value / schema 1

Default value / schema 2

…

Default value / schema n

Name of action 1

input parameters

output parameters

Name of action 2

input parameters

output parameters

Name of action k

input parameters

output parameters

…

Service Tree

Client 1 ********

Client 2 ********

…

Client r ********

Clients data

Subtransaction monitor

Service 1

Service Tree

Client 1 ********

Client 2 ********

…

Client r ********

Clients data

Subtransaction monitor

Service s

…

Terziyan V., Ontological Modelling of E-Services to Ensure Appropriate Mobile Transactions, In: International Journal of Intelligent Systems in Accounting, Finance and Management, J. Wiley & Sons, Vol. 12, 2003, 14 pp.

Ontology-Based Transaction Ontology-Based Transaction Management for the Semantic WebManagement for the Semantic Web

Consider two basic transaction management architectures in mobile environment depending on where the Transaction Monitor (TM) will be located. First one (Server-Based) assumes that TM will be located in server side, e.g. within some transaction management service. Second one (Client-Based) supposes that TM is located in mobile client terminal.

The first objective will be to provide and study an integrated mobile transaction management architecture for the Semantic Web applications, which will combine the best features from these two architectures by intelligent switching from one architecture to another one depending on current application context.

There is already some ontological support for Semantic Web resources and services interoperability based on OWL, DAML-S. However to be able to manage transactions in Semantic Web across multiple resources (or services) there will not be enough only ontologies for semantic annotations of these resources; there will be evident need of the ontology for the Semantic Web transactions itself.

The second objective will be developing pilot ontology for the RDF-based semantic annotation of mobile transactions in the Semantic Web.

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Web Resource/Service Integration:Server-Based Transaction Monitor

Server Client

Server

Webresource /

service

Webresource /

service

Transaction Service

TM

wireless

22

Web Resource/Service Integration:Mobile Client-Base Transaction Monitor

ServerClient

Server

Webresource /

service

TM

Webresource /

service

wireless

wireless

Public merchants,public customers, publicinformation providers

…

…

Clients

SMOs

SMRs

Maps<path network>

Maps<business points>

Integration,Analysis,Learning

Businessknowledge

Server

I

C

I

I

S

I

Negotiation,Contracting,

Billing

Meta-Profiles

Profiles

XMLWML

LocationProviders

Server

Map ContentProviders

Server

ContentProviders

Server

…

…

…

ExternalEnvironment

XML

$$$ Banks

Architecture for a Mobile P-Commerce ServiceArchitecture for a Mobile P-Commerce Service

Terziyan V., Architecture for Mobile P-Commerce: Multilevel Profiling Framework, IJCAI-2001 International Workshop on "E-Business and the Intelligent Web", Seattle, USA, 5 August 2001, 12 pp.

BANK: P-Commerce Service providerBANK: P-Commerce Service provider

Personal ontologyPersonal ontology General ontologyGeneral ontologyAutomatic:Automatic:

Mapping and TransactionsMapping and Transactions

Service UserService User

Service UserService User

Service UserService User Service UserService User

Service UserService User

Service UserService User

via resources and users annotationsvia resources and users annotations

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Multimeetmobile Project (2000-2001)

Information TechnologyResearch Institute(University of Jyvaskyla):Customer-oriented research anddevelopment in Information Technology

http://www.titu.jyu.fi/eindex.html

Multimeetmobile (MMM) Project(2000-2001):Location-Based Service System and TransactionManagement in Mobile Electronic Commerce

http://www.cs.jyu.fi/~mmm

Academy of FinlandProject (1999):Dynamic Integration ofClassification Algorithms

Mobile Location-Based Mobile Location-Based Service in Semantic WebService in Semantic Web

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M-Commerce LBS systemhttp://www.cs.jyu.fi/~mmm

In the framework of the Multi Meet Mobile(MMM) project at the University of Jyväskylä,a LBS pilot system, MMM Location-basedService system (MLS), has been developed.MLS is a general LBS system for mobileusers, offering map and navigation acrossmultiple geographically distributed servicesaccompanied with access to location-basedinformation through the map on terminal’sscreen. MLS is based on Java, XML and usesdynamic selection of services for customersbased on their profile and location.

Virrantaus K., Veijalainen J., Markkula J.,Katasonov A., Garmash A., Tirri H., Terziyan V.,Developing GIS-Supported Location-BasedServices, In: Proceedings of WGIS 2001 - FirstInternational Workshop on Web GeographicalInformation Systems, 3-6 December, 2001, Kyoto,Japan, pp. 423-432.

2 0

A d a p t i v e i n t e r f a c e f o r M L S c l i e n t

O n l y p r e d i c t e d s e r v i c e s , f o r t h e c u s t o m e r w i t h k n o w n p r o f i l ea n d l o c a t i o n , w i l l b e d e l i v e r e d f r o m M L S a n d d i s p l a y e d a tt h e m o b i l e t e r m i n a l s c r e e n a s c l i c k a b l e “ p o i n t s o f i n t e r e s t ”

21

Route-based personalization

Static Perspective Dynamic Perspective 2 2

I n d u c t i v e l e a r n i n g o f c u s t o m e rp r e f e r e n c e s w i t h i n t e g r a t i o n o f p r e d i c t o r s

rrmrr yxxx ,...,, 21

S a m p l e I n s t a n c e s

tmtt xxx ,...,, 21

y t

L e a r n i n g E n v i r o n m e n t

P 1 P 2 . . . P n

P r e d i c t o r s / C l a s s i f i e r s

T e r z i y a n V . , D y n a m i c I n t e g r a t i o n o f V i r t u a l P r e d i c t o r s , I n : L . I . K u n c h e v a , F .S t e i m a n n , C . H a e f k e , M . A l a d j e m , V . N o v a k ( E d s ) , P r o c e e d i n g s o f t h e I n t e r n a t i o n a l I C S CC o n g r e s s o n C o m p u t a t i o n a l I n t e l l i g e n c e : M e t h o d s a n d A p p l i c a t i o n s - C I M A ' 2 0 0 1 , B a n g o r ,W a l e s , U K , J u n e 1 9 - 2 2 , 2 0 0 1 , I C S C A c a d e m i c P r e s s , C a n a d a / T h e N e t h e r l a n d s , p p . 4 6 3 - 4 6 9 .

Machine-to-Machine CommunicationMachine-to-Machine Communication

P2P ontology

P2P ontology

Heterogeneous machines can “understand” each other while exchanging data due to shared ontologies

Semantic Web-Supported Sharing and Semantic Web-Supported Sharing and Integration of Web ServicesIntegration of Web Services

Different companies would be able to share and use cooperatively their Web resources and services due to standardized descriptions of their resources.

P2P ontology

P2P ontology

Corporate/Business HubCorporate/Business Hub

Publish own resource descriptions

Advertise own services

Lookup for resources with semantic searchAutomated access to enterprise (or partners’) resources

Hub ontologyand shared domain ontologies

Seamless integration of services

Software and data reuse

Partners / Businesses

What parties can do:What parties achieve:

Ontologies will help to glue such Enterprise-wide / Cooperative Semantic Web of shared resources

Companies would be able to create “Corporate Hubs”, which would be an excellent cooperative business environment for their applications.

Web Services for Smart DevicesWeb Services for Smart Devices

Smart industrial devices can be also Web Service “users”. Their embedded agents are able to monitor the state of appropriate device, to communicate and exchange data with another agents. There is a good reason to launch special Web Services for such smart industrial devices to provide necessary online condition monitoring, diagnostics, maintenance support, etc.

OntoServ.Net: “Semantic Web Enabled Network of Maintenance Services for Smart Devices”, Industrial Ontologies Group, Tekes Project Proposal, March 2003,

Global Network of Maintenance ServicesGlobal Network of Maintenance Services

OntoServ.Net: “Semantic Web Enabled Network of Maintenance Services for Smart Devices”, Industrial Ontologies Group, Tekes Project Proposal, March 2003,

Embedded Maintenance PlatformsEmbedded Maintenance Platforms

Service Agents

Host Agent

Embedded Platform

Based on the online diagnostics, a service agent, selected for the

specific emergency situation, moves to the embedded platform to help the host agent to

manage it and to carry out the predictive

maintenance activities

Maintenance Service

OntoServ.NetOntoServ.Net Challenges Challenges

• New group of Web service users – smart smart industrial devicesindustrial devices.

• InternalInternal (embedded) and externalexternal (Web-based) agent enabled service platformsservice platforms.

• “Mobile Service ComponentMobile Service Component” concept supposes that any service component can move, be executed and learn at any platform from the Service Network, including service requestor side.

• Semantic Peer-to-PeerSemantic Peer-to-Peer concept for service network management assumes ontology-based decentralized service network management.

Industrial Ontologies GroupIndustrial Ontologies GroupFuture Plans:Future Plans:

“Applications of Wireless Applications of Wireless Semantic WebSemantic Web”

Semantically annotated personal dataSemantically annotated personal data

Virtually all resources have to be marked with semantic labels that show explicitly theVirtually all resources have to be marked with semantic labels that show explicitly themeaning of the resource (piece of data, fact, value etc.) It will make possible for user: meaning of the resource (piece of data, fact, value etc.) It will make possible for user:

– To organize own view on data and use it for data management To organize own view on data and use it for data management – To access own and other’s resources with semantic queries using “terms” of own modelTo access own and other’s resources with semantic queries using “terms” of own model– To be able integrate data from other sources To be able integrate data from other sources

(semantics of data is important, data can be converted/translated if needed and appropriate mapping exists)(semantics of data is important, data can be converted/translated if needed and appropriate mapping exists)

Applications will have:Applications will have:– Possibility to discover and operate with user information and preferencesPossibility to discover and operate with user information and preferences– Possibility to share information with applications at other devices and elsewherePossibility to share information with applications at other devices and elsewhere

My data descriptionmodel (ontology)

Commondata semantic descriptions

(ontologies)

My resourcesand their descriptions

Personaldata-view

Applications

mapping between views

Other people’sdata-views

User data becomes available to variety of applications and other people

Semantic Web Semantic Web Inside™Inside™

Commitmentto ontology

Modelling of personal data viewsModelling of personal data views

Simple user data view (as is in most of mobile phones)Simple user data view (as is in most of mobile phones)

Model of user’s data and other resources:- Contacts (phone numbers, names etc.)- Notes (some pieces of text)- Calendar (with some events assigned)

It is rather simple, but a good beginning for own data model creation…..

Data to store in every instance of defined information model

Actually, this model is a simple ontology of “Personal Data” domain.

Using developed standard ontology languagesit will be stored in universal data format.

Building own data model…Building own data model…

added slot (property/field)

inherited slot

Building own data structureBuilding own data structure

added slot (property/field)

inherited slot

Inherited properties

“Relative is a kind of friend”

“Relative is a kind of friend”

Links to otherdata entities

Building own data structureBuilding own data structure

added slot (property/field)

inherited slot

Customized data model:Customized data model:• new kinds of datanew kinds of data• new kinds of representationnew kinds of representation• rules and constraints for data etc.rules and constraints for data etc.• association of data with applicationsassociation of data with applications

Customized data model:Customized data model:• new kinds of datanew kinds of data• new kinds of representationnew kinds of representation• rules and constraints for data etc.rules and constraints for data etc.• association of data with applicationsassociation of data with applications

Using generated interfaceUsing generated interface

Data view is described as an ontology which contains all needed information about data structure. User interface is built dynamically from ontology:• Fields for data• Form layout, types of controls (e.g. picture, checkboxes etc.)• Rules for data that can check some constraints, invoke actions, perform calculations – whatever!

For described data model forms are generated

Access your data quickly and easily…Access your data quickly and easily…

Terziyan’s Contact data

Event data

Possibilities to build flexible, easily customizable data management applications are great.

Just click to open

Every piece of data is somehow described in user’s terms from data-view ontology.Links between data make it easy to find needed information

Customizable personal information Customizable personal information management environmentmanagement environment

Personal data “view”:Personal data “view”:• Development of own view on personal data• Reusing of existing views (join, modify, extend)• Links between personal and some “global” ontology

Sharing of data:Sharing of data:• Applications use data and do it correctly (because of semantics assigned)• Applications can exchange data with external sources• Data can be translated in respect of its semantics

(for localization, between different data views, to fit some requirements etc.)

In such environment even development of own applications/scripts can be possibleIn such environment even development of own applications/scripts can be possible

Ontologies Ontologies andand Semantic Web Semantic Web will enable such kind of applicationswill enable such kind of applications

Easy-to-use, flexible, customizabledata management for users

Repositories of readydata-views

Note: Protégé-2000 ontology development and knowledge acquisition tool was used for demonstration

Enabled collaboration and interoperability

OntoCacheOntoCache

General ontology

Semantic annotations of Web-services (or any other resources) based on shared ontologies enhance much the efficiency of their search/browsing from the PDA. Local ontology adapts permanently to the user preferences.

Personalontology

OntoCacheOntoCache: : benefitsbenefits

Technology that supports future Ubiquitous Semantic Web

Effective filtering of wide variety of Web-resources

Support for semi-natural queries

Context and preferences-based adaptation

Phone calls are also possible between mobile terminal agents. They are performed without human participation in order to exchange local information.

Agent-to-Agent communicationAgent-to-Agent communication

Semantic annotation of the local data enables its intelligent processing by software. Ontologies provide interoperability between heterogeneous peers.

Agent-to-Agent communicationAgent-to-Agent communication

Health

Cooking

Business

?Whatever

semantics enablesintelligent data processing

ontological relationsdefine possible

cooperation betweendomain agents

shared ontologyensures

interoperability

TelemedicineTelemedicine

InIn thethe officeofficeOutsideOutside

FishingFishing

AnywhereAnywhere

At universityAt university

On a beachOn a beach

Health CenterHealth Center

Cases of Cases of

“Human “Human

Maintenance” Maintenance”

ActivitiesActivities

InteractionInteraction

“Recovery” Agents

“Diagnostic” Agents

“Platform Steward”

“WatchDog”“Therapist”

Human and Human and Local Health Maintenance CenterLocal Health Maintenance Center

Remote Health Maintenance CenterRemote Health Maintenance Center

“Recovery” Agents

“Diagnostic” Agents

“Therapist”

“Platform Steward”

Maintenance Crew Service

Health Maintenance Health Maintenance without without barriersbarriers

Anytime and AnywhereAnytime and Anywhere

OntoGamesOntoGames:: New Games GenerationNew Games Generation

CGPCGPPUPPUP

Personal User ProfilePersonal User Profile Common Games ProfileCommon Games Profile

Personal ontologyPersonal ontology General ontologyGeneral ontology

OntoGamesOntoGames: Semantic Games Space: Semantic Games Space

Personal ontologyPersonal ontology General ontologyGeneral ontology

OntoGamesOntoGames: Exit in the Real Life: Exit in the Real Life

Realit

y connec

tion

Realit

y connec

tion

via the g

ame

via the g

ame

Reality connection

Reality connection

via the game

via the game

General ontologyGeneral ontologyPersonal ontologyPersonal ontology

Non Stop Game - Non Stop LifeNon Stop Game - Non Stop Life

OntoGamesOntoGamesCCONNECTING ONNECTING P PEOPLEEOPLE

BANKBANK: Data : Data annotationannotation

In order to make miscellaneous data gathered and used later for some processing,every piece of data needs label assigned, which will denote its semantics in terms ofsome ontology. Software that is developed with support of that ontology can recognize the data and process it correctly in respect to its semantics.

Ontology of gathered data

Web forms and dialogs generated

An

no

tate

d d

ata

(RD

F)

Processing of data by some other semantic-aware applications

BANKBANK: : Customer’s data processingCustomer’s data processing

DataStorage

BankClients

Ontology

BankClients

Input forms

Intelligentontology-based

software

Clients clustering

BANKBANK:: Services annotationServices annotation

Semantics enabled services – Semantics enabled services – easy way to use for customereasy way to use for customer

Semantically Semantically annotated bank annotated bank

servicesservices

I want to …Information filing, Information filing, all documentation all documentation and transactionsand transactions

Less detailed Less detailed informationinformation

Agent-assistant Agent-assistant

Customer Customer

BANKBANK: Loan Borrower annotation: Loan Borrower annotation

Loan borrowersLoan borrowers

Bank - investor Bank - investor

Automated support of:Automated support of:• making decisions about trustingmaking decisions about trusting• prediction of future trends prediction of future trends via semantically annotated loan via semantically annotated loan

borrowers informationborrowers information

Read Our Recent ReportsRead Our Recent Reports

• Semantic Web: The Future Starts TodaySemantic Web: The Future Starts Today– (collection of research papers and presentations of Industrial Ontologies

Group for the Period November 2002-April 2003)

• Semantic Web and Peer-to-Peer: Semantic Web and Peer-to-Peer: Integration and Interoperability in IndustryIntegration and Interoperability in Industry

• Semantic Web Enabled Web Services: Semantic Web Enabled Web Services: State-of-Art and ChallengesState-of-Art and Challenges

• Distributed Mobile Web Services Based on Semantic Web: Distributed Mobile Web Services Based on Semantic Web: Distributed Industrial Product Maintenance SystemDistributed Industrial Product Maintenance System

• Available online in: http://www.cs.jyu.fi/ai/OntoGroup/index.html

Industrial Ontologies GroupIndustrial Ontologies Group

V. Terziyan

A. Zharko

O. Kononenko

O. Khriyenko

Semantic Web: The Future starts todaySemantic Web: The Future starts today

e-Business,net-marketse-Business,net-markets

“Web Of Trust”“Web Of Trust”

Enterprise

Application

Integration

Enterprise

Application

Integration

Interoperability standardsInteroperability standards

Web-servicesWeb-services

Industrial Ontologies Group: Examples Industrial Ontologies Group: Examples of Related Contactsof Related Contacts

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Participation inOntoWeb Network

The goal of the OntoWeb Network is to bringtogether researchers and industrials comingfrom the research and applications areas,promoting interdisciplinary work andstrengthening the European influence onSemantic Web standardisation efforts such asthose based on RDF and XML. Europe'scultural diversity and multi linguality, togetherwith the strong scientific competenciesexisting in the ontology field, may give Europea unique opportunity to fully exploit ontology-based technology and to play a leading role inthese emerging area.

http://www.ontoweb.org

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University of Jyvaskylais Member of MeT

MeT is an initiative founded byEricsson, Motorola and Nokiato establish a framework forsecure mobile transactions,ensuring a consistent userexperience independent ofdevice, service and network.

http://www.mobiletransaction.org

25

University of Jyvaskylais Member of WIM

http://www.cs.auc.dk/WIMWireless Information Management (WIM) is aresearch training network involvingresearchers from six universities in Denmark,Finland, Lithuania, Norway, and Sweden.Approximately 30 Ph.D. students and theiradvisors and colleagues take part. WirelessInformation Management encompasses themanagement of information obtained fromsensors as well as the management ofinformation involving mobile objects, both ofwhich types of information concern continuouschange, be it in virtual spaces or physicalspace. These types of data will gainprominence in step with the increasingdeployment of wireless communications andsensor technologies.The project aims to offer training in this area,in which there are significant industrialstrengths and interests in the Nordic region.

1. Aalborg University2. Norwegian University of Science and Technology3. University of Jyvaskyla4. Uppsala University5. Vilnius Gediminas Technical University6. Agder University College

26

IT Faculty (Jyvaskyla) - AI Department (Kharkov):Ukrainian students in Mobile Computing Line

Students Background

-C and JAVA Programming

-Network Management

-Mobile Technologies

-Intelligent Agents Technologies

-Web-content Filtering and Personalization

-Data and Web Mining

-Knowledge Management

-Semantic Web (XML, RDF, RDF Schema,DAML)

-Mobile Commerce Applications

-Object-oriented Design

-Database Management

Special personal abilities

-strong motivation-analytical thinking-adaptivity-self-learning-knowledge acquisition-flexibility-professionalism

http://www.cs.jyu.fi/ai/projects/master01/

Distributed Artificial Intelligence inMobile Environment (2 ov.)

Lecturer: Vagan Terziyan

University of Jyvaskyla, MIT Department, Fall 2001, 2002

Vrije Universiteit Amsterdam, AI Department, Fall 2001

Intelligent Web Applications (2 ov.)

Lecturer: Vagan Terziyan

Vrije Universiteit Amsterdam, AI Department, Fall 2002

Web Content Management (6 ov.)

Lecturer: Vagan Terziyan

Jyvaskyla Polytechnic, Spring 2002

University of Jyvaskyla Experience:University of Jyvaskyla Experience:Examples of Related CoursesExamples of Related Courses

18

Digitaalisen median erityiskysymyksiä (2 ov) seminaarin aihepiiri:

Semanttinen webLecturer: Airi Salminen

University of Jyvaskyla, CS & IS Department, Spring 200218

Structured Electronic Documentation

Lecturer: Matthieu Weber

University of Jyvaskyla, MIT Department, Fall 2001, 2002

mweber@mit.jyu.fi

Intelligent Information Integrationin Mobile Environment (4 ov.)

Lecturer: Vagan TerziyanUniversity of Jyvaskyla, MIT Department, Spring 2002

Cooperation with American UniversitiesCooperation with American Universities

Ioannis KakadiarisIoannis Kakadiaris Ass. Professor, Department of Computer Science, University of University of HoustonHouston, USA

Ioannis is the founder and Director of Visual Computing Laboratory and the Director of the Division of Bioimaging and Biocomputation at the UH Institute for Digital Informatics and Analysis. He is the recipient of a year 2000 NSF Early Career Development Award.

Cooperation focuses to investigating issues related to management of the Web content which includes human motions as its component, according to the common framework of management multimedia content in the Semantic Web. Possible applications considered:

- Automatic remote camera control (behavior recognition, intentions capture, operator (astronaut) actions control etc.)

- Semantic video transmission (transmit wireless only recognized semantics of motions).

John CannyJohn CannyProfessor, Division of Computer Science, University of University of CaliforniaCalifornia, , BerkeleyBerkeley, USA

John came from MIT in 1987 after his thesis on robot motion planning, which won the ACM dissertation award. He received a Packard Foundation Fellowship and a PYI while at Berkeley. He developed inexpensive, ubiquitous telepresence robots called "PRoPs”...

Cooperation focuses to following subjects:

- Knowledge management of a community of trust;- Collaborative Filtering with Privacy;- Intelligent Integration of Filtering Models;- Adaptive User Interfaces;- Human-Centered Computing;- Online Collaborative learning.

ConclusionConclusion

• Semantic Web is not only a technologytechnology as many used to name it;

• Semantic Web is not only an environmentenvironment as many naming it now;

• Semantic WebSemantic Web it is a new contextcontext within which one should rethink and re-interpret his existing businesses, resources, services, technologies, processes, environments, products etc. to raise them to totally new level of performance…

------------------------------------------Contact: Vagan Terziyan vagan@it.jyu.fihttp://www.cs.jyu.fi/ai/vagan (tel. +358 14 2604618)