SmartResource: Proactive Self-Maintained Resources in Semantic Web TEKES Project proposal Vagan Terziyan, Project Leader Industrial Ontologies Group Agora

SmartResource:SmartResource: Proactive Self-Maintained Proactive Self-Maintained

Resources in Semantic WebResources in Semantic Web

SmartResource:SmartResource: Proactive Self-Maintained Proactive Self-Maintained

Resources in Semantic WebResources in Semantic Web

TEKES Project proposal

Vagan Terziyan, Project Leader

Industrial Ontologies GroupAgora Center, University of Jyväskylä

ContentContent

• Introduction

• Project Essentials

• Project Potential and Future Market

• Relation to TEKES Programs

• Project Team

• Relation to InBCT TEKES Project (3.1.3.)

• Project Budget

SmartResource: Project Proposal 3 of 52

Semantic Web in Networked BusinessSemantic Web in Networked BusinessEnvironmentEnvironment

Semantic Web in Networked BusinessSemantic Web in Networked BusinessEnvironmentEnvironment

Semantic Web technology provides standards for metadata and ontology development such as semantic annotations (Resource Description Framework) and knowledge representation (Web Ontology Language). It facilitates interoperability of heterogeneous components, authoring reusable data and intelligent, automated processing of data.

Semantic Web is an enabling technology for the future Networked Business Environment

“In a networked business environment Metso will be a business hub controlling the flow of information in the network of installed Metso devices and solutions, and Metso’s customers and partners.”

Networked Business Environment requires new advanced ways of data and knowledge management

Industrial Maintenance domain is a good application case for the concept of the Networked Business Environment

Networked Maintenance EnvironmentNetworked Maintenance Environment will bring all benefits of the knowledge management, delivering value-added services and integration of businesses

Project EssentialsProject EssentialsProject EssentialsProject Essentials

Project goal is to combine the emerging Semantic Web, Web Services, Peer-to-Peer and Agent technologies for the development of a global and smart maintenance management environment, to provide Web-based support for the predictive maintenance of industrial devices by utilizing heterogeneous and interoperable Web resources, services and human experts

Tekes Project Application, Submitted January 2004


Classes of resourcesresources in maintenance systems:

• Devices - increasingly complex machines, equipment, etc., that require costs-demanding support

• Processing Units (Services) – embedded, local and remote systems, for automated intelligent monitoring, diagnostics and control over devices

• Humans (Experts) – qualified users of the system, operators, maintenance experts, a limited resource that should be reused

Industrial ResourcesIndustrial ResourcesIndustrial ResourcesIndustrial Resources


On-line learning

On-line learning

Smart Maintenance EnvironmentSmart Maintenance EnvironmentSmart Maintenance EnvironmentSmart Maintenance Environment

““Devices with Devices with on-line data”on-line data”

““Experts”Experts”

Maintenance

Maintenance

““Services”Services”

exchangeexchange

datadata

Maintenance

Maintenance

datadata

exchange

exchange

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Research and Development:

• Resource State/Condition Description Framework (RSCDF) based on Semantic Web and extension of RDF (Resource Description Framework)

• RSCDF adapters (wrappers)

for devices, services and experts:

- browsable devices

- application-expert interface

- RSCDF-enabled services

Project Objectives (Year 1)Project Objectives (Year 1)Project Objectives (Year 1)Project Objectives (Year 1)

Define Semantic Web-based framework for unification of maintenance data and interoperability in maintenance system

““Device”Device”

““Expert”Expert”

““Service”Service”

RSCDFRSCDF


• Adding agents to resources• Making resource proactive

• Enabling communication

with resource

• Implementation of agent-communication scenarios• service learning

• remote diagnostics


Development of agent-based resource management framework and enabling meaningful resource interaction

”Adapter”




Resource Resource AgentAgent

Smart MaintenanceSmart Maintenance EnvironmentEnvironment




Remote diagnostics

Service learning and remote diagnostics

ExpertExpert ~~ ServiceService



• Development of P2P agent-communication system• Resource Discovery• Maintenance Data & Knowledge Integration• Certification and credibility assessment of services

• Research of the Resource Goal/Behavior Description Framework• Semantic modelling of a resource proactive behavior• Exchanging & integrating models of resource (maintenance) behavior

• Testing “on-the-field” using• Real devices• Existing diagnostic software as Web-services• Experts

Development of networked maintenance environment


““Expert” NetworkExpert” Network



Diagnostic model


User interfaceLabelled

data

Labelled data

Labelled

Labelled

datadata

Learning

Learning

diagnostic resultsdiagnostic results

and querying

and querying

sample

sample

LabelledLabelled datadata

QueryingQuerying diagnostic

diagnostic resultsresults

Maintenance Networking EnvironmentMaintenance Networking EnvironmentMaintenance Networking EnvironmentMaintenance Networking Environment

““Device” NetworkDevice” Network

““Service” NetworkService” Network

”Adapter”““RSCDFRSCDF

Alarm Service”Alarm Service”Sensor dataSensor dataRSCDF RSCDF

datadata

”Adapter”Sensor dataSensor dataRSCDF RSCDF

datadata

““Embedded Embedded Alarm Service”Alarm Service”

Local (Embedded) PlatformLocal (Embedded) Platform

”Adapter” RSCDF RSCDF datadata

Remote Expert PlatformRemote Expert Platform

”Adapter” Learning process

RSCDF RSCDF datadata

Remote Service PlatformRemote Service Platform

History data









P2P networkingP2P networkingP2P networkingP2P networking

- highly scalable- highly scalable

- fault-tolerable - fault-tolerable

- supports dynamic changes of network structure

- supports dynamic changes of network structure

- does not need administration - does not need administration

Why to interact?

1. Resource summarizes “opinions” from multiple services;2. Services “learns” from multiple teachers;3. One service for multiple similar clients;4. Resources exchange lists of services;5. Services exchange lists of clients.

- network of hubs- network of hubs


Lear

ning

and

tes

t sa

mpl

e.

Lear

ning

and

tes

t sa

mpl

e.

Que

ryin

g di

agno

stic

res

ults

.

Que

ryin

g di

agno

stic

res

ults

.

Integrating servicesIntegrating servicesIntegrating servicesIntegrating services


Labelled data

Learning sample

Test sample


Diagnostic model

Diagnostic model


ww11

ww22

ww33

ww44

ww55

Evaluation and Evaluation and Result integration Result integration

mechanismmechanism

…

Labelled data

Labelled data

Lab

elled d

ataL

abelled

data

Device will support service composition in form of ensembles using own models of service quality estimation. Service composition is made with goal of increasing diagnostic performance.


Integrating knowledgeIntegrating knowledgeIntegrating knowledgeIntegrating knowledge


Diagnostic model

Diagnostic model

…


Labelled data

““Device”Device”““Device”Device”

Labelled data

…




Labelled data

Labelled data

Labelled data

Labelled data

1n

Device-specific diagnostic model

Device Class-specific diagnostic model

Service builds classification model; many techniques are possible, e.g.:• own model for each device;• one model from several devices of the same type (provides device experience exchange) .


CertificationCertificationCertificationCertification

Sure, there are security threats as in any open environment. Security is to be ensured using existing solutions for Internet environment. Existence of certification authorities is required in the network. Certificates gained by services and trust to the certificate issuer are factors that influence optimal service selection. The quality of service is evaluated by users as well.

Sure, there are security threats as in any open environment. Security is to be ensured using existing solutions for Internet environment. Existence of certification authorities is required in the network. Certificates gained by services and trust to the certificate issuer are factors that influence optimal service selection. The quality of service is evaluated by users as well.

53

4

Certifying party

Device

Service 1

Service 2

Service 3

612

Own evaluations

trust

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Development StagesDevelopment StagesDevelopment StagesDevelopment Stages

Year 1: Resource Adapters to the RSCDF-based unification of resourcedata; Remote resource access in Semantic Web environment

Year 2: Resource Agents for remote diagnostics; Learnability of services

Year 3: Support for semantic P2P networking and diagnostic services integration

Project will produce 3 versions of prototype software by implementing the following components and functionality:


Project ResultsProject ResultsProject ResultsProject Results

Service

Interaction ”One device – many services”Interaction ”One device – many services”

P2P environment that integrates devices, services, human experts and supports:

Discovery of necessary network components using their profiles

Interaction ”One service – many devices”

Adaptation of resources (devices, services, experts) to the Environment

Adaptation of resources (devices, services, experts) to the Environment

Support for service learning

Support for service learning

Unification of maintenance data

Unification of maintenance data

Resource Proactivity:Resource Proactivity:


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Project Potential and Future MarketProject Potential and Future MarketProject Potential and Future MarketProject Potential and Future Market



UniversalityUniversalityUniversalityUniversality

• We are heading to a development of comprehensive and universal frameworks for intelligent information management

• SmartResource project is one step in our advancement towards applications of our vision, approach and expertise in many other domains

• Semantic Web-based solutions enable to combine heterogeneous information, methods and resources together


On-line learning

On-line learning


““Devices with Devices with on-line data”on-line data”

““Experts”Experts”

Maintenance

Maintenanceexchangeexchange

datadata

Maintenance

Maintenance

datadata

exchange

exchange

““Services”Services”


On-line learning

On-line learning


Maintenance


datadata

Maintenance

Maintenance

datadata

exchange

exchange

““Human/patient with embedded medical sensors ””

““DoctorDoctor//ExpertExpert””

““Medical Web Medical Web Services”Services”


On-line learning

On-line learning


Maintenance


datadata

Maintenance

Maintenance

datadata

exchange

exchange

““Web Services Web Services for environmental for environmental

diagnostics and predictiondiagnostics and prediction””

““ExpertsExperts in environmental in environmental

monitoringmonitoring””

““Environment

with sensors ””


On-line learning

On-line learning


Maintenance


datadata

Maintenance

Maintenance

datadata

exchange

exchange

““Staff/studentsStaff/students

with monitored organizational data””

““Web Services Web Services in in organizational diagnostics and organizational diagnostics and

managementmanagement””

““ManagerManager//ExpertExpert””


Customers of the systemCustomers of the systemCustomers of the systemCustomers of the system

Producers of the Field Devices

ExpertsExperts

Providers of the diagnostic, maintenance, condition monitoring services, which want to make them available for customers through the net.

Experts, which want to provide their experience and knowledge in domain of remote diagnostics, condition monitoring and maintenance of industrial devices.

Producers of the Field Devices, which are interested to provide more effective product maintenance and remote diagnostic for their customers.

Web Service and Application providers



Smart Smart Maintenance EnvironmentMaintenance Environment

User Expert

Service- mediator

Web Service

Application

Sensor

Smart-Device

Smart-System

Manufacturer of industrial products

IT Providers: applications, services,

solutions


Application domains:Application domains:Telemedicine:WellnessTelemedicine:Wellness Application domains:Application domains:

Telemedicine:WellnessTelemedicine:Wellness

““Service”Service”““Service”Service”

““Human/Human/devicedevice””

Local Alarm System Human/device Adapter



Symptom data

Health Maintenance without Health Maintenance without barriersbarriers

Anytime and AnywhereAnytime and Anywhere

Hea

lth M

aint

enan

ce

Hea

lth M

aint

enan

ce

Health M

aintenance

Health M

aintenance



Application domains:Application domains:Building ConditioningBuilding ConditioningApplication domains:Application domains:Building ConditioningBuilding Conditioning

““Service”Service”““Service”Service”


““ExpertExpert”” ““ExpertExpert””““Expert”Expert”

Automation of the Automation of the Building Conditioning via aBuilding Conditioning via a

House Maintenance SystemHouse Maintenance System,,

embedded sensor system of a embedded sensor system of a house state, local house- house state, local house- condition alarm system, and condition alarm system, and global system for house remote global system for house remote diagnostics and predictive diagnostics and predictive maintenancemaintenance

House systems sensorsHouse systems sensors

Relation to TEKES ProgramsRelation to TEKES ProgramsRelation to TEKES ProgramsRelation to TEKES Programs



Relation to TEKES programsRelation to TEKES programsRelation to TEKES programsRelation to TEKES programs

SmartResource project is positioned out of particular TEKES program, because:

• It deals with basic and ”hottest” ICT technologies (Semantic Web, agents, web services, P2P...);

• It aims at development of expertise and ”killer” application for innovative universal solutions that contribute to competitiveness and know-how in the long run;

• Research results are potentially applicable in many other domains (beyond being studied in the industrial case).


Relation to TEKES programsRelation to TEKES programsRelation to TEKES programsRelation to TEKES programs

FENIXFENIX - Interactive Computing. human as initiators and coordinators in resource maintenance domain experts, operators as resources human interaction with Semantic Web-based environment.

Intelligent Automation SystemsIntelligent Automation Systems prototype development of industrial system proactivity of resources: Agent technology integration of heterogeneous systems Semantic Web + Web Services + P2P + Agents

DENSYDENSY - Distributed energy systems technology program

SmartResource-environment is an excellent base for launching intelligent software, which implements various collaborative logics: knowledge share, management, etc.

Drug 2000Drug 2000 - biomedicine, drug development and pharmaceutical technology We could suggest: “Ontology-Based Automated Maintenance of Globally

Distributed Approved Medications and New Drags Lists”. Large amounts of various electronic resources (databases, documents, media, hypertexts) about drugs makes difficult their management and update. Making these resources active according to our concepts we automate their maintenance.

Project TeamProject TeamProject TeamProject Team



• Head: Vagan Terziyan

• Contact Person (University of Jyväskylä): Timo Tiihonen

• Researchers: Oleksandr Kononenko Andriy Zharko Oleksiy Khriyenko Olena Kaykova …

• Consultant (Metso Automation): Jouni Pyötsiä

Our Team:Our Team: “Industrial “Industrial Ontologies” GroupOntologies” Group

[email protected]

MIT Department, University of Jyväskylä

““Industrial Ontologies” Group:Industrial Ontologies” Group: http://www.cs.jyu.fi/ai/OntoGroup/http://www.cs.jyu.fi/ai/OntoGroup/


Timo Tiihonen• Project Contact Person

• Profile: Mathematical Modeling and

Simulation Modeling and Control of

Industrial Paper-Making Processes, Metal and Semiconductor Industries

Data Integration in Management and Administration

Project MembersProject MembersProject MembersProject Members

Professor Timo Tiihonen who acts as the contact person has, as a professor of mathematical modeling and simulation, broad experience of modeling and control of industrial processes in paper making, metal and semiconductor industries. Currently he is actively integrating the data administration of the university as a vice-rector and exploiting the results of this project to management of diverse human resources.

University of JyväskyläFinland

• Vice-Rector, Professor, Ph.D.

http://www.mit.jyu.fi/tiihonen/






Vagan Terziyan• Project Leader

• Profile: Artificial Intelligence Knowledge Management Agent Technology Semantic Web Machine Learning Data Mining…

1981 Ms. Eng. (Applied mathematics)

1985 Dr. Tech. (Cybernetics and IT)

1993 Dr. (Habil) Tech. (IS and AI)

1996 Professor (Software Engineering)

2001 Docent, University of Jyvaskyla (AI and Knowledge Management)

2002-2004 Ass. Prof., Department of Mathematical Information Technology, Senior Researcher, Agora Center, University of Jyvaskyla, Visiting Prof., Free University of Amsterdam

Kharkov National University of RadioelectronicsUkraine


• Head of AI Department, Professor, Dr. (Habil) Tech.

• Associate Professor, Senior Researcher (Agora Centre)

http://www.cs.jyu.fi/ai/vagan/

http://www.cs.jyu.fi/ai/vagan/


Olena Kaykova• Researcher

• Profile: Control Systems Artificial Intelligence Temporal Logic Machine Learning Integrated Models International Relations Management…


Kharkov National University of RadioelectronicsUkraine


• Associate Professor, Dr. Tech.

• Senior Researcher (Agora Centre)

http://www.cs.jyu.fi/ai/helen/

1982 Ms. Eng. (Control Systems)

1989 Dr. Tech. (Cybernetics and IT)

1992 Ass. Prof. (Software Engineering)

…

2002-2003 Lecturer, Department of Mathematical Information Technology, University of Jyvaskyla

2004 Senior Researcher, Agora Center






Oleksandr Kononenko• Researcher-Developer

• Main Duties Software design RSCDF and RGBDF design/

Ontology development Resource Adapter

development Project documentation

2002 – 2003 Degree student at MIT Department, University of Jyväskylä. His thesis “Ontological Support for Industrial Maintenance of Smart-Devices” gets laudatur grade, and he becomes M.Sc. in Information Technology

2004-present PhD student at the MIT Department, University of Jyväskylä “Human-Computer Interaction in Semantic Web” http://www.cc.jyu.fi/~olkonone/

Educational backgrounds and Expertise

Kharkiv National University of Radioelectronics

University of Jyväskylä

Ukraine

Finland

ArtificialIntelligence

MobileComputing

SoftwareEngineering

Mathematics

M.Eng. Major

M.Eng. Minor

Software designWeb Services

Formal, numerical, probabilistic, neuro, fuzzy, etc. modeling

Mobile ServicesP2P

Agent TechnologySemantic WebMachine Learning

M.Sc. Major

M.Sc. Minor

http://www.cc.jyu.fi/~olkonone/




Oleksiy Khriyenko• Researcher-Developer

• Main Duties: Resource Agent

development Resource Adapter

development Software documentation


2002 – 2003 Degree student at MIT Department, University of Jyväskylä. He writes thesis “Distributed Mobile Web Services Based on Semantic Web” (laudatur grade), and becomes M.Sc. in Information Technology

2004-present PhD student at the MIT Department, University of Jyväskylä “Adaptive Semantic Web based Environment for Web Resources” http://www.cc.jyu.fi/~olkhriye/




Ukraine

Finland


MobileComputing

SoftwareEngineering

Mathematics

M.Eng. Major

M.Eng. Minor



Mobile ServicesP2P


M.Sc. Major

M.Sc. Minor

http://www.cc.jyu.fi/~olkhriye/







Andriy Zharko• Researcher-Developer

• Duties: Ontology development P2P communication

subsystem development Web services development 2002 – 2003

Degree student at MIT Department, University of Jyväskylä. His thesis “Peer-to-Peer Ontological Discovery of Mobile Service Components in Semantic Web” wins department’s award, he is M.Sc. in Information Technology

2004-present PhD student at the MIT Department, University of Jyväskylä “Active Resources in Semantic Web” http://www.cc.jyu.fi/~anzharko/




Ukraine

Finland


MobileComputing

SoftwareEngineering

Mathematics

M.Eng. Majors

M.Eng. Minors



Mobile ServicesP2P


M.Sc. Major

M.Sc. Minor

http://www.cc.jyu.fi/~anzharko/





Andriy Zharko• Researcher-Developer

• Profile: Semantic Web P2P Web Services

2002 – 2003 Degree student at MIT Department, University of Jyväskyla. Thesis “Peer-to-Peer Ontological Discovery of Mobile Service Components in Semantic Web” wins department’s award, he is M.Sc. in Information Technology

2004-present PhD student at the MIT Department, University of Jyväskylä “Active Resources in Semantic Web”




Ukraine

Finland


MobileComputing

SoftwareEngineering

Mathematics

Majors

Minors


Mobile ServicesP2P



At the moment, Andriy is at the IASTED-2004 (International Association of Science and Technology for Development) conferences (Innsbruck, Austria, 17-19 February, 2004), where he is presenting the research results of Industrial Ontologies Group:

Kaykova O., Kononenko O., Terziyan V., Zharko A., Formation Scenarios in OntoServ.Net – Global Network of Intelligent Industrial Maintenance Web Services, In: IASTED International Conference on Databases and Applications (DBA 2004).

Khriyenko O., Kononenko O., Terziyan V., OntoEnvironment: An Integration Infrastructure for Distributed Heterogeneous Resources, In: IASTED International Conference on Parallel and Distributed Computing and Networks (PDCN 2004).

Kaykova O., Khriyenko O., Zharko A., Visual Interface for Adaptation of Data Sources to Semantic Web, In: IASTED International Conference on Software Engineering (SE 2004).





International Cooperation (1)International Cooperation (1)International Cooperation (1)International Cooperation (1)

Dynamics of agent behaviorDynamics of agent behavior

Multiagent systems’ designMultiagent systems’ design

Prof. Catholijn JonkerProf. Catholijn Jonker

Prof. Jan TreurProf. Jan Treur

Diagnostics of organizationsDiagnostics of organizations

Semantic WebSemantic Web

Reasoning about diagnostic systemsReasoning about diagnostic systems

Ontology LearningOntology Learning

Ontology IntegrationOntology Integration

Prof. Frank HarmelenProf. Frank Harmelen

Borys OmelayenkoBorys Omelayenko


International Cooperation (2)International Cooperation (2)International Cooperation (2)International Cooperation (2)

Neuro-Fuzzy NetworksNeuro-Fuzzy Networks

Machine LearningMachine Learning

Dr. Oleksandra VitkoDr. Oleksandra Vitko

Prof. Yevgeniy BodyanskiyProf. Yevgeniy Bodyanskiy

Industrial AutomationIndustrial Automation

Bayesian NetworksBayesian Networks

Data Mining and Knowledge Discovery

Data Mining and Knowledge Discovery

Volodymyr KushnaryovVolodymyr Kushnaryov

Kharkov National University of RadioelectronicsKharkov National University of RadioelectronicsUkraineUkraine

Industrial diagnostics, prediction and control

Industrial diagnostics, prediction and control

TelemedicineTelemedicine

Ontologies in EducationOntologies in Education

StatisticsStatistics

Prof. Natalya LesnaProf. Natalya Lesna


Related European Research Related European Research Initiatives (1)Initiatives (1)


There are several going on EU funded projects, which are targeting various aspects of emerging Semantic Web. Among most strong consortiums and initiatives are:

• OntoWeb[1] network with more than 100 academic and industrial participants, which creates a technical roadmap of the next generation Web and provides guidelines to industrial and commercial applications;

• SWAP[2] (Semantic Web and Peer-to-Peer)provides a comprehensive study of the potential of Semantic Web and Peer-to-Peer for knowledge management and plan to provide an appropriate integrated software environment;

• SWWS[3] (Semantic Web Enabled Web Services)researching for scalable mediation between different and heterogeneous services based on semantic-driven descriptions and business logic;

[1] http://www.ontoweb.org[2] http://swap.semanticweb.org[3] http://swws.semanticweb.org




• SEWASIE[4] (Semantic Web and Agents in Integrated Economies)

fights the problem of access to heterogeneous data sources on the Web;

• SCULPTEUR[5] (Semantic and Content-Based Multimedia Exploitation for European Benefit)

develops the technology to create, manipulate and manage cultural archives to make European cultural heritage accessible to all;

• MOSES[6] (Modular and Scalable Environment for the Semantic Web)

sets out to create scalable ontology based Knowledge Management System and ontology-based search engine that will accept queries and produce answers in natural language;

…

and many other projects

[4] http://www.sewasie.org

[5] http://www.sculpteurweb.org

[6] http://www.hum.ku.dk/moses/


Related Industrial InitiativesRelated Industrial InitiativesRelated Industrial InitiativesRelated Industrial Initiatives

Among recent initiatives aimed at development of adoption of open information standards for operations and maintenance and implementation of interoperable cooperative industrial environments are:

MIMOSA [1] (Machinery Information Management Open System Alliance)

The project consortium pretends to build an open, industry-built, robust Enterprise Application Integration and condition-based maintenance specifications.

PROTEUS[2], funded by industrial companies and led with a goal to develop a generic maintenance-oriented platform for industry.

These initiatives are very expensive, labor and resource consuming, and still does not attempt to apply and benefit from the Semantic Web technology.

We believe, however, that without comprehensive metadata description framework, ontologies and open knowledge/semantics representation standards their results will be just next consortium-wide standards, rather than comprehensive, flexible and extensible framework. We will contribute with Semantic Web technology to industrial needs

[1] http://www.mimosa.org/

[2] http://www.proteus-iteaproject.com/

Semantic Facilitators for Semantic Facilitators for Web Information RetrievalWeb Information RetrievalInBCT Tekes PROJECT Chapter 3.1.3 :InBCT Tekes PROJECT Chapter 3.1.3 :

“Industrial Ontologies and Semantic Web”“Industrial Ontologies and Semantic Web”

Current activities


Pre-Project Activities (2003)Pre-Project Activities (2003)Pre-Project Activities (2003)Pre-Project Activities (2003)

During 2003 Industrial Ontologies GroupIndustrial Ontologies Group concentrated its point of research on Semantic Web technology applications and web-service based information management systems (particularly, in the field of maintenance of industrial devices), which can be considered as an important research input into the Project

Among results are Developed concepts:

OntoServ.Net, GUN, OntoAdapter, OntoShell, Mobile Resource, …OntoServ.Net, GUN, OntoAdapter, OntoShell, Mobile Resource, … about 20 research papers, including:

• publications in scientific journals and international conferences, on the topics related to this project

• project reports and presentation in InBCT Tekes project (section 3.1 - “Semantic Web and Industrial Ontologies”), University of Jyväskylä, Agora Center

• 3 M.Sc. theses on the topics of industrial maintenance automation and Semantic Web

Resources in 2003: 17 m/months

*Detailed list of publications can be found at http://www.cs.jyu.fi/ai/OntoGroup/


Semantic Facilitators for Web Semantic Facilitators for Web Information Retrieval (2004)Information Retrieval (2004)

Main Deliverables

1. Generic Semantic Search Facilitator concept, architecture and ideas for future utilization of semantic wrappers for non-semantic search systems

2. Implementation of Semantic Search Assistant for Google with semantic interface and domain ontology.

Resources

about 30 KEURO for 24 m/months

InBCT Tekes PROJECT Chapter 3.1.3 :InBCT Tekes PROJECT Chapter 3.1.3 :“Industrial Ontologies and Semantic Web” (year 2004)“Industrial Ontologies and Semantic Web” (year 2004)


Semantic Search Enhancement :Semantic Search Enhancement :Common (linguistic) Common (linguistic)

ontologyontology

QueryQuery : : ( ( XX XX XX XX XXXX XXXX XX XX ))

Domain ontologyDomain ontology

SemanticFilteringSemanticFiltering

Result:Result:

Enabling the Semantic SearchEnabling the Semantic SearchEnabling the Semantic SearchEnabling the Semantic Search

Semantic Search Assistant Semantic Search Assistant (Facilitator) uses ontologically (Facilitator) uses ontologically (WordNet) defined knowledge about (WordNet) defined knowledge about words and embedded support of words and embedded support of advanced Google-search query features advanced Google-search query features in order to construct more efficient in order to construct more efficient queries from formal textual description queries from formal textual description of searched information. Semantic of searched information. Semantic Search Assistant hides from users the Search Assistant hides from users the complexity of query language of complexity of query language of concrete search engine and performs concrete search engine and performs routine actions that most of users do in routine actions that most of users do in order to achieve better performance order to achieve better performance and get more relevant results.and get more relevant results.

Project BudgetProject BudgetProject BudgetProject Budget


BudgetBudget

Y1 Y2 Y3 Total

Salaries 101564 157402 154938 413904

Taxes 29453 45646 44932 120031 29%

Expenses 60268 93402 91940 245610 46%

Travels 9000 13000 18000 40000

Materials and supplies 1715 550 190 2455

Equipment 8000 0 0 8000

TOTAL 210000 310000 310000 830000 EURO

Among Project Members:

• 3 Senior Researchers, Dr.Tech.• 3 Researcher-developers, PhD students, MIT Department, JYU• 3 Researchers, Agora Center• 3 Researcher-trainees, MIT Department, JYU• 2 Visiting researchers

Total person-years: 16,3

Budget (Year 1)Budget (Year 1)

Year

Salaries

101564

Taxes 29453

Expenses 60268

Travels 9000

Materials and supplies 1715

Equipment 8000

TOTAL 210000

Person-months: 47

1 Senior Researcher Timo Tiihonen 5300 x 1 = 5 300

2 Project Leader Vagan Terziyan 3028 x 0,5 x 12 = 18 168

3 Researcher Helen Kaykova 2369 x 10 = 23 685

4 Researcher-Developer Oleksandr Kononenko 1814 x 10 = 18 137

5 Researcher-Developer Oleksiy Khriyenko 1814 x 10 = 18 137

6 Researcher-Developer Andriy Zharko 1814 x 10 = 18 137

Project Management Board Project Management Board

Veikko Hara, Dr.Tech., Senior Vice President, TeliaSonera (Head of Project Management Board)

Jouni Pyötsiä, Dr.Tech., Metso Automation

Jukka Valkonen, Director, Digital Business Development, TietoEnator

Jutta Nyblom, Paper ICT Expert, Jyväskylä Science Park

Marko Heikkinen, Tekes/Helsinki

Vagan Terziyan, Dr.Tech., Project Leader, Senior Researcher, University of Jyväskylä

Timo Tiihonen, Prof, Project Contact person, Vice-Rector, University of Jyväskylä

Pekka Neittaanmäki, Prof., Head of Agora Center, University of Jyväskylä


Industrial Partners and resources in Industrial Partners and resources in 20042004

Industrial Partners and resources in Industrial Partners and resources in 20042004

• TeliaSonera 20 000 EURO• TietoEnator 10 000• Jyväskylä Science Park 10 000• Jyväskylä University 10 000• Metso Automation 10 000 (own

work)

• Applied from Tekes 160 000• Total (2004) 210 000210 000

Documents

SmartResource: Proactive Self-Maintained Resources in Semantic Web TEKES Project proposal Vagan Terziyan, Project Leader Industrial Ontologies Group Agora