SmartResource: SmartResource: Proactive Self-Maintained Proactive Self-Maintained Resources in Semantic Web Resources in Semantic Web TEKES Project proposal Vagan Terziyan, Project Leader Industrial Ontologies Group Agora Center, University of Jyväskylä
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SmartResource: Proactive Self-Maintained Resources in Semantic Web TEKES Project proposal Vagan Terziyan, Project Leader Industrial Ontologies Group Agora.
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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 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
SmartResource: Project Proposal 5 of 52
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
• 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
- 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.
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.
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) .
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.
““Web Services Web Services in in organizational diagnostics and organizational diagnostics and
managementmanagement””
““ManagerManager//ExpertExpert””
SmartResource: Project Proposal 23 of 52
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.
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
Tekes Project Application, Submitted January 2004
SmartResource: Project Proposal 28 of 52
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).
SmartResource: Project Proposal 29 of 52
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
Tekes Project Application, Submitted January 2004
SmartResource: Project Proposal 31 of 52
• Head: Vagan Terziyan
• Contact Person (University of Jyväskylä): Timo Tiihonen
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.
Project MembersProject MembersProject MembersProject Members
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
University of JyväskyläFinland
• Head of AI Department, Professor, Dr. (Habil) Tech.
• Associate Professor, Senior Researcher (Agora Centre)
Project MembersProject MembersProject MembersProject Members
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
Project MembersProject MembersProject MembersProject Members
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/
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
Project MembersProject MembersProject MembersProject Members
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/
Educational backgrounds and Expertise
Kharkiv National University of Radioelectronics
University of Jyväskylä
Ukraine
Finland
ArtificialIntelligence
MobileComputing
SoftwareEngineering
Mathematics
M.Eng. Majors
M.Eng. Minors
Software designWeb Services
Formal, numerical, probabilistic, neuro, fuzzy, etc. modeling
Project MembersProject MembersProject MembersProject Members
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”
Educational backgrounds and Expertise
Kharkiv National University of Radioelectronics
University of Jyväskylä
Ukraine
Finland
ArtificialIntelligence
MobileComputing
SoftwareEngineering
Mathematics
Majors
Minors
Software designWeb Services
Mobile ServicesP2P
Agent TechnologySemantic WebMachine Learning
http://www.cc.jyu.fi/~anzharko/
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).
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
SmartResource: Project Proposal 40 of 52
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
SmartResource: Project Proposal 41 of 52
Related European Research Related European Research Initiatives (1)Initiatives (1)
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;
Related European Research Related European Research Initiatives (2)Initiatives (2)
Related European Research Related European Research Initiatives (2)Initiatives (2)
• 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/
SmartResource: Project Proposal 43 of 52
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”
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/
SmartResource: Project Proposal 46 of 52
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.
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.