SmartResource: Proactive Self-Maintained Resources in Semantic Web

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SmartResource Proactive Self-Maintained
Resources in Semantic Web

• TEKES Project proposal
• Vagan Terziyan, Project Leader
• Industrial Ontologies Group
• Agora Center, University of Jyväskylä

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Our Team and Consortium

University of Jyväskylä
Industrial Ontologies Group (SmartResource)
Industrial Ontologies Group http//www.cs.jyu.f
i/ai/OntoGroup/index.html
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Networked Business Environments

• Some purposes of NBE development
• knowledge management
• mining, accumulation and sharing of expert
  knowledge within the whole enterprise
• knowledge business
• deliver gained enterprise experience to external
  market
• new (value-added) services and solutions
• integrated business solutions

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 Metsos customers and
partners. (Future Care)
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
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Bringing New Value to the Data

• Reusing data
• Sharing data
• Integrating data

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 Environment will bring all benefits
of the knowledge management, delivering
value-added services and integration of businesses
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PROJECT WIDER OBJECTIVE
S m a r t R e s o u r c e

• - to combine the emerging Semantic Web, Web
  Services, Peer-to-Peer, Machine Learning 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
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Industrial Resources

• Classes of resources 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

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MAIN RESEARCH OBJECTIVE
Our intention is to provide tools and solutions
to make heterogeneous industrial resources
(files, documents, services, devices, processes,
systems, human experts, etc.) web-accessible,
proactive and cooperative in a sense that they
will be able to analyze their state independently
from other systems or to order such analysis from
remote experts or Web-services to be aware of own
condition and to plan behavior towards effective
and predictive maintenance.
Global Understanding eNvironment
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Smart Maintenance Environment
Experts
Devices with on-line data
exchange
data
Maintenance
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Project Objectives (Year 1)
Define Semantic Web-based framework for
unification of maintenance data and
interoperability in maintenance system

• 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

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Project Objectives (Year 2)
Development of agent-based resource management
framework and enabling meaningful resource
interaction

• Adding agents to resources
• Enabling resource proactive
• behavior. Designing
• Resource Goal/Behavior
• Description Framework (RGBDF - Lite)
• Designing agents to maintain
• resources (RGBDF Engine)
• Implementation of agent-communication scenarios
• service learning
• remote diagnostics

Lite
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Project Objectives (Year 3)
Development of networked maintenance environment

• 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
  behaviour
• Exchanging integrating models of resource
  (maintenance) behaviour
• Testing on-the-field using
• Real devices
• Existing diagnostic software as Web-services
• Experts

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Maintenance Networking Environment
Semantic Web environment
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P2P networking
- network of hubs
- highly scalable
- fault-tolerable

• supports dynamic changes
• of network structure

• does not need
• administration

• Why to interact?
• Resource summarizes opinions from multiple
  services
• Services learns from multiple teachers
• One service for multiple similar clients
• Resources exchange lists of services
• Services exchange lists of clients.

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Integrating services
Evaluation and Result integration mechanism
w1
w5
w2
w4
w3
Device
Labelled data
Service
Service
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Integrating knowledge
Service

• 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) .

Diagnostic model
1
Diagnostic model
n
Device
Device
Device
Labelled data
Device
Device
Device
Labelled data
Labelled data
Labelled data
Labelled data
Labelled data
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Certification
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.
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Development Stages
Project will produce 3 versions of prototype
software by implementing the following components
and functionality

• Year 1 Resource Adapters to the RSCDF-based
  unification of resource data 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

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Project Results
Adaptation of resources (devices, services,
experts) to the Environment
Support for services that are able to learrn
Discovery of necessary network components using
their profiles
Research Results RSCDF RGBDF Proactive
Resources P2P Maintenance
Interaction One device many services
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New partners
are warmly welcome!
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Obtain More Information about SmartResource from
Head of SmartResource Industrial Consortium
(Steering Committee Head) Dr. Jouni Pyötsiä,
Metso Automation Oy. Jouni.Pyotsia_at_metso.com ,
Tel. [phone]
SmartResource Contact Person Prof. Timo Tiihonen,
Vice-Rector, University of Jyväskylä tiihonen_at_it.j
yu.fi , Tel. [phone]
SmartResource Project Leader Prof. Vagan
Terziyan, Agora Center, University of
Jyväskylä vagan_at_it.jyu.fi , Tel. [phone]
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Obtain More Information about SmartResource from
Presentation of our group http//www.cs.jyu.fi/a
i/OntoGroup/IOG_Presentation.ppt Sample of
presentation of our SmartResource project
activities http//www.cs.jyu.fi/ai/Madeira.ppt 
(in text http//www.cs.jyu.fi/ai/Smart_Resource.d
oc ) Some relevant research papers of our
group http//www.cs.jyu.fi/ai/Mobile_Components.
doc http//research.i2r.a-star.edu.sg/iaamsad/ijcs
s/Journals/Vol4No2/2003-2-terzijan-5.PDF
http//www.cs.jyu.fi/ai/papers/IJWSR-2004.pdf Mo
re papers of our group http//www.cs.jyu.fi/ai/v
agan/papers.html Web sites of our group with
more information http//www.cs.jyu.fi/ai http//
www.cs.jyu.fi/ai/OntoGroup