Transcript SmartResource

SmartResource:
Proactive Self-Maintained
Resources in Semantic Web
TEKES Project proposal
Vagan Terziyan, Project Leader
Industrial Ontologies Group
Agora Center, University of Jyväskylä
Content
•
•
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•
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Introduction
Project Essentials
Project Potential and Future Market
Relation to TEKES Programs
Project Team
Relation to InBCT TEKES Project (3.1.3.)
Project Budget
Semantic Web in Networked Business
Environment
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
“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.”
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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Project Essentials
Project goal is to combine the emerging
Semantic Web, Web Services, Peer-toPeer and Agent technologies for the
development of a global and smart maintenance
management environment, to provide Webbased 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
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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Smart Maintenance Environment
“Experts”
“Devices with
on-line data”
“Services”
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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)
“Expert”
•
RSCDF adapters (wrappers)
for devices, services and experts:
- browsable devices
- application-expert interface
- RSCDF-enabled services
SmartResource: Project Proposal
“Device”
RSCDF
“Service”
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Project Objectives (Year 2)
Development of agent-based resource management
framework and enabling meaningful resource interaction
•
Adding agents to resources
•
•
“Expert”
Making resource proactive
Enabling communication
with resource
Resource
Agent
”Adapter”
“Service”
“Device”
Smart Maintenance
Environment
•
Implementation of agent-communication scenarios
•
•
service learning
remote diagnostics
“Expert”
“Device”
Remote
diagnostics
Expert ~ Service
“Service”
Service learning and
remote diagnostics
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Project Objectives (Year 3)
Development of networked maintenance environment
•
Development of P2P agent-communication system
•
•
•
•
Research of the Resource Goal/Behavior Description Framework
•
•
•
Resource Discovery
Maintenance Data & Knowledge Integration
Certification and credibility assessment of services
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
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Maintenance Networking Environment
“Expert” Network
“Expert”
“Device” Network
“Device”
User
interface
Labelled
data
Labelled
data
“Embedded
Sensor data Alarm Service”
Resource
Agent
History
data
RSCDF
data
Resource
Agent
results
”Adapter” RSCDF
data
”Adapter”
Remote Expert Platform
Labelled
“RSCDF
Sensor data
”Adapter” RSCDF Alarm Service”
data
Local (Embedded) Platform
Resource
Agent
“Service”
Diagnostic
model
“Service” Network
RSCDF
data
”Adapter”
Learning
process
Remote Service Platform
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P2P networking
- network of hubs
- highly scalable
- fault-tolerable
- supports dynamic changes
of network structure
Why to interact?
1.
2.
3.
4.
5.
- does not need
administration
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
w2
“Device”
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.
w5
w3
w4
Labelled
data
Learning
sample
Test sample
“Service”
“Service”
Diagnostic
model
…
Diagnostic
model
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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) .
Device-specific
diagnostic model
Diagnostic
model
1
…
n
Device Class-specific
diagnostic model
“Device”
Labelled
data
“Device”
Labelled
data
“Device”
Labelled
data
SmartResource: Project Proposal
Diagnostic
model
“Device”
“Device”
“Device”
…
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.
Service 1
Service 2
Service 3
5
3
4
Device
1
2
Certifying
party
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Own
evaluations
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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
P2P environment that integrates devices,
services, human experts and supports:
Adaptation of resources (devices,
services, experts) to the Environment
Unification of
maintenance data
Discovery of necessary network
components using their profiles
Support for service
learning
Resource Proactivity:
Service
Interaction ”One service – many devices”
Resource
Agent
Interaction ”One device – many services”
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Project Potential and Future Market
Tekes Project Application, Submitted January 2004
Universality
• 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
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Smart Maintenance Environment
“Experts”
“Devices with
on-line data”
“Services”
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Smart Maintenance Environment
“Doctor/Expert”
“Human/patient with
embedded medical
sensors ”
“Medical Web
Services”
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Smart Maintenance Environment
“Experts
in environmental
monitoring”
“Environment
with sensors ”
“Web Services for environmental
diagnostics and prediction”
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Smart Maintenance Environment
“Manager/Expert”
“Staff/students
with monitored
organizational data”
“Web Services in
organizational diagnostics and
management”
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Customers of the system
Experts, which want to provide
their experience and knowledge in
domain of remote
diagnostics,
condition
monitoring
and
maintenance of industrial devices.
Experts
Producers of the
Field Devices
Producers of the Field Devices,
which are interested to provide
more
effective
product
maintenance
and
remote
diagnostic for their customers.
SmartResource: Project Proposal
Web Service and
Application
providers
Providers
of
the
diagnostic,
maintenance, condition monitoring
services, which want to make them
available for customers through the
net.
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Smart Maintenance Environment
IT Providers:
Manufacturer of
applications, services,
solutions
industrial products
User
Sensor
Expert
Servicemediator
Web
Service
SmartDevice
SmartSystem
Application
Smart
Maintenance Environment
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Application domains:
Telemedicine:Wellness
Health Maintenance without
barriers
Anytime and Anywhere
“Doctor/Expert”
“Doctor/Expert”
“Human/device”
“Service”
“Service”
Symptom
data
“Service”
Local Alarm System
Human/device Adapter
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Application domains:
Building Conditioning
Automation of the
Building Conditioning via a
House Maintenance System,
“Service”
“Service”
“Service”
“Expert”
“Expert”
“Expert”
embedded sensor system of a
house state,
local housecondition alarm system, and
global
system
for
house
remote
diagnostics
and
predictive maintenance
House systems sensors
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Relation to TEKES Programs
Tekes Project Application, Submitted January 2004
Relation 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).
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Relation to TEKES programs
FENIX - Interactive Computing.

human as initiators and coordinators in resource maintenance

domain experts, operators as resources

human interaction with Semantic Web-based environment.
Intelligent Automation Systems

prototype development of industrial system

proactivity of resources: Agent technology

integration of heterogeneous systems

Semantic Web + Web Services + P2P + Agents
DENSY 
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 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.
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Project Team
Tekes Project Application, Submitted January 2004
Our Team: “Industrial Ontologies” Group
•
•
•
Head:
 Vagan Terziyan
Contact Person (University of Jyväskylä):
 Timo Tiihonen
Researchers:
 Oleksandr Kononenko
 Andriy Zharko
 Oleksiy Khriyenko
 Olena Kaykova

•
[email protected]
MIT
Department,
University of
Jyväskylä
…
Consultant (Metso Automation):
 Jouni Pyötsiä
“Industrial Ontologies” Group: http://www.cs.jyu.fi/ai/OntoGroup/
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Project Members
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

University of Jyväskylä
Finland
• Vice-Rector, Professor, Ph.D.
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.
http://www.mit.jyu.fi/tiihonen/
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Project Members
Vagan Terziyan
Kharkov National University of Radioelectronics
Ukraine
• Head of AI Department, Professor, Dr. (Habil) Tech.
• Project Leader
University of Jyväskylä
Finland
• Associate Professor, Senior Researcher
(Agora Centre)
• Profile:






Artificial Intelligence
Knowledge Management
Agent Technology
Semantic Web
Machine Learning
Data Mining…
http://www.cs.jyu.fi/ai/vagan/
SmartResource: Project Proposal
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
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Project Members
Olena Kaykova
Kharkov National University of Radioelectronics
Ukraine
• Associate Professor, Dr. Tech.
• Researcher
• Senior Researcher (Agora Centre)
• Profile:






Control Systems
Artificial Intelligence
Temporal Logic
Machine Learning
Integrated Models
International Relations
Management…
University of Jyväskylä
Finland
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

http://www.cs.jyu.fi/ai/helen/
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Project Members
Ukraine
Kharkiv National University of Radioelectronics
Oleksandr Kononenko
• Researcher-Developer
University of Jyväskylä
Educational backgrounds and Expertise
Agent Technology
Semantic Web
Machine Learning
• Main Duties

Software design

RSCDF and RGBDF design/
Ontology development
 Resource Adapter
development
 Project documentation
http://www.cc.jyu.fi/~olkonone/
SmartResource: Project Proposal
Finland
Mobile Services
P2P
M.Eng. Major
Artificial
Intelligence
Mobile
Computing
M.Sc. Major
M.Eng. Minor
Software
Engineering
Mathematics
M.Sc. Minor
Software design
Web Services
Formal, numerical,
probabilistic, neuro, fuzzy,
etc. modeling
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”
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Project Members
Ukraine
Kharkiv National University of Radioelectronics
Oleksiy Khriyenko
• Researcher-Developer
University of Jyväskylä
Educational backgrounds and Expertise
Agent Technology
Semantic Web
Machine Learning
• Main Duties:
Resource Agent
development
 Resource Adapter
development
 Software documentation

http://www.cc.jyu.fi/~olkhriye/
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Finland
Mobile Services
P2P
M.Eng. Major
Artificial
Intelligence
Mobile
Computing
M.Sc. Major
M.Eng. Minor
Software
Engineering
Mathematics
M.Sc. Minor
Software design
Web Services
Formal, numerical,
probabilistic, neuro, fuzzy,
etc. modeling
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”
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Project Members
Ukraine
Kharkiv National University of Radioelectronics
Andriy Zharko
• Researcher-Developer
University of Jyväskylä
Educational backgrounds and Expertise
Agent Technology
Semantic Web
Machine Learning
• Duties:
Ontology development
 P2P communication
subsystem development
 Web services development

http://www.cc.jyu.fi/~anzharko/
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Finland
Mobile Services
P2P
M.Eng. Majors
Artificial
Intelligence
Mobile
Computing
M.Sc. Major
M.Eng. Minors
Software
Engineering
Mathematics
M.Sc. Minor
Software design
Web Services
Formal, numerical,
probabilistic, neuro, fuzzy,
etc. modeling
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”
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Project Members
Ukraine
Kharkiv National University of Radioelectronics
Andriy Zharko
• Researcher-Developer
Finland
University of Jyväskylä
Educational backgrounds and Expertise
Agent Technology
Semantic Web
Machine Learning
Mobile Services
At the moment, Andriy is at the
P2P
IASTED-2004 (International Association of Science and Technology for Development)
conferences (Innsbruck, Austria, 17-19 February, 2004),
he is
Artificial whereMobile
Majors
Intelligence
Computing
presenting the research results of Industrial Ontologies
Group:

Software
Kaykova O., Kononenko O., Terziyan V., Zharko
A., Formation Scenarios
in OntoServ.Net –
Mathematics
Minors
Engineering
Global Network of Intelligent Industrial Maintenance Web Services, In: IASTED International
Conference on Databases and Applications (DBA 2004).
• Profile:


Software design
Web Services
 Semantic
Web O., Terziyan V., OntoEnvironment: An Integration Infrastructure for Distributed
Khriyenko
O., Kononenko
Heterogeneous Resources, In: IASTED International Conference on Parallel and Distributed Computing
 Networks
P2P (PDCN 2004).
and
2002 – 2003
Degree student at MIT Department, University of Jyväskyla. Thesis
 Web Services
Kaykova O., Khriyenko O., Zharko A., Visual
InterfaceOntological
for Adaptation
of Data
Sources
toComponents
Semantic Web
,
“Peer-to-Peer
Discovery
of Mobile
Service
in Semantic
Web”
In: IASTED International Conference on Software Engineering (SE 2004).
wins department’s award, he is M.Sc. in Information Technology
http://www.cc.jyu.fi/~anzharko/
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2004-present
PhD student at the MIT Department, University of Jyväskylä
“Active Resources in Semantic Web”
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International Cooperation (1)
Prof. Frank Harmelen
Prof. Catholijn Jonker
Dynamics of
agent behavior
Reasoning about
diagnostic systems
Multiagent systems’
design
Diagnostics of
organizations
Prof. Jan Treur
Semantic Web
Ontology Learning
Ontology Integration
Borys Omelayenko
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International Cooperation (2)
Volodymyr Kushnaryov
Prof. Yevgeniy Bodyanskiy
Neuro-Fuzzy Networks
Industrial
Automation
Industrial
diagnostics,
prediction
and control
Machine Learning
Telemedicine
Kharkov National University of Radioelectronics
Ukraine
Data Mining and
Knowledge
Discovery
Ontologies in
Education
Bayesian Networks
Dr. Oleksandra Vitko
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Statistics
Prof. Natalya Lesna
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Related European Research
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
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Related European Research
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/
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Related 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/
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Semantic Facilitators for
Web Information Retrieval
InBCT Tekes PROJECT Chapter 3.1.3 :
“Industrial Ontologies and Semantic Web”
Pre-Project Activities (2003)
During 2003 Industrial 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, …
 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/
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Semantic Facilitators for Web
Information Retrieval (2004)
InBCT Tekes PROJECT Chapter 3.1.3 :
“Industrial Ontologies and Semantic Web” (year 2004)
Main Deliverables
1.
2.
Generic Semantic Search Facilitator concept,
architecture and ideas for future utilization of semantic
wrappers for non-semantic search systems
Implementation of Semantic Search Assistant for
Google with semantic interface and domain ontology.
Resources
about 30 KEURO for
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24 m/months
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Enabling the Semantic Search
Semantic Search Enhancement :
Common (linguistic)
ontology
Domain ontology
Query : X
X
X
X
X
X
(X
X
X)
Semantic Search Assistant (Facilitator)
uses ontologically (WordNet) defined
knowledge about words and embedded
support of advanced Google-search
query features in order to construct
more efficient queries from formal
textual
description
of
searched
information. Semantic Search Assistant
hides from users the complexity of
query language of concrete search
engine and performs routine actions
that most of users do in order to
achieve better performance and get
more relevant results.
X
Result:
SemanticFiltering
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Project Budget
Tekes Project Application, Submitted January 2004
Budget
Y1
Salaries
Y2
Y3
Total
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
210000
310000
310000
830000
TOTAL
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
EURO
Budget (Year 1)
Year
Salaries
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 =
101564
18 137
Taxes
29453
Expenses
60268
Travels
9000
Materials and supplies
1715
Equipment
8000
TOTAL
Person-months: 47
210000
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
2004
•
•
•
•
•
•
•
TeliaSonera
TietoEnator
Jyväskylä Science Park
Jyväskylä University
Metso Automation
Applied from Tekes
Total (2004)
SmartResource: Project Proposal
20 000 EURO
10 000
10 000
10 000
10 000 (own work)
160 000
210 000
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