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Semantic Web: The Future Starts Today

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Title: Semantic Web: The Future Starts Today Subject: Presentation for NOKIA, 23 May 2003 Author: Vagan Terziyan, Oleksandr Kononenko, Oleksiy Khriyenko, Andriy Zharko – PowerPoint PPT presentation

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Title: Semantic Web: The Future Starts Today


1
Semantic Web The Future Starts Today
Industrial Ontologies Group
  • Industrial Ontologies Group
  • http//www.cs.jyu.fi/ai/OntoGroup/index.html

Agora Center, University of Jyväskylä, 23 May 2003
2
Industrial Ontologies Group Our History
  • 1978-1984 We took part in development of the
    first in USSR Industrial Natural Language
    Processing System DESTA, which included
    semantic analysis and ontologies
  • 1985-1989 - We took part in development of the
    first in USSR Industrial Automated Natural
    Language Programming System ALISA, which
    Enabled Semantic Annotation, Discovery and
    Integration of software components (prototype of
    today's Semantic Web Services concept)

3
Industrial Ontologies Group Our History
  • 1990-1993 under name of Metaintelligence Lab.
    we were piloting concept of a Metasemantic
    Network (triplet-based (meta-)knowledge
    representation model) prototype of todays
    RDF-based knowledge representation in Semantic
    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

4
Industrial Ontologies Group Our 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 Web concepts.

5
Industrial Ontologies Group Important 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.

6
Why and Where Semantic Web ?
  • more then 3,000,000,000 web-pages
  • Information burst
  • ICT needs comprehensive resource management
    technology

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

Business
Knowledge Management
  • Consolidate and reuse experience
  • Standardize knowledge sharing technology
  • Needs for the intelligent tools to use humans
    knowledge

7
Approach 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.

8
Word-Wide Correlated Activities
Semantic Web
Agentcities is a global, collaborative effort to
construct an open network of on-line systems
hosting diverse agent based services.
Semantic Web is an extension of the current web
in which information is given well-defined meaning
, better enabling computers and people to work
in cooperation
Agentcities
Grid Computing
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.
FIPA
FIPA is a non-profit organisation aimed at
producing standards for the interoperation of
heterogeneous software agents.
Web 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
9
Semantic Web New Users
applications
agents
10
Semantic Web Resource Integration
Semantic annotation
Shared ontology
Web resources / services / DBs / etc.
11
Semantic Web What to Annotate ?
External world resources
Web resources / services / DBs / etc.
Web users (profiles, preferences)
Shared ontology
Web agents / applications
Web access devices
Smart machines and devices
12
Ontologies the foundation of Semantic Web
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
comment
__Thing__
Author
public
private
is-a
Location
Access Rights
Document
Related to
name
Report
is-a
is-a
uri
Web-page
Subject
Instance-of
Instance-of
O. Kononenko
V. Terziyan
public
Author
Author
Access rights
doc1
doc2
name
Related to
Semantic Web
uri
Location
Subject
comment
http//www.ontogroup.net
\\AgServ\vagan\InBCT_1.doc
comment
3.1 analysis
Home page
draft
Query 1 get all documents from location X, but
not web-pages Query 2 get documents related to
Y, with more then one author, one of which is
Terziyan Query 3 are there web-pages of Z with
private access related to documents with
subject S?
13
Semantic Web Interoperability
Common (shared) ontology
System 2
System 1
A commitment to a common ontology is a guarantee
of a consistency and thus possibility of data
(and knowledge) sharing
14
Co-operative Work in Web
WWW
15
Co-operative Work in Semantic Web
Semantic Web
WWW
16
Semantic Web is not Only ...
17
but Also ...
18
Industrial Ontologies Group Samples of our
Research Applications of Semantic Web
19
Web Resource/Service Integration Server-Based
Transaction Monitor
Web resource / service
Server
Client
wireless
Web resource / service
TM
Transaction Service
Server
20
Web Resource/Service Integration Mobile
Client-Base Transaction Monitor
TM
Web resource / service
wireless
Client
Server
wireless
Web resource / service
Server
21
The conceptual scheme of the ontology-based
transaction management with multiple e-services
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.
22
Ontology-Based Transaction Management 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.
23
Architecture 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.
24
BANK P-Commerce Service provider
Automatic
Mapping and Transactions
via resources and users annotations
Service User
Service User
Service User
Service User
Service User
Service User
25
Mobile Location-Based Service in Semantic Web
26
Machine-to-Machine Communication
P2P ontology
P2P ontology
Heterogeneous machines can understand each
other while exchanging data due to shared
ontologies
27
Semantic Web-Supported Sharing and Integration 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
28
Corporate/Business Hub
Hub ontology and shared domain ontologies
Partners / Businesses
Companies would be able to create Corporate
Hubs, which would be an excellent cooperative
business environment for their applications.
What parties can do
What parties achieve
Publish own resource descriptions
Software and data reuse
Advertise own services
Automated access to enterprise (or partners)
resources
Lookup for resources with semantic search
Seamless integration of services
Ontologies will help to glue such
Enterprise-wide / Cooperative Semantic Web of
shared resources
29
Web 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"
OntoServ.Net Semantic Web Enabled Network of
Maintenance Services for Smart Devices,
Industrial Ontologies Group, Tekes Project
Proposal, March 2003,
30
Global Network of Maintenance Services
"OntoServ.Net"
OntoServ.Net Semantic Web Enabled Network of
Maintenance Services for Smart Devices,
Industrial Ontologies Group, Tekes Project
Proposal, March 2003,
31
Embedded Maintenance Platforms
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
Host Agent
Maintenance Service
Service Agents
32
OntoServ.Net Challenges
  • New group of Web service users smart industrial
    devices.
  • Internal (embedded) and external (Web-based)
    agent enabled service platforms.
  • Mobile 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-Peer concept for service network
    management assumes ontology-based decentralized
    service network management.

33
Industrial Ontologies Group Future
Plans Applications of Wireless Semantic Web
34
Semantically annotated personal data
  • Virtually all resources have to be marked with
    semantic labels that show explicitly the
  • 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 access own and others resources with semantic
    queries using terms of own model
  • To be able integrate data from other sources
  • (semantics of data is important, data can be
    converted/translated if needed and appropriate
    mapping exists)
  • Applications will have
  • Possibility to discover and operate with user
    information and preferences
  • Possibility to share information with
    applications at other devices and elsewhere

Common data semantic descriptions (ontologies)
My data description model (ontology)
mapping between views
Semantic Web Inside
Personal data-view
Commitment to ontology
Applications
User data becomes available to variety of
applications and other people
My resources and their descriptions
Other peoples data-views
35
Modelling of personal data views
  • Simple user data view (as is in most of mobile
    phones)

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
languages it will be stored in universal data
format.
  • Model of users 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..

36
Building own data model
added slot (property/field)
inherited slot
37
Building own data structure
Relative is a kind of friend
added slot (property/field)
inherited slot
38
Building own data structure
added slot (property/field)
inherited slot
39
Using generated interface
For described data model forms are generated
  • 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!

40
Access your data quickly and easily
Possibilities to build flexible, easily
customizable data management applications are
great.
Event data
Just click to open
Every piece of data is somehow described in
users terms from data-view ontology. Links
between data make it easy to find needed
information
41
Customizable personal information management
environment
Easy-to-use, flexible, customizable data
management for users
  • 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
  • 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 possible
  • Ontologies and Semantic Web will enable such kind
    of applications

Repositories of ready data-views
Enabled collaboration and interoperability
Note Protégé-2000 ontology development and
knowledge acquisition tool was used for
demonstration
42
OntoCache
General ontology
Translation
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.
Personal ontology
43
OntoCache benefits
Context and preferences-based adaptation
Support for semi-natural queries
Effective filtering of wide variety of
Web-resources
Technology that supports future Ubiquitous
Semantic Web
44
Agent-to-Agent communication
Peer-to-Peer
- - - - - - - - - - -
Semantic annotation of the local data enables its
intelligent processing by software. Ontologies
provide interoperability between heterogeneous
peers.
Phone calls are also possible between mobile
terminal agents. They are performed without human
participation in order to exchange local
information.
45
Agent-to-Agent communication
semantics enables
intelligent data processing
Business
ontological relations
define possible
Cooking
cooperation between
domain agents
Health
shared ontology
ensures
interoperability
Whatever
?
annotate problem domains
into related ontologies
programm software
basing on the ontologies
semantically enrich
data basing on ontologies
46
Telemedicine
Health Center
On a beach
At university
Anywhere
Health Maintenance without barriers
Fishing
Anytime and Anywhere
In the office
Outside
47
OntoGames New Games Generation
Personal User Profile
Common Games Profile
Personal Reality into each game
48
OntoGames Semantic Games Space
Semantical Games Space
one LIFE - one GAME
Real Life - part of the game
one game - many roles
49
OntoGames Exit in the Real Life
Game - exit in the Real Life
Reality connection via the game
Reality connection via the game
50
BANK Data annotation
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 of some ontology. Software
that is developed with support of that ontology
can recognize the data and process it correctly
in respect to its semantics.
Annotated data (RDF)
Ontology of gathered data
Web forms and dialogs generated
Processing of data by some other semantic-aware
applications
51
BANK Customers data processing
Bank Clients
Clients clustering
Input forms
Data Storage
Bank Clients Ontology
Intelligent ontology-based software
52
BANK Services annotation
Semantics enabled services easy way to use for
customer
53
BANK Loan Borrower annotation
Bank - investor
54
Read Our Recent Reports
  • Semantic 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 Integration and
    Interoperability in Industry
  • Semantic Web Enabled Web Services State-of-Art
    and Challenges
  • Distributed Mobile Web Services Based on Semantic
    Web Distributed Industrial Product Maintenance
    System
  • Available online in http//www.cs.jyu.fi/ai/OntoG
    roup/index.html

V. Terziyan
A. Zharko
O. Kononenko
O. Khriyenko
Industrial Ontologies Group
55
Semantic Web The Future starts today
Interoperability standards
e-Business, net-markets
Enterprise Application Integration
Web-services
Web Of Trust
56
Industrial Ontologies Group Examples of Related
Contacts
57
University of Jyvaskyla Experience Examples of
Related Courses
58
Cooperation with American Universities
John Canny Professor, Division of Computer
Science, University of California, Berkeley, USA
Ioannis Kakadiaris Ass. Professor, Department of
Computer Science, University of Houston, 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.
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 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).
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.
59
Conclusion
  • Semantic Web is not only a technology as many
    used to name it
  • Semantic Web is not only an environment as many
    naming it now
  • Semantic Web it is a new context 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_at_it.jyu.fi
  • http//www.cs.jyu.fi/ai/vagan (tel. 358 14
    2604618)
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