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Ulrich Reimer, Univ. of Applied Sciences St. Gallen 1Semantic Web Technologies, Japan 2006
Semantic Web Technologies forReal World Applications
Ulrich Reimer
Institute for Information and Process Management
University of Applied Sciences St. Gallen
Switzerland
2Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Overview
1. Introduction
2. Application Areas for Semantic Web Technology
2.1 Content-Oriented Retrieval
2.2 Reference Modeling & Model-Driven Development
2.3 Information & Process Integration
2.4 Flexible Business Transactions
3. Opportunities, Barriers, and Future Development
3Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
getinformation
provide information,affect the world
Information Retrieval Web Services
The Web: Information retrieval and web services
4Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
What characterizes a Semantic Web application?
An application employing Semantic Web technology contains a model of the application domain:
• an ontology, i.e. concepts, their properties, relationships, axioms
• rules representing regularities, constraints, norms of the domain
5Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Overview
1. Introduction
2. Application Areas for Semantic Web Technology
2.1 Content-Oriented Retrieval
2.2 Reference Modeling & Model-Driven Development
2.3 Information & Process Integration
2.4 Flexible Business Transactions
3. Opportunities, Barriers, and Future Development
6Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Time-consuming information search (1)
Many studies show:
A large percentage of daily work deals with information
(search, obtain, transform, distribute, file):
about 6 weeks/year for administrative workers
60 – 80% for knowledge workers
Recent study of a DMS company:
80% of interviewed companies need a whole day to find relevant information (although the DMS offers a search engine).
Reason:In many cases there are no guidelines for how to file documents.
7Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Consequences of inefficient and insufficient information provision:
higher costs
longer process durations
longer time to market
important information is not found:
inferior quality of decisions, processes, etc.
compliance violations
reinventing the wheel
Time-consuming information search (2)
8Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Information search with search engines
“tanker accident” atlantic
. . .
words contained in the documents
On 19 July 1979,the Atlantic Empressand the AegeanCaptain collided witheach other in theCaribbean Sea, offTobago island. ...
The tanker accident…
A single oil tankeraccident coulddestroy the entirecoastline. ...
Two tankers passedthe coast everyweek, transportingoil across theAtlantic to the USA. ...
The leaking oiltanker Prestige sinks off Spain'snorth-western coast...
9Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Contents:tanker accident, Atlantic Ocean,oil spill, environmental pollution
Author: -Language: EnglishDokument type: news text
Using meta data to describe document contents
words contained in meta data
The leaking oiltanker Prestige sinks off Spain'snorth-western coast...
“tanker accident” atlantic
10Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Contents:tanker collision, Atlantic Ocean,oil spill, environmental pollution
Author: -Language: EnglishDokument type: news text
Different terms in meta data and query formulation
words contained in meta data
“tanker accident” atlantic
11Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Contents:tanker collision, Gulf of Biscay,oil spill, environmental pollution
Author: -Language: EnglishDokument type: news text
words contained in meta data
Different vocabulary for indexing and querying
“tanker accident” atlantic
12Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
tanker accident
accidentis-a
ship accident
is-a
train accident
. . . is-awater
inland water
is-a is-a
sea
Pacific Ocean
is-a
Atlantic Ocean
is-a . . .
Contents:tanker accident, Atlantic Ocean
Ontology
Controlled vocabulary for indexing and querying
Ontology: controlled vocabulary
“tanker accident” atlantic
13Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Using background knowledge to extend query
tanker accident
Atlantic Ocean
tanker collision
Carribean Sea Bermuda Sea
part-of part-of
synonymy
Gulf of Biscay
part-of
(tanker collision OR tanker accident) AND (Atlantic Ocean OR Carribean Sea OR Bermuda Sea OR ...)
Ontology
Ontology: background knowledge
automaticquery extension
“tanker accident” atlantic
14Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
tanker accident
Atlantic Ocean
tanker collision
part-of part-of
synonymy
part-of
OntologySemanticsof relations
automaticquery extension
(tanker collision OR tanker accident) AND (Atlantic Ocean OR Carribean Sea OR Bermuda Sea OR ...)
Ontology: background knowledge
Using background knowledge to extend query
Carribean Sea Bermuda SeaGulf of Biscay
“tanker accident” atlantic
15Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Required background knowledge can be complex
automaticquery extension
The leaking oiltanker Prestige sinks off Spain'snorth-western coast...
document stillnot found
(tanker collision OR tanker accident) AND (Atlantic Ocean OR Carribean Sea OR Bermuda Sea OR ...)
“tanker accident” atlantic
16Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Technical realisation
What is needed:
• assign meta data to information objects
• content description with concepts and relations between them
• provision of background knowledge
• provision of the semantics of relations for query extension, ontology integration, etc.
RDF
RDF Schema, OWL,Rules
17Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Ontology-based skills management
descriptionof skills
Ontology
Ulrich Reimer, Univ. of Applied Sciences St. Gallen 18Semantic Web Technologies, Japan 2006
19Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
20Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Architecture
21Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
An ontology itself does not guarantee good query resultsSemantic query extension:
descend the concept hierarchy:described skill: WLANqueried skill: LAN
ascend the concept hierarchy:described skills: LANqueried skills: WLAN
Query extension (1)
LAN
WLAN
is-a
22Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
include siblings:described skill: Linuxqueried skill: BSD Unix
include synonyms:described skill: Voice over IPqueried skill: VoIP
Query extension (2)
VoIP Voice over IPsynonymy
operating system
Linux
is-a
BSD Unix
is-a
23Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
• an ontology is absolutely needed
• ontology development requires strong guidance by ontology experts
• keep ontology as small as possible
• query extension very important
Conclusion to ontology-based skills management
24Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Overview
1. Introduction
2. Application Areas for Semantic Web Technology
2.1 Content-Oriented Retrieval
2.2 Reference Modeling & Model-Driven Development
2.3 Information & Process Integration
2.4 Flexible Business Transactions
3. Opportunities, Barriers, and Future Development
25Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Closure
Tool for Project Management
LogoutAdministrationControlling P-OfficeSearchMonitoringPlanning ExecutionInitialisation
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
PortfolioE-Gov-Project
Process analysisSOA
Web ServicesRegistryOrchestration
OntologyGUI
Forecast
∑7,850.00∑7,850.00∑4,250.00
Project information system
Save Edit Cancel
26Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Modelling vs. Programming
Projectinformation system
Contractinformation system
etc.
hard-wired:
generic:
Genericinformation system
Projectontology
Contractsontology
27Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Genericinformation system
Projectontology
Modelling vs. Programming
Portfolio
Project
Sub-project
Workpackage
MilestoneDocumentIssueClient
status
Responsible
Person
is-a
contains
has-part
has-part
28Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Closure
Tool for Project Management
LogoutAdministrationControlling P-OfficeSearchMonitoringPlanning ExecutionInitialisation
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
PortfolioE-Gov-Project
Process analysisSOA
Web ServicesRegistryOrchestration
OntologyGUI
Forecast
∑7,850.00∑7,850.00∑4,250.00
How to present objects at the user interface?
Save Edit Cancel
29Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Closure
Tool for Project Management
LogoutAdministrationControlling P-OfficeSearchMonitoringPlanning ExecutionInitialisation
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
PortfolioE-Gov-Project
Process analysisSOA
Web ServicesRegistryOrchestration
OntologyGUI
Forecast
∑7,850.00∑7,850.00∑4,250.00
How to present objects at the user interface?
Save Edit Cancel
Navigation
Functions
30Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
ClosureControllingPlanning Execution
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
ClientsIssuesMilestones Documents
Welcome Mr. John Q. Public 11/07/200311/07/2003
MonitoringSub-Projects
Project: E-Gov-Project 2006/05/18
ControllingExecution
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
GUIOntology
Welcome Mr. John Q. Public 11/07/200311/07/2003
Process analysis
Status ReportDate
Responsible Start End Budget
April 06 Johnny B. Good1 March
20068 kEuro
Workpackages:
Web Services
Registry
Orchestration
SOA
Presenting subprojects and workpackages differently
versus
Project: E-Gov-Project
31Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
ClosureControllingPlanning Execution
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
ClientsIssuesMilestones Documents
Welcome Mr. John Q. Public 11/07/200311/07/2003
MonitoringSub-Projects
Project: E-Gov-Project 2006/05/18
ControllingExecution
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
GUIOntology
Welcome Mr. John Q. Public 11/07/200311/07/2003
Process analysis
Status ReportDate
Responsible Start End Budget
April 06 Johnny B. Good1 March
20068 kEuro
Workpackages:
Web Services
Registry
Orchestration
SOA
Presenting subprojects and workpackages differently
versus
Project: E-Gov-Project
32Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Portfolio
Project
Sub-project
Workpackage
MilestoneDocumentIssueClient
status
Responsible
Person
is-a
contains
has-part
has-part
Navigation tree
proj-root
proj-node-l1
proj-node-l2
proj-tree “Portfolio”
is-ahas-root
has-successor
has-successor
label
Information objects
GUI objectspositionsizehas-size has-position
Mapping GUI objects to information objects
33Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Portfolio
Project
Sub-project
Workpackage
MilestoneDocumentIssueClient
status
Responsible
Person
is-a
contains
has-part
has-part
Navigation tree
proj-root
proj-node-l1
proj-node-l2
proj-tree “Portfolio”
is-ahas-root
has-successor
has-successor
label
Information objects
GUI objectspositionsizehas-size has-position
Mapping GUI objects to information objects: Rule
34Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Portfolio
Project
Sub-project
Workpackage
MilestoneDocumentIssueClient
status
Responsible
Person
is-a
contains
has-part
has-part
proj-tree
root-1
node-1
node-12
tree-1 “Portfolio”
“E-Gov-Project”
“Process analysis”
instance-ofhas-root
has-successorlabel
has-successor
label
label
e-gov-project
sp-1
has-part
instance-of
instance-of
Information objects
GUI objectspositionsizehas-size has-position
Mapping GUI objects to information objects
top-left
has-position
35Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
ClosureControllingPlanning Execution
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
ClientsIssuesMilestones Documents
Welcome Mr. John Q. Public 11/07/200311/07/2003
MonitoringSub-Projects
Project: E-Gov-Project 2006/05/18
ControllingExecution
Welcome Mr. John Q. Public 11/07/200311/07/2003Welcome Mr. John Q. Public 2004/05/18
GUIOntology
Welcome Mr. John Q. Public 11/07/200311/07/2003
Process analysis
Status ReportDate
Responsible Start End Budget
April 06 Johnny B. Good1 March
20068 kEuro
Workpackages:
Web Services
Registry
Orchestration
SOA
Presenting subprojects and workpackages differently
versus
Project: E-Gov-Project
36Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Portfolio
Project
Sub-project
Workpackage
MilestoneDocumentIssueClient
status
Responsible
Person
is-a
contains
has-part
has-part
Tab sequence
tab-11tab-sequence-1 “Sub-Projects”
“SOA”
instance-offirst label
e-gov-project
sp-1
has-part
instance-of
instance-of
Information objects
GUI objectspositionsizehas-size has-position
tab-sequence-2tab-21firstlabel
“Process analysis”
tab-22
has-successorlabel
Mapping GUI objects to information objects
37Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project
Milestone
IssueClient
Document
Milestone
Issue
Client
Document
Project 1
Relationships in ontology: Navigation hierarchy:
Navigation hierarchy from relations between concepts
Milestone 1
Milestone 2
+-
++++
38Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project
Milestone
IssueClient
Document
Milestone
Issue
Client
Document
Project 1
Relationships in ontology: Navigation hierarchy:
Navigation hierarchy from relations between concepts
Milestone 1
Milestone 2
+-
++++
instance
39Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project
Sub-project
Workpackage
has-part
has-part
Navigation hierarchy from instances of related concepts
Sub-project 1
Sub-project 3
Sub-project 4
Sub-project 2
Project 1
Workpackage 11
Workpackage 12
+-
++++
Relationships in ontology: Navigation hierarchy:
40Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project
Sub-project
Workpackage
has-part
has-part
Navigation hierarchy from instances of related concepts
Sub-project 1
Sub-project 3
Sub-project 4
Sub-project 2
Project 1
Workpackage 11
Workpackage 12
+-
++++
Relationships in ontology: Navigation hierarchy:
instance
41Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project
Project
Navigation hierarchy from attribute values: classification
Attribute in ontology: Navigation hierarchy:
Projects: in time
Projects: delayed++
delay: { yes, no }
42Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project
Project
Navigation hierarchy from attribute values: classifiction
Attribute in ontology: Navigation hierarchy:
Projects: in time
Projects: delayed++
delay: { yes, no }
concept
43Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project Project
Navigation hierarchy from type of related instance
Relationships in ontology: Navigation hierarchy:
Client: Insurance
Client: Bank++
Client
Bank Insurance
is-ais-a
44Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project Project
Navigation hierarchy from attribute values
Relationships in ontology: Navigation hierarchy:
Client: Insurance
Client: Bank++
Client
concept
Bank Insurance
is-ais-a
45Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
app
licat
ion
alG
UI
Many aspects to model
domain ontology
rules
workflows
functions
roles & rights
GUI ontology
Some aspects are declarative
(i.e. model elements),
some are procedural
(i.e. pieces of code).
46Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Reference modelling
Projectinformation system
for Automotive
Projectontology forAutomotive
Projectontology
Reference Project Model
Generic projectinformation system
Projectinformation system
for Acme Inc.
Projectontology
for Acme Inc.
Reference Automotive Project Model
Specialization
Specialization
47Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Holistic Project Information System
Project Info System: Basic
Project Info System: Milestones
Project Info System: Budget
etc.
Aggregation of sub-models: Holistic vs. modular
Modular Project Information System
app
licat
ion
alG
UI
domain ontology
rules
workflows
functions
roles & rights
GUI ontology
applicational ontologies
GUI ontology
applicational ontologies
GUI ontology
applicational ontologies
GUI ontology
48Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Reference modelling: Specialization
Projectinformation system
for Automotive
Projectontology forAutomotive
Projectontology
Reference Project Model
Generic projectinformation system
Projectinformation system
for Acme Inc.
Projectontology
for Acme Inc.
Reference Automotive Project Model
Controllinginformation system
for Automotive
Controllingontology forAutomotive
Controllingontology
Reference Controlling Model
Generic controllinginformation system
Controllinginformation system
for Acme Inc.
Controllingontology
for Acme Inc.
Reference Automotive Controlling Model
Specialization
Specialization
49Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Reference modelling: Specialization and Aggregation
Projectinformation system
for Automotive
Projectontology forAutomotive
Projectontology
Reference Project Model
Generic projectinformation system
Projectinformation system
for Acme Inc.
Projectontology
for Acme Inc.
Reference Automotive Project Model
Controllinginformation system
for Automotive
Controllingontology forAutomotive
Controllingontology
Reference Controlling Model
Generic controllinginformation system
Controllinginformation system
for Acme Inc.
Controllingontology
for Acme Inc.
Reference Automotive Controlling Model
Specialization
Specialization
50Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Reference modelling: Specialization and Aggregation
Projectinformation system
for Automotive
Projectontology forAutomotive
Projectontology
Reference Project Model
Generic projectinformation system
Reference Automotive Project Model
Controllinginformation system
for Automotive
Controllingontology forAutomotive
Controllingontology
Reference Controlling Model
Generic controllinginformation system
Reference Automotive Controlling Model
Specialization
Specialization
Projectinformation system
for Acme Inc.
Projectontology
for Acme Inc.
Controllinginformation system
for Acme Inc.
Controllingontology
for Acme Inc.
51Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
project project manager
project staff
sub-project
workpackage
employee assignment
task
Ontology forResource Management
has-parthas-part
has-part
has
for
is-resp
has-assigned
Basic Project Ontology
Different concepts for same/similar thingshamper integration
52Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
project project manager
project staff
sub-project
workpackage
employee assignment
taskhas-parthas-part
has-part
has
for
is-resp
has-assigned
project taskemployee
is-ais-ais-a
is-a
is-a
Ontology forResource ManagementBasic Project Ontology
Extension of sub-ontologies destroys independence
project task
is-a
53Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
project project manager
project staff
sub-project
workpackage
employee assignment
taskhas-parthas-part
has-part
has
for
is-resp
has-assigned
project task employee
is-a
is-a
is-ais-a is-a is-a
is-a
Ontology forResource ManagementBasic Project Ontology
Upper-LevelOntology
Instead relate sub-ontologies to an upper-level-ontology
54Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Project Info System: Basic Project Info System: Milestones
Upper-level ontology facilitates aggregation of sub-models
Upper-Level Ontology
Project Info System: MilestonesProject Info System: Basic
Upper-Level OntologyAggregatedmodel
+
=
applicational ontologies
GUI ontology
applicational ontologies
GUI ontology
applicational ontologies
GUI ontology
applicational ontologies
GUI ontology
55Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Co
nfi
gu
rati
on
wo
rkb
ench
Model-driven development: From models to code
Genericinformation system
Projectontology forAutomotive
Genericinformation system
Projectontology
for Acme Inc.
Reference Project Model
Projectinformation system
for Acme Inc.
Compilation
Specialization
Run-time system
56Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Overview
1. Introduction
2. Application Areas for Semantic Web Technology
2.1 Content-Oriented Retrieval
2.2 Reference Modeling & Model-Driven Development
2.3 Information & Process Integration
2.4 Flexible Business Transactions
3. Opportunities, Barriers, and Future Development
57Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
A-Bank
Trustee
Company
Revenue tax declaration: Chaotic process withmany media breaks
B-Bank
Tax authority 1
Tax authority 2
58Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
tax documents
Process & information integration
A-Bank
Company
B-Bank
Tax authority 1
Tax authority 2
Trustee
59Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Different process for each province
A-Bank
Company
B-Bank
Tax authority 1
Tax authority 2
Trustee
tax documents
60Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
tax documents
Reference process model for revenue tax declaration
A-Bank
Tax authority 1
Company
B-Bank
Tax authority 2
Reference Model:Revenue tax declaration
Trustee
generic process model
61Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
tax documents
Reference process model plus specializations of it
A-Bank
Trustee
Company
B-Bank
Reference Model:Revenue tax declaration
Specialized model for Province 1
Specialized model for Province 2
Tax authority 1
Tax authority 2
62Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Different vocabulary for each province
A-Bank
Company
B-Bank
Tax authority 1
Tax authority 2
Trustee
tax documents
Ontology 1
Ontology 2
63Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Reference ontology with mappings to local ontologies
A-Bank
Company
B-Bank
Tax authority 1
Tax authority 2
Trustee
tax documents
Ontology 1
Ontology 2
Reference Ontology
64Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Process participants can get different views
Reference Model: Revenue tax declaration
Law ®ulations
Processdescriptions
Ontology
Specialized model for Province 1
Law ®ulations
Processdescriptions
Ontology
Specialized model for Province 2
Law ®ulations
Processdescriptions
Ontology
specialization
specialization
Company
Taxauthority 1
Taxauthority 2
65Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
How to get from models to IT systems?
????
OntologyOntologyOntology OntologyOntologyProcessdescriptions
OntologyOntologyLaw ®ulations
Reference model with all specializations
66Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Process control
WS
Company
WS
Tax authority
WS
Bank
WS
Trustee
electronictax documents
Orchestration Engine
Web Services
OrchestratedWeb Services
(BPEL)Rule Engine
OntologyOntologyOntology OntologyOntologyProcessdescriptions
OntologyOntologyLaw ®ulations
Reference model with all specializationsModel-drivendevelopment:From themodelto SOA
Service-orientedarchitecture
67Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS WSWSWSWSWSWSWeb Services / SOA:• legacy independence• reusability• integration
Model-driven development: The ideal case
Business process view:• application-driven
68Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS WSWSWSWSWSWS
Model-driven development: The ideal case
Top-down:From process modelto orchestratedweb service
Web Services / SOA:• legacy independence• reusability• integration
Business process view:• application-driven
69Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS
WSWS
Top-down:From process modelto orchestratedweb service
WSWS WSWSWSWSWSWS
Model-driven development: The ideal case
Web Services / SOA:• legacy independence• reusability• integration
Business process view:• application-driven
70Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS WSWSWSWSWSWS
Model-driven development: The reality
Web Services / SOA:• legacy independence• reusability• integration
Business process view:• application-driven
semantic gap
71Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS WSWSWSWSWSWS
Model-driven development: The reality
It does not fit!
Web Services / SOA:• legacy independence• reusability• integration
Business process view:• application-driven
72Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS WSWSWSWSWSWS
Model-driven development: The solution
Top-down:From the modelto orchestratedweb service
Bottom-up:Build the modelfrom the existingweb services
Web Services / SOA:• legacy independence• reusability• integration
Business process view:• application-driven
73Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
WSWS WSWSWSWSWSWS
Model-driven development: The solution
Top-down:From the modelto orchestratedweb service
Bottom-up:Build the modelfrom the existingweb services
WSWS
WSWS
Web Services / SOA:• legacy independence• reusability• integration
Business process view:• application-driven
74Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Overview
1. Introduction
2. Application Areas for Semantic Web Technology
2.1 Content-Oriented Retrieval
2.2 Reference Modeling & Model-Driven Development
2.3 Information & Process Integration
2.4 Flexible Business Transactions
3. Opportunities, Barriers, and Future Development
75Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Travel industry: Emergence of new business models
after: M.Y. Kabbaj: Strategic and Policy Prospects for Semantic Web Services Adoption in US Online Travel Industry.M.Sc. Thesis. June 2003.
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Current business models:
• manual bundling
• pre-fabricated travel packages
Advantages of travel packages:
• higher margins
• simple business processes
Disadvantages:
• fixed itineraries
• inflexible dates
• limited options
76Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
. . .
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Dynamic Packaging: New business model
Advantages:
• single point of contact
• satisfaction of individual customer needs
• increased revenues by revenue management
77Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Traditional Distribution Model
Travel Supplier /Inventory Owner
Tour Operator /Wholesaler
Retailer /Sales OrderProcessing
Consumer
New distribution model needed
Current distribution model impedes dynamic packaging
78Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Retailer
Travel Supplier /Inventory Owner
Travel Supplier /Inventory Owner
Consumer
ElectronicDemand-driven
Marketplace
Sales OrderProcessing
New distribution model:Combine information from distributed sources
79Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Requirements for dynamic packaging:
• reach across multiple markets, countries, currencies, suppliers
• automatic comparison of products
• automatic aggregation of products
• automatic negotiation of discounts
• trustworthy transactions
With current technology not efficient and not profitable!
Electronic marketplace needs Semantic Web Services
80Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
car rentalshotelsairlines
conventional registriesrequire programming
railway
Dynamic information gathering and transactions needed
81Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
machine understandable service descriptions
car rentalshotelsairlines
Dynamic information gathering and transactions needed
railway
82Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Input: <place>Output: bag-of( url( <car-rentals>) )
Precondition:¬∃ r: ( known( car-rental( r ) ∧ place-of( r ) = <place> )∧ ¬known(¬∃ r: car-rental( r ) ∧ place-of( r ) = <place> )
Postcondition:∃ r: ( known( car-rental( r ) ∧ place-of( r ) = <place> )∨ known(¬∃ r: car-rental( r ) ∧ place-of( r ) = <place> )
Ontology
Semantic Web Services:Ontology-based service description
83Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Travel Supplier /Inventory Owner
ElectronicDemand-driven
Marketplace
Sales OrderProcessing
business logicrepresented internally
business logicas rule markup
Business logic needed for negotiation and aggregation
84Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
The full potential of the Semantic Web
Dynamic
Static
Web ServicesUDDI, WSDL, SOAP
WWWURI, HTML, HTTP
Semantic Web ServicesOWL-S, WSMF, etc.
Semantic WebRDF Schema, OWL
SemanticTexts, images,
Web Service descriptions
85Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Overview
1. Introduction
2. Application Areas for Semantic Web Technology
2.1 Content-Oriented Retrieval
2.2 Reference Modeling & Model-Driven Development
2.3 Information & Process Integration
2.4 Flexible Business Transactions
3. Opportunities, Barriers, and Future Development
86Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
• Alleviation of information overload
• Querying facts instead of searching texts
• Integration of heterogeneous information sources
• Process integration
• Dynamic formation of business transactions
• Model-driven development of information systems
• Specialization and aggregation of reference models
Semantic Web Technologies: Opportunities
87Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Semantic Web Technologies: Barriers
• Where do the ontologies come from?
But: Many ontologies already exist
• Where do the semantic content descriptions come from?Ontology development is expensive.
• Not many people have the expertise to build ontologies.
• How to achieve good cost/benefit ratio?
88Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
UMLS (Unified Medical Language System):• semantically related medical terms• terms from ca. 100 heterogeneous classification systems and medical
terminologies in 15 languages
UNSPSC (United Nations Standard Products and Services Code):• hierarchical classification system for products and services
Geneontology:• controlled vacabulary to describe genes and proteins • 19’000 concepts• is-a and part-of relationships
and many more
Ontologies do not necessarily need to be big!
Many ontologies or predecessors already exist
89Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006
Conclusion
• Semantic Web Semantic Web technology
• Modeling will gain in importance over programming.
• Models will be ubiquitous because
– they are easier to create, modify, maintain
– they are easier to exchange and adapt (specialized, aggregated)
– versions can be better maintained (changes propagated top-down)
• Practical applications mostly need lightweight semantics, whereasmost research is about heavy-weight semantics.
90Ulrich Reimer, Univ. of Applied Sciences St. GallenSemantic Web Technologies, Japan 2006