Copyright 2003 by The MIT RE Corporation 1 Dr. Leo Obrst Dr. Leo Obrst MITRE MITRE Center for Innovative Computing & Informatics Center for Innovative Computing & Informatics Information Semantics Information Semantics [email protected][email protected]June 26, 2022 June 26, 2022 Ontologies for Ontologies for Semantically Semantically Interoperable Systems Interoperable Systems Semantic Representation Semantic Mapping Semantic Interoperability
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Copyright 2003 by The MITRE Corporation 1 Dr. Leo Obrst MITRE Center for Innovative Computing & Informatics Information Semantics [email protected] February.
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Copyright 2003 by The MITRE Corporation
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Dr. Leo ObrstDr. Leo ObrstMITRE MITRE
Center for Innovative Computing & InformaticsCenter for Innovative Computing & InformaticsInformation SemanticsInformation Semantics
Simple Syntactic Object Integration& CompositionAlignment of embedded interface definition language statements mapping two CORBA, Javabean objects
Simple Semantic Model, Knowledge Integration & CompositionUnification of tree or graph structures,with reasoning, simple Semantic Webontologies:
- signifies the composition operation
Complex Semantic Model, Knowledge, System Integration & Composition
Unification of complex networks of graph Structures, with complex reasoning, complex Semantic Web ontologies:
1960
1998
20052010
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Dimensions of Interoperability & Integration
Enterprise
Object
Data
System
Application
Component
0% 100%
6 Levels o
f Inte
ropera
bility
3 Kinds of Integration
Interoperability Scale
Our interest lies here
Community
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Semantic Interoperability/Integration Definition
• To interoperate is to participate in a common purpose– Operation sets the context– Purpose is the intention, the end to which activity is directed
• Semantics is fundamentally interpretation– Within a particular context– From a particular point of view
• Semantic Interoperability/Integration is fundamentally driven by communication of purpose– Participants determined by interpreting capacity to meet operational
objectives– Service obligations and responsibilities explicitly contracted
9weak semanticsweak semantics
strong semanticsstrong semantics
Is Disjoint Subclass of with transitivity property
Modal Logic
Logical Theory
Thesaurus Has Narrower Meaning Than
TaxonomyIs Sub-Classification of
Conceptual Model Is Subclass of
DB Schemas, XML Schema
UML
First Order Logic
RelationalModel, XML
ER
Extended ER
Description LogicDAML+OIL, OWL
RDF/SXTM
Ontology Spectrum: One View
Syntactic Interoperability
Structural Interoperability
Semantic Interoperability
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Logical Theory
Thesaurus Has Narrower Meaning Than
TaxonomyIs Sub-Classification of
Conceptual Model Is Subclass of
Is Disjoint Subclass of with transitivity property
weak semanticsweak semantics
strong semanticsstrong semantics
DB Schemas, XML Schema
UML
Modal LogicFirst Order Logic
RelationalModel, XML
ER
Extended ER
Description LogicDAML+OIL, OWL
RDF/SXTM
Ontology Spectrum: One View
Problem: Very GeneralSemantic Expressivity: Very High
Problem: Local Semantic Expressivity: Low
Problem: GeneralSemantic Expressivity: Medium
Problem: Local Semantic Expressivity: High
Syntactic Interoperability
Structural Interoperability
Semantic Interoperability
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.251.25SquareXAB035
.751.5RoundXAB023
…Price ($US)
Size (in)
ShapeCatalog No.
.4531S550298
.3537R550296
…Price ($US)
Diam (mm)
Geom.Part No.
Washer
Catalog No.Shape Size Price
iMetal Corp.E-Machina
iMetal Corp.E-Machina
Manufacturer
.451.25Square550298
.351.5Round550296
.751.5RoundXAB023
.251.25SquareXAB035
…Price ($US)
Size (in)
ShapeMfr No.
Supplier ASupplier
B
Buyer
Ontology
A Business Example of Ontology
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Architecture: Ontology & Applications
Ontology Layer
Ontology Application Services Layer
Application Layer
User Interface Layer
SemanticRepresentationRequirements
User (& presentation)Requirements
Support for Userto RepresentationRequirements
Search Transact
User RolesBuyer (Engr., Analyst)Seller
Search Transact Navigate Get/Put Data
Make/Get Alias Look-up Contextualize Infer
Taxonomies Metadata Attributes
In the emerging Web Services paradigm, Levels 1 - 4 consist of composable services
1
2
3
4
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What Problems Do Ontologies Help Solve?• Heterogeneous database problem
– Different organizational units, Service Needers/Providers have radically different databases
– Different syntactically: what’s the format?– Different structurally: how are they structured?– Different semantically: what do they mean? – They all speak different languages (access, description, schemas, meaning)– Integration: rather than N2 problem, with single, adequate Ontology reduces to N
Enterprise-wide system interoperability problemEnterprise-wide system interoperability problem– Currently: system-of-systems, vertical stovepipes– Ontologies act as conceptual model representing enterprise consensus
semantics
• Relevant document retrieval/question-answering problem– What is the meaning of your query?– What is the meaning of documents that would satisfy your query?– Can you obtain only meaningful, relevant documents?
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Enabling Semantic Interoperability
• Semantic Interoperability is enabled through:– Establishing base semantic representation via ontologies (class level) and
their knowledge bases (instance level)– Defining semantic mappings & transformations among ontologies (and
treating these mappings as individual theories just like ontologies)– Defining algorithms that can determine semantic similarity and employing
their output in a semantic mapping facility that uses ontologies
• The use of ontologies & semantic mapping software can reduce the loss of semantics (meaning) in information exchange among heterogeneous applications, such as:– Web Services– E-Commerce, E-Business– Enterprise architectures, infrastructures, and applications– Complex C4ISR systems-of-systems – Integrated Intelligence analysis
– Attribute: Address = H– Attribute: City = I– Attribute: StateProvince = J– Attribute: Country = K– Attribute: MailCode = L
Approximately Semantically
Equivalent to?
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Electronic Commerce Example:One Company
Products
MetalHealthElectronic Chemical
DistributorManufacturer
Wholesaler
Retailer
EndRun
TradingPartners
TransWorld iMicro
3InitialLocation
Africa Europe
SpainPortugal
Asia
Time
Point Interval
CoordinateSystem
UTMGeographic
LatLongGPS
UnitOfMeasure
DistanceMass
Liquid Solid
ShippingMethods
AirGround
Truck
RegionalCarrierLocalCarrier
Sea
ApplicationsTradingHub RFI/RFQ
Sell
ShippedBy
ObtainedFrom LocatedAt
GivenBy
MeasuredBy
UsesSupport
AvailableAt
Train
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Now Assume Each Company Has Separate Enterprise Semantics, Multiply by the Number of Companies, & Have Them Interoperate and Preserve Semantics
Try doing this without Ontologies! You can, but it’s a Nightmare, and it COSTS: Now & Later!Try doing this without Ontologies! You can, but it’s a Nightmare, and it COSTS: Now & Later!
Products
MetalHealthElectronic Chemical
DistributorManufacturer
Wholesaler
Retailer
EndRun
TradingPartners
TransWorld iMicro
3InitialLocation
Africa Europe
SpainPortugal
Asia
Time
Point Interval
Coordinate
System
UTMGeographic
LatLongGPS
UnitOfMeasure
DistanceMass
LiquidSolid
Shipping
MethodsAirGround
Truck
RegionalCarrierLocalCarrier
Sea
ApplicationsTradingHub RFI/RFQ
Sell
ShippedBy
ObtainedFrom LocatedAt
GivenBy
MeasuredBy
UsesSupport
AvailableAt
Train
Products
MetalHealthElectronic Chemical
DistributorManufacturer
Wholesaler
Retailer
EndRun
TradingPartners
TransWorld iMicro
3InitialLocation
Africa Europe
SpainPortugal
Asia
Time
Point Interval
Coordinate
System
UTMGeographic
LatLongGPS
UnitOfMeasure
DistanceMass
LiquidSolid
Shipping
MethodsAirGround
Truck
RegionalCarrierLocalCarrier
Sea
ApplicationsTradingHub RFI/RFQ
Sell
ShippedBy
ObtainedFrom LocatedAt
GivenBy
MeasuredBy
UsesSupport
AvailableAt
Train
Products
MetalHealthElectronic Chemical
DistributorManufacturer
Wholesaler
Retailer
EndRun
TradingPartners
TransWorld iMicro
3InitialLocation
Africa Europe
SpainPortugal
Asia
Time
Point Interval
Coordinate
System
UTMGeographic
LatLongGPS
UnitOfMeasure
DistanceMass
LiquidSolid
Shipping
MethodsAirGround
Truck
RegionalCarrierLocalCarrier
Sea
ApplicationsTradingHub RFI/RFQ
Sell
ShippedBy
ObtainedFrom LocatedAt
GivenBy
MeasuredBy
UsesSupport
AvailableAt
Train
Products
MetalHealthElectronic Chemical
DistributorManufacturer
Wholesaler
Retailer
EndRun
TradingPartners
TransWorld iMicro
3InitialLocation
Africa Europe
SpainPortugal
Asia
Time
Point Interval
Coordinate
System
UTMGeographic
LatLongGPS
UnitOfMeasure
DistanceMass
LiquidSolid
Shipping
MethodsAirGround
Truck
RegionalCarrierLocalCarrier
Sea
ApplicationsTradingHub RFI/RFQ
Sell
ShippedBy
ObtainedFrom LocatedAt
GivenBy
MeasuredBy
UsesSupport
AvailableAt
Train
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Emerging XML Stack Architecture for the Semantic Web + Grid + Agents• Semantic Brokers
• Intelligent Agents
• Advanced Applications
• Use, Intent: Pragmatics
• Trust: Proof + Security + Identity
• Reasoning/Proof Methods
• OWL, DAML+OIL: Ontologies
• RDF Schema: Ontologies
• RDF: Instances (assertions)
• XML Schema: Encodings of Data Elements & Descriptions, Data Types, Local Models
• XML: Base Documents
• Grid & Semantic Grid: New System Services, Intelligent QoS
Sem-Grid Services Water, LISP?
Syntax: Data
Structure
Semantics
Higher Semantics
Reasoning/Proof
XML
XML Schema
RDF/RDF Schema
OWL
Inference Engine
Trust Security/Identity
Use, Intent Pragmatic Web
Intelligent Domain Services, Applications
Agents, Brokers, Policies
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Semantic Web Services Stack
OWL, OWL-S, OWL-Rules
Service Entities, Relations, Rules
RDF/S Service Instances
BPEL4WS (Business Process Execution Language for Web Services)
Service Flow & Composition
Trading Partner Agreement
Service Agreement
UDDI/WS Inspection
Service Discovery (focused & unfocused)
UDDI Service Publication
WSDL Service Description
WS Security Secure Messaging
SOAP XML Messaging
HTTP, FTP, SMTP, MQ, RMI over IIOP
Transport
Adapted from: Bussler, Christoph; Dieter Fensel; Alexander Maedche,. 2003. A Conceptual Architecture for Semantic Web Enabled Web Services.
The Semantic Web: The Future of XML, Web Services, and Knowledge Management, -- Mike Daconta, Leo Obrst, & Kevin Smith, Wiley, June, 2003http://www.amazon.com/exec/obidos/ASIN/0471432571/qid%3D1050264600/sr%3D11-1/ref%3Dsr%5F11%5F1/103-0725498-4215019
Contents: 1. What is the Semantic Web?2. The Business Case for the Semantic Web3. Understanding XML and its Impact on the Enterprise4. Understanding Web Services5. Understanding the Resource Description Framework6. Understanding the Rest of the Alphabet Soup7. Understanding Taxonomies8. Understanding Ontologies9. Crafting Your Company’s Roadmap to the Semantic Web
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Backup
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Ontology & Ontologies 1
• An ontology defines the terms used to describe and represent an area of knowledge (subject matter)
– An ontology also is the model (set of concepts) for the meaning of those terms
– An ontology thus defines the vocabulary and the meaning of that vocabulary
• Ontologies are used by people, databases, and applications that need to share domain information
– Domain: a specific subject area or area of knowledge, like medicine, tool manufacturing, real estate, automobile repair, financial management, etc.
• Ontologies include computer-usable definitions of basic concepts in the domain and the relationships among them
– They encode domain knowledge (modular)
– Knowledge that spans domains (composable)
– Make knowledge available (reusable)
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Ontology & Ontologies 2
• The term ontology has been used to describe models with different degrees of structure (Ontology Spectrum)
– Less structure: Taxonomies (Semio taxonomies, Yahoo hierarchy, biological taxonomy), Database Schemas (many) and metadata schemes (ICML, ebXML, WSDL)
Object Level to the KR Language Level, Meta Level to the Instance Level
Person, Location, Event, Parent, Hammer, River, FinancialTransaction, BuyingAHouse, Automobile, TravelPlanning, etc.
Ontology Instance (OI) Level:
Object Level to the Ontology Concept Level
Harry X. Landsford III, Ralph Waldo Emerson, Person560234, PurchaseOrderTransactionEvent6117090, 1995-96 V-6 Ford Taurus 244/4.0 Aerostar Automatic with Block Casting # 95TM-AB and Head Casting 95TM