Semantic Business Process Management Lecture 5 Semantic ... · rule-based expert systems) Examples:...
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Semantic Business Process Management
Lecture 5 – Semantic Technologies I
OMG Ontology Definition Metamodel
Prof. Dr. Adrian Paschke
Corporate Semantic Web (AG-CSW)
Institute for Computer Science, Freie Universitaet Berlin
http://www.inf.fu-berlin.de/groups/ag-csw/
Arbeitsgruppe
Problem: Only Syntactic BPM Models
Lacks of Web Service Technology
Current BPM technologies allow usage of Web Services
But: only syntactical information descriptions
syntactic support for discovery, composition and execution
=> Web Service usability, usage, and integration needs to be inspected manually
no semantically marked up content / services
no support for the Semantic Web rules and ontologies
=> current Web Service Technology Stack failed to
realize the promise of Web Services
Overview
Overview Semantic Technologies
Ontologies
OMG Ontology Definition Metamodel
W3C Web Ontology Language
Rules
OMG SBVR
OMG PRR
W3C RIF
RuleML
Semantic Computing Technologies
4. Software Agents and Web-based Services Rule Responder, FIPA, Semantic Web Services, …
3. Rules and Event/Action Logic & Inference RIF, SBVR, PRR, RuleML, Logic Programming
Rule/Inference Engines,…
2. Ontologien ODM, CL, Topic Maps RDFS, OWL Lite|DL|Full, OWL 2,
…
1. Explicit Meta-data and Terminologies vCard, PICS, Dublin Core, RDF, RDFa, Micro Formats,
FOAF, SIOC …
1. Explicit Metadata on the Web
Metadata are data about data
Metadata on the Web: Machine processable information about information on the Web
Projects e.g., PICS, Dublin Core, RDF, FOAF, SIOC, …
Problem domains: Syntax:
Which representation and interchange format for metadata?
Semantics: Which metadata are allowed for resources (metadata vocabulary, schema)
Association problem: How to connect metadata with resources (who defines the metadata, are
metadata separated from the content, etc.)
2. Ontologies
“An ontology is an explicit specification of a conceptualization “ T. Gruber
Ontologies described the common knowledge of a domain (semantics): Semantics interoperability between (connected) vocabularies
Typical components:1. Classes (concepts) of the domain
2. Properties (roles) of the classes
3. Constraints
4. Individuals (instances) of classes
3. Rules (Logic and Inference)
Logic is a discipline concerned with the principles of inference and reasoning
Formal languages for the representation of knowledge with clear semantics Declarative knowledge representation:
express what is valid, the responsibility to interpret this and to decide on how to do it is delegated to an interpreter / reasoner
Automated reasoner, e.g., a rule engine, can derive conclusions from given knowledge (inference)
4. Software Agents and Semantic Web Services
Intelligent Software Agents act autonomously and pro-active They have an internal knowledge base with decision/reaction logic (e.g.
rule-based expert systems)
Examples: Personal agents (e.g. Rule Responder), search robots
Web Service In general: any IT service provided on the Web
“A 'Web service' (also Web Service) is defined by the W3C as "a software system designed to support interoperable Machine to Machine interaction over a network." Web services are frequently just Web APIs that can be accessed over a network, such as the Internet, and executed on a remote system hosting the requested services.” (Wikipedia)
=> no clear separation between web agents and web services (in the broad sense) but level of self-autonomous decisions is higher in web agents
Ontologies
Aristotle - Ontology
Before: study of the nature of being
Since Aristotle: study of knowledge representation and reasoning
Terminology: Genus: (Classes)
Species: (Subclasses)
Differentiae: (Characteristics which allow to group or distinguish objects from each other)
Syllogisms (Inference Rules)
[Aristotle] Science of Being, Methapysics, IV, 1
What is an Ontology? (in IT)
An Ontology is a
formal specification Executable, Discussable
of a shared Group of persons
conceptualization About concepts; abstract class
of a domain of interest e.g. an application, a specific area, the “world model”
[Gruber 1993] - T.R. Gruber, Toward Principles for the Design of Ontologies Used forKnowledge Sharing, Formal Analysis in Conceptual Analysis and KnowledgeRepresentation, Kluwer, 1993.
Requirements for Ontology Languages
Ontology languages allow users to write explicit, formal conceptualizations of domain models
The main requirements are:
a well-defined syntax
efficient reasoning support
a formal semantics
sufficient expressive power
convenience of expression
Concept - Instance
Concept / Class / Universal (Metaphysics)
an abstract or general idea inferred or derived from specific
instances
Instance / Individual / Particular (Metaphysics)
object in reality, a copy of a abstract concept with actual values for
properties
Person
Person
Name: Adrian Paschke
Teaches: Computer Science
LivesIn: Berlin
WorksAt: Freie Universität Berlin
Types of ontologies
[Guarino et al. 1999] - N. Guarino, C. Masolo, G. Vetere. OntoSeek: Content-BasedAccess to the Web. In: IEEE Intelligent Systems, 14(3), 70--80, 1999.
Taxonomy
Taxonomy := Segmentation, classification and ordering of elements into a classification systemaccording to their relationships
Object
Person DocumentTopic
Student LetterResearcher Movie
Doctoral Student PhD Student
Thesaurus
Terminology for a specific domain
Taxonomy plus fixed relationships (similar, synonym, related to)
originate from bibliography
Object
Person DocumentTopic
Student LetterResearcher Email
similar
Doctoral Student PhD Student
synonym
related to
Topic Map
Topics (nodes), relationships, and occurrences of documents
ISO-Standard
typically for navigation and visualisation
Object
Person DocumentTopic
Student Letter
Doctoral Student
Researcher Email
PhD Student
synonym
similar
writes
knows described_in
Tel Affiliation
related to
Ontology (in our sense)
Representation Languages: ODM, RDF(S); OWL; Predicate Logic; F-Logic, ISO CL,…
Object
Person DocumentTopic
Student LetterResearcher Email
is_similar_to
knows described_in
Doctoral StudentPhD Student
Tel
Affiliation
Affiliation
is_a-1
is_a-1
is_a-1
is_a-1
is_a-1
is_a-1
instance_of-1
is_a-1
Hans Muster
is_a-1
FUB+49 030 608 ….
T D T D
D T P T
described_in
is_about knows
is_about
Pwrites
RULES, e.g.:
writes
related_to
Formality of KR Languages
Many Ontology Languages
Entity Relationship Modell
UML with OCL
Frames
Predicate Logic
Common Logic
Description Logic (formal Semantics, Reasoning)
SHOE, XOL, OML, SKOS, OBO
RDFS, DAML+OIL -> OWL
ODM
…
No special ontolgy languages,
but might be used to describe
ontologies
Ontologies and their relatives
Based on AAAI’99 Ontologies Panel – McGuiness, Welty, Ushold, Gruninger, Lehmann
Ontologies and their relatives (2)
24
Standards/Recommendations/Specificationsfor Semantic Computing
ISO/IEC JTC 1/SC 32
ISO/IEC
11179
Metadata
Registries
Metadata Registry
TerminologyThesaurusTaxonomy
Data
Standards
Ontology
Structured
Metadata
Terminology
CONCEPT
Referent
Refers To Symbolizes
Stands For
“Rose”,
“ClipArt
Rose”
ISO TC 37
Semantic
Web
W3C
Object
Management
MOF
ODM
PRR
SBVR
OMG
Node
Node
Edge
Subject
Predicate
Object
Graph RDF(S) / OWL
RIF
Ontology Definition Metamodel
OMG ODM
OMGOntology Definition Metamodel (ODM)
ODM is the OMG standard for model driven ontology
development
Adopted as an OMG standard in October 2006
http://www.omg.org/cgi-bin/doc?ptc/2007-09-09
Not one model, but a family of metamodels
Supports exchange of independently developed models
Provides standard profiles for ontology development in UML
Enables consistency checking and validation of models in
general
Ontology Definition Metamodel
ODM brings together the communities by providing:
Broad interoperation within Model Driven Architecture
MDA tool access to ontology based reasoning capability
UML notation for ontologies and ontological interpretation
of UML
OMG MOF and OMG MDA
Excurse
OMG MOF
The Meta-Object Facility (MOF) is an Object Management Group (OMG) standard for model-driven engineering.
M0 Layer Concrete representation of data.
M1 Layer Models, e.g. knowledge models, process modes, UML / object
models, which define the data on the M0 layer.
M2 Layer Meta-Models. Define the structure and architecture of models.
M3 Layer Meta-Meta-Models (MOF layer). Abstract layer, which is used to
define the M2 layer.
MOF-Based Metadata Management
MOF tools use metamodels to generate code that manages metadata, as XML documents, CORBA objects, Java objects
Generated code includes access mechanisms, APIs to Read and manipulate
Serialize/transform
Abstract the details based on access patterns
MOF
Related standards: XML Metadata Interchange (XMI®)
CORBA Metadata Interface (CMI)
Java Metadata Interface (JMI)
Metamodels are defined for Relational and hierarchical database modeling
Online analytical processing (OLAP)
Business process definition, business rules specification
XML, UML, and CORBA ID
OMG Model-driven Architecture (MDA) is a kind of domain engineering, and supports model-driven engineering (MDE)
1. Computation Independent Model (CIM)
2. Platform Independent Model (PIM)
3. Platform Specific Model (PSM)
Insulates business applications from technology evolution, for Increased portability and platform
independence
Cross-platform interoperability
Domain-relevant specificity
OMG MDA
OMG MDA - MOF Consists of standards and best practices across a range of software
engineering disciplines The Unified Modeling Language (UML®)
The Meta-Object Facility (MOF™)
The Common Warehouse Metamodel (CWM™)
MOF defines the metadata architecture for MDA Database schema, UML and ER models, business and manufacturing
process models, business rules, API definitions, configuration and deployment descriptors, etc.
Supports automation of physical management and integration of enterprise metadata
MOF models of metadata are called metamodels
MDA tools take models (e.g. MOF M1-3 models) as input and generate models as output
MDA principles can also apply to other areas such as business rules / ontologies modeling and business process modeling
MDA from a Knowledge Representation Perspective
Enterprise integration solutions rely on strict adherence to agreements based on common information models that take weeks or months to build
Modifications to the interchange agreements are costly and time consuming
Today, the analysis and reasoning required to align multiple parties‟ information models has to be done by people
Machines display only syntactic information models and informal text describing the semantics of the models
Without formal semantics, machines cannot aid the alignment process
Translations from each party‟s syntactic format to the agreed-upon common format have to be hand-coded by programmers
MOF and MDA provide the basis for automating the syntactic transformations
MOF and KR Together MOF technology streamlines the mechanics of managing models as XML
documents, Java objects, CORBA objects
Knowledge Representation supports reasoning about resources
Supports semantic alignment among differing vocabularies and nomenclatures
Enables consistency checking and model validation, business rule analysis
Allows us to ask questions over multiple resources that we could not answer previously
Enables business rules / processes driven applications to leverage existing knowledge, rules, processes to solve business problems
Detect inconsistent financial transactions
Support business policy enforcement
Facilitate next generation network management and security applications
while integrating with existing RDBMS and OLAP data stores
MOF provides no help with reasoning
KR is not focused on the mechanics of managing models or metadata
Complementary technologies – despite some overlap
back to OMG ODM …
Five EMOF platform independent metamodels (PIMs), four
normative
Mappings (MOF QVT)
UML2 Profiles
RDFS & OWL
Topic Maps
Collateral
XMI
Java APIs
Proof-of-concepts
Conformance
RDFS & OWL
Multiple Options
TM, CL Optional
Informative Mappings
CL
<<metamodel>>
TM
<<metamodel>> RDFS
<<metamodel>>
(from RDF)
RDFWeb
<<metamodel>>
(from RDF)
OWLBase
<<metamodel>>
(from OWL)
merge
DL
<<metamodel>>
RDFBase
<<metamodel>>
(from RDF)merge
merge
RDF
<<metamodel>>
OWLDL
<<metamodel>>
(from OWL)
merge
OWLFull
<<metamodel>>
(from OWL)
merge
merge
OWL
<<metamodel>>
(non-normative)
Model Driven Ontology Development: ODM Overview
ODM defines … Platform Independent (Normative) Metamodels (PIMs) include
RDFS & OWL – abstract syntax, constraints for OWL DL & OWL Full, several
compliance options
ISO Common Logic (CL)
ISO Topic Maps (TM)
Informative Models DL Core, relatively unconstrained Description Logics based metamodel
Identifier (keys) model extension to UML for ER
UML Profiles
RDFS/OWL Profile
Topic Maps Profile
Set of Mappings
UML to OWL,
Topic Maps to OWL
RDFS/OWL to Common Logic
ODM UML Profiles and Metamodels
Metamodels
To “precisely” represent the abstract syntax of target
ontology definition languages
UML mappings
To leverage existing UML models and ontologies
UML profiles
To facilitate the use of UML notation (and tools) for
ontology modeling
The ODM Architecture
<<metamodel>>
UML2
<<metamodel>>
DL
<<metamodel>>
SCL
<<metamodel>>
TM
<<metamodel>>
OWL
<<metamodel>>
RDFS
<<metamodel>>
ER
extension mapping
Ontology
Modeling
Languages
Ontology Description
Languages
NOTE: UML2 metamodel is an existing OMG standard
UML
Profiles for
Ontology
-- RDFS
-- OWL
-- TM
UML
NotationsOntology
Logic
Languages
dependency
Topic Maps
Topic Maps represent another XML Schema based
approach for conceptual knowledge representation
Topic Maps are collections of topics, each of which
represent a single subject, related to one another by
associations
Similar to ER in some respects
Originally based on the notion of a publications index
Used primarily in Europe, increasing interest in US
Recently standardized by ISO
ISO 13250 – Data Model and XML Serialization
ISO 18024 – Query Language
ISO 19756 – Constraint Language
ODM TM Metamodel OverviewTop Level Constructs
TopicMapConstructs are the basic element in the ODM TM
TopicMap is a collection of MapItem that are it‟s Topics
and Associations
Topics may, and typically do, have a set of Characteristics
Characteristic MapItem
Association
TopicMapConstruct
Topic
0..n +characteristic
0..n {set}
/hasA
Locator 0..n
+sourceLocator
{set} 0..n
TopicMap 0..n +content
0..n {set}
/containment
1
0..n
+parent 1
+topics 0..n {set}
1
0..n
+parent 1
+associations 0..n {set}
ODM TM OverviewCharacteristics
AssociationRoles connect
Topics together into
Associations
similar to UML Association
Ends, or UML Properties in
UML 2.0
Occurrences define
attributes of Topics
similar to UML Attributes
Names represent human
readable labels or
descriptions
they are not identifying.
ODM TM Topic Identifiers and Locators
TM distinguishes two types of Locators
Identifiers – The entity is about the subject.
Locators –The entity located is the subject.
ODM TM Scoping and Typing
Topics are class-like in that they can be used as „types‟
A Topics Characteristics and Associations may be limited to a specified scope.
AssociationCharacteristic
Scope_able
Topic
0..n
+scope
0..n
Type_able
0..1
+type
0..1
Common Logic Metamodel Overview
Sentence
Name
name : String
ExclusionSet
0..*
0..*
+excludedName0..*
+exclusionSet
0..*
ExcludedName
Importation
Phrase
Module
0..1 0..*+exclusionSet
0..1
+module0..*
ExcludedSet
Identifier
1
1
+localDomain1
+module1
ModuleName
1
0..*
+assertedContent1
+context0..*
NameForImportation
Comment
comment : String
Text
0..*
0..*
+phrase
0..*
+text0..*
PhraseForText
1
0..*
+body1
+moduleForBody
0..*
ModuleBody
0..1
0..*
+identifierForText0..1
+namedText0..*NameForText
0..*
0..1
+commentForText
0..*
+commentedText0..1
CommentedText
Provides a first-order, more expressive logic metamodel for ODM
– Next generation KIF, designed for the Semantic Web
– In use by DoD, intelligence community, researchers world-wide
– Needed to support complex process, service semantics
– Grounds the logical formulations of SBVR
Metamodel developed synergistically with ISO Common Logic
Common Logic Phrases
CL Terms & Atoms
Sentences
Boolean Sentences
There are no explicit 'true' and 'false' elements in the metamodel. These are empty cases of Conjunction (true) and Disjunction (false). That is why a Disjunction or Conjunction of zero sentences is allowed.
Quantified Sentences
Description Logics Metamodel
Many variations on DLs, depending on application requirements and reasoning capabilities (OWL represents a commonly used subset)
Resource Description Framework (RDF) Metamodel Overview
RDFBase – primary
package
Reflects basic abstract
syntax from RDF Concepts
Minimal implementation
requirements, e.g., for RDF
triple/quad store
RDFS – adds vocabulary
related to RDF Schema
RDFWeb – fits the model
to the Web via document
model
RDFS
<<metamodel>>
RDFBase
<<metamodel>>
RDFWeb
<<metamodel>>
merge
merge
RDF
<<metamodel>>
(from org.omg.odm)
RDFBase Package - Statements
Supports named graphs (e.g., per SPARQL), reification, blank node identifiers, essentially RDF basics
Limited coverage to RDF Concepts document rather than along namespace boundaries, which didn‟t work from a UML perspective
Promotion of the blank node identifier to RDFSResource addresses MOF multiple classification, non-normative work-around
RDFS Package –Classes & Utilities
RDFS assists us in “getting around”MOF multiple
classification limitations through rdf:type
RDFS Package –Properties
Note that rdf:domain and rdf:range are global properties – limiting their
usage enhances reusability of ontology components
RDFWebPackage –Documents
Web Ontology Language (OWL) Metamodel Overview
OWL metamodel components
include:
OWLBase: common abstract
syntax & constraints
OWLDL: OWL DL constraints
OWLFull: OWL Full constraints
“Semantic MOF” or SMOF spec,
currently in work at OMG
fills in the gaps for MOF multiple
classification
provides additional capabilities for
KR applications, SBVR, domain-
specific languages
OWLBase
<<metamodel>>
OWL
<<metamodel>>
(from org.omg.odm)
RDFBase
<<metamodel>>
(from RDF)
RDFS
<<metamodel>>
(from RDF)
merge
RDFWeb
<<metamodel>>
(from RDF)merge
RDF
<<metamodel>>
(from org.omg.odm)
OWLDL
<<metamodel>>
OWLFull
<<metamodel>>
mergemerge
merge
merge
Excerpt OWL Metamodel
The OWL metamodel is implemented by extending the RDFS metamodel.
OWLBase Package –OWL Ontology
OWLBase Package –OWL Classes
OWLBase Package –Restrictions
OWLBase Package –OWL Properties
UML Profile for RDF & OWL
Intended to be highly intuitive for UML users
Reuses UML constructs when they have the same semantics as OWL When this is not possible, stereotypes UML constructs
that are consistent and as close as possible to OWL semantics
Uses standard UML 2 notation In the few cases where this is not possible, follows the
clarifications and elaborations of stereotype notation defined in UML 2.1
Key Features of the RDF Profile
rdfs:Resource is modeled as UML::InstanceSpecification
Introduction of <<reifies>> stereotype of UML::Dependencyto allow such instance specifications to reify classes, properties, individuals, statements, etc.
rdf:Property is modeled as UML::AssociationClass and UML::Property, to provide greatest possible flexibility
Several possible representations of various aspects of rdf:Property
RDF Property Subsetting Options
Example OWL Number, Value Constraints
OWL Cardinality –Restricted Mulitplicity in Subtype
OWL allValuesFrom –Property Redefinition
OWL Property Redefinition (allValuesFrom) Using Association Classes
OWL Intersection, Union, Complement
OWL Disjointness Options
Simple binary disjoint relationship
Disjointness, multiple participants,
common parent
Disjointness, multiple participants, no
common parent
OWL Inverse Options
Simple inverse relationship
Inverse relationship among association classes
ODM UML-OWL Bridge
UML to OWL Transformation
Example: Museum UML Model
Example: UML2OWL Transformation
MDA-based Ontology Engineering with ODM
ODM Summary
Standard for model driven ontology development ODM brings together the Software Engineering and Knowledge
Representation communities
Platform Independent (Normative) Metamodels (PIMs) include –RDF & OWL – abstract syntax, constraints for OWL DL & OWL
Full, several compliance options
–ISO Common Logic (CL)
–ISO Topic Maps (TM)
Informative Models –DL Core –high-level, relatively unconstrained Description Logics
based metamodel (non-normative, informational)
Identifier (keys) model extension to UML for ER
Adopted as an OMG standard in October 2006
Questions ?
Literature
OMG Ontology PSIG http://www.omg.org/ontology/
OMG ODM 1.0http://www.omg.org/spec/ODM/1.0/
Eclipse ATL ODM http://www.eclipse.org/m2m/atl/usecases/ODMImplementation/