SlideShare una empresa de Scribd logo
1 de 12
Descargar para leer sin conexión
Motivation                              Standard                             Example                         Roadmap




     Ontology Integration and Interoperability
    (OntoIOp) – Part 1: The Distributed Ontology
                  Language (DOL)
                                  OASIS Symposium @ ISWC 2011


                     Till Mossakowski, Oliver Kutz, Christoph Lange

                                             Universität Bremen, Germany


                                                   2011-10-24


Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    1
Motivation                              Standard                             Example                         Roadmap



Interoperable Assistive Technology
         Assistive technology increasingly relies on communication
                  among users,
                  between users and their devices, and
                  among these devices.
         Making such ICT accessible and inclusive is costly or even
         impossible
         We aim at more interoperable
                  devices,
                  services accessing these devices, and
                  content delivered by these services
         . . . at the levels of
                  data and metadata
                  data models and data modelling methods
                  metamodels as well as a meta ontology language
Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    2
Motivation                                           Standard                                       Example                                   Roadmap



The Big Picture of Interoperability
                                    Knowledge Infrastructure                        Service-Oriented                      Smart Environment
                                                                                      Architecture

                                   Concepts/Data/Individuals                              Service                            Target (Device)
                                                                                                                                 Device
              rabil r
                   ity
                  fo




                                           Ontology                               Service Description                       Target Description
     inte ppings
         rope
       ma




                                   Ontology Language/Logic                      Service Descr. Language                 Target Descr. Language



             Data           Concepts/Data/Individuals    processes              Service               accesses      Target (Device)
                                                                                                                        Device
                                        represented in terms of                     satisfies                                conforms to
        Models                      Ontology              refers to        Service Description                     Target Description
                                        written in                                  written in                               written in

  Metamodels                Ontology Language/Logic                     Service Descr. Language                  Target Descr. Language

                                   Knowledge                                Software Agents                            Hardware




                         For now we focus
                         on the “content”/
                         “knowledge”
                         column
Mossakowski/Kutz/Lange (OASIS; U. Bremen)                             OntoIOP Part 1: Distributed Ontology Language (DOL)                 2011-10-24    3
Motivation                              Standard                             Example                         Roadmap



DOL (Distributed Ontology Language)
         In practical applications, one ontology language and one
         logic doesn’t suffice to achieve semantic integration and
         interoperability
         Part 1 of the OntoIOp standard provides a meta-language
         (DOL) for:
                  logically heterogeneous ontologies
                  modular ontologies
                  formal and informal links between ontologies/modules
                  annotation and documentation of ontologies
         DOL will have a formal semantics and concrete XML, RDF and
         text serializations
         We leave services and devices to future parts of the standard

Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    4
Motivation                              Standard                             Example                         Roadmap



Why a Standard?
         DOL is now being developed
                  as ISO Working Item 17347
                  within ISO TC 37 (Terminology and other language and content
                  resources) / SC 3 (Systems to manage terminology, knowledge
                  and content)
                  by a project team (= us) and experts from ≈ 15 countries
         In practice, interoperability can only be achieved via standards
         (cf. Christian Galinski @ OASIS 2009)
                  formulate consensual rules under participation of major
                  stakeholders (here: ontology language communities)
                  improve suitability of products, processes and services
                  facilitate communication
                  reduce complexity (and thus costs)
                  increase quality via certification
Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    5
Motivation                              Standard                             Example                         Roadmap



Requirements I



         DOL should be generally applicable, open, and extensible
         DOL shall be a logic-agnostic metalanguage
         DOL should have user- and machine-readable serializations
         DOL should have a well-defined formal, logic-based
         semantics




Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    6
Motivation                                       Standard                                  Example                                       Roadmap



The Onto-Logical Translation Graph
                               OBOOWL




                     OBO 1.4
                                                                                                                     bRDF




                                                        EL             QL             RL     RDF


                          PL


                                                       OWL                     RDFS


                                        DDLOWL



                                                                  RDFSOWL                   grey: no fixed expressivity

                                                                                            green: decidable ontology languages

                                                                                            yellow: semi-decidable
                               ECoOWL
                                                                        FOL=
                                                                                            orange: some second-order constructs

                                                                                            red: full second-order logic

                    CL         ECoFOL      Rel-S
                                                             F-logic


                                                                                                       subinstitution

                   CASL                                                                                theoroidal subinstitution

                                                                                                       simultaneously exact and
                                                                   FOLms=                              model-expansive comorphisms
                   HOL
                                                                                                       model-expansive comorphisms



Mossakowski/Kutz/Lange (OASIS; U. Bremen)                    OntoIOP Part 1: Distributed Ontology Language (DOL)                     2011-10-24    7
Motivation                              Standard                                Example                         Roadmap



Requirements II
         DOL should allow for expressing logically heterogeneous
         ontologies (and literal reuse of existing modules)
         DOL should allow for expressing links between ontologies
                                                DOL
                                                             Common          Common
                                                   OWL        Logic           Logic
                                                       ontology        ontology
                                                       language     interpretation
                                                      translation

                                       import                                               import

                                     DOL                                             DOL
                                     OWL-XML                                         CLIF
                                      ASK-IT Ontologies:                             DOLCE
                                      • Transportation                               Foundational
                                      • Tourism                                      Ontology
                                      • Personal Support


Mossakowski/Kutz/Lange (OASIS; U. Bremen)             OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    8
Motivation                              Standard                             Example                         Roadmap



Requirements III



         DOL should allow for writing down ontologies and ontology
         links as implicitly as possible and as explicitly as needed
         DOL should allow for rich annotation and documentation of
         ontologies




Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24    9
Motivation                              Standard                             Example                         Roadmap



Conformance Criteria
         DOL should work with any existing or future ontology
         language (if the latter conforms!)
         We shall establish the conformance of OWL, Common Logic,
         RDFS, F-logic, UML class diagrams, and OBO
         Conformance of a logic (directly or by translation):
         semantic conformance > entailment conformance
         Conformance of a serialization:
         XML conformance > RDF conformance > text conformance >
         standoff markup conformance
         Conformance of a document
         (“Is this document a DOL ontology?”)
         Conformance of an application:
         A DOL-conforming application produces DOL-conforming
         documents!
Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24   10
Motivation                              Standard                             Example                         Roadmap



Example: A Heterogeneous Time Ontology

logic OWL                                                     logic CommonLogic
spec TimeOWL =                                                spec TimeCL = TimeRIF then
  Class: TemporalEntity                                       . (forall (t1 t2)
  ObjectProperty: before                                                (or (before t1 t2)
    Domain: TemporalEntity                                                  (before t2 t1)
    Range: TemporalEntity                                                   (= t1 t2)))
    Characteristics: Transitive                               end
end
                                                              Existing and future DOL features relevant here:
logic RIF                                                              literal inclusion of existing languages
spec TimeRIF = TimeOWL then
  Group (                                                              modular reuse
    Forall ?t1 ?t2 ?t3                                                 XML and RDF serializations
    (before(?t1 ?t3) :-
                                                                       further link types
      before(?t1 ?t2)
      before(?t2 ?t3))                                                 documenting translations explicitly
end
                                                                       rich annotations and documentation


Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24   11
Motivation                              Standard                             Example                         Roadmap



Roadmap

 Current development is done via mailing list and file repository.
 Later, we will more and more follow the formal ISO procedures.
      Now (Oct–Dec 2011): WD (Working Draft) in preparation of the
      CD (Committee Draft) ballot
         from Dec 2011: experts review and prepare formal vote on CD;
         discussions at meetings in Feb 2012 and Jun 2012
         Aug 2013: DIS (Draft International Standard)
         Feb 2015: FDIS (Final Draft International Standard)
         Aug 2015: IS (International Standard)
 http://ontolog.cim3.net/cgi-bin/wiki.pl?OntoIOp


Mossakowski/Kutz/Lange (OASIS; U. Bremen)          OntoIOP Part 1: Distributed Ontology Language (DOL)   2011-10-24   12

Más contenido relacionado

La actualidad más candente

Semantic Technology: State of the arts and Trends
Semantic Technology: State of the arts and TrendsSemantic Technology: State of the arts and Trends
Semantic Technology: State of the arts and TrendsWon Kwang University
 
Wed 1430 kartik_subramanian_color
Wed 1430 kartik_subramanian_colorWed 1430 kartik_subramanian_color
Wed 1430 kartik_subramanian_colorDATAVERSITY
 
Object Oriented Programming in Python
Object Oriented Programming in PythonObject Oriented Programming in Python
Object Oriented Programming in PythonJordi Vilaplana
 
CSTalks-Natural Language Processing-17Aug
CSTalks-Natural Language Processing-17AugCSTalks-Natural Language Processing-17Aug
CSTalks-Natural Language Processing-17Augcstalks
 
Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189Editor IJARCET
 
Knowledge Multimedia Processes in Technology Enhanced Learning
Knowledge Multimedia Processes in Technology Enhanced LearningKnowledge Multimedia Processes in Technology Enhanced Learning
Knowledge Multimedia Processes in Technology Enhanced LearningRalf Klamma
 
E0502 01 2327
E0502 01 2327E0502 01 2327
E0502 01 2327IJMER
 
Pal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologiesPal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologiesMustafa Jarrar
 
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...Seokhwan Kim
 
Pal gov.tutorial4.session8 1.ontologymodelingchallenges
Pal gov.tutorial4.session8 1.ontologymodelingchallengesPal gov.tutorial4.session8 1.ontologymodelingchallenges
Pal gov.tutorial4.session8 1.ontologymodelingchallengesMustafa Jarrar
 
Information filtering, By Hadi Mohammadzadeh
Information filtering, By Hadi MohammadzadehInformation filtering, By Hadi Mohammadzadeh
Information filtering, By Hadi MohammadzadehHadi Mohammadzadeh
 
A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...
A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...
A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...kevig
 
Modeling of Speech Synthesis of Standard Arabic Using an Expert System
Modeling of Speech Synthesis of Standard Arabic Using an Expert SystemModeling of Speech Synthesis of Standard Arabic Using an Expert System
Modeling of Speech Synthesis of Standard Arabic Using an Expert Systemcsandit
 
A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...
A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...
A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...Editor IJARCET
 

La actualidad más candente (17)

Semantic Technology: State of the arts and Trends
Semantic Technology: State of the arts and TrendsSemantic Technology: State of the arts and Trends
Semantic Technology: State of the arts and Trends
 
Wed 1430 kartik_subramanian_color
Wed 1430 kartik_subramanian_colorWed 1430 kartik_subramanian_color
Wed 1430 kartik_subramanian_color
 
Object Oriented Programming in Python
Object Oriented Programming in PythonObject Oriented Programming in Python
Object Oriented Programming in Python
 
CSTalks-Natural Language Processing-17Aug
CSTalks-Natural Language Processing-17AugCSTalks-Natural Language Processing-17Aug
CSTalks-Natural Language Processing-17Aug
 
Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189
 
Knowledge Multimedia Processes in Technology Enhanced Learning
Knowledge Multimedia Processes in Technology Enhanced LearningKnowledge Multimedia Processes in Technology Enhanced Learning
Knowledge Multimedia Processes in Technology Enhanced Learning
 
Semantic Search Trend
Semantic Search TrendSemantic Search Trend
Semantic Search Trend
 
E0502 01 2327
E0502 01 2327E0502 01 2327
E0502 01 2327
 
A Rewriting Approach to Concurrent Programming Language Design and Semantics
A Rewriting Approach to Concurrent Programming Language Design and SemanticsA Rewriting Approach to Concurrent Programming Language Design and Semantics
A Rewriting Approach to Concurrent Programming Language Design and Semantics
 
Pal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologiesPal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologies
 
Tutorial kcc-2011
Tutorial kcc-2011Tutorial kcc-2011
Tutorial kcc-2011
 
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...
 
Pal gov.tutorial4.session8 1.ontologymodelingchallenges
Pal gov.tutorial4.session8 1.ontologymodelingchallengesPal gov.tutorial4.session8 1.ontologymodelingchallenges
Pal gov.tutorial4.session8 1.ontologymodelingchallenges
 
Information filtering, By Hadi Mohammadzadeh
Information filtering, By Hadi MohammadzadehInformation filtering, By Hadi Mohammadzadeh
Information filtering, By Hadi Mohammadzadeh
 
A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...
A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...
A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUA...
 
Modeling of Speech Synthesis of Standard Arabic Using an Expert System
Modeling of Speech Synthesis of Standard Arabic Using an Expert SystemModeling of Speech Synthesis of Standard Arabic Using an Expert System
Modeling of Speech Synthesis of Standard Arabic Using an Expert System
 
A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...
A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...
A Combined Approach to Part-of-Speech Tagging Using Features Extraction and H...
 

Similar a Ontology Integration and Interoperability (OntoIOp) – Part 1: The Distributed Ontology Language (DOL)

The Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility
The Distributed Ontology Language (DOL): Use Cases, Syntax, and ExtensibilityThe Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility
The Distributed Ontology Language (DOL): Use Cases, Syntax, and ExtensibilityChristoph Lange
 
Making Heterogeneous Ontologies Interoperable Through Standardisation
Making Heterogeneous Ontologies Interoperable Through StandardisationMaking Heterogeneous Ontologies Interoperable Through Standardisation
Making Heterogeneous Ontologies Interoperable Through StandardisationChristoph Lange
 
8 ontology integration and interoperability (onto i op)
8 ontology integration and interoperability (onto i op)8 ontology integration and interoperability (onto i op)
8 ontology integration and interoperability (onto i op)AEGIS-ACCESSIBLE Projects
 
An ontology driven module for accessing chronic pathology literature- CHRONIO...
An ontology driven module for accessing chronic pathology literature- CHRONIO...An ontology driven module for accessing chronic pathology literature- CHRONIO...
An ontology driven module for accessing chronic pathology literature- CHRONIO...Riccardo Albertoni
 
Proposal of an Ontology Applied to Technical Debt on PL/SQL Development
Proposal of an Ontology Applied to Technical Debt on PL/SQL DevelopmentProposal of an Ontology Applied to Technical Debt on PL/SQL Development
Proposal of an Ontology Applied to Technical Debt on PL/SQL DevelopmentJorge Barreto
 
Php oops interview questions
Php oops interview questionsPhp oops interview questions
Php oops interview questionsVIjay Sunder
 
Semantic Rules Representation in Controlled Natural Language in FluentEditor
Semantic Rules Representation in Controlled Natural Language in FluentEditorSemantic Rules Representation in Controlled Natural Language in FluentEditor
Semantic Rules Representation in Controlled Natural Language in FluentEditorCognitum
 
Owl web ontology language
Owl  web ontology languageOwl  web ontology language
Owl web ontology languagehassco2011
 
Owl web ontology language
Owl  web ontology languageOwl  web ontology language
Owl web ontology languagehassco2011
 
A Mathematical Approach to Ontology Authoring and Documentation
A Mathematical Approach to Ontology Authoring and DocumentationA Mathematical Approach to Ontology Authoring and Documentation
A Mathematical Approach to Ontology Authoring and DocumentationChristoph Lange
 
A Comparative Study of Ontology building Tools in Semantic Web Applications
A Comparative Study of Ontology building Tools in Semantic Web Applications A Comparative Study of Ontology building Tools in Semantic Web Applications
A Comparative Study of Ontology building Tools in Semantic Web Applications dannyijwest
 
A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications IJwest
 
A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications dannyijwest
 
Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...
Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...
Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...Facultad de Informática UCM
 
Gellish A Standard Data And Knowledge Representation Language And Ontology
Gellish   A Standard Data And Knowledge Representation Language And OntologyGellish   A Standard Data And Knowledge Representation Language And Ontology
Gellish A Standard Data And Knowledge Representation Language And OntologyAndries_vanRenssen
 
A Methodological Framework for Ontology and Multilingual Termontological Data...
A Methodological Framework for Ontology and Multilingual Termontological Data...A Methodological Framework for Ontology and Multilingual Termontological Data...
A Methodological Framework for Ontology and Multilingual Termontological Data...Christophe Debruyne
 
Pal gov.tutorial4.session1 1.needforsharedsemantics
Pal gov.tutorial4.session1 1.needforsharedsemanticsPal gov.tutorial4.session1 1.needforsharedsemantics
Pal gov.tutorial4.session1 1.needforsharedsemanticsMustafa Jarrar
 
Question answer template
Question answer templateQuestion answer template
Question answer templateThanuw Chaks
 
Are Data Models Superfluous Nov2003
Are Data Models Superfluous Nov2003Are Data Models Superfluous Nov2003
Are Data Models Superfluous Nov2003Andries_vanRenssen
 

Similar a Ontology Integration and Interoperability (OntoIOp) – Part 1: The Distributed Ontology Language (DOL) (20)

The Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility
The Distributed Ontology Language (DOL): Use Cases, Syntax, and ExtensibilityThe Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility
The Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility
 
Making Heterogeneous Ontologies Interoperable Through Standardisation
Making Heterogeneous Ontologies Interoperable Through StandardisationMaking Heterogeneous Ontologies Interoperable Through Standardisation
Making Heterogeneous Ontologies Interoperable Through Standardisation
 
8 ontology integration and interoperability (onto i op)
8 ontology integration and interoperability (onto i op)8 ontology integration and interoperability (onto i op)
8 ontology integration and interoperability (onto i op)
 
An ontology driven module for accessing chronic pathology literature- CHRONIO...
An ontology driven module for accessing chronic pathology literature- CHRONIO...An ontology driven module for accessing chronic pathology literature- CHRONIO...
An ontology driven module for accessing chronic pathology literature- CHRONIO...
 
Proposal of an Ontology Applied to Technical Debt on PL/SQL Development
Proposal of an Ontology Applied to Technical Debt on PL/SQL DevelopmentProposal of an Ontology Applied to Technical Debt on PL/SQL Development
Proposal of an Ontology Applied to Technical Debt on PL/SQL Development
 
Php oops interview questions
Php oops interview questionsPhp oops interview questions
Php oops interview questions
 
Semantic Rules Representation in Controlled Natural Language in FluentEditor
Semantic Rules Representation in Controlled Natural Language in FluentEditorSemantic Rules Representation in Controlled Natural Language in FluentEditor
Semantic Rules Representation in Controlled Natural Language in FluentEditor
 
Owl web ontology language
Owl  web ontology languageOwl  web ontology language
Owl web ontology language
 
Owl web ontology language
Owl  web ontology languageOwl  web ontology language
Owl web ontology language
 
A Mathematical Approach to Ontology Authoring and Documentation
A Mathematical Approach to Ontology Authoring and DocumentationA Mathematical Approach to Ontology Authoring and Documentation
A Mathematical Approach to Ontology Authoring and Documentation
 
A Comparative Study of Ontology building Tools in Semantic Web Applications
A Comparative Study of Ontology building Tools in Semantic Web Applications A Comparative Study of Ontology building Tools in Semantic Web Applications
A Comparative Study of Ontology building Tools in Semantic Web Applications
 
A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications
 
A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications A Comparative Study Ontology Building Tools for Semantic Web Applications
A Comparative Study Ontology Building Tools for Semantic Web Applications
 
Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...
Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...
Languages, Ontologies and Automatic Grammar Generation - Prof. Pedro Rangel H...
 
Gellish A Standard Data And Knowledge Representation Language And Ontology
Gellish   A Standard Data And Knowledge Representation Language And OntologyGellish   A Standard Data And Knowledge Representation Language And Ontology
Gellish A Standard Data And Knowledge Representation Language And Ontology
 
A Methodological Framework for Ontology and Multilingual Termontological Data...
A Methodological Framework for Ontology and Multilingual Termontological Data...A Methodological Framework for Ontology and Multilingual Termontological Data...
A Methodological Framework for Ontology and Multilingual Termontological Data...
 
Pal gov.tutorial4.session1 1.needforsharedsemantics
Pal gov.tutorial4.session1 1.needforsharedsemanticsPal gov.tutorial4.session1 1.needforsharedsemantics
Pal gov.tutorial4.session1 1.needforsharedsemantics
 
Question answer template
Question answer templateQuestion answer template
Question answer template
 
Are Data Models Superfluous Nov2003
Are Data Models Superfluous Nov2003Are Data Models Superfluous Nov2003
Are Data Models Superfluous Nov2003
 
Lit mtap
Lit mtapLit mtap
Lit mtap
 

Más de Christoph Lange

Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...
Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...
Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...Christoph Lange
 
Research Careers in Applied Computer Science
Research Careers in Applied Computer ScienceResearch Careers in Applied Computer Science
Research Careers in Applied Computer ScienceChristoph Lange
 
OSCOSS: Opening Scholarly Communication in Social Sciences
OSCOSS: Opening Scholarly Communication in Social SciencesOSCOSS: Opening Scholarly Communication in Social Sciences
OSCOSS: Opening Scholarly Communication in Social SciencesChristoph Lange
 
WDAqua ITN – Answering Questions using Web Data
WDAqua ITN – Answering Questions using Web DataWDAqua ITN – Answering Questions using Web Data
WDAqua ITN – Answering Questions using Web DataChristoph Lange
 
Machine Support for Interacting with Scientific Publications Improving Inform...
Machine Support for Interacting with Scientific Publications Improving Inform...Machine Support for Interacting with Scientific Publications Improving Inform...
Machine Support for Interacting with Scientific Publications Improving Inform...Christoph Lange
 
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...Christoph Lange
 
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect match
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect matchLinked Open (Geo)Data and the Distributed Ontology Language – a perfect match
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect matchChristoph Lange
 
Linking Big Data to Rich Process Descriptions
Linking Big Data to Rich Process DescriptionsLinking Big Data to Rich Process Descriptions
Linking Big Data to Rich Process DescriptionsChristoph Lange
 
Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...
Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...
Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...Christoph Lange
 
Semantic Web Technology: The Key to Making Scientific Information Systems Social
Semantic Web Technology: The Key to Making Scientific Information Systems SocialSemantic Web Technology: The Key to Making Scientific Information Systems Social
Semantic Web Technology: The Key to Making Scientific Information Systems SocialChristoph Lange
 
TCP – zuverlässiger Ende-zu-Ende-Datenstrom
TCP – zuverlässiger Ende-zu-Ende-DatenstromTCP – zuverlässiger Ende-zu-Ende-Datenstrom
TCP – zuverlässiger Ende-zu-Ende-DatenstromChristoph Lange
 
Previewing OWL Changes and Refactorings Using a Flexible XML Database
Previewing OWL Changes and Refactorings Using a Flexible XML DatabasePreviewing OWL Changes and Refactorings Using a Flexible XML Database
Previewing OWL Changes and Refactorings Using a Flexible XML DatabaseChristoph Lange
 
JOBAD – Interactive Mathematical Documents
JOBAD – Interactive Mathematical DocumentsJOBAD – Interactive Mathematical Documents
JOBAD – Interactive Mathematical DocumentsChristoph Lange
 
Publishing Math Lecture Notes as Linked Data
Publishing Math Lecture Notes as Linked DataPublishing Math Lecture Notes as Linked Data
Publishing Math Lecture Notes as Linked DataChristoph Lange
 
sTeX+ – a System for Flexible Formalization of Linked Data
sTeX+ – a System for Flexible Formalization of Linked DatasTeX+ – a System for Flexible Formalization of Linked Data
sTeX+ – a System for Flexible Formalization of Linked DataChristoph Lange
 
Krextor – An Extensible Framework for Contributing Content Math to the Web of...
Krextor – An Extensible Framework for Contributing Content Math to the Web of...Krextor – An Extensible Framework for Contributing Content Math to the Web of...
Krextor – An Extensible Framework for Contributing Content Math to the Web of...Christoph Lange
 
Mathematical Semantics of Statistical Data
Mathematical Semantics of Statistical DataMathematical Semantics of Statistical Data
Mathematical Semantics of Statistical DataChristoph Lange
 
Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...
Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...
Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...Christoph Lange
 
Processing and Publishing Content Math with JOMDoc and JOBAD
Processing and Publishing Content Math with JOMDoc and JOBADProcessing and Publishing Content Math with JOMDoc and JOBAD
Processing and Publishing Content Math with JOMDoc and JOBADChristoph Lange
 
TNTBase – a Versioned Database for XML (Mathematical) Documents
TNTBase – a Versioned Database for XML (Mathematical) DocumentsTNTBase – a Versioned Database for XML (Mathematical) Documents
TNTBase – a Versioned Database for XML (Mathematical) DocumentsChristoph Lange
 

Más de Christoph Lange (20)

Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...
Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...
Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...
 
Research Careers in Applied Computer Science
Research Careers in Applied Computer ScienceResearch Careers in Applied Computer Science
Research Careers in Applied Computer Science
 
OSCOSS: Opening Scholarly Communication in Social Sciences
OSCOSS: Opening Scholarly Communication in Social SciencesOSCOSS: Opening Scholarly Communication in Social Sciences
OSCOSS: Opening Scholarly Communication in Social Sciences
 
WDAqua ITN – Answering Questions using Web Data
WDAqua ITN – Answering Questions using Web DataWDAqua ITN – Answering Questions using Web Data
WDAqua ITN – Answering Questions using Web Data
 
Machine Support for Interacting with Scientific Publications Improving Inform...
Machine Support for Interacting with Scientific Publications Improving Inform...Machine Support for Interacting with Scientific Publications Improving Inform...
Machine Support for Interacting with Scientific Publications Improving Inform...
 
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...
 
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect match
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect matchLinked Open (Geo)Data and the Distributed Ontology Language – a perfect match
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect match
 
Linking Big Data to Rich Process Descriptions
Linking Big Data to Rich Process DescriptionsLinking Big Data to Rich Process Descriptions
Linking Big Data to Rich Process Descriptions
 
Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...
Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...
Bringing Mathematics To the Web of Data: the Case of the Mathematics Subject ...
 
Semantic Web Technology: The Key to Making Scientific Information Systems Social
Semantic Web Technology: The Key to Making Scientific Information Systems SocialSemantic Web Technology: The Key to Making Scientific Information Systems Social
Semantic Web Technology: The Key to Making Scientific Information Systems Social
 
TCP – zuverlässiger Ende-zu-Ende-Datenstrom
TCP – zuverlässiger Ende-zu-Ende-DatenstromTCP – zuverlässiger Ende-zu-Ende-Datenstrom
TCP – zuverlässiger Ende-zu-Ende-Datenstrom
 
Previewing OWL Changes and Refactorings Using a Flexible XML Database
Previewing OWL Changes and Refactorings Using a Flexible XML DatabasePreviewing OWL Changes and Refactorings Using a Flexible XML Database
Previewing OWL Changes and Refactorings Using a Flexible XML Database
 
JOBAD – Interactive Mathematical Documents
JOBAD – Interactive Mathematical DocumentsJOBAD – Interactive Mathematical Documents
JOBAD – Interactive Mathematical Documents
 
Publishing Math Lecture Notes as Linked Data
Publishing Math Lecture Notes as Linked DataPublishing Math Lecture Notes as Linked Data
Publishing Math Lecture Notes as Linked Data
 
sTeX+ – a System for Flexible Formalization of Linked Data
sTeX+ – a System for Flexible Formalization of Linked DatasTeX+ – a System for Flexible Formalization of Linked Data
sTeX+ – a System for Flexible Formalization of Linked Data
 
Krextor – An Extensible Framework for Contributing Content Math to the Web of...
Krextor – An Extensible Framework for Contributing Content Math to the Web of...Krextor – An Extensible Framework for Contributing Content Math to the Web of...
Krextor – An Extensible Framework for Contributing Content Math to the Web of...
 
Mathematical Semantics of Statistical Data
Mathematical Semantics of Statistical DataMathematical Semantics of Statistical Data
Mathematical Semantics of Statistical Data
 
Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...
Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...
Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web I...
 
Processing and Publishing Content Math with JOMDoc and JOBAD
Processing and Publishing Content Math with JOMDoc and JOBADProcessing and Publishing Content Math with JOMDoc and JOBAD
Processing and Publishing Content Math with JOMDoc and JOBAD
 
TNTBase – a Versioned Database for XML (Mathematical) Documents
TNTBase – a Versioned Database for XML (Mathematical) DocumentsTNTBase – a Versioned Database for XML (Mathematical) Documents
TNTBase – a Versioned Database for XML (Mathematical) Documents
 

Último

2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CVKhem
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 

Último (20)

2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 

Ontology Integration and Interoperability (OntoIOp) – Part 1: The Distributed Ontology Language (DOL)

  • 1. Motivation Standard Example Roadmap Ontology Integration and Interoperability (OntoIOp) – Part 1: The Distributed Ontology Language (DOL) OASIS Symposium @ ISWC 2011 Till Mossakowski, Oliver Kutz, Christoph Lange Universität Bremen, Germany 2011-10-24 Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 1
  • 2. Motivation Standard Example Roadmap Interoperable Assistive Technology Assistive technology increasingly relies on communication among users, between users and their devices, and among these devices. Making such ICT accessible and inclusive is costly or even impossible We aim at more interoperable devices, services accessing these devices, and content delivered by these services . . . at the levels of data and metadata data models and data modelling methods metamodels as well as a meta ontology language Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 2
  • 3. Motivation Standard Example Roadmap The Big Picture of Interoperability Knowledge Infrastructure Service-Oriented Smart Environment Architecture Concepts/Data/Individuals Service Target (Device) Device rabil r ity fo Ontology Service Description Target Description inte ppings rope ma Ontology Language/Logic Service Descr. Language Target Descr. Language Data Concepts/Data/Individuals processes Service accesses Target (Device) Device represented in terms of satisfies conforms to Models Ontology refers to Service Description Target Description written in written in written in Metamodels Ontology Language/Logic Service Descr. Language Target Descr. Language Knowledge Software Agents Hardware For now we focus on the “content”/ “knowledge” column Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 3
  • 4. Motivation Standard Example Roadmap DOL (Distributed Ontology Language) In practical applications, one ontology language and one logic doesn’t suffice to achieve semantic integration and interoperability Part 1 of the OntoIOp standard provides a meta-language (DOL) for: logically heterogeneous ontologies modular ontologies formal and informal links between ontologies/modules annotation and documentation of ontologies DOL will have a formal semantics and concrete XML, RDF and text serializations We leave services and devices to future parts of the standard Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 4
  • 5. Motivation Standard Example Roadmap Why a Standard? DOL is now being developed as ISO Working Item 17347 within ISO TC 37 (Terminology and other language and content resources) / SC 3 (Systems to manage terminology, knowledge and content) by a project team (= us) and experts from ≈ 15 countries In practice, interoperability can only be achieved via standards (cf. Christian Galinski @ OASIS 2009) formulate consensual rules under participation of major stakeholders (here: ontology language communities) improve suitability of products, processes and services facilitate communication reduce complexity (and thus costs) increase quality via certification Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 5
  • 6. Motivation Standard Example Roadmap Requirements I DOL should be generally applicable, open, and extensible DOL shall be a logic-agnostic metalanguage DOL should have user- and machine-readable serializations DOL should have a well-defined formal, logic-based semantics Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 6
  • 7. Motivation Standard Example Roadmap The Onto-Logical Translation Graph OBOOWL OBO 1.4 bRDF EL QL RL RDF PL OWL RDFS DDLOWL RDFSOWL grey: no fixed expressivity green: decidable ontology languages yellow: semi-decidable ECoOWL FOL= orange: some second-order constructs red: full second-order logic CL ECoFOL Rel-S F-logic subinstitution CASL theoroidal subinstitution simultaneously exact and FOLms= model-expansive comorphisms HOL model-expansive comorphisms Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 7
  • 8. Motivation Standard Example Roadmap Requirements II DOL should allow for expressing logically heterogeneous ontologies (and literal reuse of existing modules) DOL should allow for expressing links between ontologies DOL Common Common OWL Logic Logic ontology ontology language interpretation translation import import DOL DOL OWL-XML CLIF ASK-IT Ontologies: DOLCE • Transportation Foundational • Tourism Ontology • Personal Support Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 8
  • 9. Motivation Standard Example Roadmap Requirements III DOL should allow for writing down ontologies and ontology links as implicitly as possible and as explicitly as needed DOL should allow for rich annotation and documentation of ontologies Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 9
  • 10. Motivation Standard Example Roadmap Conformance Criteria DOL should work with any existing or future ontology language (if the latter conforms!) We shall establish the conformance of OWL, Common Logic, RDFS, F-logic, UML class diagrams, and OBO Conformance of a logic (directly or by translation): semantic conformance > entailment conformance Conformance of a serialization: XML conformance > RDF conformance > text conformance > standoff markup conformance Conformance of a document (“Is this document a DOL ontology?”) Conformance of an application: A DOL-conforming application produces DOL-conforming documents! Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 10
  • 11. Motivation Standard Example Roadmap Example: A Heterogeneous Time Ontology logic OWL logic CommonLogic spec TimeOWL = spec TimeCL = TimeRIF then Class: TemporalEntity . (forall (t1 t2) ObjectProperty: before (or (before t1 t2) Domain: TemporalEntity (before t2 t1) Range: TemporalEntity (= t1 t2))) Characteristics: Transitive end end Existing and future DOL features relevant here: logic RIF literal inclusion of existing languages spec TimeRIF = TimeOWL then Group ( modular reuse Forall ?t1 ?t2 ?t3 XML and RDF serializations (before(?t1 ?t3) :- further link types before(?t1 ?t2) before(?t2 ?t3)) documenting translations explicitly end rich annotations and documentation Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 11
  • 12. Motivation Standard Example Roadmap Roadmap Current development is done via mailing list and file repository. Later, we will more and more follow the formal ISO procedures. Now (Oct–Dec 2011): WD (Working Draft) in preparation of the CD (Committee Draft) ballot from Dec 2011: experts review and prepare formal vote on CD; discussions at meetings in Feb 2012 and Jun 2012 Aug 2013: DIS (Draft International Standard) Feb 2015: FDIS (Final Draft International Standard) Aug 2015: IS (International Standard) http://ontolog.cim3.net/cgi-bin/wiki.pl?OntoIOp Mossakowski/Kutz/Lange (OASIS; U. Bremen) OntoIOP Part 1: Distributed Ontology Language (DOL) 2011-10-24 12