SlideShare una empresa de Scribd logo
1 de 11
Authoring OWL 2 ontologies with the 
TEX-OWL syntax 
Mauro Dragoni 
Fondazione Bruno Kessler (FBK), Shape and Evolve Living Knowledge Unit (SHELL) 
https://shell.fbk.eu/index.php/Mauro_Dragoni - dragoni@fbk.eu 
work done in collaboration with 
Marco Rospocher1, Matteo Matassoni2, Paolo Bouquet2 
1Fondazione Bruno Kessler, Trento 
2University of Trento 
OWLED 2014 – Riva del Garda, Trento 
October, 18th 2014
Outline 
1. The Rationale Behind 
2. The Syntax and Implementation 
3. Evaluation
The Rationale Behind 
 Find a way for writing ontology quickly 
 Using syntaxes XML-like are verbose and hard to write by hand 
 Avoiding the overhead of learning authoring tools functionalities and using 
them
Syntax 
 Why a LaTeX-like syntax? 
 Overcome known problems and limits based on the experience of the 
previous attempt 
 Syntax document available at 
https://github.com/matteomatassoni/TexOwl/blob/master/docs/grammar.pdf 
 Aligned as much as possible with OWL specification
Syntax Example 
ns <http://www.mydomain.org/african#> 
begin{ontology}[<http://www.mydomain.org/african>] 
% Animals form a class 
animal c 
% Plants form a class disjoint from animals 
animal cdisjoint plant 
% Trees are a type of plant 
tree cisa plant 
% Branches are parts of trees 
branch cisa oforall{is_part_of}{tree} 
% Leaves are parts of branches 
leaf cisa oforall{is_part_of}{branch} 
% Herbivores are exactly those animals that eat only plants or parts of plants 
herbivore ceq (animal cand oforall{eats}{(plant cor oforall{is_part_of}{plant})}) 
% Carnivores are exactly those animals that eat animals 
carnivore ceq (animal cand oexists{eats}{animal}) 
% Giraffes are herbivores, and they eat only leaves 
giraffe cisa (herbivore cand oforall{eats}{leaf}) 
% Lions are animals that eat only herbivores 
lion cisa (animal cand oforall{eats}{herbivore}) 
% Tasty plants are plants that are eaten both by herbivores and carnivores 
tasty_plant cisa candof{plant,oexists{eaten_by}{herbivore},oexists{eaten_by}{carnivore}} 
% eats and eaten_by are inverse of each other 
eaten_by oinv eats 
% Everything that eats is an animal 
eats odomain animal 
end{ontology}
Using TeXOwl in Tools 
 Built on top of the OWL API Library using JavaCC 
 Parser + Renderer 
 Source code available at: http://github.com/matax87/TexOwl/
Evaluation - 1 
 Evaluated the suitability, easiness, and comprehensiveness of the syntax 
 Two questionnaires have been designed (http://goo.gl/Cjpqtg): 
• intuitiveness, conciseness, and understandability have been measured on 10 
different examples 
• usability of the new syntax for authoring a small ontology
Evaluation - 2 
Syntax name Intuitiveness Conciseness 
LaTeX-like 6.5 9.7 
Manchester 6.8 2.7 
Functional 4.8 5.3 
Turtle 1.1 1.0 
OWL/XML 1.3 0.1 
RDF/XML 0.4 0.0 
 Average comprehensibility: 3.75 / 5.00
Evaluation - 3 
 10 axioms about the African Wildlife domain 
 3 questions: 
• How difficult was the formalization task? 
3.5 
• Is the syntax easy to remember? 
3.17 
• Compare the use of this syntax to others syntaxes that you previously used for 
authoring ontology 
3.67
Next steps? 
Visit us at the Poster & Demo session of ISWC 2014 for testing our 
demo and for discussing about possible improvements!!! 
or 
try it online at: http://dkmlab.fbk.eu:8080/converter-webapp/ 
and maybe… 
in the future our work will be part of the OWL API Library… 
Mauro Dragoni 
https://shell.fbk.eu/index.php/Mauro_Dragoni 
dragoni@fbk.eu

Más contenido relacionado

Similar a Authoring OWL 2 ontologies with the TEX-OWL syntax

Cross-lingual event-mining using wordnet as a shared knowledge interface
Cross-lingual event-mining using wordnet as a shared knowledge interfaceCross-lingual event-mining using wordnet as a shared knowledge interface
Cross-lingual event-mining using wordnet as a shared knowledge interfacepathsproject
 
WEB ONTOLOGY LANGUAGE: OWL
WEB ONTOLOGY LANGUAGE: OWLWEB ONTOLOGY LANGUAGE: OWL
WEB ONTOLOGY LANGUAGE: OWLTochukwu Udeh
 
Venkatesan bosc2010 onto-toolkit
Venkatesan bosc2010 onto-toolkitVenkatesan bosc2010 onto-toolkit
Venkatesan bosc2010 onto-toolkitBOSC 2010
 
247th ACS Meeting: Experiment Markup Language (ExptML)
247th ACS Meeting: Experiment Markup Language (ExptML)247th ACS Meeting: Experiment Markup Language (ExptML)
247th ACS Meeting: Experiment Markup Language (ExptML)Stuart Chalk
 
Question answer template
Question answer templateQuestion answer template
Question answer templateThanuw Chaks
 
Collaborative Ontology Building with Wiki@nt
Collaborative Ontology Building with Wiki@ntCollaborative Ontology Building with Wiki@nt
Collaborative Ontology Building with Wiki@ntJie Bao
 
An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...
An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...
An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...dannyijwest
 
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEWONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEWijait
 
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW ijait
 
SWSN UNIT-3.pptx we can information about swsn professional
SWSN UNIT-3.pptx we can information about swsn professionalSWSN UNIT-3.pptx we can information about swsn professional
SWSN UNIT-3.pptx we can information about swsn professionalgowthamnaidu0986
 
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...IOSR Journals
 
OEG tools for supporting Ontology Engineering
OEG tools for supporting Ontology EngineeringOEG tools for supporting Ontology Engineering
OEG tools for supporting Ontology Engineeringdgarijo
 
OEG-Tools for supporting Ontology Engineering
OEG-Tools for supporting  Ontology EngineeringOEG-Tools for supporting  Ontology Engineering
OEG-Tools for supporting Ontology EngineeringIdafen Santana Pérez
 
OEG-Tools for supporting Ontology Engineering
OEG-Tools for supporting Ontology EngineeringOEG-Tools for supporting Ontology Engineering
OEG-Tools for supporting Ontology EngineeringMaría Poveda Villalón
 
Building an Ontology in Educational Domain Case Study for the University of P...
Building an Ontology in Educational Domain Case Study for the University of P...Building an Ontology in Educational Domain Case Study for the University of P...
Building an Ontology in Educational Domain Case Study for the University of P...IJRES Journal
 
Taxonomy extraction from automotive natural language requirements using unsup...
Taxonomy extraction from automotive natural language requirements using unsup...Taxonomy extraction from automotive natural language requirements using unsup...
Taxonomy extraction from automotive natural language requirements using unsup...ijnlc
 
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...Association Rule Mining Based Extraction of Semantic Relations Using Markov L...
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...IJwest
 

Similar a Authoring OWL 2 ontologies with the TEX-OWL syntax (20)

Knowledge Organization Systems (KOS): Management of Classification Systems in...
Knowledge Organization Systems (KOS): Management of Classification Systems in...Knowledge Organization Systems (KOS): Management of Classification Systems in...
Knowledge Organization Systems (KOS): Management of Classification Systems in...
 
Cross-lingual event-mining using wordnet as a shared knowledge interface
Cross-lingual event-mining using wordnet as a shared knowledge interfaceCross-lingual event-mining using wordnet as a shared knowledge interface
Cross-lingual event-mining using wordnet as a shared knowledge interface
 
WEB ONTOLOGY LANGUAGE: OWL
WEB ONTOLOGY LANGUAGE: OWLWEB ONTOLOGY LANGUAGE: OWL
WEB ONTOLOGY LANGUAGE: OWL
 
Owl assignment udeh
Owl assignment udehOwl assignment udeh
Owl assignment udeh
 
Venkatesan bosc2010 onto-toolkit
Venkatesan bosc2010 onto-toolkitVenkatesan bosc2010 onto-toolkit
Venkatesan bosc2010 onto-toolkit
 
247th ACS Meeting: Experiment Markup Language (ExptML)
247th ACS Meeting: Experiment Markup Language (ExptML)247th ACS Meeting: Experiment Markup Language (ExptML)
247th ACS Meeting: Experiment Markup Language (ExptML)
 
Question answer template
Question answer templateQuestion answer template
Question answer template
 
Collaborative Ontology Building with Wiki@nt
Collaborative Ontology Building with Wiki@ntCollaborative Ontology Building with Wiki@nt
Collaborative Ontology Building with Wiki@nt
 
An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...
An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...
An Approach to Owl Concept Extraction and Integration Across Multiple Ontolog...
 
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEWONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
 
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
ONTOLOGY VISUALIZATION PROTÉGÉ TOOLS – A REVIEW
 
AICOL2015_paper_16
AICOL2015_paper_16AICOL2015_paper_16
AICOL2015_paper_16
 
SWSN UNIT-3.pptx we can information about swsn professional
SWSN UNIT-3.pptx we can information about swsn professionalSWSN UNIT-3.pptx we can information about swsn professional
SWSN UNIT-3.pptx we can information about swsn professional
 
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
 
OEG tools for supporting Ontology Engineering
OEG tools for supporting Ontology EngineeringOEG tools for supporting Ontology Engineering
OEG tools for supporting Ontology Engineering
 
OEG-Tools for supporting Ontology Engineering
OEG-Tools for supporting  Ontology EngineeringOEG-Tools for supporting  Ontology Engineering
OEG-Tools for supporting Ontology Engineering
 
OEG-Tools for supporting Ontology Engineering
OEG-Tools for supporting Ontology EngineeringOEG-Tools for supporting Ontology Engineering
OEG-Tools for supporting Ontology Engineering
 
Building an Ontology in Educational Domain Case Study for the University of P...
Building an Ontology in Educational Domain Case Study for the University of P...Building an Ontology in Educational Domain Case Study for the University of P...
Building an Ontology in Educational Domain Case Study for the University of P...
 
Taxonomy extraction from automotive natural language requirements using unsup...
Taxonomy extraction from automotive natural language requirements using unsup...Taxonomy extraction from automotive natural language requirements using unsup...
Taxonomy extraction from automotive natural language requirements using unsup...
 
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...Association Rule Mining Based Extraction of Semantic Relations Using Markov L...
Association Rule Mining Based Extraction of Semantic Relations Using Markov L...
 

Más de Mauro Dragoni

Keynote given at ISWC 2019 Semantic Management for Healthcare Workshop
Keynote given at ISWC 2019 Semantic Management for Healthcare WorkshopKeynote given at ISWC 2019 Semantic Management for Healthcare Workshop
Keynote given at ISWC 2019 Semantic Management for Healthcare WorkshopMauro Dragoni
 
Exploiting Multilinguality For Creating Mappings Between Thesauri
Exploiting Multilinguality For Creating Mappings Between ThesauriExploiting Multilinguality For Creating Mappings Between Thesauri
Exploiting Multilinguality For Creating Mappings Between ThesauriMauro Dragoni
 
A Fuzzy Approach For Multi-Domain Sentiment Analysis
A Fuzzy Approach For Multi-Domain Sentiment AnalysisA Fuzzy Approach For Multi-Domain Sentiment Analysis
A Fuzzy Approach For Multi-Domain Sentiment AnalysisMauro Dragoni
 
Using Semantic and Domain-based Information in CLIR Systems
Using Semantic and Domain-based Information in CLIR SystemsUsing Semantic and Domain-based Information in CLIR Systems
Using Semantic and Domain-based Information in CLIR SystemsMauro Dragoni
 
Multilingual Knowledge Organization Systems Management: Best Practices
Multilingual Knowledge Organization Systems Management: Best PracticesMultilingual Knowledge Organization Systems Management: Best Practices
Multilingual Knowledge Organization Systems Management: Best PracticesMauro Dragoni
 
Collaborative Modeling of Processes and Ontologies with MoKi
Collaborative Modeling of Processes and Ontologies with MoKiCollaborative Modeling of Processes and Ontologies with MoKi
Collaborative Modeling of Processes and Ontologies with MoKiMauro Dragoni
 

Más de Mauro Dragoni (6)

Keynote given at ISWC 2019 Semantic Management for Healthcare Workshop
Keynote given at ISWC 2019 Semantic Management for Healthcare WorkshopKeynote given at ISWC 2019 Semantic Management for Healthcare Workshop
Keynote given at ISWC 2019 Semantic Management for Healthcare Workshop
 
Exploiting Multilinguality For Creating Mappings Between Thesauri
Exploiting Multilinguality For Creating Mappings Between ThesauriExploiting Multilinguality For Creating Mappings Between Thesauri
Exploiting Multilinguality For Creating Mappings Between Thesauri
 
A Fuzzy Approach For Multi-Domain Sentiment Analysis
A Fuzzy Approach For Multi-Domain Sentiment AnalysisA Fuzzy Approach For Multi-Domain Sentiment Analysis
A Fuzzy Approach For Multi-Domain Sentiment Analysis
 
Using Semantic and Domain-based Information in CLIR Systems
Using Semantic and Domain-based Information in CLIR SystemsUsing Semantic and Domain-based Information in CLIR Systems
Using Semantic and Domain-based Information in CLIR Systems
 
Multilingual Knowledge Organization Systems Management: Best Practices
Multilingual Knowledge Organization Systems Management: Best PracticesMultilingual Knowledge Organization Systems Management: Best Practices
Multilingual Knowledge Organization Systems Management: Best Practices
 
Collaborative Modeling of Processes and Ontologies with MoKi
Collaborative Modeling of Processes and Ontologies with MoKiCollaborative Modeling of Processes and Ontologies with MoKi
Collaborative Modeling of Processes and Ontologies with MoKi
 

Último

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
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
[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
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
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
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersThousandEyes
 
Google AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAGGoogle AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAGSujit Pal
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
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
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 

Último (20)

Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
[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
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
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
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
 
Google AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAGGoogle AI Hackathon: LLM based Evaluator for RAG
Google AI Hackathon: LLM based Evaluator for RAG
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
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
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 

Authoring OWL 2 ontologies with the TEX-OWL syntax

  • 1. Authoring OWL 2 ontologies with the TEX-OWL syntax Mauro Dragoni Fondazione Bruno Kessler (FBK), Shape and Evolve Living Knowledge Unit (SHELL) https://shell.fbk.eu/index.php/Mauro_Dragoni - dragoni@fbk.eu work done in collaboration with Marco Rospocher1, Matteo Matassoni2, Paolo Bouquet2 1Fondazione Bruno Kessler, Trento 2University of Trento OWLED 2014 – Riva del Garda, Trento October, 18th 2014
  • 2. Outline 1. The Rationale Behind 2. The Syntax and Implementation 3. Evaluation
  • 3. The Rationale Behind  Find a way for writing ontology quickly  Using syntaxes XML-like are verbose and hard to write by hand  Avoiding the overhead of learning authoring tools functionalities and using them
  • 4. Syntax  Why a LaTeX-like syntax?  Overcome known problems and limits based on the experience of the previous attempt  Syntax document available at https://github.com/matteomatassoni/TexOwl/blob/master/docs/grammar.pdf  Aligned as much as possible with OWL specification
  • 5. Syntax Example ns <http://www.mydomain.org/african#> begin{ontology}[<http://www.mydomain.org/african>] % Animals form a class animal c % Plants form a class disjoint from animals animal cdisjoint plant % Trees are a type of plant tree cisa plant % Branches are parts of trees branch cisa oforall{is_part_of}{tree} % Leaves are parts of branches leaf cisa oforall{is_part_of}{branch} % Herbivores are exactly those animals that eat only plants or parts of plants herbivore ceq (animal cand oforall{eats}{(plant cor oforall{is_part_of}{plant})}) % Carnivores are exactly those animals that eat animals carnivore ceq (animal cand oexists{eats}{animal}) % Giraffes are herbivores, and they eat only leaves giraffe cisa (herbivore cand oforall{eats}{leaf}) % Lions are animals that eat only herbivores lion cisa (animal cand oforall{eats}{herbivore}) % Tasty plants are plants that are eaten both by herbivores and carnivores tasty_plant cisa candof{plant,oexists{eaten_by}{herbivore},oexists{eaten_by}{carnivore}} % eats and eaten_by are inverse of each other eaten_by oinv eats % Everything that eats is an animal eats odomain animal end{ontology}
  • 6. Using TeXOwl in Tools  Built on top of the OWL API Library using JavaCC  Parser + Renderer  Source code available at: http://github.com/matax87/TexOwl/
  • 7. Evaluation - 1  Evaluated the suitability, easiness, and comprehensiveness of the syntax  Two questionnaires have been designed (http://goo.gl/Cjpqtg): • intuitiveness, conciseness, and understandability have been measured on 10 different examples • usability of the new syntax for authoring a small ontology
  • 8. Evaluation - 2 Syntax name Intuitiveness Conciseness LaTeX-like 6.5 9.7 Manchester 6.8 2.7 Functional 4.8 5.3 Turtle 1.1 1.0 OWL/XML 1.3 0.1 RDF/XML 0.4 0.0  Average comprehensibility: 3.75 / 5.00
  • 9. Evaluation - 3  10 axioms about the African Wildlife domain  3 questions: • How difficult was the formalization task? 3.5 • Is the syntax easy to remember? 3.17 • Compare the use of this syntax to others syntaxes that you previously used for authoring ontology 3.67
  • 10. Next steps? Visit us at the Poster & Demo session of ISWC 2014 for testing our demo and for discussing about possible improvements!!! or try it online at: http://dkmlab.fbk.eu:8080/converter-webapp/ and maybe… in the future our work will be part of the OWL API Library… 

Notas del editor

  1. and sometimes tools do not fully support the OWL standard