SlideShare a Scribd company logo
1 of 20
Download to read offline
ALTER-NET AND SERONTO
  Nic Bertrand on behalf of ALTER-Net I6 Team
OVERVIEW
• Brief   introduction

• Ontology    Creation Process

• Lessons    Learned - What work and what could work better
ALTER-NET
• Network    for Long term ecological research

• Need    to integrate data from many different sources, types...
 etc...

• Metadatainformation catalogue (InfoBase) (What’s being
 measured, where)

• Semantic   framework for data integration (SERONTO)

Socio-Ecological Research and Observation oNTOlogy
SERONTO Components

                                                                        OBOE
                                ISO19115
                                                        Units                        EML

Core Ontology
                     Ecosystems
Domain Ontologies
                                                                                  Biodiversity
Imported/Mapped                                     Core
                                                  ontology

Standards &          Landscape


Ontologies                          Socio-                      InfoBase
                                                                                Taxonomy
                                    Economics


                                                                    External      Common domain
                    Core ontology     Domain ontology                             knowledge space
                                                                   ontologies
Uses of SERONTO

Short term perspective:
 Common model on how ecological and socio-ecological
  observations can be structured for data management
 Agreed common representation on observations across
  different domains
 Agreed common key domain concepts (common
  knowledge space)

Mid-to long term perspective:
 Integrative data model for seamless data access and
  querying across multiple institutions and diverse data
  types (tested, mid-to long term perspective)
SERONTO CORE ONTOLOGY
There are five main aspects to consider:
1. Sampling structure (where does the quot;objectquot; of measurement come from, and how is it selected)
2. Observation on “objectsquot;: what parameter, when (time stamp) and how (method chains)
3. For each parameter precision, scale, units and dimensions are identified
4. Make use of available knowledge collected in the reference catalogue
5. Grouping method for connecting pieces of information which relate to each other
Ontology Creation Process
ROLES AND RESPONSIBILITIES
  Role                                       Who                                      Description

  decision forum                             The whole community (if small) or        decides on proposed ontology solutions for each
                                             delegates of the community for which the issue and ensure the common acceptance in the
                                             ontology is developed                    community




  ontology working group                     formed by members of the community       Carry out the ontology process steps 1 to 3,
                                             who are working on a specific ontology   including the creation of examples (step 5)
                                             aspect




     working group coordinator                  One member of the working group       overview over the group process (WIKI)



     responsible person for ontology issue      One member of the working group       overview over the specific issue, the deadlines
                                                                                      (WIKI)


  ontology experts                           Experts of the community                 Carry out ontology process step 4 to bring all
                                                                                      solutions together formalized in ontologies




  ontology coordinator                       Process experts of the community         overview over whole process, deadlines; facilitates
                                                                                      the process and acts as a process mediator
WORKSHOPS / FACE TO FACE
             Brainstorm
               Conceptual Models
                     Load into Protege
           Create examples / instances
           Document Examples in Wiki
          Document Issues in Wiki
DOMAIN ONTOLOGY
 WORKING GROUPS
              Small Groups
         Work through examples
       to develop domain ontology
           Test Core Ontology
               Raise issues
          Communicate findings
            with other groups
Ontology Creation Process




                                                                            prolonged
                 work in progress         under discussion    voting period voting period
        a1
         WPS                        WPE                      DD           VD           PVD

Issue                                                                                        Decision
WIKI AS A DECISION FORUM
WIKI AS A DECISION FORUM
WIKI AS A DECISION FORUM
WIKI AS A DECISION FORUM
WIKI AS A TOOL TO REFINE DEV PROCESS
TOOL TO REFINE PROCESS
CONCLUSIONS
•   It’s hard!

•   Technical solutions can get in the way

•   Emotions can get in the way

•   Groups / Leadership change

•   Strong coordination is essential

•   A Clear, Open and agreed Process help

•   Well managed Face to Face meetings are key

•   Everybody will eventually contribute -- It takes time and effort
WHAT COULD HAVE WORKED BETTER
• Documentation      of discussions

• Focus
      on short-term application of ontology to demonstrate
 benefits of approach

• Closure     of contentious points

• Develop     examples earlier

• Work    with real data earlier

• Establish   clearer framework for domain ontologies

• Publish
http://www5.umweltbundesamt.at/ALTERNet/index.php?title=Ont:Ontology_Creation_Portal

More Related Content

Similar to Seronto Process

Luciano pr 08-849_ontology_evaluation_methods_metrics
Luciano pr 08-849_ontology_evaluation_methods_metricsLuciano pr 08-849_ontology_evaluation_methods_metrics
Luciano pr 08-849_ontology_evaluation_methods_metricsJoanne Luciano
 
Pal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologiesPal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologiesMustafa Jarrar
 
0810ijdms02
0810ijdms020810ijdms02
0810ijdms02ayu dewi
 
Open hpi semweb-06-part2
Open hpi semweb-06-part2Open hpi semweb-06-part2
Open hpi semweb-06-part2Nadine Ludwig
 
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
 
Applying systems thinking & aligning it to systems engineering
Applying systems thinking & aligning it to systems engineeringApplying systems thinking & aligning it to systems engineering
Applying systems thinking & aligning it to systems engineeringJoseph KAsser
 
Opening Horizons keynote COST Poland 2011
Opening Horizons keynote COST Poland 2011Opening Horizons keynote COST Poland 2011
Opening Horizons keynote COST Poland 2011Totti Könnölä
 
Governance in Science and Technology: Johan Evers
Governance in Science and Technology: Johan EversGovernance in Science and Technology: Johan Evers
Governance in Science and Technology: Johan EversSocial Innovation Exchange
 
EGIforum-Amsterdam-15-Sep2010
EGIforum-Amsterdam-15-Sep2010EGIforum-Amsterdam-15-Sep2010
EGIforum-Amsterdam-15-Sep2010Alex Hardisty
 
Debs2009 Event Processing Languages Tutorial
Debs2009 Event Processing Languages TutorialDebs2009 Event Processing Languages Tutorial
Debs2009 Event Processing Languages TutorialOpher Etzion
 
Pal gov.tutorial4.session1 2.whatisontology
Pal gov.tutorial4.session1 2.whatisontologyPal gov.tutorial4.session1 2.whatisontology
Pal gov.tutorial4.session1 2.whatisontologyMustafa Jarrar
 
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
 
Ontological realism as a strategy for integrating ontologies
Ontological realism as a strategy for integrating ontologiesOntological realism as a strategy for integrating ontologies
Ontological realism as a strategy for integrating ontologiesBarry Smith
 
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet OntologyKOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet OntologyVassilis Protonotarios
 

Similar to Seronto Process (20)

Luciano pr 08-849_ontology_evaluation_methods_metrics
Luciano pr 08-849_ontology_evaluation_methods_metricsLuciano pr 08-849_ontology_evaluation_methods_metrics
Luciano pr 08-849_ontology_evaluation_methods_metrics
 
Pal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologiesPal gov.tutorial4.session8 2.stepwisemethodologies
Pal gov.tutorial4.session8 2.stepwisemethodologies
 
0810ijdms02
0810ijdms020810ijdms02
0810ijdms02
 
Open hpi semweb-06-part2
Open hpi semweb-06-part2Open hpi semweb-06-part2
Open hpi semweb-06-part2
 
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...
 
Applying systems thinking & aligning it to systems engineering
Applying systems thinking & aligning it to systems engineeringApplying systems thinking & aligning it to systems engineering
Applying systems thinking & aligning it to systems engineering
 
Opening Horizons keynote COST Poland 2011
Opening Horizons keynote COST Poland 2011Opening Horizons keynote COST Poland 2011
Opening Horizons keynote COST Poland 2011
 
Governance in Science and Technology: Johan Evers
Governance in Science and Technology: Johan EversGovernance in Science and Technology: Johan Evers
Governance in Science and Technology: Johan Evers
 
Varieties of Self-Awareness and Their Uses in Natural and Artificial Systems ...
Varieties of Self-Awareness and Their Uses in Natural and Artificial Systems ...Varieties of Self-Awareness and Their Uses in Natural and Artificial Systems ...
Varieties of Self-Awareness and Their Uses in Natural and Artificial Systems ...
 
EGIforum-Amsterdam-15-Sep2010
EGIforum-Amsterdam-15-Sep2010EGIforum-Amsterdam-15-Sep2010
EGIforum-Amsterdam-15-Sep2010
 
Debs2009 Event Processing Languages Tutorial
Debs2009 Event Processing Languages TutorialDebs2009 Event Processing Languages Tutorial
Debs2009 Event Processing Languages Tutorial
 
Anna Karenina in Ontology Matching
Anna Karenina in Ontology MatchingAnna Karenina in Ontology Matching
Anna Karenina in Ontology Matching
 
Apollon Overview Pieter Ballon
Apollon Overview Pieter BallonApollon Overview Pieter Ballon
Apollon Overview Pieter Ballon
 
Pal gov.tutorial4.session1 2.whatisontology
Pal gov.tutorial4.session1 2.whatisontologyPal gov.tutorial4.session1 2.whatisontology
Pal gov.tutorial4.session1 2.whatisontology
 
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...
 
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
 
Ontological realism as a strategy for integrating ontologies
Ontological realism as a strategy for integrating ontologiesOntological realism as a strategy for integrating ontologies
Ontological realism as a strategy for integrating ontologies
 
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet OntologyKOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
 

Recently uploaded

Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
[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
 
#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
 
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
 
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
 
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
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
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
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
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
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
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
 

Recently uploaded (20)

Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
[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
 
#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
 
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
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 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
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
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
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
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
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
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
 

Seronto Process

  • 1. ALTER-NET AND SERONTO Nic Bertrand on behalf of ALTER-Net I6 Team
  • 2. OVERVIEW • Brief introduction • Ontology Creation Process • Lessons Learned - What work and what could work better
  • 3. ALTER-NET • Network for Long term ecological research • Need to integrate data from many different sources, types... etc... • Metadatainformation catalogue (InfoBase) (What’s being measured, where) • Semantic framework for data integration (SERONTO) Socio-Ecological Research and Observation oNTOlogy
  • 4. SERONTO Components OBOE ISO19115 Units EML Core Ontology Ecosystems Domain Ontologies Biodiversity Imported/Mapped Core ontology Standards & Landscape Ontologies Socio- InfoBase Taxonomy Economics External Common domain Core ontology Domain ontology knowledge space ontologies
  • 5. Uses of SERONTO Short term perspective:  Common model on how ecological and socio-ecological observations can be structured for data management  Agreed common representation on observations across different domains  Agreed common key domain concepts (common knowledge space) Mid-to long term perspective:  Integrative data model for seamless data access and querying across multiple institutions and diverse data types (tested, mid-to long term perspective)
  • 6. SERONTO CORE ONTOLOGY There are five main aspects to consider: 1. Sampling structure (where does the quot;objectquot; of measurement come from, and how is it selected) 2. Observation on “objectsquot;: what parameter, when (time stamp) and how (method chains) 3. For each parameter precision, scale, units and dimensions are identified 4. Make use of available knowledge collected in the reference catalogue 5. Grouping method for connecting pieces of information which relate to each other
  • 8. ROLES AND RESPONSIBILITIES Role Who Description decision forum The whole community (if small) or decides on proposed ontology solutions for each delegates of the community for which the issue and ensure the common acceptance in the ontology is developed community ontology working group formed by members of the community Carry out the ontology process steps 1 to 3, who are working on a specific ontology including the creation of examples (step 5) aspect working group coordinator One member of the working group overview over the group process (WIKI) responsible person for ontology issue One member of the working group overview over the specific issue, the deadlines (WIKI) ontology experts Experts of the community Carry out ontology process step 4 to bring all solutions together formalized in ontologies ontology coordinator Process experts of the community overview over whole process, deadlines; facilitates the process and acts as a process mediator
  • 9. WORKSHOPS / FACE TO FACE Brainstorm Conceptual Models Load into Protege Create examples / instances Document Examples in Wiki Document Issues in Wiki
  • 10. DOMAIN ONTOLOGY WORKING GROUPS Small Groups Work through examples to develop domain ontology Test Core Ontology Raise issues Communicate findings with other groups
  • 11. Ontology Creation Process prolonged work in progress under discussion voting period voting period a1 WPS WPE DD VD PVD Issue Decision
  • 12. WIKI AS A DECISION FORUM
  • 13. WIKI AS A DECISION FORUM
  • 14. WIKI AS A DECISION FORUM
  • 15. WIKI AS A DECISION FORUM
  • 16. WIKI AS A TOOL TO REFINE DEV PROCESS
  • 17. TOOL TO REFINE PROCESS
  • 18. CONCLUSIONS • It’s hard! • Technical solutions can get in the way • Emotions can get in the way • Groups / Leadership change • Strong coordination is essential • A Clear, Open and agreed Process help • Well managed Face to Face meetings are key • Everybody will eventually contribute -- It takes time and effort
  • 19. WHAT COULD HAVE WORKED BETTER • Documentation of discussions • Focus on short-term application of ontology to demonstrate benefits of approach • Closure of contentious points • Develop examples earlier • Work with real data earlier • Establish clearer framework for domain ontologies • Publish