Webinar@AIMS, 21/2/2014

Knowledge Organization Systems (KOS):

Management of Classification Systems
in the case of Organi...
Contents of the presentation
 (Short)

introduction to KOS
 Open source KOS management tools
 The MoKi tool
 The Organ...
Introduction to KOS
About KOS
KOS = Knowledge Organization Systems
◦ a generic term used in knowledge
organization including the following typ...
Focusing on ontologies


Ontology: Explicit formal specification
of terms in a domain AND the relations
among them
Tree-view of an ontology
But why use KOSs?
A standardized mean for referring to
the same concept using a unique
name
 A mean for the classificatio...
Open Source KOS Management
tools (indicative list)
Talking about KOS
management


Manage entries
◦ Add, revise, delete

Translate entries
 Change relationships
 Import ex...
Tools: VocBench
available at
http://vocbench.uniroma2.it/
 developed by FAO and its partners;
 a web-based, multilingual...
VocBench screenshot
Tools: Protégé







Available at http://protege.stanford.edu
developed by the Stanford Center for
Biomedical Inform...
Protégé screenshot
Tools: TemaTres
Available at
http://www.vocabularyserver.com
 a tool for the development &
management of









c...
TemaTres screenshot
Tools: Neologism





Available at: http://neologism.deri.ie/
developed by DERI (Digital Enterprise
Research Institute...
Neologism screenshot
The MoKi tool
MoKi:
the Enterprise Modelling WiKi


Available at
https://moki.fbk.eu/website/index.php

Developed by FBK, Italy
 Suppo...
MoKi screenshot (2011)
MoKi evolution


During the Organic.Lingua ICT/PSP
project:
◦ Multilinguality options
 Integration of three machine tran...
The Organic.Edunet ontology
The Organic.Edunet ontology
a conceptual model useful for
classifying learning materials on the
Organic Agriculture (OA) a...
The Organic.Edunet ontology


Currently consists of 381 concepts
translated in 18 languages
Translating the OE ontology
(2010)
Building the Organic.Edunet
ontology (1/3)
OA & AE domain experts
elaborated a list including all the
relevant terms in th...
Building the Organic.Edunet
ontology (2/3)
3.

4.
5.

Domain experts added agreed,
unambiguous definitions for the
terms, ...
Building the Organic.Edunet
ontology (3/3)
Evolution of the Organic.Edunet
ontology using MoKi
Time for evolution


Organic.Lingua ICT-PSP project (20112014)
◦ Aims to enhance the multilinguality options
of the Organ...
The requirements


Multilinguality
◦ Facilitate the translation processes
 Avoid using spreadsheets for translations
 U...
The process (1/2)


Formation of teams
◦ Ontology experts / knowledge engineers
◦ Domain experts
◦ Language experts



D...
The process (2/2)


Development of scenarios
◦ A number of scenarios was developed per
task & with specific deadlines


...
Discussions in MoKi
Concept management


Refers to
 Editing concept
 Renaming concept
 Deleting concept
Introduction of new concepts


Ontology suggestion service





Verified Keywords,
User (modified) Keywords,
(Automat...
Translation of concepts
(2013)
Mapping to AGROVOC
Exposure of concepts
Ontology service = use of API
http://wiki.organiclingua.eu/APIs#Ontology_Service_API


◦ Publish/exp...
Case study: the use of the
ontology service API
OE ontology evolution in
numbers
Next steps
Next steps in the ontology
evolution (1/2)


Further work on the concepts
◦
◦
◦
◦

Introduction of new concepts
Refinemen...
Next steps in the ontology
evolution (2/2)


Publication of ontology as linked data
◦ Definition of a namespace
◦ Ensure ...
Acknowledgements
The Organic.Edunet ontology was
developed in the context of the
Organic.Edunet project under the
eContent...
www.organic-lingua.eu

Contact me at:
vprot@agroknow.gr
Thank you!
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KOS Management - The case of the Organic.Edunet Ontology

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Presentation made in the context of the FAO AIMS Webinar titled “Knowledge Organization Systems (KOS): Management of Classification Systems in the case of Organic.Edunet” (http://aims.fao.org/community/blogs/new-webinaraims-knowledge-organization-systems-kos-management-classification-systems)

21/2/2014

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  • Image source: http://en.wikipedia.org/wiki/File:TopicMapKeyConcepts2.PNG
  • Classification based on http://www.clir.org/pubs/reports/pub91/1knowledge.html
  • Image taken from Plant Ontology
  • Source: http://www.slideshare.net/Agro-Know/managing-multilingual-vocabularies-and-ontologies
  • KOS Management - The case of the Organic.Edunet Ontology

    1. 1. Webinar@AIMS, 21/2/2014 Knowledge Organization Systems (KOS): Management of Classification Systems in the case of Organic.Edunet” Vassilis Protonotarios, Agricultural Biotechnologist, PhD Agro-Know, Greece / University of Alcalá, Spain
    2. 2. Contents of the presentation  (Short) introduction to KOS  Open source KOS management tools  The MoKi tool  The Organic.Edunet ontology  Using MoKi for managing the Organic.Edunet ontology  Next steps
    3. 3. Introduction to KOS
    4. 4. About KOS KOS = Knowledge Organization Systems ◦ a generic term used in knowledge organization including the following types ◦ Term lists  Authority Files  Glossaries  Dictionaries • Relationship Lists • Thesauri • Semantic Networks • Topic maps • ◦ Classifications & Categories Ontologies  Subject Headings
    5. 5. Focusing on ontologies  Ontology: Explicit formal specification of terms in a domain AND the relations among them
    6. 6. Tree-view of an ontology
    7. 7. But why use KOSs? A standardized mean for referring to the same concept using a unique name  A mean for the classification of different resources in a domain  …and of course the backbone of linking heterogeneous data sources 
    8. 8. Open Source KOS Management tools (indicative list)
    9. 9. Talking about KOS management  Manage entries ◦ Add, revise, delete Translate entries  Change relationships  Import existing lists of terms/concepts  Export the lists as OWL/SKOS 
    10. 10. Tools: VocBench available at http://vocbench.uniroma2.it/  developed by FAO and its partners;  a web-based, multilingual, editing and workflow tool;  manages thesauri, authority lists and glossaries using SKOS;  facilitates the collaborative editing of multilingual terminology and semantic concept information. 
    11. 11. VocBench screenshot
    12. 12. Tools: Protégé      Available at http://protege.stanford.edu developed by the Stanford Center for Biomedical Informatics Research at the Stanford University School of Medicine; ontology editor and knowledge-base framework; supports modeling ontologies via a web client or a desktop client; Protégé ontologies can be developed in a variety of formats including OWL, RDF(S), and XML Schema
    13. 13. Protégé screenshot
    14. 14. Tools: TemaTres Available at http://www.vocabularyserver.com  a tool for the development & management of       controlled vocabularies, thesauri, taxonomies other types of formal representations of knowledge ensures consistency & integrity of data and relationships between terms
    15. 15. TemaTres screenshot
    16. 16. Tools: Neologism     Available at: http://neologism.deri.ie/ developed by DERI (Digital Enterprise Research Institute), Ireland a vocabulary publishing platform for the Web of Data focuses on ease of use and compatibility with Linked Data principles ◦ facilitates the creation of RDF classes and properties   supports the RDFS standard, and a part of OWL Is NOT ontology/SKOS editor and does not support multilingual labels
    17. 17. Neologism screenshot
    18. 18. The MoKi tool
    19. 19. MoKi: the Enterprise Modelling WiKi  Available at https://moki.fbk.eu/website/index.php Developed by FBK, Italy  Supports the construction of integrated domain & process models  Easy editing of a wiki page by means of forms  Automatic import and export in OWL and BPMN 
    20. 20. MoKi screenshot (2011)
    21. 21. MoKi evolution  During the Organic.Lingua ICT/PSP project: ◦ Multilinguality options  Integration of three machine translation services ◦ Ontology enrichment services  Automatically suggests new concepts for the ontology ◦ Mapping component  Used for mapping the OE ontology to AGROVOC ◦ Collaboration options  Decisions made on discussions ◦ Ontology service  Exposure of ontology through REST API
    22. 22. The Organic.Edunet ontology
    23. 23. The Organic.Edunet ontology a conceptual model useful for classifying learning materials on the Organic Agriculture (OA) and Agroecology (AE) domain  Developed in the context of the Organic.Edunet eContentPlus project  Used by Organic.Edunet for the classification of educational resources 
    24. 24. The Organic.Edunet ontology  Currently consists of 381 concepts translated in 18 languages
    25. 25. Translating the OE ontology (2010)
    26. 26. Building the Organic.Edunet ontology (1/3) OA & AE domain experts elaborated a list including all the relevant terms in the domain of OA & AE Using the list of terms as input, domain experts identified sub-domains with the aim of dividing the original list into microthesauri 1. 2. ◦ with the help of librarians and guidance from the ontology experts
    27. 27. Building the Organic.Edunet ontology (2/3) 3. 4. 5. Domain experts added agreed, unambiguous definitions for the terms, thus producing a “concept list” Ontology experts developed an initial ontology from the concept list The ontology produced in the previous step was evaluated making use of upper ontologies
    28. 28. Building the Organic.Edunet ontology (3/3)
    29. 29. Evolution of the Organic.Edunet ontology using MoKi
    30. 30. Time for evolution  Organic.Lingua ICT-PSP project (20112014) ◦ Aims to enhance the multilinguality options of the Organic.Edunet Web portal ◦ provided the opportunity for updating & revising the Organic.Edunet ontology
    31. 31. The requirements  Multilinguality ◦ Facilitate the translation processes  Avoid using spreadsheets for translations  Use of machine translation tools ◦ Automate process  Collaborative work ◦ Use web-based tool ◦ Enable discussions for concept revisions ◦ Enable different translations to take place at the same time  Exposure ◦ Automatic exposure of the ontology through API
    32. 32. The process (1/2)  Formation of teams ◦ Ontology experts / knowledge engineers ◦ Domain experts ◦ Language experts  Definition of tasks ◦ Deprecation of less-frequently used concepts ◦ Refinement of most widely-used concepts ◦ Addition of new concepts ◦ Translation of concepts
    33. 33. The process (2/2)  Development of scenarios ◦ A number of scenarios was developed per task & with specific deadlines  Collaborative work ◦ Discussions in MoKi ◦ Evolution based on discussions ◦ Validation of revisions by experts
    34. 34. Discussions in MoKi
    35. 35. Concept management  Refers to  Editing concept  Renaming concept  Deleting concept
    36. 36. Introduction of new concepts  Ontology suggestion service     Verified Keywords, User (modified) Keywords, (Automatically) Extracted Keywords and Search-Query-Logs
    37. 37. Translation of concepts (2013)
    38. 38. Mapping to AGROVOC
    39. 39. Exposure of concepts Ontology service = use of API http://wiki.organiclingua.eu/APIs#Ontology_Service_API  ◦ Publish/expose the ontology ◦ Enable up-to-date publishing  Two different interfaces: ◦ Linked Open Data (LOD): Provides data in SKOS format ◦ RESTful RDF: Exposes data in OWL2 or LOD format
    40. 40. Case study: the use of the ontology service API
    41. 41. OE ontology evolution in numbers
    42. 42. Next steps
    43. 43. Next steps in the ontology evolution (1/2)  Further work on the concepts ◦ ◦ ◦ ◦ Introduction of new concepts Refinement of existing ones Deprecation of existing ones Translation of concepts in additional languages ◦ Mapping of the ontology to additional ones
    44. 44. Next steps in the ontology evolution (2/2)  Publication of ontology as linked data ◦ Definition of a namespace ◦ Ensure compliance with existing standards  Link ontology with other related ones ◦ Already linked to AGROVOC
    45. 45. Acknowledgements The Organic.Edunet ontology was developed in the context of the Organic.Edunet project under the eContentPlus Programme  Parts of the work described in this presentation were partially funded by the Organic.Lingua project under the ICT Policy Support Programme 
    46. 46. www.organic-lingua.eu Contact me at: vprot@agroknow.gr Thank you!
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