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KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
KOS Management - The case of the Organic.Edunet Ontology
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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” …

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
  • Transcript

    • 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. 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. Introduction to KOS
    • 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. Focusing on ontologies  Ontology: Explicit formal specification of terms in a domain AND the relations among them
    • 6. Tree-view of an ontology
    • 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. Open Source KOS Management tools (indicative list)
    • 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. 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. VocBench screenshot
    • 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. Protégé screenshot
    • 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. TemaTres screenshot
    • 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. Neologism screenshot
    • 18. The MoKi tool
    • 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. MoKi screenshot (2011)
    • 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. The Organic.Edunet ontology
    • 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. The Organic.Edunet ontology  Currently consists of 381 concepts translated in 18 languages
    • 25. Translating the OE ontology (2010)
    • 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. 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. Building the Organic.Edunet ontology (3/3)
    • 29. Evolution of the Organic.Edunet ontology using MoKi
    • 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. 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. 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. 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. Discussions in MoKi
    • 35. Concept management  Refers to  Editing concept  Renaming concept  Deleting concept
    • 36. Introduction of new concepts  Ontology suggestion service     Verified Keywords, User (modified) Keywords, (Automatically) Extracted Keywords and Search-Query-Logs
    • 37. Translation of concepts (2013)
    • 38. Mapping to AGROVOC
    • 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. Case study: the use of the ontology service API
    • 41. OE ontology evolution in numbers
    • 42. Next steps
    • 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. 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. 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. www.organic-lingua.eu Contact me at: vprot@agroknow.gr Thank you!

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