1. Margherita Sini, FAO 1/ http://www.fao.org/aims/ FAO projects in the area of the Semantic Technologies 23rd APAN Meeting Manila, Philippines margherita.sini@fao.org

2. Margherita Sini, FAO 2/ http://www.fao.org/aims/ Outline Introduction The AGROVOC/CS Workbench Future works

3. Margherita Sini, FAO 3/ http://www.fao.org/aims/ Introduction

4. Margherita Sini, FAO 4/ http://www.fao.org/aims/ FAO as a Knowledge Organization Knowledge Exchange & Capacity Building Division Teminological resources (AGROVOC, FAOTERM, Glossaries, etc.) –Avian Influenza Glossary (Avian Influenza/Pandemic Influenza Glossary in collaboration with World Health Organization) Subdomain ontologies Agricultural IM standards: http://www.fao.org/aims http://www.fao.org/aims

5. Margherita Sini, FAO 5/ http://www.fao.org/aims/ The AGROVOC/CS Workbench

6. Margherita Sini, FAO 6/ http://www.fao.org/aims/ Background (1/2) AGROVOC –Used worldwide –Multilingual (online 11 languages) –Term-based (as opposed to concept based) –Limited semantics (NT, BT, RT, USE/UF) –Maintained as a relational database –Distributed in several formats (RDBMS, TagText, ISO2709,...)

7. Margherita Sini, FAO 7/ http://www.fao.org/aims/ Background (2/2) Draft versions available in TBX, SKOS, OWL Access to full thesaurus through seven Web Services Agricultural Ontology Service (AOS)

8. Margherita Sini, FAO 8/ http://www.fao.org/aims/ collaborative AGROVOC/CS Workbench: a collaborative ontology development tool Support and manage the multi-language terminology work of information management specialists in the development, maintenance, and quality assurance of the CS.

9. Margherita Sini, FAO 9/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Users Term editors Ontology editors Validators Publishers Administrators  distributed user-base!

10. Margherita Sini, FAO 10/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Features Text processing Corpus Creation Corpus Analysis Manage –Concepts, Terms, Relationships –Classification Schemes Quality Assurance Other functionalities –Search –Import / Export –Validations –Administration –Help

11. Margherita Sini, FAO 11/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Overall design.doc,.pdf,.xml, etc. Concept Hierarchy input AOS/CS Workbench concordance pattern-matching multilingual text corpus input

12. Margherita Sini, FAO 12/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Home Page

13. Margherita Sini, FAO 13/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Search Page

14. Margherita Sini, FAO 14/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Export Page

15. Margherita Sini, FAO 15/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Navigate Concepts

16. Margherita Sini, FAO 16/ http://www.fao.org/aims/ AGROVOC/CS Workbench: Concept’s relationships

17. Margherita Sini, FAO 17/ http://www.fao.org/aims/ Current status AGROVOC/CS Workbench construction (ongoing) –CS OWL model described –Test project available –Full AGROVOC conversion procedure using the OWL model (ongoing) –Relationships definition (in collaboration with CNR, Italy) (ongoing) –Performance tests (ongoing)

18. Margherita Sini, FAO 18/ http://www.fao.org/aims/ Next steps Completion of the AGROVOC/CS Workbench AGROVOC conversion and further refinement Extensive testing on scalability, concurrent use of the Workbench etc. Create a network of ontology experts –Multilingual subject experts: term editors, ontology editors, validators –Workshops/Trainings NeOn

19. Margherita Sini, FAO 19/ http://www.fao.org/aims/ Future works and collaborations 1

20. Margherita Sini, FAO 20/ http://www.fao.org/aims/ The Semantic Web meets WEB 2.0: cataloguing and annotating Web Resources (1/3) Producing semantically rich, multilingual knowledge repositories Combine social bookmarking with Ontology based bookmarking Composing, organizing and offering information from different knowledge repositories (distributed ontologies)

21. Margherita Sini, FAO 21/ http://www.fao.org/aims/ The Semantic Web meets WEB 2.0 (2/3) Collaborative aspects –Distribution of ontological data –Collaborative semantic annotation –Collaborative editing of ontologies Data Integration –Ontology Learning –Automatic discovery of ontologies (Ontology Crawling) –Linking/Merging of ontologies Linguistic Aspects –Identity of concepts: discovering of linguistic phenomena like synonymy/homonymy –Linguistic Enrichment of Ontologies –Multilinguality

22. Margherita Sini, FAO 22/ http://www.fao.org/aims/ The Semantic Web meets WEB 2.0 (3/3) People/Expert discovery service Working on the case study: avian flu Partners –FAO –University of Rome Tor Vergata, Italy –Kasetsart University, Bangkok, Thailand –Yahoo, UK/Ireland –Elsevier, Netherlands –University of Bielefeld, Germany –....

23. Margherita Sini, FAO 23/ http://www.fao.org/aims/ demos

24. Margherita Sini, FAO 24/ http://www.fao.org/aims/ Semantic Turkey Università Tor Vergata Roma, Italy Semantic Web technologies are offering standards for knowledge representation and for content exchange Obtain a clear separation between pure knowledge data (the WHAT) and web links (the WHERE) Offer innovative navigation of both the acquired information and of the pages where it has been collected The project has been focused on innovative solutions for browsing the web and for organizing the information which is observed during navigation

25. Margherita Sini, FAO 25/ http://www.fao.org/aims/

26. Margherita Sini, FAO 26/ http://www.fao.org/aims/ OntoLing Università Tor Vergata Roma, Italy Exploiting Linguistic Resources for building linguistically motivated ontologies Linguistic Enrichment of Ontologies –Manually –Automatically

27. Margherita Sini, FAO 27/ http://www.fao.org/aims/

28. Margherita Sini, FAO 28/ http://www.fao.org/aims/ Future works and collaborations 2

29. Margherita Sini, FAO 29/ http://www.fao.org/aims/ Early warning systems (1/3) Emerging infectious diseases warning system Use cases: Bird Flu, Rice Problem: today systems in many domains already exist but there is no efficient access to them. The information is scattered and not organized Structured information (e.g. the CS) can be used to organize unstructured information (wikis and blogs)

30. Margherita Sini, FAO 30/ http://www.fao.org/aims/ Resources –FAO CS, Metadata and multilingual subject ontologies –AGRIS data –Department of Livestock data Topics –From unstructured information to structured information –Distributed and collaborative knowledge building –Knowledge mapping –Topic map –Knowledge engineering, knowledge mining, data mining –Intelligent decision support systems (diagnosis analysis) Early warning systems (2/3)

31. Margherita Sini, FAO 31/ http://www.fao.org/aims/ Partners –Thai Ministry of Science and Technology (NECTEC) –Thai Ministry of Agriculture (Department of Livestock) –Kasetsart University, Bangkok, Thailand –Thai Agris Center, Bangkok, Thailand –HAII, Bangkok, Thailand –FAO –Consortium of Asian countries (APEC) –..... Early warning systems (3/3)

32. Margherita Sini, FAO 32/ http://www.fao.org/aims/ Future works and collaborations 3

33. Margherita Sini, FAO 33/ http://www.fao.org/aims/ Grid Technologies in Digital Libraries (1/2) Combine distributed repositories through ontologies by means of the grid technology –Several institutions –Repositories of scientific data, GIS, statistical data –Domain of fisheries / aquaculture

34. Margherita Sini, FAO 34/ http://www.fao.org/aims/ Grid Technologies in Digital Libraries (2/2) Partners –FAO –Italian National Research Center (CNR), Italy –Thai National Grid Center, Kasetsart University, Bangkok –Thai National Agris Center, Kasetsart University, Bangkok –NECTEC, Thailand –....

35. Margherita Sini, FAO 35/ http://www.fao.org/aims/ Thank you! More information: http://www.fao.org/aims/ margherita.sini@fao.org … open discussion …