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Semantic Technologies at FAO

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Presentation on theme: "Semantic Technologies at FAO"— Presentation transcript:

1 Semantic Technologies at FAO
International Society for Knowledge Organization (ISKO) 3 Aprile 2009, Torino Margherita Sini

2 Few words about myself

3 Just a very rapid introduction
What? semantic, semantic web, semantic technologies ontologies, Knowledge Organization Systems, metadata Why? interoperability, exchange, share user orientation, precision and recall multilinguality, cultural views, context Who? everybody, all domains, all countries, all .org Which instruments? experts, NLP, methodologies and techniques

4 Outline Semantic projects involving FAO Conclusions AOS
IPFSAPH, FNA, CWR, Fisheries, Food & nutrition, Geopolitical ontology, AGROVOC Concept Server Thai Rice Onto, Agropedia Indica Conclusions ontology-based applications Collaborations Take home messages

5 Semantic projects involving FAO

6 Inferencing Reasoning
Why AOS Semantic navigation, Clustering, Ranking, ... Interoperability ship or container Terminology brokering Intelligent query expansion Inferencing Reasoning Machine learning vessel? craft? boat? bateaux? barco?

7 Agricultural Ontology Service
An FAO initiative for more coherence in Agricultural Information Systems Need of a semantic approach AOS elements: AGROVOC Concept Server KOS registry Mapping registries Metadata standards Tools Publications (guidelines, ...) Built from AGROVOC Domain concepts Categories AGROVOC Concept Server Ontology registry Sub-domain ontologies Metadata ontologies



10 The Ontology

11 Creation of the core ontology
Agrovoc Information Resources Brainstorming Codex Alimentarius SPS Agreement Ontology 1600 concepts subject specialists Food Safety Documents Generic Documents Ontology Editor (OI-Modeler)

12 Concept Search The same records will be retrieved regardless of the specific synonyms or singular/plural forms that the user uses to refer to a concept. Related concepts

13 Multilinguality The system is also able to understand a concept even when different languages are used.

14 Check spelling Spelling errors are corrected: e.g. “desease” into “disease”

15 Paraphrasing “mad cow disease symptoms” or “clinical signs of bovine spongiform encephalopathy”

16 give the same results, which are ranked.

17 Semantic navigation of the bibliographical metadata (1)

18 Semantic navigation of the bibliographical metadata (2)

19 Semantic Navigation of Knowledge
parent concept(s) children concept(s)

20 FNA


22 Creation of the core ontology

23 Ontology Relationships

24 The ontology concepts Publication Issue Work Subject Term Category
Article Subject Term Category Author Region Language Year

25 The ontology instances

26 Features Multilingual concept resolution
Get suggestions for the navigation (e.g. synonyms) Guided query formulation Easy navigation of the objects by following the semantic links

27 RDFa

28 CWR

29 Hierarchy

30 The project Undertaken by FAO with partners
Developed in harmony with CWR descriptor list First version (English only) available by December 2006 About 800 core terms + acronyms + spelling variants; Clearly definition of concepts (AGROVOC + other sources); and Relationships: hierarchical + causative

31 More semantics Term: wild plants subclass of plants
superclass of crop wild relatives adapted by domestication benefits from resource conservation

32 Properties (1/2)

33 Properties (2/2)

34 Overall Solution (1/2) Subject specific Portals News feed service
Value-added information services Aggregated Database View Subject specific Portals News feed service Information System (n) Shared layer of interoperability Common exchange layer (Vocabularies,Ontologies, RDF/XML) datasetn dataset1 dataset2 Distributed Datasets

35 Overall Solution (2/2) Data

36 Fisheries

37 Fisheries Ontologies The initial goal The approach Evolution: NeOn
Making information interchangeable between ASFA, FIGIS, OneFish and AGROVOC The approach Creating an ontology, integrating or mapping the 3 different systems + AGROVOC Linking of the Ontology through wrappers to the different Information Systems Evolution: NeOn

38 FIGIS Reference Tables
ASFA FIGIS DTD ONE FISH AGROVOC Foundational Ontology FOS core FOS integrated FOS merged

39 Fisheries Ontologies (2/2)
OneFish FIGIS AGROVOC Aquaculture Resource Water Area land strains Species life cycle Farming system management Production center Spawning technique Breeding Hatchery Expl. form Regulation Farming technique Environment Institution Health monitoring diseases suppliers ASFA

40 Features Form versus meaning: Traditional Search Concept Search
Implemented functionalities: synonym search multilingual capability terminology brokering disambiguation related concepts query expansion Basic natural language queries Semantic navigation of bibliographical metadata Semantic Navigation of Knowledge Alphabetic list ... Core Fishery Concepts ...

41 Ontology properties

42 Example "tell me what vessels from a nearby country are currently in the marine area 50N060W within Atlantic Ocean, provided that also some Thunnus alalunga stock can be fished by those vessels, through allowed techniques"

43 Using multilingual lexicalizations

44 Using hierarchically related concepts
Polyvalent Trawlers hierarchically related concept

45 Using non-hierarchically related concepts
gears non-hierarchically related concept

46 Help the user formulate queries
Original query: bateau de pêche To refine your query, click on the concepts you are interested in. They will appear to the left. Search:

47 Reconcile different vocabularies
AGROVOC or ASFA or other “fishing vessels,” “fishing boat,” “navire de pêche”, “fishing vessel”, “embarcaciones de pesca” AGROVOC: “fishing vessels”, “barco”, etc... ASFA: “fishing vessels”

48 Semantic Navigation of Knowledge: Thesaurus based
Highlighting the originator thesaurus. User can select a specific thesaurus to look for.

49 Geopolitical ontology

50 Geopolitical ontology
Incorporate geopolitical data Will serve as a bridge to allow communication between the various systems.

51 Properties isValidFrom hasOfficialName hasCode isSuccessorOf
hasBorderWith dependsOn

52 Nutrition Ontology


54 Procedure <?xml version="1.0"?> <rdf:RDF xmlns=" xmlns:protege=" xmlns:rdf=" xmlns:xsd=" xmlns:rdfs=" xmlns:owl=" xmlns:daml=" xmlns:dc=" xml:base=" <owl:Ontology rdf:about=""> <owl:imports rdf:resource=" <owl:versionInfo rdf:datatype=" >Revision 4.0</owl:versionInfo> <protege:defaultLanguage rdf:datatype=" >en</protege:defaultLanguage> <rdfs:comment rdf:datatype=" >International Network of Food Data Systems (INFOODS) was established in 1984 on the basis of the recommendations of an international group convened under the auspices of the United Nations University (UNU). Its goal was to .....</rdfs:comment> </owl:Ontology> <owl:Class rdf:ID="c_0413"> <code rdf:datatype=" >0413</code> <rdfs:subClassOf> <owl:Class rdf:ID="c_041"/> </rdfs:subClassOf> <rdfs:label xml:lang="en">Vitamin D</rdfs:label> </owl:Class> =CONCATENATE("<owl:Class rdf:ID=""",J2,"""><rdfs:subClassOf><owl:Class rdf:ID=""c_",B2,"""/></rdfs:subClassOf><rdfs:label xml:lang=""en""><![CDATA[",D2,"]]></rdfs:label><code><![CDATA[",J2,"]]></code><TAGNAME><![CDATA[",J2,"]]></TAGNAME>",S2, T2,"</owl:Class>")


56 AOS Core: the Concept Server
Other thesauri and terminologies integration ABACA NT1 Food NT2 Apple ANIMAL BT Organ NT .... Other thesauri & terminologies ABACA NT1 Food NT2 Apple ANIMAL BT Organ NT .... Terminology Workbench AGROVOC OWL AGROVOC RDFS formats (e.g. SKOS) and TagText ISO2709 mapping Export

57 Concept Server project
Refine semantics and enrich data pool and lexicon Develop a workbench for terminology and ontology development and maintenance. Support information management specialists in the development, maintenance, and quality assurance of the AOS/CS Global knowledge vs local knowledge

58 AGROVOC Concept Server
AGROVOC cleaning and refinement Current AGROVOC MySQL Improved AGROVOC OWL Revision and Refinement

59 Modelling Conversion to UTF-8 Migration to MySQL (from SQL server)
Migration to PostgreSQL (from MySQL) Incorporated AGRIS/CARIS classification scheme (multilingual) and the mapping with AGROVOC keywords Modified structure to store multiple classification schemes Revised RDBMS scheme for ontology representation Designed OWL models Export to OWL format (v0.8a) Export to SKOS format (v0.8a)

60 Methods Concepts from descriptors
Synonym <owl:DatatypeProperty rdf:ID="synonym"> Acronyms <owl:AnnotationProperty rdf:about=" <owl:Class rdf:about=" <rdfs:label xml:lang="en">ABA</rdfs:label> <rdfs:label xml:lang="fr">ABA</rdfs:label> <rdfs:label xml:lang="es">ABA</rdfs:label> <rdfs:label xml:lang="ar">آبا</rdfs:label> <rdfs:label xml:lang="zh">脱落酸</rdfs:label> <synonym xml:lang="en">[8565] Abscisic acid</synonym> <rdfs:subClassOf rdf:resource=" <rdfs:subClassOf rdf:resource=" </owl:Class>

61 SKOS SKOS export from AGROVOC Concept Server Workbench (WB)
SKOS web services SKOS-services for DSpace plug-in SKOS for mapping projects

62 Web Services triple store SKOS maintain AGROVOC CS Workbench export
access Web Services access response

63 Ontology models (AGROVOC Concept Server, LIR, ...)
Relationships between concepts Lexicalization/ Term String strings terms designated by manifested as Other information: language/culture subvocabulary/scope audience type, etc. Note annotation relationship Relationship All terms are created as instances of the class o_terms. All at the same level. Only one language per term. term level string level concept level

64 Agropedia Indica

65 References

66 Conclusions

67 Ontology-based applications
Better exploitation of the potentiality at the application level: powerful IR No more words but URIs in IS Networked Ontologies Ontology Web services (OWS)

68 Collaborations With AOS partners Within EU Projects
NeOn SEMIC.EU With other initiatives GFIS Ecoterm Mapping projects GBIF Global Biodiversity Information Facility secretariat JRC + BGS + Biblioteca Nazionale di Firenze

69 Take-home message There are many uses for terminology & ontology systems in food and agriculture, both for information access and information processing FAO has several projects using such systems FAO is deploying the Agricultural Ontology Server (AOS) as a global resource SKOS and other knowledge representation standards play a key role

70 Questions? Thanks Margherita Sini:
Johannes Keizer: Dagobert Soergel: Asanee Kawtrakul: But Also: Gudrun Johannsen, Boris Lauser, Claudio Baldassarre, Gauri Salokhe, Marta Iglesias, Caterina Caracciolo, Sachit Rajbhandari, Jeetendra Singh, Mary Redahan, Shrestha, Prashanta, Ton, Imm, Thanapth, Trakul, and many others...

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