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Towards Ontology based Agricultural Knowledge Services
Asanee Kawtrakul
At FAO, Italy
21 September 2007
National Electronic and Computer Technology CenterNational Science and Technology Development Agency
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Outline
• Why need Agricultural Knowledge Service?
• Who are the target of the Services?• Three steps for providing the knowledge
service• Q&A system:Case Studies on Rice.• Conclusion: Current and Next Steps
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Why need Agricutural Knowledge Services?
• Information Scattered
• Information Overload
Solutions: Assumption: Knowledge derived from Appropriate Information
• Right Information (Necessary and Sufficient) for Right Purpose
• Right Information Representation for the good Imaginary
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Who are the Target of Knowledge services?
Farmer, Naïve People, SME- Business
Domain Specific Researchers,Knowledge Broker
Related area Researchers
Policy
Decision Maker
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Three steps for providing the knowledge service
• Ontology Base Construction and Maintenance with Good Acquisition Tool or Workbench
• Content Management with Good Browser• Knowledge Service with Good Devices
System
Data Reposit
ory
Sesame APIJDBC API
SeRQLSQL
Validation
System Statistic Report
User management
Group management
System preference
GUI for Ontology Acquisition & Maintenance
Task-Oriented Parsing
Ontology Extraction
Lexicon Informati
on Integrati
onFiltering & Correcting
Morphological
Analysis and Phrase chunking
MRD
Ontology Integration
Concept management
Relationship management
Search Scheme management
Import ExportConsistency check
User Manage
ment
Ontological Knowledge
Management
Authoring Tools
Communities
Text
Ontology Repository in OWL format (MySQL)
Printed Dictionaries
System management module
• User management• Group management• System preference • System Statistic Report
Ontological Knowledge Authoring Tools
Structured Corpus
Raw Text Dictionary
Morphological Analysis
Merging & Organizing
VerificationSystem
Ontology
Thesaurus
Taxonomic, Part-of, Synonym Relationship Acquisition by
using PatternRelationship Refinement
Relationship Acquisition (Phrase Level)
Structure Analysis
Non-Taxonomic Relationship Acquisition (Sentence Level)
An Example of Rice Ontology MergingPlant products
Khao Dore Jasmine rice Luang Patiw
Cereals
RiceMaize
ko-kho15 Jasmine rice 105
Jasmine rice
Tung kula ronghai
Luang Patiw
Paddy
Processed plant products
Towards Knowledge management with good Content management and
Knowledge Service Tool
Business
Researchers
Government
Farmers
Harvest Technology
Organization Based
Pest
WWW
Rice Variet
y
Disease
Knowledge Portal
Construction
Knowledge Service Provision
Knowledge Extraction & generalizati
on
Information Extraction & Integration
Inference Engine
Knowledge
Tracking
Query Processin
g
Structured Knowledge &
rules
Document Warehouse
Ontology Acquisition
Distributed Information Collection
Preriodic web
crawler
Task Oriented Ontology & Linguistic Knowledge
Meta Data
Rice Variet
y
Q & A SystemDifferent Answer for Different Need
For Knowledge Broker
Economic Plants -> Rice and Sugar
Types of rice -> Jasmine and Basmati
Jasmine -> 2 types Jasmine 105 and Jasmine 192
Jasmine 105 -> can have Pest 1 and Pest 2
Pest 1 -> can be controlled using Method 1 and Method 2
Pest 2 -> can be controlled using Method 3
For ResearchersResearch Organization
Kasetsart University FAONII
Author 1
Author 2
Author 3
Author 4 Author 5
Author 6
Author 7Author 10
•D1.pdf•D2.htm•D3.doc•D4.doc•D5.pdf•D6.pdf
•D7.rdf•D8.xml
•D9.xls•D10.htm•D11.htm•D12.htm•D13.ps
•D14.doc•D15.txt•D16.pdf
•D17.pdf•D18.pdf•D19.jpg•D20.jpg•D21.rdf•D22.xtm•D23.xml•D24.pdf•D25.pdf
•D26.doc•D27.doc•D28.doc
•D29•D30•D31•D32•D33•D34
•D35.sql•D36.xml •D45.ppt
•D35•D36•D37•D38•D39•D40•D41•D42•D43
for the Farmers
Question:
What method can be used to remove
pest [Pest Name 1]
for rice [Jasmine 105] ?Jasmine 105Rice Name:
Pest Name: Pest 1
Search
Answer:
1.Method 12.Method 2
K-service for the Exporter/SME
Where does the upland rice grow in?
Know Where
Southern Region
K-service for General People
What kind of rice enrich with Vitamin B1 for beriberi disease protecting?
Know What
1. Hom Mali (Jasmine rice)
2. Sang Yod (ข้�าวสั�งข้�หยด)
What kind of rice that resist Sheath Rot Disease and Ragged Stunt Disease
Phatumthanee 60 and Supanburi 90
K-service for the Farmers
Conclusion: Current and Next Steps:
• Ontology Workbench Implementation with the experts on rice
• Do detail in End-users requirement (Q&A)• Develop Knowledge Portal about Rice• Develop the K-Service (Know-how, Know-why,
Know-who, Know-what• Evaluate and Test by different end users