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1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007
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Page 1: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

1

Towards Ontology based Agricultural Knowledge Services

Asanee Kawtrakul

At FAO, Italy

21 September 2007

Page 2: 1 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

Page 3: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

3

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

Page 4: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

4

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

Page 5: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

5

Who are the Target of Knowledge services?

Farmer, Naïve People, SME- Business

Domain Specific Researchers,Knowledge Broker

Related area Researchers

Policy

Decision Maker

Page 6: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

6

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

Page 7: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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)

Page 8: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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

Page 9: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

Towards Knowledge management with good Content management and

Knowledge Service Tool

Page 10: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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

Page 11: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

Q & A SystemDifferent Answer for Different Need

Page 12: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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

Page 13: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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

Page 14: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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

Page 15: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

K-service for the Exporter/SME

Where does the upland rice grow in?

Know Where

Southern Region

Page 16: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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)

Page 18: 1 Towards Ontology based Agricultural Knowledge Services Asanee Kawtrakul At FAO, Italy 21 September 2007.

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


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