Semantic Web Tools For Agricultural Materials

Semantic Web Tools in support of Agricultural Content

Representation & Retrieval

Gerard Sylvester

The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)

This research is being carried out at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) under the guidance of Dr. V Balaji by the Knowledge Management and Sharing team at ICRISAT. This is supported by the NAIP of the ICAR.

http://www.icrisat.org/

Acknowledgement

Chaos in Agricultural Research and Extension

• Agricultural content is dispersed and there is no unified view to integrate the resources.

• Difficulty in sharing common content in the agricultural realms

• Content is tightly coupled with the context and the presentation medium

The Solution!

• Unified Knowledge/Resource organization model needed – Integrated View

• Semantic Tools provide for Knowledge Representation & Sharing

• Specialized and enhanced navigation

• Provides for rapid information aggregation from reusable information objects

Why Semantic Web Tools?

• To associate meaning with content

• Establishing a layer of machine understandable data that would facilitate automated agents, sophisticated search engines and interoperable services.

• It will enable a higher degree of automation and more intelligent applications.

• THE ULTIMATE GOAL : to allow machines to share and exploitation of knowledge in the Web way

Components of the experiment

• Content Organization (Semantic Mediawiki & Topic Map)

• Content Packaging (eXe Editor)

• Content Navigation (Topic Maps & Semantic Mediawiki)

Semantic VASAT Wiki Ingredients

+ + =

FAO’s AGROVOC provides the Ontology to link information objects in the Wiki facilitated by OntoWorld’s Semantic Tool

Semantic ToolMediaWiki S/w FAO’s AGROVOCSemantic

VASAT Wiki

http://vasatwiki.icrisat.org

An Ongoing Experiment with SMW + Ontology

• Uploaded agricultural content onto VASAT wiki (1000 articles uploaded from Wikipedia)

• Categorized content according to AGROVOC

• Manually divided available articles into information objects and

• Created ontological relationships (Semantics) among the information objects in the VASAT wiki

Workflow

Curation

SemanticVASAT Wiki

VersionStaging

AGROVOC

Ontologies, categorization

Agriculture article

Extract Agricultural Articles

Wiki +

Semantic tool +

Ontology

CommunityReview

http://vasatwiki.icrisat.org/index.php/Chickpea

Information objects

Information Objects on VASAT Wiki

Wikipedia Articlehttp://en.wikipedia.org/wiki/Pigeonpea

VASAT Wiki Articlehttp://vasatwiki.icrisat.org/index.php/Pigeonpea

Article extracted and Semantic links established manually

1

4

32

An Ongoing Experiment with Topic Maps + Ontology

• Topic Maps to facilitate Repurposing of Agricultural Information Objects

• Provides a meta-structure over dispersed information objects

• Provides the ability to map dynamic content onto the knowledge structure

Aggregate Resources

Content aggregated from VASAT Wiki

Content from externalWebsite

Integrate content from various sources

Content aggregated thus could also be exported to various formats

Wiki Article

External Website

Content Package

Content Packaging from different sources

Content RepurposingContent repackaging and repurposing to be exported to many different formats

The Topic Map ConceptChickpea

Pests

Legume

Rust

PigeonpeaDiseases

Cultural practices

DBWeb pages

Associations

Occurrences

Web page

Knowledge

Layer

Information

Layer

Topic Map for VASAT’s Learning Objects

VASAT LO repository

AGROVOC

ICRISAT’sCrop Topic Map

Available at: http://test2.icrisat.org/

Topic Map - Visualized

A Pigeonpea Topic Map displayed using Ontopoly Software

Looking Forward…

Content Organization

Ontology + Wiki-like interface

ICAR

Intl.agencies

OtherNARS

agenciesCommodity

Markets

Weather / Meteorology

DynamicData

SAUs

K-Base

Imagery/Maps

KVKs NGOs DoA

Q&A; activitieslog