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

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

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

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)

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 Tool MediaWiki S/w FAO’s AGROVOC Semantic 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

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 Semantic VASAT Wiki Version Staging AGROVOC Ontologies, categorization Agriculture article Extract Agricultural Articles Wiki + Semantic tool + Ontology Community Review http:// vasatwiki.icrisat.org/index.php/Chickpea Information objects

Information Objects on VASAT Wiki Wikipedia Article http://en.wikipedia.org/wiki/Pigeonpea VASAT Wiki Article http://vasatwiki.icrisat.org/index.php/Pigeonpea Article extracted and Semantic links established manually 1 4 3 2

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

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 external Website 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 Repurposing Content repackaging and repurposing to be exported to many different formats

The Topic Map Concept Chickpea Pests Legume Rust Pigeonpea Diseases Cultural practices DB Web pages Associations Occurrences Web page Knowledge Layer Information Layer

Topic Map for VASAT’s Learning Objects VASAT LO repository AGROVOC Content Ontology ICRISAT’s Crop 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 Other NARS agencies Commodity Markets Weather / Meteorology Dynamic Data SAUs K-Base Imagery/ Maps KVKs NGOs DoA Q&A; activities log