This document discusses using semantic web tools to better organize and share agricultural content online. It describes an ongoing experiment using semantic mediawiki and topic maps linked to an agricultural ontology to categorize over 1000 agricultural articles. The goals are to provide a unified knowledge model, associate meaning with content, and allow machines to better share and exploit agricultural knowledge on the web. Components include organizing content with a wiki and topic maps, packaging content from different sources, and facilitating navigation and retrieval of information objects.

1. Semantic Web Tools in support of Agricultural Content Representation & Retrieval Gerard Sylvester The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)

2. 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

3. 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

4. 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

5. 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

6. Components of the experiment Content Organization (Semantic Mediawiki & Topic Map) Content Packaging (eXe Editor) Content Navigation (Topic Maps & Semantic Mediawiki)

7. 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

8. 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

9. 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

10. 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

12. 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

13. 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

14. Wiki Article External Website Content Package Content Packaging from different sources

15. Content Repurposing Content repackaging and repurposing to be exported to many different formats

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

17. Topic Map for VASAT’s Learning Objects VASAT LO repository AGROVOC Content Ontology ICRISAT’s Crop Topic Map Available at: http://test2.icrisat.org/

18. Topic Map - Visualized A Pigeonpea Topic Map displayed using Ontopoly Software

20. 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