Ongoing experiment in the Use of Semantic Wiki Tool to Build a Repository of Re-usable Information objects in Agricultural Education and Extension 

There has been significant interest in applying semantic technologies to build a repository of reusable information objects in Agricultural Education and Extension. An example is the pioneering efforts of the DEAL group in conceptualising an AGROPEDIA for India (http://emandi.mla.iitk.ac.in/agropedia/). The Wiki has offered unprecedented opportunities in collaborative content development while tools of the semantic web will offer altogether new advantages in terms of search and personalisation, to mention just two. The AGROVOC’s English language keywords has been used to generate classifications for content description at a top level.

We used the 17 broad categories of AGROVOC’s English terms to harvest entries from the Wikipedia (http://en.wikipedia.org/wiki). Based on these categories, as the top level keywords, we noted that agricultural content forms a relatively minor part of the Wikipedia classified under 53 subcategories. A total of around 500 entries, as on 21.May.2007, were downloaded and posted onto a local Wiki server, running MediaWiki software. A semantic tool (available at http://ontoworld.org/wiki/Semantic_MediaWiki) was used to create additional tags in the hosted entries and links were formed. The searches inside the semantically re-constructed collection are more specific compared to searches on the downloaded collection from the Wikipedia. An even more interesting possibility that emerges is the ease with which the entries can be constituted into information objects that can be reused because their relationships with other objects in this re-constituted domain are rich and complex. 

Topic Maps based technology, an ISO standard gives the ability to seperate the information layer from knowledge layer. In continuation of the above experiment, All the terms related to the five mandate crops of ICRISAT (Pigeonpea, Chickpea, Pearlmillet, Groundnut and Sorghum) are collected, classified and incorporated into a topic map using an open source software, TM4L (http://compsci.wssu.edu/iis/nsdl/download.html), for creating and editing topic maps. The ontological relationships between different topics are defined using FAO's AGROVOC’s relationship legends. The topics are linked onto resources on VASAT’s learning resources repository.

The topic map for each crop is integrated with the information objects of the VASAT learning resources.

Test the Semantic extensions enabled Wiki at  http://vasatwiki.icrisat.org/index.php/

The topic map driven website is currently under test at  http://test2.icrisat.org/