Web-based online communities like blogs, forums, scientific communities etc. have become important places for people to 

seek and share expertise. Existing search engines like Google, Yahoo!, Live etc. are not yet capable to answer queries 
that require deep semantic understanding of the query or the document. Instead, it is preferable to find and ask someone

 who has related expertise or experience on a topic and these online communities are the places for people to seek 
advice or help. But before such analysis can be done, we need to gather the data (questions and answers, social support 

or discussion, comments or advice, content rating, social relations etc) that describes these online communities. There 

is no universal standard data structure for the outline of user participation in these communities. Also as these 
communities rarely interoperate, each is typically only aware of its own social data and cannot benefit from other 
communities data. Thus extracting, aggregating and analyzing data from these communities for finding experts on a single

 framework is a challenging task. In this draft, we present a Grid-enabled framework of expertise search (GREFES) engine

 which utilizes online communities as sources for experts on various topics. This draft suggest an open data structure 
called SNML (Social Network Markup Language) to outline user participation in online communities. The architecture 
addresses major challenges in crawling of community data and query processing by utilizing the computational power and 
high bandwidth inherently available in the Grid. Besides, our framework supports open APIs for third party pro