Building a semantic blog support system for gene Learning Objects on Web 2.0 environment / by Wei Yuan.

Abstract

Blogging has become a popular practice on Internet in recent years, and it has been used as information publishing and participate platforms. In recent years, a style of blog called 'semantic blogs' have been introduced into the field. Semantic blogs are blogs enriched with machine-understandable metadata (Mller, Breslin, & Decker, 2005). They are an extension of regular blogs. Recently, a new web technology theory was proposed called Web 2.0. Unlike traditional web technology which only allows web users to accept information passively, Web 2.0 provides web users the option to actively modify web information. Learning Objects are digital entities deliverable over the Internet. Any number of people can access and use them simultaneously. Moreover, users can collaborate on learning objects and benefit immediately from adding their information or appending others' work to Learning Objects and share with other users over the Internet. This thesis is dedicated to the development of a semantic blog prototype for Gene Ontology annotation and navigation as a Web 2.0 support system. We are developing this semantic blog specifically because we did not find an effective system already in place that can provide support for biomedical researchers. The existing Gene Ontology systems can be classified into various categories: offline applications, client-server applications, web search engines, portals, and FTP servers. Researchers face a number of bottlenecks within the current system; all of them are based on traditional web technology with no collaboration among individual gene ontology researchers, and annotation can only be published by certain organizations. This thesis seeks the possibility to use Learning Object with Gene Ontology along with the semantic of how researchers collaborate as represented by FOAF. We have therefore introduced a new Gene ontology Annotation and navigation System. Colloquially referred to as GAS, it is based on Web 2.0 technologies with extended semantic capabilities that include Gene Ontology semantics, SCORM semantics, FOAF semantics, RSS syndication, aggregation semantics, as well as a useful and important gene ontology and annotation navigation system - Gene Ontology Navigation (GON). Our evaluation of the GAS prototype has proven to be extremely effective.