Human-Computer Interaction Institute
School of Computer Science, Carnegie Mellon University


Towards a Semantic Web of
Community, Content and Interactions

Anupriya Ankolekar

September 2005

Ph.D. Thesis


Keywords: Human-computer interaction, artificial intelligence, computer-supported cooperative work, semantic web, open source software communities, semantic web applications

The Web plays a critical role in hosting Web communities, their content and interactions. A prime example is the open source software (OSS) community, whose members, including software developers and users, interact almost exclusively over the Web. The OSS community constantly generates, shares and refines content in the form of software code through active interaction over the Web on code design and bug resolution processes. The knowledge and implementation experiences around the software content are implicit in the interactions in the community discussion forums on the Web. The Semantic Web is an envisaged extension of the current Web, in which content is given a well-defined meaning, through the specification of metadata and ontologies, that can be understood by software agents. This increases the utility of the content and enables information from heterogeneous sources to be integrated. Although the individual components of a Semantic Web are fairly well-understood, there is a research gap in the application of SemanticWeb to a specific domain.

This thesis work explores the application of the Semantic Web in the context of a typical OSS community, the OpenACS community, with a focus on the interactions around the bug resolution process. The research answers three questions: How to create a Semantic Web around the OSS community, the software content, and the interactions? How to use the Semantic Web in the bug resolution process? What is the potential impact of the Semantic Web on the bug resolution process, and vice versa? To answer these questions, we developed a prototype Semantic Web system for OSS communities, Dhruv. Dhruv provides an enhanced semantic interface to bug resolution messages and recommends related software objects and artifacts. Dhruv uses an integrated model of the OpenACS community, the software, and the Web interactions, which is semi-automatically populated from the existing artifacts of the community. Comparison of Dhruv s recommendations with historical bug resolution data reveals that Dhruv is able to recommend relevant artifacts for bug resolution messages. A qualitative think-aloud study of Dhruv with OpenACS community members indicates that Dhruv has high potential of being useful to the OpenACS community. Study participants found the enhanced semantic interface particularly compelling.

211 pages

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