Annotated data play an important role in enhancing the usability of information resources. Single users can be easily frustrated
by the task of annotating. Collaborative approaches to annotation have been applied to web resources, but have not yet been
applied to the task of local documents, due in part to the lack of a uniform identification method. In this paper, we use
hash-based virtual URIs for identifying documents, and introduce the concept of a STAN (Social, Trusted Annotation Network),
which enables collaborative annotation of documents through their URIs. STAN also incorporates quantitative trust rates between
users in social networks based on their interactions with each other. The STAN framework is described, demonstrating how these
trust networks are constructed through collaborative annotation. Finally, we evaluate the usefulness of collaborative annotation
and the feasibility of the resulting trust rates through empirical experiment.
Keywords Semantic Desktop - Social - Trusted Annotation Network - Trust Network - Hash algorithm - Virtual URI