Harvana

Abstract

Collaborative, social tagging and annotation systems have exploded on the Internet as part of the Web 2.0 phenomenon. Systems such as Flickr, Del.icio.us, Technorati, Connotea and LibraryThing, provide a community-driven approach to classifying information and resources on the Web, so that they can be browsed, discovered and re-used. Although social tagging sites provide simple, user-relevant tags, there are issues associated with the quality of the metadata and the scalability compared with conventional indexing systems. In this paper we propose a hybrid approach that enables authoritative metadata generated by traditional cataloguing methods to be merged with community annotations and tags. The HarvANA (Harvesting and Aggregating Networked Annotations) system uses a standardized but extensible RDF model for representing the annotations/tags and OAI-PMH to harvest the annotations/tags from distributed community servers. The harvested annotations are aggregated with the authoritative metadata in a centralized metadata store. This streamlined, interoperable, scalable approach enables libraries, archives and repositories to leverage community enthusiasm for tagging and annotation, augment their metadata and enhance their discovery services. This paper describes the HarvANA system and its evaluation through a collaborative testbed with the National Library of Australia using architectural images from PictureAustralia.