Harvesting community annotations on 3D models of museum artefacts to enhance knowledge, discovery and re-use

Many cultural heritage organizations responsible for providing access to large online collections recognize the potential value that social tagging systems can add to their collections. Projects such as Steve.Museum aim to give online users a voice in describing the content of publicly-held collections of digital heritage, through online social tagging and annotation tools. However, there are a number of unresolved challenges associated with re-using community tags, aggregating them within the museum's authoritative metadata stores and incorporating them within museum “metasearch” services. Although social tagging sites provide simple, user-relevant tags, there are issues associated with the quality of the metadata, the scalability compared with conventional indexing systems and a lack of interoperability across social tagging and annotation systems. In this paper, we propose an integrated system that overcomes many of the limitations of social tagging systems and maximizes their potential value-add within the context of museum collections. The Harvesting and Aggregating Networked Annotations (HarvANA) system firstly enables communities to attach tags/annotations to digitized 3D museum artefacts through web-based annotation services. The annotations/tags are represented using a standardized but extensible Resource Description Framework (RDF) model and an ontology-directed folksonomy. This approach facilitates interoperability between tags/annotations. Secondly, the system uses the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) API to automatically harvest the annotations/tags from distributed community servers. The harvested annotations are aggregated with the authoritative museum metadata in a centralized metadata store. The HarvANA system provides a streamlined, interoperable, scalable approach that enables cultural organizations to leverage community enthusiasm for tagging and annotation, augment their institutional metadata with community tags and enhance their discovery and browse services over 3D models.