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This paper presents the results of our study regarding the different facets and ways of using annotations in both digital libraries and collaboratories. This study represents an innovative attempt at gathering methodological tools and synergies from both fields in order to effectively define a comprehensive model for annotations. Thus we propose a conceptual model for annotations in order to develop an annotation service that can be plugged into digital libraries and collaboratories. Finally, starting from our model, we introduce a search strategy for exploiting annotations in order to search and retrieve relevant documents for a user query.

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In this paper we introduce POLAR, a probabilistic objectoriented logical framework for annotation-based information retrieval. In POLAR, the knowledge about digital objects, annotations and their relationships in a digital library repository can be modelled considering certain characteristics of annotations and annotated objects. Insights about these characteristics are gained by an analysis of the annotation models behind existing systems and a discussion of an object-oriented, logical view on relevant objects in a digital library. Retrieval methods applied in a digital library should take annotations into account to satisfy users' information needs. POLAR thus supports a wide range of flexible and powerful annotation-based fact and content queries by making use of knowledge and relevance augmentation. An evaluation of our approach on email discussions shows performance improvements when annotation characteristics are considered.