Abstract. This paper describes the design and prototype implementation of a novel architecture for integrated concept, metadata and content based browsing and retrieval of museum information. The work is part of a European project involving several major galleries and the aim is to provide more versatile access to digital collections of museum artefacts, including 2-D images, 3-D models and other multimedia representations. An ontology for the museum domain, based on the CIDOC Conceptual Reference Model, is being developed as a semantic layer with references to the digital collection as instance information. A graphical concept browser is an integral component in the user interface, allowing navigation through the semantic layer, display of thumbnails, or full representations of artefacts and textual information in appropriate viewers and the invocation of conventional content based searching or combined querying. Semantic Web technologies are used in system integration to describe how tools for analysis and visualisation can be applied to different data types and sources. This supports flexible and managed formulation, execution and interpretation of the results of distributed multimedia queries. Combined searches using concepts, content and metadata can be initiated from a single user interface.
The future-focussed academic library "must be distinguished by the scope and quality of its service programs in the same way it has long been by the breadth and depth of its locally-held collections." (Walker, 2011). To be successful the design and development of those services have to be shaped and informed by the customers. Services must also be under continual evaluation to measure impact on customers, assess customer satisfaction, and encourage the modification of service in response to evaluation. Like any other customer-centred organisation, the library has a variety of methods at its disposal to gather information from and about their customer, such as usage data, survey results, focus groups, and face to face opportunistic encounters.
Abstract-A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.Index Terms-Art images, content based image retrieval, crack analysis, wavelets.
Abstract. This paper presents an updated technical overview of an integrated content and metadata-based image retrieval system used by several major art galleries in Europe including the Louvre in Paris, the Victoria and Albert Museum in London, the Uffizi Gallery in Florence and the National Gallery in London. In our approach, the subjects of a query (e.g. images, textual metadata attributes), the operators used in a query (e.g. SimilarTo, Contains, Equals) and the rules that constrain the query (e.g. SimilarTo can only be applied to Images) are all explicitly defined and published for each gallery collection. In this way, cross-collection queries are dynamically constructed and executed in a way that is automatically constrained to the capabilities of the particular image collections being searched. The application of existing, standards based, technology to integrate metadata and content based queries underpins an open standards approach to extending interoperability across multiple image databases.
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