Visualizing Mapping of Metadata Properties
Publication from Digital
Proceedings of 2nd Workshop on Semantic Multimedia Database Technologies, 12/2010
Millions of hours of audiovisual content are held by collections of dedicated broadcast, film and sound archives, institutional or corporate archives, libraries and museums. There is a large heterogeneity between the different audiovisual archives resulting from their history and tradition but also from cultural differences of the countries where those archives reside. Consequently metadata models covering the work ows and necessities in the archives differ as well. This fact and the need for metadata for various different use cases in the archives lead to a number of metadata models and standards. Thus mapping between different metadata models is inevitable in practical applications. We are currently developing a system for automating metadata mapping by formalizing semantics of properties in the different formats and their relations, based on an intermediate ontology, namely the meon ontology. In order to enable users to validate the automatically determined mappings visualization functionalities are required in the system. This paper describes the integration of the ontology visualization developed in into our mapping system prototype. Creating comprehensive, clear and intuitive visualizations of ontologies and RDF graphs is an ongoing challenge. Different approaches can be found in applications for Semantic Web engineers. An example is Protege1, which is an open, platform independent environment for creating and editing ontologies and knowledge bases. The application is extensible by its plug-in architecture and thus provides several visualizations. IsaViz2 is a visual tool for browsing and authoring of RDF models. Resource nodes are represented by ellipses, literals as rectangles and properties are displayed as lines with arrows. OntoSphere 3D uses a collection of three-dimensional visualization techniques displaying ontologies. gFacet combines the graph visualization with facet search in the graph. These applications use different kinds of visualization techniques to present the user a possibly easy to understand and complete overview of the whole RDF graph. Using graph visualizations of RDF data especially for end users has a number of drawbacks. For example, these visualizations are at and every node is treated as a primary node. Also, displaying a graph with hundreds of nodes and edges results in a cluttered visualization. Nonetheless graph visualizations have their place, especially for Semantic Web engineers.