Interactive visualization of large graphs and networks
Interactive visualization of large graphs and networks
Effective Visualization and Navigation in a Multimedia Document Collection Using Ontology
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
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Web-based data sources, particularly in Life Sciences, grow in diversity and volume. Most of the data collections are equipped with common document search, hyperlink and retrieval utilities. However, users' wishes often exceed simple document-oriented inquiries. With respect to complex scientific issues it becomes imperative to aid knowledge gain from huge interdependent and thus hard to comprehend data collections more efficiently. Especially data categories that constitute relationships between two each or more items require potent set-oriented content management, visualization and navigation utilities. Moreover, strategies are needed to discover correlations within and between data sets of independent origin. Wherever data sets possess intrinsic graph structure (e.g. of tree, forest or network type) or can be transposed into such, graphical support is considered indispensable. The Viator tool family presented during this demo depicts large graphs on the whole in a hyperbolic geometry and provides means for set-oriented context mining as well as for correlation discovery across distinct data sets at once. Its utility is proven for but not restricted to data from functional genome, transcriptome and proteome research. Viator versions are being operated either as user-end database applications or as template-fed stand-alone solutions for graphical networking.