Graph Visualization and Navigation in Information Visualization: A Survey
IEEE Transactions on Visualization and Computer Graphics
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Multi-Level Graph Layout on the GPU
IEEE Transactions on Visualization and Computer Graphics
Survey of Text Mining II: Clustering, Classification, and Retrieval
Survey of Text Mining II: Clustering, Classification, and Retrieval
Technical Section: EXOD: A tool for building and exploring a large graph of open datasets
Computers and Graphics
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We deal in this paper with the problem of creating an interactive and visual map for a large collection of Open datasets. We first describe how to define a representation space for such data, using text mining techniques to create features. Then, with a similarity measure between Open datasets, we use the K-nearest neighbors method for building a proximity graph between datasets. We use a force-directed layout method to visualize the graph (Tulip Software). We present the results with a collection of 300,000 datasets from the French Open data web site, in which the display of the graph is limited to 150,000 datasets. We study the discovered clusters and we show how they can be used to browse this large collection.