Download Database Issues for Data Visualization: IEEE Visualization by John P. Lee, Georges G. Grinstein PDF

By John P. Lee, Georges G. Grinstein

This quantity offers the court cases of the foreign Workshop on Database matters for facts Visualization, held at the side of the IEEE Visualization '93 convention in San Jose, California in October 1993.
The publication includes thirteen technical contributions equipped in sections on datamodels; process integration matters; and interplay, consumer interfaces, and presentation concerns. moreover there are 3 introductory part surveys and an total workshop description summarizing the full occasion. In overall, the reader is gifted with a completely refereed and punctiliously edited cutting-edge document at the scorching interdisciplinary subject of database matters and knowledge visualization.

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Read or Download Database Issues for Data Visualization: IEEE Visualization '93 Workshop San Jose, California, USA, October 26, 1993 Proceedings PDF

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Extra info for Database Issues for Data Visualization: IEEE Visualization '93 Workshop San Jose, California, USA, October 26, 1993 Proceedings

Example text

Frank, "Towards a Spatial Query Language, User Interface Considerations", Proceedings of the l$th Internatinoal Conference on Very Large Databases, Los Angeles CA, 1988, 60-69. , "Abstracts: A Latency-Hiding Technique for High-Capacity Mass-Storage Systems", Sequoia 2000 Technical Report 92/11, University of California at Berkeley, June 1992. , C. Beshers, "Visualizing n-Dimensional Virtual Worlds with nvision", Computer Graphics, v24, n2n March 1990, 37-38. , "Lessons from a 'Living in a Database' Graphical User Interface", Proceedings of ACM-SIGMOD International Conference on Management of Data, 1984.

2 Research Areas To advance the state of the art in combining database and visualization systems from the human user perspective, focused research in five primary areas is required. The five research areas for interaction, user interfaces, and data presentation are: 1. A t a x o n o m y of the various information spaces, comprised of graphic, cognitive, perceptual, logical and physical elements. Also of taxonomic concern are the types of data sets resident within the system, which have a profound effect on the information spaces and structures created to deal with them.

G. , in case of a sensor failure). A structural data model defines behavior rather than implementation, but does so in terms of an underlying structure. That is, primitive types describe the operations that can be applied to primitive objects, but do so under the assumption that the state of a primitive object is a simple mathematical value. Similarly, aggregate types describe operations that return objects as functions of other objects, but do so in terms of hierarchical and network relations between objects.

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