Cross-Scale, Multi-Scale, and Multi-Source Data Visualization and Analysis Issues and Opportunities - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 341

￿

Develop quantifiable scalable visual representations, data representations, and
software tools for various domains.

￿ Develop new methods for abstraction of massive streaming data from textual

sources, satellite data, Sensor data, video data, and other information streams.

￿ Develop new research capabilities for information fusion. These methods should

utilize visual analytic techniques to extract the relevant nuggets of information
from heterogeneous multi-source multi-dimensional time-varying information
streams, fusing these pieces into explorable information space.

References

1. Eick, S.G., Karr, A.F.: Visual scalability. J. Comput. Graph. Stat. 11 (1), 22-43 (2002)
2. Robertson, G.G., Ebert, D.S., Eick, S.G., Keim, D.A., Joy, K.: Scale and complexity in visual
analytics. Inf. Vis. 8 (4), 247-253 (2009)
3. Thomas, J.J., Cook, K.A. (eds.): Illuminating the path: the research and development agenda for
visual analytics. IEEE CS Press, NJ (2005)