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Maintaining interactivity while exploring massive time series
2008
2008 IEEE Symposium on Visual Analytics Science and Technology
The speed of data retrieval qualitatively affects how analysts visually explore and analyze their data. To ensure smooth interactions in massive time series datasets, one needs to address the challenges of computing ad hoc queries, distributing query load, and hiding system latency. In this paper, we present ATLAS, a visualization tool for temporal data that addresses these issues using a combination of high performance database technology, predictive caching, and level of detail management. We
doi:10.1109/vast.2008.4677357
dblp:conf/ieeevast/ChanXGH08
fatcat:kazdl6j4abavfdzogxievujjvq