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Visual Control of Big Data


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A new data-visualization tool lets users highlight aberrations and possible patterns in the graphical display.

Researchers at the Massachussetts Institute of Technology have come up with a data visualization tool that allows users to highlight abnormalities and possible patterns in a graphical display, and to determine which data sources are responsible for each.

Credit: Christine Daniloff/MIT

Researchers at the Massachusetts Institute of Technology (MIT) have developed DBWipes, a data visualization tool that enables users to highlight abnormalities and possible patterns in the graphical display. The tool also automatically determines which data sources are responsible for which.

The researchers also have designed a provenance-tracking system for large data sets. If a visualization system summarizes 100 million data entries into 100 points to render on the screen, then each of the 100 points will in some way summarize 1 million data points. The researchers say the provenance-tracking system provides a compact representation of the source of the summarized data so users can easily trace visualized data back to the source.

In addition, the researchers have developed a new algorithm, called Scorpion, that tracks down the records responsible for particular aspects of a DBWipes visualization and then recalculates the visualization to either exclude or emphasize the data they contain. MIT professor Samuel Madden says Scorpion's development was partly motivated by a study conducted by a researcher at a Boston hospital, who noticed a subset of patients in one of the hospital's wards was incurring much higher treatment costs than the rest.

From MIT News
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