Communications of the ACM
Software Transforms Complex Data Into Visualizable Shapes
Researchers at Dartmouth College have developed an open source software package that leverages mathematical techniques to understand high-dimensional datasets via the underlying geometric structures they reflect.
Credit: Contextual Dynamics Laboratory/Dartmouth College
HyperTools is an open source software package developed by Dartmouth College researchers that leverages a suite of mathematical techniques to understand high-dimensional datasets via the underlying geometric structures they reflect.
The software can be used to convert data into visualizable shapes or animations, which can then be employed to compare different datasets, intuitively gain insights into underlying patterns; generalize across datasets, and develop and test theories relating to big data.
"Our tool turns complex data into intuitive 3D [three-dimensional] shapes that can be visually examined and compared," says Dartmouth's Jeremy R. Manning.
The researchers demonstrated their work with HyperTools visualizations of brain activity in response to movie frames, of changes in temperature measurement across the Earth between 1975 and 2013, and of the content of political tweets by Hillary Clinton and Donald Trump during the 2016 presidential campaign.
HyperTools can also be used to guide the development of new machine learning algorithms.
From Dartmouth College
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