Techniques provide users with insights into high-dimensional datasets
Every dataset in the observable universe has a fundamental geometry or shape to it, but that structure can be highly complicated. To make it easier to visualize complicated datasets, a Dartmouth research team has created HyperTools-- an open-source software package that leverages a suite of mathematical techniques to gain intuitions about high-dimensional datasets through the underlying geometric structures they reflect. The findings are published in the Journal of Machine Learning Research.
This is a visualization using HyperTools to represent the content of Wikipedia articles. Each dot represents a single Wikipedia article (from a set of 3,000 randomly chosen articles). The dot positions reflect what the articles are about (nearby dots are about similar topics), and the dot colors reflect automatically discovered "clusters" of articles that are about similar themes. To view a 3-D animation of this data (GIF file), go to: http://discovery.dartmouth.edu/~jmanning/hypertools_gifs/wiki.gif
Credit: Static image by Contextual Dynamics Laboratory, Dartmouth College
HyperTools can be used to transform data into visualizable shapes or animations, which can be used to: compare different datasets, gain insights into underlying patterns in an intuitive way, make generalizations across datasets, and develop and test theories relating to the Big Data.
"The datasets we're faced with as modern scientists can be enormously complex, often reflecting many interacting components," explains senior author, Jeremy R. Manning, an assistant professor of psychological and brain sciences and director of the Contextual Dynamics Lab at Dartmouth.
"Our tool turns complex data into intuitive 3-D shapes that can be visually examined and compared. Essentially, we are leveraging the visual system's amazing ability to find patterns in the world around us to also find patterns in complex scientific data."
The researchers demonstrate how HyperTools can be applied to various types of data. In the paper, they showcase visualizations of: brain activity, movie frames and brain responses to watching those frames; changes in temperature measurements across the Earth's surface from 1875 to 2013; and the thematic content of political tweets issued by Hillary Clinton and Donald Trump during the 2016 US presidential campaign.
In addition to using HyperTools to directly understand the geometric structure of data, the insights revealed by the tool can also be used to guide the development of machine learning algorithms. For example, the data visualizations can reveal how different types of observations form structured distinct clusters (e.g. Trump tweets vs. Clinton tweets) that could be used to understand the similarities and differences between groups.
As part of the HyperTools toolbox, Manning's lab continues to develop and release other types of geometric visualization analyses, including the recently launched text analyses.
Manning is available for comment at: email@example.com.
The study's other authors include Dartmouth postdoctoral researcher Andrew Heusser and graduate student Kirsten Ziman (lead co-authors) and graduate student Lucy Owen, all members of Manning's lab.
GIFs and hi-res still images are available upon request.
Amy D. Olson | EurekAlert!
Quantum computers by AQT and University of Innsbruck leverage Cirq for quantum algorithm development
16.09.2019 | Universität Innsbruck
Artificial Intelligence speeds up photodynamics simulations
12.09.2019 | University of Vienna
Researchers from the Department of Atomically Resolved Dynamics of the Max Planck Institute for the Structure and Dynamics of Matter (MPSD) at the Center for Free-Electron Laser Science in Hamburg, the University of Hamburg and the European Molecular Biology Laboratory (EMBL) outstation in the city have developed a new method to watch biomolecules at work. This method dramatically simplifies starting enzymatic reactions by mixing a cocktail of small amounts of liquids with protein crystals. Determination of the protein structures at different times after mixing can be assembled into a time-lapse sequence that shows the molecular foundations of biology.
The functions of biomolecules are determined by their motions and structural changes. Yet it is a formidable challenge to understand these dynamic motions.
At the International Symposium on Automotive Lighting 2019 (ISAL) in Darmstadt from September 23 to 25, 2019, the Fraunhofer Institute for Organic Electronics, Electron Beam and Plasma Technology FEP, a provider of research and development services in the field of organic electronics, will present OLED light strips of any length with additional functionalities for the first time at booth no. 37.
Almost everyone is familiar with light strips for interior design. LED strips are available by the metre in DIY stores around the corner and are just as often...
Later during this century, around 2060, a paradigm shift in global energy consumption is expected: we will spend more energy for cooling than for heating....
Researchers from the Department of Atomically Resolved Dynamics of the Max Planck Institute for the Structure and Dynamics of Matter (MPSD) at the Center for Free-Electron Laser Science in Hamburg, the University of Potsdam (both in Germany) and the University of Toronto (Canada) have pieced together a detailed time-lapse movie revealing all the major steps during the catalytic cycle of an enzyme. Surprisingly, the communication between the protein units is accomplished via a water-network akin to a string telephone. This communication is aligned with a ‘breathing’ motion, that is the expansion and contraction of the protein.
This time-lapse sequence of structures reveals dynamic motions as a fundamental element in the molecular foundations of biology.
Two research teams have succeeded simultaneously in measuring the long-sought Thorium nuclear transition, which enables extremely precise nuclear clocks. TU Wien (Vienna) is part of both teams.
If you want to build the most accurate clock in the world, you need something that "ticks" very fast and extremely precise. In an atomic clock, electrons are...
10.09.2019 | Event News
04.09.2019 | Event News
29.08.2019 | Event News
18.09.2019 | Innovative Products
18.09.2019 | Physics and Astronomy
18.09.2019 | Materials Sciences