<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Goodman, Alyssa A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Principles of High-Dimensional Data Visualization in Astronomy</style></title><secondary-title><style face="normal" font="default" size="100%">Astronomische Nachrichten</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://astrobites.com/2012/05/24/data-overload-how-to-deal-with-multidimensional-data-sets/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">333</style></volume><pages><style face="normal" font="default" size="100%">505-514</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;sets, though, interactive exploratory data visualization can give far more insight than an approach where data processing&lt;br /&gt;
and statistical analysis are followed, rather than accompanied, by visualization. This paper attempts to charts a course&lt;br /&gt;
toward “linked view” systems, where multiple views of high-dimensional data sets update live as a researcher selects,&lt;br /&gt;
highlights, or otherwise manipulates, one of several open views. For example, imagine a researcher looking at a 3D volume&lt;br /&gt;
visualization of simulated or observed data, and simultaneously viewing statistical displays of the data set’s properties&lt;br /&gt;
(such as an x-y plot of temperature vs. velocity, or a histogram of vorticities). Then, imagine that when the researcher&lt;br /&gt;
selects an interesting group of points in any one of these displays, that the same points become a highlighted subset in&lt;br /&gt;
all other open displays. Selections can be graphical or algorithmic, and they can be combined, and saved. For tabular&lt;br /&gt;
(ASCII) data, this kind of analysis has long been possible, even though it has been under-used in Astronomy. The bigger&lt;br /&gt;
issue for Astronomy and several other “high-dimensional” fields is the need systems that allow full integration of images&lt;br /&gt;
and data cubes within a linked-view environment. The paper concludes its history and analysis of the present situation&lt;br /&gt;
with suggestions that look toward cooperatively-developed open-source modular software as a way to create an evolving,&lt;br /&gt;
flexible, high-dimensional, linked-view visualization environment useful in astrophysical research.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">5-6</style></issue></record></records></xml>