Smart Brushing for Parallel Coordinates

The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges whenusing parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address thesechallenges. Since its conception, limited improvements have been made to brushing both in the form of visual design and functionalinteraction. We present a set of novel, smart brushing techniques that enhance the standard interactive brushing of a parallel coordinatesplot. We introduce two new interaction concepts: Higher-order, sketch-based brushing, and smart, data-driven brushing. Higher-orderbrushes support interactive, flexible, n-dimensional pattern searches involving an arbitrary number of dimensions. Smart, data-drivenbrushing provides interactive, real-time guidance to the user during the brushing process based on derived meta-data. In addition, weimplement a selection of novel enhancements and user options that complement the two techniques as well as enhance the explorationand analytical ability of the user. We demonstrate the utility and evaluate the results using a case study with a large, high-dimensional,real-world telecommunication data set and we report domain expert feedback from the data suppliers

AgentVis: Visual Analysis of Agent Behavior with Hierarchical Glyphs

Glyphs representing complex behavior provide a useful and common means of visualizing multivariate data. However, due to their complex shape, overlapping and occlusion of glyphs is a common and prominent limitation. This limits the number of discreet data tuples that can be displayed in a given image. Using a real-world application, glyphs are used to depict agent behavior in a call center. However, many call centers feature thousands of agents. A standard approach representing thousands of agents with glyphs does not scale. To accommodate the visualization incorporating thousands of glyphs we develop clustering of overlapping glyphs into a single parent glyph. This hierarchical glyph represents the mean value of all child agent glyphs, removing overlap and reducing visual clutter. Multi-variate clustering techniques are explored and developed in collaboration with domain experts in the call center industry. We implement dynamic control of glyph clusters according to zoom level and customized distance metrics, to utilize image space with reduced overplotting and cluttering. We demonstrate our technique with examples and a usage scenario using real-world call-center data to visualize thousands of call center agents, revealing insight into their behavior and reporting feedback from expert call-center analysts

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity