npGLC-Vis Library for Multidimensional Data Visualization

LUQUE, LEANDRO E.; GANUZA, MARÍA LUJÁN; ANTONINI, ANTONELLA S.; CASTRO, SILVIA M.

Cloud Computing, Big Data & Emerging Topics

Springer Nature

Año: 2021; p. 188 - 202

While information is growing exponentially, datasets are get-ting bigger and bigger containing valuable information that can expandhuman knowledge. To extract meaningful information from these densedatasets, the need for effective graphical representations that take advan-tage of the the human?s visual perception capabilities is revealed. Thevisualization of these kind of data is a complex task. These big datasetsare in general inherently multidimensional (n-D), facing the challenge offinding suitable mappings from the n-D space to a 2D or 3D space. Eventhough multiple visualization methods have been developed for n-D data,many of them do not allow the restoration of the n-D data completelyfrom its reduced representation and/or do not represent the completen-D dataset. The General Lines Coordinates (GLC) are reversible visualrepresentations that preserve n-D information for knowledge discovery.In this paper, we present thenpGLC-VisLibrary, a data visualizationlibrary supporting Non-Paired General Line Coordinates (npGLC) withassociated traditional interactions like brushing, zooming, and panning.npGLC-Visis a collection of visualization methods, designed for exper-imenting withnpGLCtechniques in the development of visualizationapplications. We present the library design and implementation, and ex-emplify it through the representation of different datasets.