Creates visualization plots for 2D projected data including ellipse plots, Voronoi diagram plots, and combined ellipse-Voronoi plots. Designed to visualize class separation in dimensionally reduced data from techniques like principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or others. For more details see Lotsch and Ultsch (2024) <doi:10.1016/j.imu.2024.101573>.

Fortune's (1987, <doi:10.1007/BF01840357>) algorithm is a very efficient method to perform Voronoi tessellation and Delaunay triangulation. This package is a port of the original code published in the early 1990's by Steven Fortune.

The d3.js framework with the plugins d3-voronoi-map, d3-voronoi-treemap and d3-weighted-voronoi
        are used to generate Voronoi treemaps in R and in a shiny application.
        The computation of the Voronoi treemaps are based on Nocaj and Brandes (2012)
        <doi:10.1111/j.1467-8659.2012.03078.x>.

Export dataframes and automatically start importing into 
    'Vorteks'. 'Vorteks Visualization Environment (VVE)' and 'Vorteks Data Manager (VDM)' will start an import. 'Vorteks Processing Environment (VPE)' will start a new project and
    add a file reader with the dataframe file already set.
    Warning: WINDOWS ONLY. Requires installation of 'Vorteks' software.

Contains selected data from two publications,
    Campbell 'et' 'al'. (2016) <DOI:10.1080/14486563.2015.1028486>
    and 'Pacioni' 'et' 'al'. (2017) <DOI:10.1071/PC17002>.
    The data is provided both as raw outputs from the population viability
    analysis software 'Vortex' and packaged as R objects.
    The R package 'vortexR' uses the raw data provided here to illustrate its
    functionality of parsing raw 'Vortex' output into R objects.

Collects tweets and metadata for threaded conversations and
    generates networks.

A 'Shiny' application for the interactive visualisation and
    analysis of networks that also provides a web interface for collecting
    social media data using 'vosonSML'.