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This folder contains advice and resources on high-quality visualization of astronomical data. Please email the ASAIP Editors for additional entries.


Circos A free (GPL) software package from Canada for data visualization in a circular layout.  Written in Perl.  Effective for big datasets in high dimensions, particularly with spatial relationships.  

D3.js  D3, or Data Driven Documents, is an open-source software package written in Javascript with a wide variety of graphs: bubble chart, dendrogram, streamgraph, chord diagram, circular graphs (node-line tree, hierarchical edge-bundling), Voronoi diagram, parallel coordinates, chloropleth, word cloud, contour plot,  animated Self-Organizing Map, and more.  Emphasis on producing Web documents from arbitrary datasets.  Written by Mike Bostock of the Stanford Vis Group and NY Times.  

Filtergraph  An interactive portal for fast display of large multivariate datasets.  Capabilities include scatter plots, histograms and tables with zoom, rotation, filtering, sorting, sharing, and flexible I/O.  Developed by the Vanderbilt Initiative in Data-Intensive Astrophysics.   

imMens  A system designed to support interactive visual exploration of large (billion-element) datasets of several types (ordinal, numeric, temporal, geographic).  Provides interactive brushing and linking, low dimensional projects, and rendering.  Developed in 2013 by the Stanford Vis Group.  

LCanimator  A visualizer of univariate time series as a movie of the data `assembling' over time.  Developed by the Vanderbilt Initiative in Data-Intensive Astrophysics.   

the Tractor Astronomical source detection, separation and photometry with an inferential basis.  Part of the project led by David Hogg and Dustin Lang. 

Viewpoints  A high-performance, interactive, exploratory analysis tool for large high-dimensional data. Its primary functionality is linked scatter plots with brushing for samples up to 107 rows and 102 columns that fit into CPU memory.  Developed at NASA-Ames, it is available here.    

yt  A Python-based analysis and visualization package for volumetric, multi-resolution data.  It is designed to visualize products of astrophysical theory such as hydrodynamical calculations allowing slices, projections, volume rendering, and multivariate maps.  

Collection of recent public visualization tools from, a large resource for data visualization and infographics in Switzerland. 

Collection of commercial and free visualization software from KDnuggets

Collection of 3D graphics and visualization tools for astronomy, particularly Blender, by Brian Kent (NRAO). 


Color schemes

ColorBrewer 2.0 Color advice for cartography.  Provides dozens of recommended color schemes for filling contour maps and displaying two-dimensional structures.  Designations in RGB, CMYK and HEX color systems are provided.

Color Hex Color Codes gives information about colors including color models (RGB,HSL,HSV and CMYK), Triadic colors, monochromatic colors and analogous colors calculated in color page.  Includes Popular Color Palettes, Latest Users Favourite Colors and >500 Color Names (e.g. DarkSeaGreen4 = #698b69).

HCL-Based Color Palettes Hue-Chroma-Luminance (HCL) is a perceptually-based color space discussed here that is well-designed for statistical graphics.  It is implemented for the R software system in the CRAN package colorspace.


Scientific visualization galleries

Universe3D hosts links to web content that enable the enhancement of our three-dimensional view of the Universe, with 3D viewers, datasets, images and videos from Alyssa Goodman at Harvard University. 

Cosmography of the Local Universe A superb movie of the 3-dimensional distribution of galaxies within ~50 Mpc of the Milky Way Galaxy, from IRFU CEA Saclay. 

NASA/Goddard Scientific Visualization Studio with animations and movies from Earth and solar science.  

Boston University's Introduction to scientific visualization tutorial

Collection of visualization galleries from D3

Astronomical research articles

B. R. Kent, 2013, Visualizing Astronomical Data with Blender, Pub. Astro. Soc. Pacific, 125, 731. High-quality three-dimensional graphics, from NRAO

A. H. Hassan et al., 2013, Tera-scale astronomical data analysis and visualization, Mon. Not. Royal Astro. Soc., 429, 2442-2455. High-throughput image analysis and visualization using a GPU cluster.

Buddelmeijer, H. & Valentijn, E., 2013, Query driven visualization of astronomical catalogs, Experimental Astronomy, 35, 283-300.  Visualization of large, dispersed catalogs using the Virtual Observatory's SAMP protocol. 

Koribalski, B. S., 2012, Overview on Spectral Line Source Finding and Visualisation, Publ. Astro. Soc. Australia, 29, 359-370.  Visualization of datacubes from radio interferometers using KARMA, SPLOTCH and other software packages. 

Goodman, A. A., 2012, Principles of high-dimensional data visualization in astronomy, Astron. Nachr., 333, 505-514.  Review of methods and software for linked-view, seamless visualization of multi-dimensional tabular, imaging, and catalog astronomical data.  

Woodring, J., et al., 2011, Analyzing and vlsualizing cosmological simulations with ParaView, Astrophys. J. Suppl, 195, #11.  Visualization of billion-particle 3D+time simulations of structure formation in the expanding universe. 

Hassan, A. & Fluke, C. J., 2011, Scientific visualization in astronomy: Towards the peta-scale astronomy era, Pub. Astro. Soc. Australia, 28, 150-170. Thorough review of visualizations needs, methods and software for modern astronomy.
Costa, A. et al. 2011, VisIVOWeb: A WWW environment for large-scale astrophysical visualization, Pub. Astro. Soc. Pacific, 123, 503-013.  Web portal for visual discovery of astronomical datasets within the Virtual Observatory framework.  
Rosales-Ortega, F., 2011, PINGSOFT: An IDL visualization and manipulation tool for integral field spectroscopic data, New Astronomy, 16, 220-228.
Hassan, A., Fluke, C. J. & Barnes, D. G. Interactive visualization of the largest radio astronomy cubes, New Astronomy, 16, 100-109. Uses a heterogeneous cluster of CPUs and GPUs. 


General research articles 

Johnson, C. 2004, Top scientific visualization research problems, IEEE Computer Graphics and Applications, 24, 13-17

Chen, C., 2005, Top 10 unsolved information visualization problems, IEEE Computer Graphics and Applications, 25, 12-16