VisAstro 2020

Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, Educating the Earth

Part of IEEE VIS 2020

A virtual workshop, 12:00 PM - 3:30 PM MDT, October 26, 2020.


Juna Kollmeier
Staff Scientist
Carnegie Institution for Science
Director of the fifth phase of the Sloan Digital Sky Survey (SDSS-V)
jak AT

Lauren Anderson
Carnegie Postdoctoral Fellow
Carnegie Institution for Science
landerson AT

Bei Wang
Assistant Professor
School of Computing
Scientific Computing and Imaging (SC) Institute
University of Utah
beiwang AT

New! Data Challenge: Visualizing the Cosmic Web

Data challenge introduction and motivation

The standard model of cosmology posits that the Universe is dominated by unknown forms of dark matter and dark energy. In order to test this extraordinary scenario, we require precise, theoretical predictions for how such a Universe would appear when observed. One of our most powerful tools to do so are cosmological, hydrodynamical simulations. These are "Universes in a box" -- large numerical calculations which seek to simulate a large volume of a synthetic Universe. Starting from initial conditions shortly after the Big Bang, they solve mathematical models for the coupled evolution of dark matter, gas, stars, and black holes within an expanding space-time, for the 14 billion years of time until the present day. Within these virtual Universes, astrophysical processes lead to the formation and evolution of galaxies as well as the "cosmic web" of large-scale structure.

IllustrisTNG is a suite of several cosmological simulations. It provides catalogs of simulated galaxies: their positions in 3D space, together with dozens of additional properties, such as their mass, shape, size, gas contents, star formation activity, and so on. The positions of galaxies (or, of matter itself) can be used to construct a model for the cosmic web, made up of different structures: voids, sheets, and filaments. Many properties of galaxies are thought to be intricately linked to their position and relationship to this cosmic web, but these links are not well understood.

Our data challenge to visualize this cosmic web and its relationship to the embedded galaxies.

Novel visualizations of the relationship between galaxies and the cosmic web they are embedded within can lead to new insights on the physical processes which shape galaxies across cosmic time. For inspiration, specific concrete examples could include: do galaxies "know" about their place in the cosmic web? Does the "color" of a galaxy depend on its distance to the nearest sheet, void, or node of the web? For spiral, disk-shaped galaxies, is the direction of their rotation aligned with the direction(s) of nearby filaments?


All the data is available at (requires making an account).

Use snapshot 99 under TNG100-1 which is redshift zero (present day).

One can follow the short “Example Scripts” tutorial on that same webpage to get familiar with how the catalog is structured, how to load it, etc.

For questions regarding the dataset itself, please contact Dylan Nelson (dnelson AT

For questions regarding the data challenge, please contact Lauren Anderson (landerson AT

Submission Guidelines

Your submission should include: Submissions of solution to the Data Challenge can be done by sharing the solution with Lauren Anderson (landerson AT via Google Drive (or similar file storage service). Submission that is less than 20 MB may be emailed directly.

The submission deadline is Oct 19, 2020

The submissions will be reviewed by the organizers and discussed during the workshop. The organizers might contact the authors for additional information and feedbacks.


Congratulations to Joseph N. Burchett, David Abramov, Oskar Elek, and Angus G. Forbes for winning the data challenge!

Award Certificate: Visualization in Astrophysics: Data Challenge Certificate

Winning submission:


The Workshop: Goals, Scope, and Focus

Astrophysics has been a primary beneficiary of Moore’s law. Advances in computational infrastruc- ture have enabled both our capacity to record increasing amounts of information for an increasingly large number of objects in the universe, and our ability to numerically predict the full evolutionary history of the universe.

Although we have benefited from these advances, we have not fully utilized these rich data sources, and we observe an even greater disparity in our future. Certainly, we have made major discoveries with these datasets, and our theoretical predictions are the most sophisticated the field has ever seen. However, with the next generation of advanced computations and surveys, we find ourselves face-to-face with a “digital tsunami” of both simulated and observed data. It is clear that our 20th century interrogation techniques will be insufficient for the task at hand. The data is too large and rich to be simplified to basic equations and summary statistics – the classical way we test our predictions, or to be visualized naively without careful consideration of its scale.

Generously, the same revolution that gave us this great wealth of data can also provide the solution. Far from a fantasy of the future, modern computational power is enabling us to visualize and analyze the complex data sets we are predicting and observing. We just need to bring these modern visual and analysis techniques to these rich datasets; we need to bring together experts from both visualization and astronomy.

Why Now?

Until relatively recently, we have been using traditional analytic and statistical methods to analyze the astronomy datasets. Typically the data were sufficiently simple that these techniques were adequate; this is no longer the case. For example, we now have very large quantities of high- dimensionality data, and by applying the same, old techniques to this data we are, necessarily, losing information. This information is hard-earned, either from years of surveying the sky or millions of hours of CPU computation time. In order to make the best use of this data, we must focus on novel methods of analysis and visualization.

Goals and Scope

With this workshop, we aim to bring together members of the astronomical community and members of the visualization community with the goals of discussing:


The focus of this workshop is to build connections and collaborations between these two communities: data-rich, but technique-starved astronomers, and data-hungry and technique-rich visualization experts. These connections are ripe with low hanging fruits, which can be discussed and worked on during a single day workshop. To facilitate a common language and collaborations, we will present visualization min-challenges with a well-curated astronomy dataset on the workshop website 6 months prior to the workshop. For more challenging problems/datasets, the workshop serves as a forum to establish the initial collaborations. It helps visualization researchers to understand astronomy datasets, and it offers astronomers an opportunity to understand existing visualization techniques and tools. Co-organizer L. Anderson has precisely a dataset and visualization mini-challenge appropriate to this goal. We will also solicit other data challenges from throughout the astronomical community for interested individuals. We anticipate that the solution to these data challenges will be published in the astronomical and perhaps visualization literature but will be publicly accessible through arXiv. We are confident that the very specific mini-challenge will serve to rapidly focus both groups on existing problems (rather than purely esoteric and/or theoretical grounds) and thus begin a larger cross-community dialog.

Confirmed Keynote Speakers

Alyssa Goodman, Department of Astronomy, Harvard University
Alexander Bock, Linköping University and University of Utah, Development Lead for the OpenSpace project

Confirmed Invited Speakers

Jackie Faherty, American Museum of Natural History
Matthew J Turk, Department of Astronomy, University of Illinois at Urbana-Champaign
Michelle Borkin, Khoury College of Computer Sciences, Northeastern University
Angus Forbes, Computational Media Department, University of California, Santa Cruz
Joseph N. Burchett, Department of Astronomy, New Mexico State University


The workshop will be a half-day event.

Participants and Intended Audience

The workshop targets both visualization researchers and astronomers. We welcome participation from both the astronomy and visualization communities. We expect a reasonable presence of astronomers at the workshop given the large presence of astronomers at local universities. And given the dearth of visualization techniques currently available to the astronomical community, we also think this workshop, and it’s hands-on approach, will peak the interest of many non-local astronomers as well. The VIS 2020 conference ensures a quorum of visualization experts.


Tentative Schedule

12:00 PM - 1:30 PM: Session 1 (90 minutes) 1:30 PM - 2:00 PM: Break (25 minutes)

2:00PM - 3:30 PM: Session 2 (90 minutes)


The Past, Present and Future of Visualization in Astronomy

Alyssa Goodman

Abstract: Astronomers have been visually representing their ideas and observations throughout human history. Today, astronomers' visualization challenges extend to some of the largest, most diverse, and high-dimensional data sets in science, and their largely open-source tools are being optimized to accelerate the pace of discovery. In this talk, I will begin with a very short history of astronomy visualization, highlighting the work of Ptolemy and Galileo. Then, I’ll focus on how tools and libraries used by today’s astronomers (including astropy, WorldWide Telescope, yt, glue, OpenSpace, the Jupyter ecosystem, and more) are evolving into a flexible, modular, system of systems that allows experts and novices alike to carry out exploratory and explanatory data visualization. I will conclude with thoughts on the future, with particular focus on how new generations of astronomers may be trained to think about data science, visualization, astrophysics, education, and outreach simultaneously, using systems flexible enough to facilitate a seamless spectrum connecting basic education to cutting-edge research.

Speaker Bio: Alyssa Goodman is the Robert Wheeler Willson Professor of Applied Astronomy at Harvard University, co-Director for Science at the Radcliffe Institute for Advanced Study, and a Research Associate of the Smithsonian Institution. Goodman's research and teaching interests span astronomy, data visualization, and online systems for research and education. Goodman received her undergraduate degree in Physics from MIT in 1984 and a Ph.D. in Physics from Harvard in 1989. Goodman was awarded the Newton Lacy Pierce Prize from the American Astronomical Society in 1997, became full professor at Harvard in 1999, was named a Fellow of the American Association for the Advancement of Science in 2009, and chosen as Scientist of the Year by the Harvard Foundation in 2015. Goodman has served as Chair of the Astronomy Section of the American Association for the Advancement of Science and on the National Academy's Board on Research Data and Information, and she currently serves on the both the IAU and AAS Working Groups on Astroinformatics and Astrostatistics.

Goodman's personal research presently focuses primarily on new ways to visualize and analyze the tremendous data volumes created by large and/or diverse astronomical surveys, and on improving our understanding of the structure of the Milky Way Galaxy. She is the PI of the NSF and NASA-sponsored glue software effort, which creates new tools for high-dimensional data visualization across science and education. She also works closely with colleagues at the American Astronomical Society and Harvard to expand the use of the WorldWide Telescope Universe Information System, in both research and education. Goodman leads the Prediction project at Harvard University, focused on tracing back the roots of modern computer simulation, as prediction, through history, all the way back to the sheep entrail divination practiced in Mesopotamia.

Bridging the Gap: Bringing Expert Tools into Planetariums and Living Rooms

Alexander Bock

Abstract: We are living in a world in which our understanding of the cosmos is driven primarily by data, both acquired through telescopes as well as simulations. The bottleneck for disseminating this wealth of information is usually the ability for the interested general public to start exploring the data by themselves in a guided fashion. Thus far, there have been gaps between tools that the public can use to explore the universe and the tools used by scientists to discovery new phenomena. In this talk, I will present our ongoing work on the software platform OpenSpace, which is an open-source software that aims to close this gap by enabling the use of the same software platform for scientists, presenters in a planetarium, and the general public on their home computer. Using the same software in these diverse usage cases makes it possible to shorten the distance between scientific discoveries and the dissemination of it.

Speaker Bio: Alexander Bock has received his PhD in Visualization and Interaction from Linköping University, Sweden for his work on designing visualization applications tailored for both scientific discoveries and use for the general public. He is currently a Research Fellow at Linköping University and the University of Utah. Prior to this, he has been a Moore-Sloan Data Science Fellow at New York University and a visiting Research Scholar with the Community Coordinated Modeling Center at NASA's Goddard Space Flight Center, USA in 2015. Aside from conducing scientific visualization research, he is also the Development Lead on the open-source Astrovisualization software OpenSpace, developed in collaboration between Linköping University, the American Museum of Natural History, NASA, New York University, and the University of Utah. Bock was awarded 2014 and 2015 with the Best Scientific Visualization poster and 2017 with the Best Scientific Visualization paper awards at the IEEE Visualization conference for his work in the field of Astrovisualization.

Visualizing the Dynamic Milky Way for Science and Education

Jacqueline Faherty

Abstract: The European space agency's second catalog of the Gaia mission is revolutionizing astronomy. Arguably all scientific questions can benefit from the nearly 1.4 billion parallaxes and proper motions, over 7 million radial velocities, photometric data in Gaia’s three bands (G, R, and B), variability information, and effective temperatures for a subset of objects. The Gaia results provide a unique opportunity for astronomers, data visualizers, and educators. Stellar positions and velocities enable us to map the Milky Way and examine the dynamics of stellar streams, co-moving companions, hypervelocity stars, nearby moving groups, and solar system encounters. From a visualization perspective, real time rendering of Gaia data is a challenge. In this presentation, I will show the results of our visualization efforts with the Gaia catalog at the American Museum of Natural History. The visuals generated for this talk isolate scientifically rich data and stories, which can lead to scientific discovery and will illuminate Gaia data for students, teachers and the general public.

Speaker Bio: Dr. Jackie Faherty received her bachelors degree in Physics from the University of Notre Dame and her PhD in Physics from Stony Brook University. Post PhD, she spent two years at the Universidad de Chile on a National Science Foundation International Research Fellowship (NSF-IRFP) and three years at the Carnegie Institution for Science on a NASA Hubble Fellowship. She is now a permanent scientific staff member jointly in the department of Astrophysics and the department of Education at the American Museum of Natural History (AMNH). Dr. Faherty co-runs a dynamic research group at AMNH entitled Brown Dwarfs in New York City (BDNYC). Her team has won multiple grants from NASA, NSF, and the Heising Simons foundation to support projects focused on characterizing planet-like objects. She has also co-founded the popular citizen science project entitled Backyard Worlds: Planet 9 which invites the general public to help scan the solar neighborhood for previously missed cold worlds. Faherty has over 90 peer reviewed articles in Astrophysical journals, has been an invited speaker at University’s and conferences across the globe and is a major advocate for utilizing visualization tools for both science and education advancements. Aside from a love of scientific research, Dr. Faherty is a passionate educator and can often be found giving public lectures in the Hayden Planetarium. She holds a unique position at the American Museum of Natural History that allows her to pursue scientific research at the forefront of exoplanet characterization studies while mentoring and advising education programs for students and general public alike.

A Grammar of Analysis for Volumetric Astrophysical Data

Matthew Turk

Abstract: Analyzing complex, multi-source, multi-format and multi-modal data from astrophysical simulations, observations and theory requires methods for transforming raw numbers into manipulable quantities, and the application of high-level semantic models on top of those quantities. In this talk I will present methods for defining and applying a grammar of analysis to volumetric astrophysical data, and describe the implications this has for visualization, analysis and inference in astrophysics.

Speaker Bio: Matthew Turk is an assistant professor in the School of Information Sciences at the University of Illinois Urbana-Champaign and also holds an appointment with the Department of Astronomy in the College of Liberal Arts and Sciences. His research is focused on how individuals interact with data and how that data is processed and understood. He received his doctoral degree in physics from Stanford University in 2009. He completed postdoctoral work at the University of California at San Diego and an NSF Fellowship in Transformative Computational Science at Columbia University. He came to Illinois in 2014 to work as a research scientist at the National Center for Supercomputing Applications and as a research assistant professor in the Department of Astronomy.

Bridging Domains and Dimensions with glue

Michelle Borkin

Abstract: In this talk I will share personal experiences and reflections on opportunities for visualization in astrophysics and beyond through the lens of my personal journey from the fields of astrophysics to visualization and back. As part of my talk I will feature my current astrophysics visualization work and collaborations, in particular the glue multi-dimensional linked-data exploration software ( Glue is an open-source Python library to explore relationships within and between related datasets and was originally developed for astronomy to facilitate data analysis and visualization for NASA's James Webb Space Telescope. Glue continues to grow to bridge domains and data dimensions in support of effective data analysis and visualization.

Speaker Bio: Michelle Borkin is an Assistant Professor in the Khoury College of Computer Sciences, Northeastern University. Her research focuses on the development of novel visualization techniques and tools to enable new insights and discoveries in data. Her research spans visualization and human-computer interaction with interests across disciplines including medical imaging, network visualization, perception and cognition, accessibility, and astronomy and physics. She is the visualization research lead and an original project member of the NSF and NASA-sponsored glue multi-dimensional linked-data exploration software.

Michelle received a Ph.D. in 2014 and an M.S. in 2011, both in Applied Physics, and a B.A. in Astronomy and Astrophysics & Physics from Harvard University. Prior to joining Northeastern, Borkin was a postdoctoral research fellow in computer science at the University of British Columbia and a research fellow at Brigham & Women’s Hospital. She was previously a National Science Foundation graduate research fellow, a National Defense Science and Engineering graduate fellow, and a TED fellow.

Visualizing Extragalactic Ecosystems

Joseph N. Burchett and Angus G. Forbes

Abstract: We present results from a series of projects developed collaboratively over the last two years by a team of interdisciplinary researchers at University of California, Santa Cruz, which includes experts in visual analytics, simulation, data sonification, and astrophysics. These projects investigate the intergalactic medium (IGM) and circumgalactic medium (CGM) in context with the galaxies residing within, representing the inherently multi-dimensional datasets using novel interactive visualization techniques: IGM-Vis is a web-based spectroscopic analysis tool for the intergalactic medium; Polyphorm is an interactive visualization tool that enables inferring Cosmic Web structure using a novel method based on the foraging behavior of slime mold; CosmoVis is a web-based tool for analyzing large cosmological simulations. In addition to presenting details about these projects and describing the scientific results they have produced, we discuss effective collaboration strategies and outline future research tasks enabled by our visualization approaches.

Speaker Bio for Joseph N. Burchett: Dr. Joseph N. Burchett is an Assistant Professor of Astronomy at New Mexico State University. An observational astronomer, Joe studies the evolution of galaxies and the most massive structures in the Universe with an emphasis on the gas in and around these objects. In addition to using traditional astronomical techniques, he embraces novel interdisciplinary approaches such as creative data visualization and sonification. He earned his Ph.D. in Astronomy at the University of Massachusetts Amherst and then went on to University of California, Santa Cruz as a postdoctoral fellow before joining NMSU this Fall.

Speaker Bio for Angus G. Forbes: Dr. Angus G. Forbes is an Associate Professor at University of California, Santa Cruz, where he directs the Creative Coding Lab within the Department of Computational Media. Angus’ research investigates novel techniques for visualizing and interacting with complex scientific information. He was the Arts Papers chair for ACM SIGGRAPH in 2018 and will serve as the ACM SIGGRAPH Art Gallery chair in 2021. He currently serves on the IEEE VIS InfoVis Program Committee and he chaired the IEEE VIS Arts Program (VISAP) from 2013 to 2017.

Recent Literature on Visualization in Astrophysics (An Incomplete List)

Please email Bei Wang (beiwang AT if a certain paper should be added to the list.

New! Survey Website

(Beta version, developed by Michael Young)
  1. Techniques and Methods for Astrophysical Data Visualization.
    Brian R. Kent, Guest Editor
    Publications of the Astronomical Society of the Pacific (PASP)
    A special focus issue from the PASP.

  2. Scientific Visualization in Astronomy: Towards the Petascale Astronomy Era.
    Amr Hassan, Christopher J. Fluke
    Publications of the Astronomical Society of Australia
    DOI: 10.1071/AS10031

  3. Visualization for the Physical Sciences.
    Dan R. Lipşa, Robert S. Laramee, Simon J. Cox, Jonathan C. Roberts, Rick Walker, Michelle A. Borkin, Hanspeter Pfister
    Computer Graphics Forum
    DOI: 10.1111/j.1467-8659.2012.03184.x

  4. Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes.
    Paul Rosen, Anil Seth, Betsy Mills, Adam Ginsburg, Julia Kamenetzky, Jeff Kern, Chris R. Johnson, Bei Wang.
    Topology-Based Methods in Visualization (TopoInVis), 2019.

  5. New Thinking on, and with, Data Visualization.
    Alyssa A. Goodman, Michelle A. Borkin, Thomas P. Robitaille

  6. The Application of the Montage Image Mosaic Engine to the Visualization of Astronomical Images.
    G. Bruce Berriman, J. C. Good
    Publications of the Astronomical Society of the Pacific
    DOI: 10.1088/1538-3873/aa5456

  7. Interactive Exploration of Cosmological Dark-Matter Simulation Data.
    Aaron Scherzinger, Tobias Brix, Dominik Drees, Andreas Volker, Kiril Radkov, Niko Santalidis, Alexander Fieguth, Klaus H Hinrichs
    IEEE Computer Graphics and Applications
    DOI: 10.1109/MCG.2017.20

  8. Visual verification of space weather ensemble simulations.
    Alexander Bock, Asher Pembroke, M. Leila Mays, Lutz Rastaetter, Timo Ropinski, Anders Ynnerman
    2015 IEEE Scientific Visualization Conference (SciVis)
    DOI: 10.1109/SciVis.2015.7429487

  9. Cosmography and Data Visualization
    Daniel Pomarède, Hélène M. Courtois, Yehuda Hoffman, R. Brent Tully
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/aa5b73

  10. Interactive Visual Exploration of Halos in Large Scale Cosmology Simulation
    Guihua Shan, Maojin Xie, FengAn Li, Yang Gao, Xuebin Chi
    Journal of Visualization
    DOI: 10.1007/s12650-014-0206-5

  11. An integrated visualization system for interactive analysis of large, heterogeneous cosmology data
    Annie Preston, Ramyar Ghods, Jinrong Xie, Franz Sauer, Nick Leaf, Kwan-Liu Ma, Esteban Rangel, Eve Kovacs, Katrin Heitmann, Salman Habib
    2016 IEEE Pacific Visualization Symposium (PacificVis)
    DOI: 10.1109/PACIFICVIS.2016.7465250

  12. Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe
    Timothy Basil Luciani, Brian Cherinka, Daniel Oliphant, Sean Myers, W. Michael Wood-Vasey, Alexandros Labrinidis, G. Elisabeta Marai
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2014.2312008

  13. Revealing the Dark Threads of the Cosmic Web
    Joseph N. Burchett, Oskar Elek, Nicolas Tejos, J. Xavier Prochaska, Todd M. Tripp, Rongmon Bordoloi, Angus G. Forbes
    The Astrophysical Journal
    DOI: 10.3847/2041-8213/ab700c

  14. IGM‐Vis: Analyzing Intergalactic and Circumgalactic Medium Absorption Using Quasar Sightlines in a Cosmic Web Context
    Joseph N. Burchett, David Abramov, Jasmine Otto, Cassia Artanegara, J. Xavier Prochaska, and Angus G. Forbes
    Computer Graphics Forum
    DOI: 10.1111/cgf.13705

  15. Vaex: big data exploration in the era of Gaia
    Maarten A. Breddels and Jovan Veljanoski
    Astronomy and Astrophysics
    DOI: 10.1051/0004-6361/201732493

  16. Felix: A Topology Based Framework for Visual Exploration of Cosmic Filaments
    Nithin Shivashankar, Pratyush Pranav, Vijay Natarajan, Rien van de Weygaert, E.G. Patrick Bos, Steven Rieder
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2015.2452919

  17. A Case Study in Astronomical 3D Printing: The Mysterious η Carinae
    Thomas I. Madura
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/129/975/058011

  18. Linking the X3D Pathway to Integral Field Spectrographs: YSNR 1E 0102.2-7219 in the SMC as a Case Study
    Frédéric P. A. Vogt, Ivo R. Seitenzahl, Michael A. Dopita, and Ashley J. Ruiter
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/129/975/058012

  19. Walking Through an Exploded Star: Rendering Supernova Remnant Cassiopeia A into Virtual Reality
    Kimberly K. Arcand, Elaine Jiang, Sara Price, Megan Watzke, Tom Sgouros, Peter Edmonds
    Communicating Astronomy with the Public Journal

  20. Touching the stars: improving NASA 3D printed data sets with blind and visually impaired audiences
    Kimberly Kowal Arcand, April Jubett, Megan Watzke, Sara Price, Kelly T.S. Williamson, Peter Edmonds
    Journal of Science Communication (JCOM)
    DOI: 10.22323/2.18040201

  21. Interactive 3D visualization for theoretical virtual observatories
    Tim Dykes, Amr Hassan, Claudio Gheller, Darren Croton, and Mel Krokos
    Monthly Notices of the Royal Astronomical Society
    DOI: 10.1093/mnras/sty855

  22. The Fabric of the Universe: Exploring the Cosmic Web in 3D Prints and Woven Textiles
    Benedikt Diemer and Isaac Facio
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/aa6a46

  23. 3DMAP-VR, A Project to Visualize Three-dimensional Models of Astrophysical Phenomena in Virtual Reality
    Salvatore Orlando, Ignazio Pillitteri, Fabrizio Bocchino, Laura Daricello, and Laura Leonardi
    Research Notes of the AAS
    DOI: 10.3847/2515-5172/ab5966

  24. A Novel Approach to Visualizing Dark Matter Simulations
    Ralf Kaehler, Oliver Hahn, and Tom Abel
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2012.187

  25. Shape: A 3D Modeling Tool for Astrophysics
    Wolfgang Steffen, Nicholas Koning, Stephan Wenger, Christophe Morisset, and Marcus Magnor
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2010.62

  26. Visualization of Astronomical Nebulae via Distributed Multi-GPU Compressed Sensing Tomography
    Stephan Wenger, Marco Ament, Stefan Guthe, Dirk Lorenz, Andreas Tillmann, Daniel Weiskopf, and Marcus Magnor
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2012.281

  27. Visualizing Three-dimensional Volumetric Data with an Arbitrary Coordinate System
    Rhys Taylor
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/129/972/028002

  28. Houdini for Astrophysical Visualization
    J.P. Naiman, Kalina Borkiewicz, and A.J. Christensen
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/aa51b3

  29. Voxel Datacubes for 3D Visualization in Blender
    Matías Gárate
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/129/975/058010

  30. AVIATOR: Morphological object reconstruction in 3D. An application to dense cores
    Birgit Hasenberger, and João Alves
    Astronomy and Astrophysics (A&A)
    DOI: 10.1051/0004-6361/201936095

  31. 3D shape of Orion A from Gaia DR2
    Josefa E. Grossschedl, Joao Alves, Stefan Meingast, Christine Ackerl, Joana Ascenso, Herve Bouy, Andreas Burkert, Jan Forbrich, Verena Fuernkranz, Alyssa Goodman, Alvaro Hacar, Gabor Herbst-Kiss, Charles J. Lada, Irati Larreina, Kieran Leschinski, Marco Lombardi, Andre Moitinho, Daniel Mortimer, and Eleonora Zari
    Astronomy and Astrophysics (A&A)
    DOI: 10.1051/0004-6361/201833901

  32. OpenSpace: A System for Astrographics
    Alexander Bock, Emil Axelsson, Jonathas Costa, Gene Payne, Micah Acinapura, Vivian Trakinski, Carter Emmart, Cláudio Silva, Charles Hansen, and Anders Ynnerman
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2019.2934259

  33. Gaia Sky: Navigating the Gaia Catalog
    Antoni Sagristà, Stefan Jordan, Thomas Müller, and Filip Sadlo
    IEEE Transactions on Visualization and Computer Graphics
    DOI: 10.1109/TVCG.2018.2864508

  34. Dynamic Scene Graph: Enabling Scaling, Positioning, and Navigation in the Universe
    Emil Axelsson, Jonathas Costa, Cláudio Silva, Carter Emmart, Alexander Bock, Anders Ynnerman
    Computer Graphics Forum
    DOI: 10.1111/cgf.13202

  35. Visualization of Multi-mission Astronomical Data with ESASky
    Deborah Baines, Fabrizio Giordano, Elena Racero, Jesús Salgado, Belén López Martí, Bruno Merín, María-Henar Sarmiento, Raúl Gutiérrez, Iñaki Ortiz de Landaluce, and Ignacio León
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/129/972/028001

  36. LSSGalPy: Interactive Visualization of the Large-scale Environment Around Galaxies
    M. Argudo-Fernández, S. Duarte Puertas, J. E. Ruiz, J. Sabater, S. Verley, and G. Bergond
    Publications of the Astronomical Society of the Pacific (PASP)
    DOI: 10.1088/1538-3873/aa5785

  37. Fast Image‐Based Modeling of Astronomical Nebulae
    Stephan Wenger, Dirk Lorenz, Marcus Magnor
    Computer Graphics Forum
    DOI: 10.1111/cgf.12216

  38. aflak: Visual programming environment enabling end-to-end provenance management for the analysis of astronomical datasets
    Malik OlivierBoussejra, Rikuo Uchiki, Yuriko Takeshima, Kazuya Matsubayashi, ShunyaTakekawa, Makoto Uemura, Issei Fujishiro
    Visual Informatics
    DOI: 10.1016/j.visinf.2019.03.001

  39. yt: A Multi-code Analysis Toolkit for Astrophysical Simulation Data
    Turk, Matthew J.; Smith, Britton D.; Oishi, Jeffrey S.; Skory, Stephen; Skillman, Samuel W.; Abel, Tom; Norman, Michael L.
    The Astrophysical Journal
    DOI: 10.1088/0067-0049/192/1/9