The IEEE Visualization Conference (VIS) is an annual conference on
scientific visualization,
information visualization, and
visual analytics administrated by the
IEEE Computer SocietyTechnical Committee on Visualization and Graphics. As ranked by
Google Scholar's
h-index metric in 2016, VIS is the highest rated venue for visualization research and the second-highest rated conference for computer graphics over all.[1] It has an 'A' rating from the Australian Ranking of ICT Conferences,[2] an 'A' rating from the Brazilian ministry of education, and an 'A' rating from the China Computer Federation (CCF). The conference is highly selective with generally < 25% acceptance rates for all papers.[3][4]
An image dataset, VIS30K, has been created from figures and tables in the conference publications.[5]
Location
The conference is held in October and rotates around the US generally West, Central and East.[citation needed] In 2014, for its 25th anniversary, the conference took place for the first time outside of the US, namely in
Paris.[6]
FlowSense: A Natural Language Interface for Visual Data Exploration within a Dataflow System: Bowen Yu, Claudio Silva
InfoVis
Data Changes Everything: Challenges and Opportunities in Data Visualization Design Handoff: Jagoda Walny, Christian Frisson, Mieka West, Doris Kosminsky, Søren Knudsen, Sheelagh Carpendale, Wesley Willett
SciVis
InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations: Wenbin He, Junpeng Wang, Hanqi Guo, Ko-Chih Wang, Han-Wei Shen, Mukund Raj, Youssef S. G. Nashed, Tom Peterka
2018:
VAST
TPFlow: Progressive Partition and Multidimensional Pattern Extraction for Large-Scale Spatio-Temporal Data Analysis, Dongyu Liu, Panpan Xu, Liu Ren
InfoVis
Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco, Dominik Moritz, Chenglong Wang, Greg L. Nelson, Halden Lin, Adam M. Smith, Bill Howe, Jeffrey Heer
SciVis
Deadeye: A Novel Preattentive Visualization Technique Based on Dichoptic Presentation Authors: Andrey Krekhov, Jens Krüger
2017:
VAST
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow, Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson, Dandelion Mané, Doug Fritz, Dilip Krishnan, Fernanda B. Viégas, and Martin Wattenberg
InfoVis
Modeling Color Difference for Visualization Design, Danielle Albers Szafir
SciVis
Globe Browsing: Contextualized Spatio-Temporal Planetary Surface Visualization, Karl Bladin, Emil Axelsson, Erik Broberg, Carter Emmart, Patric Ljung, Alexander Bock, and Anders Ynnerman
2016:
VAST
An Analysis of Machine- and Human-Analytics in Classification, Gary K.L. Tam, Vivek Kothari, Min Chen
InfoVis
Vega-Lite: A Grammar of Interactive Graphics, Arvind Satyanarayan, Dominik Moritz, Kanit Wongsuphasawat, and
Jeffrey Heer
SciVis
Jacobi Fiber Surfaces for Bivariate Reeb Space Computation, Julien Tierny and Hamish Carr
2015
VAST
Reducing Snapshots to Points: A Visual Analytics Approach to Dynamic Network Exploration, Stef van den Elzen, Danny Holten, Jorik Blaas,
Jarke van Wijk
InfoVis
HOLA: Human-like Orthogonal Network Layout, Steve Kieffer, Tim Dwyer, Kim Marriott, Michael Wybrow
SciVis
Visualization-by-Sketching: An Artist’s Interface for Creating Multivariate Time-Varying Data, David Schroeder, Daniel Keefe
2014
VAST
Supporting Communication and Coordination in Collaborative Sensemaking, Narges Mahyar, Melanie Tory
InfoVis
Multivariate Network Exploration and Presentation: From Detail to Overview via Selections and Aggregations, Stef van den Elzen,
Jarke van Wijk
SciVis
Visualization of Brain Microstructure through Spherical Harmonics Illumination of High Fidelity Spatio-Angular Fields, Sujal Bista, Jiachen Zhou, Rao Gullapalli, Amitabh Varshney
2013
VAST
A Partition-Based Framework for Building and Validating Regression Models, Thomas Muhlbacher, Harald Piringer
InfoVis
LineUp: Visual Analysis of Multi-Attribute Rankings, Samuel Gratzl, Alexander Lex, Nils Gehlenborg,
Hanspeter Pfister, Marc Streit
SciVis
Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles, Mathias Hummel, Harald Obermaier, Christoph Garth, Kenneth I. Joy
To earn the IEEE
VGTC Visualization Career Award, an individual must demonstrate that their research and service has had broad impacts on the field over a long period of time.
^Ebert, David (2016). "The 2016 Visualization Technical Achievement Award". 2016 IEEE Conference on Visual Analytics Science and Technology (VAST). pp. xi.
doi:
10.1109/VAST.2016.7883503.
ISBN978-1-5090-5661-3.
^Dill, John (2017). "The 2016 Visualization Career Award". IEEE Transactions on Visualization and Computer Graphics. 23 (1): xxiv.
doi:
10.1109/TVCG.2016.2599298.
ISSN1077-2626.