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A Matter of Scale - Scale Matters

Friday, OCTOBER 6
Location: 101-ABC

Arthur Olson (Organizer), The Scripps Research Institute
Eduard Groeller (Organizer), TU Vienna
Alan M. MacEachren, Pennsylvania State University
Todd Richmond, USC Institute for Creative Technologies
Claudio Silva, New York University


Scale and scalability have been recurring topics in our field. Recent developments like smart data, machine learning, and advances in domains like biology, cartography, smart communities, and communication pose novel challenges to scalability and use of scale. Examples include support for scale-transparent visual computing, cross-scale visualization and interaction, massive multi-scale techniques, scale integration, cross-scale labeling and annotation, cross scales on structure and dynamics, and continuous scales.

Diversity in Visualization

Thursday, OCTOBER 5
2:00PM-3:40PM Location: TBD

Robert S. Laramee (Organizer), Swansea University
Rita Borgo, Kings College Vetria Byrd, Purdue Polytechnic Institute
Aviva Frank, TBA University
Kelly Gaither, University of Texas, Austin
Ronald Metoyer, University of Notre Dame Erica Yang, Science and Technology Facilities Council (STFC)


This panel will address the lively topic of diversity in the fields of data visualization and visual analytics from gender, cultural, and technological points of view.

How do Recent Machine Learning Advances Impact the Data Visualization Research Agenda?

Thursday, OCTOBER 5
Location: 207 Lecture Hall

Timo Ropinski (Organizer), Ulm University
Daniel Archambault, Swansea University
Min Chen, Oxford University
Ross Maciejewski, Arizona State University
Klaus Mueller, Stony Brook University
Alexandru Telea, University of Groningen
Martin Wattenberg, Google


Nowadays, machine learning approaches have revolutionized many domains. As this pushes the human out of the loop, the human-in-the-loop paradigm might be endangered. Thus, we would like to investigate, which old visualization challenges are rendered obsolete, and which new visualization challenges arise from the recent advances in machine learning.

Increasing the Impact of Visualization Research

Tuesday, OCTOBER 3
Location: 101-ABC

Steven M. Drucker, Microsoft Research
Adam Perer, IBM Research
Daniela Oelke, Siemens
Melanie Tory, Tableau Research
Krist Wongsuphasawat, Twitter
Justing Talbot, Tableau Research


The Vis in Practice panel is part of the IEEE VIS 2017 main program and provides visualization researchers and practictioners with the chance to hear from leaders in the field. This year our panelists will discuss how visualization research impacts industry. The panelists have deep and diverse experience applying ideas from the research domain to visualization problems and products within industry. The panelists will provide their perspectives on questions such as: What visualization papers or threads of research have had particular impact on your industry? When developing new features or systems, to what extent do you turn to existing research to inform your decisions? What types of papers are most relevant to your work? What makes a paper more or less applicable? Are there general visualization questions that are of critical interest to your company that are not currently being addressed by the research community?

Reflection on Reflection in Design Studies

Thursday, OCTOBER 5
Location: 101-ABC

Jason Dykes (Organizer), City University of London
Miriah Meyer (Organizer), University of Utah
Uta Hinrichs, St. Andrews University Nathalie Henry Riche, Microsoft Research
Remco Chang, Tufts University
Petra Isenberg, Inria
Heidi Lam, Tableau Research
Tamara Munzner, University of British Columbia


Design study research methodologies emphasize the need for reflection to generate knowledge. We ask six researchers to reflect upon the role of reflection in design studies, as we try to share and develop good practice. Come along to participate in an interactive conversation around reflection, that underpins applied visualization research.

Vision Science Meets Visualization

Wednesday, OCTOBER 4
Location: 101-ABC

Christine Nothelfer (Organizer), Northwestern University
Zoya Bylinskii (Organizer), Massachusetts Institute of Technology
Madison Elliott (Organizer), University of British Columbia
Cindy Xiong (Organizer), Northwestern University
Danielle Albers Szafir (Organizer), University of Colorado Boulder
Ronald Rensink, University of British Columbia
Steven Franconeri, Northwestern University
Karen Schloss, University of Wisconsin-Madison
Ruth Rosenholtz, Masachusetts Institute of Technology

Contact: Danielle.Szafir@Colorado.EDU

Vision science can explain what people see when looking at visualizations–what data people attend to, what statistics they extract, and what they ultimately remember. This panel features talks from vision scientists who will survey the modern vision science landscape to foster new collaborative opportunities between visualization and vision science.