Sunday, October 1 8:30AM-5:55PM 102-ABC
Benjamin Bach, University of Edinburgh, UK / Harvard University, MA Maxime Cordeil, Monash University, VIC Tim Dwyer, Monash University, VIC Bongshin Lee, Microsoft Research Bahador Saket, Georgia Tech Alex Endert, Georgia Tech Christopher Collins, University of Ontario Institute of Technology Sheelagh Carpendale, University of Calgary
Contact: benj.bach@gmail.com
Immersive Analytics is a new multidisciplinary initiative to explore future visualization and interaction technologies for data analytics. Immersive Analytics aims to bring together researchers in Information Visualization, Visual Analytics, Virtual and Augmented Reality and Natural User Interfaces. This workshop looks at immersive technologies (e.g., AR, VR, Mixed reality, NUIs, large displays), scenarios, theories and frameworks, collaboration, physical and tangible visualization, as well as interaction techniques.
Monday, October 2 8:30AM-5:55PM 101-ABC
David Rogers, Los Alamos National Lab Dan Keefe, University of Minnesota Francesca Samsel, University of Texas at Austin Miriah Meyer, University of Utah Cecilia Aragon, University of Washington
Contact: info@discoveryjam.com
You’ve heard of Game Jams and Hack-a-thons–DiscoveryJam brings this same intense, hands-on approach to scientific discovery. Our full day workshop brings scientists together with VIS participants in an interactive day-long workshop to create innovative approaches to scientific discovery problems. Each DiscoveryJam scientist is matched with a small group of attendees. In the morning each group holds interactive discussions with their scientist about specific data and science problems. In the afternoon, each group hacks away on the scientist’s data. We’ll create sketches, prototypes, and sample visualizations, and then present them to the entire workshop. You’ll leave the workshop with skills for communicating with scientists, approaches to cross-disciplinary collaboration, and research ideas to pursue further. Bring your laptop and your favorite vis tools to dig into data with us.
Monday, October 2 8:30AM-12:10PM 211-AB
Remco Chang, Tufts University Danyel Fisher, Microsoft Research Jeffrey Heer, University of Washington Carlos Scheidegger, University of Arizona
Contact: organizers@interactive-analysis.org
DSIA brings together researchers at the intersection of databases, machine learning, and interactive visualization. These three areas have important things to say to each other. Modern data visualization depends on the cutting edge of both database and machine learning research: database researchers are exploring techniques for storing and querying massive amounts of data; machine learning techniques provide ways to discover unexpected patterns and to automate and scale well-defined analysis procedures. This workshop explores the idea that the next generation of database, machine learning, and interactive visualization systems should not be designed in isolation. For example, machine learning techniques might recommend improved data transformation and visual encoding decisions. Or, database query optimizers might take advantage of perceptual constraints, while prefetching methods reduce latency by modeling likely interactions. This workshop seeks to increase cross-pollination between these fields.
Monday, October 2 8:30AM-12:10PM 105-ABC
Geoffrey Ellis, University of Konstanz, Germany Evanthia Dimara, Inria Saclay, France Donald Kretz, Applied Research Associates, USA Alex Endert, Georgia Tech, USA
Contact: ellis@dbvis.inf.uni-konstanz.de
We make thousands of subconscious decisions daily and often apply simplified rules or heuristics to speed up the process. Most of these are good enough, however when there is some uncertainty we can make what appears to be irrational decisions, leading to inaccurate judgements, also known as cognitive biases. Over the last 40 years, hundreds of cognitive biases have been documented, such as the confirmation bias, where people unconsciously seek out information that confirms their current belief, ignoring information to the contrary. Despite a growing awareness of the detrimental effects of cognitive biases on decision making, there is little work on how to detect this behaviour in those who use visualisation-based applications and even less on how to minimise their effect. The aim of this workshop is to bring together people from a wide range of disciplines such as information visualisation, visual analytics, software engineering, cognitive psychology and decision science, as well as those close to end-user groups like intelligence analysts and medical practitioners, to explore some of the ways in which cognitive biases impact user performance and share ideas about practical ways to reduce or overcome these potentially harmful effects, especially in adapting the tools developers design and build.
Sunday, October 1 2:00PM-5:55PM 106-ABC
Alark Joshi, University of San Francisco Eytan Adar, University of Michigan Enrico Bertini, New York University Sophie Engle, University of San Francisco Marti Hearst, University of California Berkeley Daniel Keefe, University of Minnesota
Contact: apjoshi@usfca.edu
The pedagogy of data visualization is becoming increasingly important as data visualization techniques and tools proliferate. In this workshop, we propose to create a community of practice that provides a structured medium to learn from data visualization teaching strategies from each other. The focus is on sharing innovations in the classroom when teaching data visualization. The half-day interactive workshop will include lightning talks/demonstrations followed by breakout sessions focused on topics related to teaching large classes, teaching at a liberal arts college, teaching a professional masters’ course, and so on.
Monday, October 2 2:00PM-5:55PM 105-ABC
Stefan Janicke, Leipzig University, Germany Christopher Collins, University of Ontario Institute of Technology, Canada Michael Correll, University of Washington, USA Mennatallah El-Assady, University of Konstanz, Germany Daniel Keim, University of Konstanz, Germany David Wrisley, New York University Abu Dhabi, UAE
Contact: stjaenicke@informatik.uni-leipzig.de
The first Workshop on Visualization for the Digital Humanities at VIS 2016 created a new platform to discuss challenges in the emerging digital humanities field. The 2nd workshop this year aims (1) to single out new research directions in visualization for the digital humanities, (2) to familiarize the visualization research community with the problems faced by digital humanities researchers, and (3) to establish future collaborations between visualization and digital humanities scholars.
Monday, October 2 2:00PM-5:55PM 211-AB
Jaegul Choo, Korea University Shixia Liu, Tsinghua University Jason Yosinski, Uber AI Labs Deokgun Park, University of Maryland, College Park
Contact: jchoo@korea.ac.kr
VADL 2017, the workshop on visual analytics for deep learning, is a half-day workshop held in conjunction with the IEEE VIS 2017 Conference. The primary goal of the workshop is to bridge the gap by bringing together researchers from both the machine learning and visual analytics fields, which allows us to push the boundary of deep learning. The workshop should provide an opportunity to discuss and explore ways to harmonize the power of automated techniques and exploratory nature of interactive visualization.
Sunday, October 1 8:30AM-12:10PM 106-ABC
Penny Rheingans, University of Maryland, Baltimore County Kelly Gaither, University of Texas
Contact: rheingan@umbc.edu
In the US and in most countries abroad, women account for a relatively small fraction of those earning degrees in computer science. Those from some ethnic backgrounds are also greatly underrepresented. While no specific figures are currently available to describe the diversity of the visualization community, a glance around a typical room during VIS seems to suggest that demographics are similar. Research studies have documented that diverse teams and companies produce better outcomes (more robust designs, more productivity, more profit). This lack of diversity in our community limits our potential. This half-day workshop seeks to address that lack by encouraging undergraduates from underrepresented groups and their allies to consider graduate study and careers in visualization. The workshop includes an overview of the diversity and climate of the visualization community, panels by near peers and senior researchers, and interaction opportunities. Participants should leave the workshop with increased knowledge about opportunities in visualization, a greater understanding of challenges and strategies, and a wider network of those sharing their goals.
Monday, October 2 2:00PM-5:55PM 207 Lecture Hall
Bernd Hentschel, RWTH Aachen University Daniela Oelke, Siemens AG Justin Talbot, Tableau Research
Contact: vip@ieeevis.org
The 2017 ViP Workshop on Visualization Solutions in the Wild is an opportunity for visualization practitioners and researchers to meet and share experiences, insights, and ideas in applying the latest visualization and visual analytics research to real world problems. It targets work at the interface between visualization research and specific application domains. It is highly interdisciplinary and focused on delivering actual value to users. This year, we specifically focus on visualization solutions in the wild, i.e. on tools, systems, or frameworks which are actively used. The workshop will cover all aspects from their initial conception and design, the process of getting them into use, and the long-term work of extending and sustaining them.
