Organizer: Jock Mackinlay (Tableau Software),
Moderator: Jessica Hullman (Northwestern University)
Panelists: Ben Shneiderman (University of Maryland), Tamara Munzner (University of British Columbia), Jack van Wijk (Eindhoven University of Technology)
We like to think that most of the important lessons learned about visualization can be extracted from research papers and books. But visualization research and innovation are also driven by the perspectives, goals, and values of those making and witnessing discoveries. Findings about what visualization techniques, methods, or theories don’t seem to work, and perspectives on visualization’s value in improving data work that experts develop over years, are critical for guiding future innovation efficiently toward maximum impact. This IEEE VIS 2021 panel brings together four experts with multiple decades of active involvement in visualization innovation for a lively discussion with each other, the moderator, and the audience. We’ll target what’s not so obvious from the papers alone, and how these reflections point toward important areas for future innovation.
Organizers: Alfie Abdul-Rahman (King’s College London)
Panelists: Min Chen (University of Oxford), David Ebert (University of Oklahoma), Lace Padilla (University of California Merced), Yixuan Zhang (Georgia Institute of Technology)
Visualization and visual analytics (VIS) plays an important role in combating COVID-19. We can clearly observe this fact in the charts and graphs for public consumption in the media, and can also identify various visual analytics techniques that have been developed for domain experts in their analysis and modeling of COVID-19 data. In this panel, we ask four researchers - “What is the Role of VIS in Combating COVID-19?”. Our panelists will cover a number of topics including developing VIS techniques and systems, conducting empirical studies, and deploying VIS for public health surveillance and intervention planning. The panelists will discuss a range of questions, reflecting on the recent and ongoing work by VIS colleagues and examining challenges in deploying a wide range of VIS techniques in emergency responses.
For more details and announcements, visit this link: http://thisisalfie.com/vis-combating-covid19.html
Organizers: Alark Joshi (University of San Francisco)
Panelists: Katy Börner (Indiana University), Robert S Laramee (University of Nottingham), Lane Harrison (Worcester Polytechnic Institute), Elif E. Firat (University of Nottingham), Bum Chul Kwon (IBM Research)
In this panel, we will discuss strategies and challenges associated with increasing the visualization literacy of general audiences (and adjacent data-related fields). We will hear from experts who have tested various techniques to increase visualization literacy and developed interactive apps/games/websites to inform and educate varying audiences about the fundamentals of data visualization. We will hear from experts who have worked towards increasing the visualization literacy of participants through various strategies such as videos, websites, tutorials, and so on. The panel will discuss open challenges in the field of visualization literacy and the problems faced when introducing novel visualization techniques to potential users.
Organizers: Morgan L. Turner (University of Minnesota)
Panelists: Ruth West (University of North Texas), Adrien Segal (California College of the Arts and the University of San Francisco), Sheelagh Carpendale (Simon Fraser University), Daniel Keefe (University of Minnesota)
The field of visualization is inherently interdisciplinary: problems from another domain are often used to drive application and development of visualization tools in computer science. While collaborations addressing these problems often include a mix of computer scientists and domain specialists, interdisciplinary individuals with expertise spanning both visualization and domain-specific areas have a unique perspective on the field of visualization and ability to facilitate collaboration.
This panel features four interdisciplinary researchers and practitioners who have made substantial contributions to the field of visualization (Ruth West, Adrien Segal, Sheelagh Carpendale, and Daniel Keefe). With a breadth of domain expertise (including visual arts and design, sculpture, biology, psychology, music, information visualization, human-computer interaction, data empowerment, data storytelling, and data physicalization), as well as collaborations that extend into several domains beyond, this panel will explore their perspectives on:
• What it means to be multi/trans/inter-disciplinary
• Navigating a career with expertise in multiple disciplines and finding the right collaborations, funding, and home department
• The role, impact, and challenges of being an interdisciplinary researcher and practitioner in visualization
• The intersection and influence of personal and artistic identities on disciplinary interests, approach, and trajectory
• Advice for early career individuals considering pursuing an interdisciplinary career
Questions from the audience are welcomed during the panel discussion.
Organizers: Derya Akbaba (University of Utah), Kiran Gadhave (University of Utah)
Panelists: Saiph Savage (Northeastern University), Danielle Albers Szafir (University of North Carolina), Alexander Lex (University of Utah), Steve Haroz (Inria, Universite Paris-Saclay)
As crowdsourced platforms have become more popular with evaluating visualizations, so have the stakes of using these platforms. Since the pandemic, the stakes of having a minimum wage have been hotly debated: some finding it outrageous, others pointing out that it is barely a living wage for most. Should we as researchers care about wages? Is it our responsibility to pay people?
The purpose of this panel is to begin discussing and drawing the ethical and practical boundaries of how much we should pay our study participants, what is a fair pay, and should ethics around payments be part of the review process.
Our choice of panelists (Saiph Savage, Danielle Szafir, Alexander Lex, Steve Haroz, and Khairi Reda) represent researchers with significant experience in running crowdsourced studies as well as researchers who work directly with crowd workers to understand the needs of the crowdworkers. We expect the discussion to trigger a discourse in the visualization community around the practice of paying ethically and holding ourselves accountable.
For more details and announcements, visit this link: https://fairpayvis2021.github.io/fairpayvis2021/
Organizers: Arvind Satyanarayan (MIT CSAIL), Danielle Szafir (UNC Chapel Hill), Crystal Lee (MIT CSAIL), Alan Lundgard (MIT CSAIL), Keke Wu (CU Boulder)
Panelists: Cynthia Bennett (CMU and Apple), Lilian de Greef (Apple), Chancey Fleet (New York Public Library), Zoe Gross (Autistic Self Advocacy Network), Ariel Schwartz (MGH Institute of Health Professions), Rua Williams (Purdue University)
Despite frequently citing the crucial role visualizations play in our data-driven society, little visualization research has grappled with how the medium is inaccessible to people with disabilities. This panel convenes a group of experts in disability advocacy and assistive technology to catalyze a conversation around accessible data representations. Our panelists will draw on their lived experiences and prior work with visual and intellectual disabilities to help the community understand how visualization researchers can make contributions that go beyond “disability dongles,”’ a term coined by disability design expert Liz Jackson to refer to a “well intended, elegant, yet useless solution to a problem we [people with disabilities] never knew we had”. In other words, without close participation and inclusion with relevant disability communities—heretofore largely excluded from IEEE VIS—well-intentioned visualization researchers may inadvertently design products and data representations that are ultimately unusable to their intended audience. As interest in accessibility gains momentum within the visualization community, this panel aims to ensure that its designs are produced inclusively and equitably.