These workshops were pre-approved by the VIS Executive Committee. Please visit their individual websites for details on the topics and submission deadlines.
- BELIV 2022: 9th Workshop on evaluation and BEyond - methodoLogIcal approaches for Visualization
- VIS4DH: 7th Workshop on Visualization for the Digital Humanities
- VISxAI: 5th Workshop on Visualization for AI Explainability
These workshops went through our submission/review process. Please visit their individual websites for details on the topics and submission deadlines, or contact the organizers directly if no website is available yet.
- VisGuides: 4th IEEE Workshop on Visualization Guidelines in Research, Design, and Education
- alt.VIS 2022
- Visualization in BioMedical AI
- NLVIZ Workshop: Exploring Research Opportunities for Natural Language, Text, and Data Visualization
- Fifth Workshop on Visualization for Communication (VisComm)
- Viz4Climate - Workshop on High-Impact Techniques for Visual Climate Science Communication
- TREX: Workshop on TRust and EXpertise in Visualization
- TopoInVis – Topological Data Analysis and Visualization
- Visualization for Social Good 2022
- Visualization in Testing of Hardware, Software, and Manufacturing
Anastasia Bezerianos, Université Paris Saclay
Kyle Hall, University of Calgary
Samuel Huron, Télécom ParisTech
Matthew Kay, Northwestern University
Miriah Meyer, Linköping University,
BELIV 2022 is the international forum to broadly discuss research methods in visualization. Our discussions span from novel and not-yet fully established evaluation methods for visualization tools and techniques, to methods that more generally establish the validity and scope of acquired visualization knowledge. BELIV supports contributions and discussions from the rich spectrum of visualization researchers, embracing the varied ways that researchers self-identify with respect to the main conference tracks at VIS.
Alfie Abdul-Rahman, King’s College London
Houda Lamqaddam, KU Leuven
The VIS4DH workshop brings together researchers and practitioners from the fields of visualization and the humanities to discuss new research directions at the intersection of visualization and (digital) humanities research.
Adam Perer, Carnegie Mellon University
Angie Boggust, Massachusetts Institute of Technology
Fred Hohman, Apple
Hendrik Strobelt, MIT-IBM Watson AI Lab
Mennatallah El-Assady, ETH AI Center
Zijie Jay Wang, Georgia Tech
The role of visualization in artificial intelligence (AI) gained significant attention in recent years. With the growing complexity of AI models, the critical need for understanding their inner-workings has increased. Visualization is potentially a powerful technique to fill such a critical need.
The goal of this workshop is to initiate a call for “explainables” / “explorables” that explain how AI techniques work using visualization. We believe the VIS community can leverage their expertise in creating visual narratives to bring new insight into the often obfuscated complexity of AI systems.
Benjamin Bach, The School of Informatics, University of Edinburgh
Alfie Abdul-Rahman, Department of Informatics, King’s College London
Alexandra Diehl, University of Zurich
The VisGuides 2022 Workshop focuses on the analysis, design, reflection, and discussion of applicable frameworks to mastering guidelines in visualization by the broader visualization community, embedded in a larger research agenda of visualization theory and practices. Goals include: Illustrating the use of best practices and guidelines in the wild; Constructing an open and democratic discussion about principles, guidelines, and recommendations; Discussing ideas and proposals of feasible approaches towards the formalization of visualization guidelines; To raise questions about the ethical, practical, and technical implications of establishing guidelines. Submit your work and ideas as either a short paper, long paper, or a guideline report discussing a guideline, its empirical evidence, application, and limitations. Submission deadline is July 22.
The VisGuides 2022 Workshop focuses on the analysis, design, reflection, and discussion of applicable frameworks to mastering guidelines in visualization by the broader visualization community, embedded in a larger research agenda of visualization theory and practices. It follows-up the ideas from the IEEE VIS 2016, 2018, and 2020 Workshop on Creation, Curation, Critique and Conditioning of Principles and Guidelines in Visualization (C4PGV).
The workshop also features an open call for being part of the program committee (PC) to provide an opportunity to advocate for guidelines in a broad range of topics. If you would like to get involved, contact firstname.lastname@example.org.
The workshop will be held in a hybrid format. You can attend online or in person though we hope that you can join us in-person. Online sessions will be synchronous with the in-person workshop.
Lonni Besançon, Linköpings Universitet
Andrew M McNutt, Computer Science, University of Chicago
Arnaud Prouzeau, Potioc, Inria
Jane L. Adams, Complex Systems Center, University of Vermont
Derya Akbaba, School of Computing, University of Utah
Charles Perin, Department of Computer Science, University of Victoria
Often the most transformative ideas and challenges come from unexpected and serendipitous sources. Yet, conferences are not often perceived as a place for non-traditional, controversial, or outré work. We propose to continue the success of last year’s “alt.VIS” workshop that borrows from the long-running and successful “alt.chi” model from the ACM SIGCHI conference; once again providing an avenue for surfacing work that would otherwise not find a home through the standard VIS conference review process.
Qianwen Wang, Biomedical Informatics, Harvard Medical School
Vicky Yao, Computer Science, Rice University
Bum Chul Kwon, IBM Research
Nils Gehlenborg, Biomedical Informatics, Harvard Medical School
Artificial Intelligence (AI) is advancing biomedical science in many ways, from improving image-based diagnostics to identifying new drugs. Effective visualization can significantly improve the communication between AI systems and human users and is playing an increasingly important role in biomedical AI. However, visualization in biomedical AI is highly interdisciplinary and a mutual understanding is still missing across disciplines.
The aim of this workshop is to explore the challenges and opportunities in this highly interdisciplinary research by bringing together researchers from data visualization, biomedical informatics, machine learning, and computational biologists. We hope this workshop can 1) attract more research interest from the VIS community to this newly emerging topic by showcasing successful applications and promising directions for using visualization in biomedical AI studies and 2) demonstrate the importance of design and share good visualization practices to biomedical AI researchers and broaden the impact of visualization research.
Vidya Setlur, Tableau Research
Arjun Srinivasan, Tableau Research
Natural language processing (NLP) has evolved as a promising field for helping users in their exploration and interaction with data for visual analysis tasks. The applications of NLP for supporting various aspects of the visual analysis workflow include: employing text processing methods for data preparation, supporting interaction modalities to help people naturally “ask” questions of their data, and generating captions and textual summaries to help readers take away key information from the chart or dashboard, among others. As the field of NLP matures, computers now have an increased capability of interpreting natural language and engaging in conversations with people. But, can NLP techniques and interactive visualizations work in concert to support an analytical conversation? If so, how? How can the increasing number of domain-specific corpora and their semantics be better utilized for supporting smarter data transformations and visualization defaults? How can we develop models to effectively summarize visualizations and highlight key data findings? Can text and charts be interactively linked to support interpretation and data-driven communication? Addressing these questions calls for research at the intersection of human-computer interaction, information visualization, and NLP, three fields with natural connections (pun intended) but rather infrequent meetings.
Barbara Millet, School of Communication, University of Miami
Jonathan Schwabish, Urban Institute
Alvitta Ottley, Department of Computer Science and Engineering, Washington University in St. Louis
Alice Feng, Urban Institute
While the visualization field consists of researchers exploring how people perceive information and different data visualization tools and platforms, there is an even larger community of analysts, practitioners, and organizations who are creating data and information visualizations and communicating their work every day. The challenges these groups face in communicating their work are often distinct from the research taking place in the academic community.
The VisComm workshop brings together practitioners and researchers from a broad range of disciplines to address questions raised by the new and evolving role of data visualization in our everyday lives. We encourage participation from journalists, designers, practitioners, health communicators, and others who do not typically attend IEEE VIS.
Helen-Nicole Kostis, Scientific Visualization Studio, NASA Goddard Space Flight Center
Dr. Mark SubbaRao, Scientific Visualization Studio, NASA Goddard Space Flight Center
Marlen Promann, Computer Graphics Technology, Purdue University
Communicating climate science to the general public is necessary to enhance salience, understanding, and engagement and to accelerate action. Visualizations of climate data offer an integral way of communicating climate change findings to diverse audiences; however it is challenging due to the multi-dimensionality of data, the complexity of science, the diversity of users, their biases, and needs across different stakeholder groups. While graphics support thinking and enhance storytelling, creating data visualizations of climate data that can overcome comprehension difficulties, avoid misconceptions, preserve scientific integrity, and instill trust remains a challenge. This half-day workshop aims to establish a community of practice around data-driven visual climate science communication and in so doing address one of the grand challenges in our era. The workshop seeks to define what ‘high impact’ means in the domain of climate science communication, and to unpack the techniques, methods, and challenges for achieving it. The mission is to pull expertise from within IEEE Vis, bridge the gap between research and practice, and others who typically do not attend the conference, share lessons learned, identify directions for research, foster collaborations, and understand where and what we should do better as a community of practice.
Mahsan Nourani, University of Florida, Gainesville
Eric Ragan, University of Florida, Gainesville
Alireza Karduni, Computer Science, Northwestern University
Cindy Xiong, College of Information and Computer Sciences, University of Massachusetts Amherst
Brittany Davis, Pierson Pacific North National Lab
Interactive visualization systems combine computational support, human cognitive, and perceptual skills to explore and analyze data. Many of these systems incorporate machine learning (ML) and Artificial Intelligence (AI) algorithms to introduce some level of automation to the analytical process. However, there are aspects that can impact the effectiveness of the human-machine collaboration, including, but not limited to: 1) People’s domain and system expertise; 2) Human biases, including cognitive and perceptual biases; 3) Trust in ML models and visual representation of data. The goal of this workshop is to highlight and foster a conversation around the intersection of visualization and human-centered AI research and practice by providing an interdisciplinary platform from relevant fields to communicate challenges and novel findings around such topics.
Talha Bin Masood, Department of Science and Technology, Linköping University
Vijay Natarajan, Indian Institute of Science
Paul Rosen, University of South Florida
Julien Tierny, CNRS, Paris, France Sorbonne Université
The IEEE VIS Workshop on Topological Data Analysis and Visualization aims at being an inclusive forum for the fast dissemination of the latest results in theory, algorithms, and applications of topological methods for the interactive and visual analysis of data. This workshop is a remodeling of the established TopoInVis workshop series, with the goal of being more diverse (in terms of applications) and inclusive (in terms of communities), with a clear will to open to other members of the visualization community potentially interested in topological methods, or experts in topological methods from other communities willing to experiment with interactive and visual applications.
Leilani Battle, Paul G. Allen School of Computer Science & Engineering, University of Washington
Michelle A. Borkin, Khoury College of Computer Sciences, Northeastern University
Lane Harrison, Worcester Polytechnic Institute
Narges Mahyar, College of Information and Computer Sciences, University of Massachusetts Amherst
Dr. Emily Wall, Emory University
There are many ways that work in visualization can have immediate social impact— working closely with community stakeholders, exploring how to present data for mass audiences, evaluating the potential of visualization for advocacy or as a tool to shape public policy— all have the potential to reshape society for the better. Thoughtfulness, reflection, and critique are likewise important to build up a clear picture of both the potential benefits and potential harms of visualization research.
The Visualization for Social Good Workshop (Vis4Good) aims to provide a central venue within the IEEE VIS community for surfacing work that critiques, defines, or explores the impact of data visualization on society. Through a blend of paper sessions, invited presentations, and break-out groups, we hope that the inaugural Vis4Good 2022 Workshop encourages attendees to harness visualization research to tackle critical challenges in responsible AI, clean energy, human health and well-being, and other domain areas with critical societal impact.
Katherine E. Isaacs, Computer Science, University of Arizona
Steffen Koch, University of Stuttgart
Timo Ropinski, Visual Computing Group, Ulm University
Stefan Wagner, Institute of Software Engineering, University of Stuttgart
Daniel Weiskopf, University of Stuttgart
Testing hardware, software, and other products is a highly relevant task to ensure quality and reliability. Due to the increasing complexity of such systems or products, testing tasks are not only an inevitable step that can occur at different stages of product life cycles, but they are getting increasingly complex as well. Such tasks include among others: test planning, defining tests and test data, carrying out test plans, as well as collecting and analyzing test results. Monitoring and profiling tasks are added when later phases in the life cycle of systems and products are taken into account. All these different tasks need to scale with an increasing number of tests conditions, parameters, test samples, boundary conditions, etc., and with more sophisticated analysis methods including AI-based approaches.
While the visual representation of test results is not uncommon, interactive steering has the potential to advance test processes at different stages in a system’s or product’s life cycle. Interactive visualization can support test practitioners to cope with inherent complexity, e.g., by helping to orchestrate complex test procedures and analyses.
Currently, there is a gap between industry practice in testing and visualization research. This workshop aims to bring together researchers and practitioners from different domains where testing is relevant. We see it as a first step toward building a community of stakeholders from industry and academia interested in visualizing test and monitoring-related problems. To achieve this gaol, the workshop will start a discussion on intrinsic problems of different test procedures to improve the understanding of differences and commonalities in different domains. In addition, we would like to collect examples for supporting test tasks visually and to discuss which testing problems can benefit from interactive visualization. By gathering examples and research approaches from this area, we aim to collect best practices that will serve as the basis for setting up a research agenda.