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Workshops

CityVis: 2nd Workshop on Urban Data Visualization — Focus: The Role of the Citizen

Date and Time: TBD

Lyn Bartram, Simon Fraser University
Alex Godwin, American University
Sarah Goodwin, Monash University
Sebastian Meier, Technologiestiftung Berlin

Contact: contact@sebastianmeier.eu

With the growth and increasing density of urban areas, new technologies are emerging and data is becoming an essential asset to modern cities. Visualization as a tool for analysis, exploration and communication has become a driving force in the task of unravelling the complex urban fabrics that form our cities. In this workshop series, we want to critically assess this notion and ask how can data and data visualization be used to serve and better understand or even organize urban processes? We are particularly interested in multidisciplinary perspectives, especially on the human-centric component of urban visualizations. In the initial workshop at IEEE VIS 2018, we established a definition, goals and challenges for urban visualizations. Based on these findings, we propose to focus discussions in the 2nd workshop on the critical role of citizens in urban visualization and how they can help ensure future urban visualizations are designed, developed and evaluated more effectively.

DSIA 2019: Data Systems for Interactive Analysis

Date and Time: TBD

Leilani Battle, University of Maryland, College Park
Dominik Moritz, University of Washington
Joseph Cottam, Pacific Northwest National Laboratory

Contact: leilani@cs.umd.edu

The primary goal of the DSIA workshop is to bring together researchers from the database and machine learning community to participate in VIS. The premise of the workshop is that the development of back-end data systems is of increasing importance for visualization tools due to the growing size and complexity of data and the increased demand for interactivity. However, tackling the issue of data systems cannot be addressed by VIS researchers alone. Collaboration with other communities is essential to ensure integration between the front-end visualization and back-end storage and computation.

EVIVA-ML: Evaluation of Interactive Visual Machine Learning Systems

Date and Time: TBD

Nadia Boukhelifa, INRA
Anastasia Bezerianos, Univ Paris-Sud
Enrico Bertini, New York University
Christopher Collins, University of Ontario Institute of Technology
Steven Drucker, Microsoft Research
Alex Endert, Georgia Institute of Technology
Jessica Hullman, Northwestern University
Michael Sedlmair, University of Stuttgart

Contact: nadia.boukhelifa@inra.fr

In interactive visual machine learning (IVML), a human operator and a machine collaborate to achieve a task mediated by an interactive visual interface. Work in interactive visual machine learning has mainly focused on developing working prototypes, and less on methods to evaluate IVML systems. The limited existing work on the evaluation of such systems has focused on explainable machine learning and aims to test whether analysts understand what the artificial intelligence is learning or what powers its decisions. The human-in-the-loop approaches to machine learning though extend the role of the human to not only be there to interpret and understand the underlying models or decisions, but to also actively act on, and react to, these models. This brings forth not only numerous intelligibility, trust and usability issues, but also many open questions with respect to the evaluation of the various facets of the IVML system, both as separate components, and as a holistic entity that includes both human and machine intelligence. The goal of this workshop is to bring together visualization researchers and practitioners to discuss experiences and viewpoints on how to effectively evaluate interactive visual machine learning systems. And ultimately to form a plan to develop a research agenda for IVML evaluation.

MLUI: Machine Learning from User Interactions for Visualization and Analytics

Date and Time: TBD

John Wenskovitch, Virginia Tech
Michelle Dowling, Virginia Tech
Chris North, Virginia Tech
Remco Chang, Tufts University
Alex Endert, Georgia Institute of Technology
David Rogers, Los Alamos National Laboratory
Fabian Camilo Peña Lozano, Universidad de los Andes
Sriram Yarlagadda, DePaul University
Eli T Brown, DePaul University

Contact: johnwenskovitch@gmail.com

The high-level goal of this workshop is to bring together researchers from across the VIS community to share their knowledge and build collaborations at the intersection of the Machine Learning and Visu- alization fields, with a focus on learning from user interaction. Our hope in this workshop is to pull expertise from across all fields of VIS in order to generate open discussion about how we currently learn from user interaction and where we can go with future research. To achieve this goal, we propose a half-day workshop that incor- porates paper presentations, posters, and free-form discussion. Our goal is to allow for the presentation of cutting-edge research, while also providing participants and speakers with time to exchange ideas and to discuss new research directions.

Multilayer Nets: Challenges in Multilayer Network Visualization and Analysis

Date and Time: TBD

Fintan McGee, Luxembourg Institute of Science and Technology
Tatiana von Landesberger, TU Darmstadt
Daniel Archambault, Swansea University
Mohammad Ghoniem, Luxembourg Institute of Science and Technology

Contact: fintan.mcgee@list.lu

Multiple types of nodes/edges in a network are often flattened into a single network. However, real-world data and systems are often more accurately modelled as a set of interacting networks, or layers, with different node and edge types. The concept of Multilayer Networks has recently become prominent in the field of complex systems and the topic is increasing in popularity in a range of domains. Multilayer Networks provide new challenges for visualization, visual analytics, interaction, and modelling. Building on a recent Dagstuhl seminar, our half day workshop will provide a venue for discussion of this important emerging topic. The vision is to stimulate research on Multilayer Networks within the wider visualization and visual analytics communities. The workshop will provide a platform for short presentations on work in progress related to this topic, time for discussions, and a keynote from Prof. Guy Melançon – a leading researcher in the visualization of multilayer networks.

SetVA: Set Visual Analytics

Date and Time: TBD

Daniel Archambault, Swansea University
Wouter Meulemans, TU Eindhoven
Luana Micallef, University of Copenhagen

Contact: w.meulemans@tue.nl

The visualization of sets of elements and their intersections is a fundamental problem of interest to the visualization and visual analytics community – as well as many application areas. As such, it has garnered wide-reaching interest not only in our community but in other communities that do not frequently meet with VIS/VA and each other: Diagrams/Logic, Graph Drawing, Computational Geometry, and application areas such as Biosciences. In this proposal for an IEEE VIS workshop, we seek to establish a venue for exchange between these communities, so that we are able to mutually benefit from our research activities. The workshop will primarily consist of longer presentations from each of the major areas, short talks/posters to make researchers aware of these activities, and longer discussion sessions to facilitate future collaboration.

Vis X AI: 2nd Workshop on Visualization for AI Explainability

Date and Time: TBD

Hendrik Strobelt, IBM Research AI
Mennatallah El-Assady, University of Konstanz
Adam Perer, Carnegie Mellon University
Duen Horng Chau, Georgia Institute of Technology
Fernanda Viegas, Google Brain

Contact: hendrik@strobelt.com

This workshop focuses on how we, as a visualization community, can use our expertise to explain machine learning models visually. By focusing on explainables submissions, our workshop will impact many beyond the visualization academic com- munity, providing educational sources for both visual and advanced ML techniques. Furthermore, our primer submissions will expose state-of-the-art ML techniques to the visualization community, allowing us to better understand how we can impact this field. Finally, our interactive audience sessions will attempt to bring together researchers interesting in better explaining machine learning models, spurring new collaborations.

Vis X Vision: Workshop on Novel Directions in Vision Science and Visualization Research

Date and Time: TBD

Madison Elliott, University of British Columbia
Zoya Bylinskii, MIT
Christine Nothelfer, Northwestern University
Cindy Xiong, Northwestern University
Danielle Albers Szafir, University of Colorado Boulder

Contact: maelliott1010@gmail.com

Interdisciplinary work across vision science and visualization has provided a new lens to advance research methods and the empirical understanding of mechanisms involved with viewing visual information. By studying how people leverage visual cognition to perceive and interpret visualized data, researchers gain direct insight towards evaluative metrics. Topics in vision sciences, such as memory, ensemble coding, numerical cognition, saliency, color perception, search, and pattern recognition map directly to common challenges encountered in visualization research. Designers can use insights from vision research to inform effective visualization designs, which can in turn inspire new opportunities to understand how such visualizations work. Building on the growing interest from both the vision science and visualization communities, this workshop provides a venue to bring new researchers to VIS, to discuss innovative discoveries at this intersection, share cutting-edge research methods/findings/proposals, and inspire new collaborations.

VisComm: Workshop on Visualization for Communication

Date and Time: TBD

Benjamin Watson, North Carolina State University
Robert Kosara, Tableau Research
Steve Haroz, INRIA
Noeska Natasja Smit, University of Bergen

Contact: bwatson@ncsu.edu

Our proposed half-day workshop will bring together communicative visualization practitioners with researchers from several research fields in visualization to address the questions raised by the rapidly growing communicative uses of visualization (in news graphics, information graphics, etc.). These questions span issues of audience, application, evaluation, understanding and practice. To encourage participation from communities that do not typically attend IEEE Visualization and write academic papers, we will not only accept short papers but also visual case studies, and recruit program committee members from those communities.