Tutorials

Accepted Tutorials

Here is the list of the accepted tutorials.

Please see the Schedule for times.

Visualization Analysis and Design

Tamara Munzner, University of British Columbia

This introductory tutorial will provide a broad foundation for thinking systematically about visualization systems, built around the idea that becoming familiar with analyzing existing systems is a good springboard for designing new ones. The major data types of concern in visual analytics, information visualization, and scientific visualization will all be covered: tables, networks, and sampled spatial data. This tutorial is focused on data and task abstractions, and the design choices for visual encoding and interaction; it will not cover algorithms. No background in computer science or visualization is assumed.

Developing Immersive and Collaborative Visualizations with Web Technologies

Sunday, October 13, 2024: Morning

David Saffo, J.P. Morgan Chase & Co
Cheng Yao Wang, J.P. Morgan Chase & Co
Feiyu Lu, J.P. Morgan Chase & Co
Blair MacIntyre, J.P. Morgan Chase & Co
Benjamin Lee, J.P. Morgan Chase & Co

Immersive analytics (IA), the application of immersive technologies such as augmented and virtual reality towards the task of data visualization and analytics, is a rapidly growing area of research.Web-technologies have the potential to greatly benefit the development of immersive visualizations and systems with their affordances for multi-device distribution and networking. This tutorial is aimed at researchers and developers who want to learn how to implement immersive and collaborative visualizations and system with web-technologies. Tutorial participants will learn these skills through hands on coding activities using the latest tools for developing web applications. Furthermore, participants will gain practical skills and knowledge of WebXR, Anu.js, D3.js, Vite, and Coleuses. By the end of this half-day course, participants will be able to view and interact with an immersive visualization of their making along side their peers in a multi-user collaborative environment—all through their devices web-browser.

Generating Color Schemes for your Data Visualizations

Theresa-Marie Rhyne, Visualization Consultant

This tutorial provides an overview of the basics of color theory and shows how to use Generative AI tools, like ChatGPT and Adobe Firefly, to expand your data color scheme choices. You explore how to build your own colormaps by transforming color harmonies into data color schemes. The course is intended for a broad audience of individuals interested in understanding, applying, and building color schemes for data visualization.

With a five stage colorization process, you learn how to build and select a data color scheme with color harmony, incorporate color models concepts and address color deficiency. You discover the differences between mixing colors in perceptual, display, printer, and traditional painter color spaces. You explore online and mobile color apps, like ChatGPT, Adobe Firefly, Adobe Color, Adobe Capture, ColorBrewer, HCL Wizard, and Data Color Picker to help with continued colorization. Along the way, color vision principles, perceptual uniformity with the Hue Chroma Luminance (HCL) model as well as color gamut, spaces and systems are examined. Concepts like extending the fundamentals of the Bauhaus into digital media ,the Rainbow colormap dilemma, and overviews of appearance principals are covered. Bring your digital visualization examples for hands on experiences in generating color suggestions and schemes.

Running Online User Studies with the reVISit Framework

Jack Wilburn, University of Utah
Hilson Shrestha, Worcester Polytechnic Institute
Zach Cutler, University of Utah
Yiren Ding, Worcester Polytechnic Institute
Brian Bollen, University of Utah
Carolina Nobre, University of Toronto
Lane Harrison, Worcester Polytechnic Institute
Alexander Lex, University of Utah

There currently are two main approaches for running online user studies: experimenters can use commercial survey tools, which are easy to use but can be costly, hamper reproducibility, and have limitations for complex stimuli; or they can build custom software to run and instrument a study, which is a laborious and complex task. In this tutorial, we introduce participants to a new, open-source alternative: the reVISit study platform. Many studies quickly reach a level of complexity such that designers have not only to consider their stimuli and experimental tasks, but also the study UI, data hosting, participant recruiting, randomization, etc. ReVISit ameliorates these problems and allows study designers to focus more on the research questions and stimulus design. ReVISit removes the tedium of study design by providing built-in components that most studies will need. ReVISit uses a domain specific language to allow study designers to quickly create studies, and to deploy them as static websites that are publicly accessible. This tutorial will introduce reVISit to the visualization community and allow com- munity members to get hands on experience with it through a series of practical examples. Throughout the tutorial, participants will im- prove on a study until they have developed and deployed a study of an interactive, fully instrumented data visualization.

LLM4Vis: Large Language Models for Information Visualization

Monday, October 14, 2024: Morning

Enamul Hoque, York University

This tutorial will provide an introduction to natural language processing (NLP) to interested researchers in the visualization (Vis) community. It will first motivate why NLP4Vis is an important area of research and provide an overview of research topics on combining NLP and Vis techniques. Then an overview of deep learning models for NLP will be covered. A particular focus will be provided on highlighting the recent progress on large language models such as ChatGPT and how such models can be leveraged to solve various NLP tasks for visualizations. In the final part, we will focus on various application tasks at the intersection of NLP and Vis. We will conclude with an interactive discussion of future challenges for NLP+Vis applications. The audience will include researchers interested in applying NLP for visualizations as well as others who focus more generally at the intersection of AI and visualization.

Enabling Scientific Discovery: A Tutorial for Harnessing the Power of the National Science Data Fabric for Large-Scale Data Analysis

Amy Gooch, University of Utah
Aashish Panta, University of Utah
Alper Şahıstan, University of Utah
Xuan Huang, University of Utah
Michela Taufer, University of Tennessee
Jack Marquez, University of Tennessee
Giorgio Scorzelli, University of Utah
Valerio Pascucci, University of Utah

In this interactive half-day tutorial, participants explore the advanced applications of the National Science Data Fabric (NSDF) services and comprehensive strategies for end-to-end scientific data analysis. The tutorial targets a broad audience, from researchers and students to developers and scientists, each finding valuable insights into managing and analyzing large datasets, with a particular focus on datasets exceeding 100TB. Attendees gain hands-on experience constructing modular workflows, leveraging public and private data storage and streaming solutions, and deploying sophisticated visualization and analysis dashboards for scientific discovery. The tutorial highlights NSDF’s role in supporting the SC conference’s themes by providing scalable solutions for high-performance computing, networking, storage, and analysis. It covers various topics, from an overview of NSDF’s capabilities to addressing common pain points in data analysis to intermediate hands-on exercises using NSDF services for Earth science data and advanced applications, including handling and visualizing massive datasets in domains requiring high-resolution data management. Participants leave a deeper understanding of how NSDF services integrate into their research workflows to enhance data accessibility, sharing, and collaborative scientific discovery. This tutorial advances the knowledge of data-intensive computing and empowers attendees to harness the full potential of NSDF in their fields.

Preparing, Conducting, and Analyzing Participatory Design Sessions for Information Visualizations

Adriana Arcia, University of San Diego
Samantha Stonbraker, University of Colorado
Sabrina Mangal, University of Washington
Maichou Lor, University of Wisconsin-Madison

Participatory design is a recognized method for ensuring that design products are effective among and acceptable to target audiences. Despite the growing popularity of participatory design, existing guidelines and recommendations for how to conduct participatory design sessions gloss over important details that can have a profound impact on how smoothly design sessions run and the extent to which they maintain rigor and generate actionable data. Furthermore, there are unique considerations that apply when the product of participatory design is a visualization rather than, say, text. Therefore, in an effort to address this gap and support others wishing to undertake participatory design work, our team has drafted a practical manual based on our collective experiences, complete with tips for iteration tracking, a session guide template, suggested design session prompts, a note-taking template, and a comprehensive preparation checklist. In this interactive tutorial, attendees will be introduced to the design session manual and related resources before practicing the techniques in small groups with static visualizations.