Tutorials

Accepted Tutorials

Here is the list of the accepted tutorials.

Visualization Analysis and Design

Sunday, October 22, 2023: 9:00 AM-12:00 PM AEDT (UTC+11)

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.

A Hands-on TTK Tutorial for Absolute Beginners

Sunday, October 22, 2023: 9:00 AM-12:00 PM AEDT (UTC+11)

Christoph Garth, RPTU Kaiserslautern-Landau
Robin Georg Claus Maack, University of Kaiserslautern
Mathieu Pont, CNRS, Sorbonne Université
Julien Tierny, CNRS, Sorbonne Université

This tutorial provides a basic, beginner’s introduction to topological data analysis and visualization with the Topology ToolKit (TTK). While previous editions of the TTK tutorial (2018 to 2022) were organized as mini-symposia (focused on the descriptions of TTK’s latest features), this year, in contrast, we would like to organize a very basic beginner’s hands-on tutorial. Specifically, the goal of this tutorial is to accompany attendees in the installation of TTK on their laptop as well as in the running of a few basic examples, all in a very beginner-friendly step-by-step description. This decision is motivated by attendee feedback which we collected at previous editions of the TTK tutorial. We address this feedback in this tutorial proposal. Then, for the first time, beginners would be able to come to the tutorial without prior TTK experience, and walk out with TTK installed on their system, capable of running a few examples and ready to go further. We believe this basic hands-on tutorial will facilitate the adoption of TTK and topological techniques to a broader audience. The tutorial will be organized as follows. The first hands-on exercise will be dedicated to the installation of TTK. The second hands-on exercise will be focused on ParaView’s basic usage. The following three hands-on exercises will be dedicated to the step-by-step replication of three examples extracted from TTK’s online example database (vortex extraction in fluid dynamics, Morse-Smale complex extraction in quantum chemistry and merge tree comparison in ensemble data).

We kindly ask potential attendees to optionally pre-register at the following address, in order for us to reach out to them ahead of the tutorial with information updates (for instance, last minute updates, instructions to download the tutorial material package, etc.): https://forms.gle/t4xX4a3pJjyiU67D9 Tutorial web page (data, material, schedule, etc.): https://topology-tool-kit.github.io/ieeeVisTutorial.html

NLP4Vis: Natural Language Processing for Information Visualization

Sunday, October 22, 2023: 9:00 AM-12:00 PM AEDT (UTC+11)

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.

Demystifying Color in Your Data Visualizations

Sunday, October 22, 2023: 2:00 PM-5:00 PM AEDT (UTC+11)

Theresa-Marie Rhyne, Visualization Consultant

This tutorial provides an overview of the basics of color theory while exploring various color mysteries. New to 2023, we show how to use Adobe’s Firefly, a creative generative AI model in Beta, to expand your data color scheme choices. You also learn how to build your own colormaps by transforming color harmonies. Several puzzling notions are examined. These include but are not limited to discovering that Magenta is not a spectral color, merging Red and Green lights results in Yellow, and most Blues in Data Visualizations turn out to be Cyan-Blue combinations. 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. For example, you learn how to transition from Red as a primary hue in RGB display space to Red as a secondary combination of Magenta and Yellow in CMYK printer space. You explore online and mobile color apps, like Adobe Firefly, and HCL Wizard, to help with continued colorization. Many of these tools are freely available. 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 with color suggestion tools.

Mining Useful Information Via Complex Network Visualization

Monday, October 23, 2023: 9:00 AM-12:00 PM AEDT (UTC+11)

Sonali Agarwal, IIIT Allahabad, Prayagraj
Garima Jindal, IIIT Hyderabad
Sanjay Kumar Sonbhadra, ITER, Shiksha ’O’ Anusandhan
Narinder Singh Punn, IIITM Gwalior
Sadhana Tiwari Sadhana, IIIT Allahabad, Prayagraj
Ritesh Chandra, IIIT Allahabad, Prayagraj

The process of visually representing networks of connected entities, links as well as nodes is termed as network visualization, also referred to as graph visualization or link analysis. The proposed tutorial is intended to provide a detailed coverage of contemporary complex network visualization techniques to support the understanding of various existing complex systems. The tutorial is covering basics of complex networks along with various visualization techniques under faceting perspective, application perspective and system perspective. After introducing several use cases of complex networks, the critical challenges incurred while developing multi-layer graph visualization will also be covered. Furthermore, future research directions are uncovered to address such challenges. Multilayer networks are expected to play a significant role in the study of complex systems in the future. It will bring the visualization community closer to the application domains as well as the complex systems communities.

Transparent Practices for Quantitative Empirical Research

Monday, October 23, 2023: 2:00 PM-5:00 PM AEDT (UTC+11)

Abhraneel Sarma, Northwestern University
Chat Wacharamanotham, Swansea University
Fumeng Yang, Northwestern University
Maryam Hedayati, Northwestern University

Transparent research practices enable the research design, materials, analytic methods, and data to be thoroughly evaluated and potentially reproduced. This tutorial presents current best practices and tools that increase research transparency for VIS researchers, practitioners, and students. The tutorial will cover the most relevant concepts, guidelines, and practices in Open Science—how to transparently conduct quantitative empirical research, report the results, and share the artifacts of your research. We will also include exercises where participants will be able to apply transparent research practices.

TAURUS: a Unified Framework for Creating Graph Layouts

Monday, October 23, 2023: 2:00 PM-5:00 PM AEDT (UTC+11)

Yunhai Wang, Shandong University
Oliver Deussen, University of Konstanz
Mingliang Xue, Shandong University
Zhi Wang, Shandong University

Graph layout is a key technique in graph visualization. There is a wide variety of techniques related to graph layout available, but there is no suitable tutorial to help new researchers understand the differences and connections between these techniques. In this tutorial, we will systematically classify existing graph layout techniques such as force-based and stress-based models and explain the connections between them. Using our framework TAURUS we will map most of them to a unified formulation, which helps to compare them. In parallel we will show the effects of the techniques by interactively generating results using our fast solver, various parameters will be edited to show the effects of the different methods. In the second part of the tutorial, we will focus on non-physical-based models such as tsNET that do not follow a physical metaphor. At the end, we will move towards machine learning for graph layouts and show various applications for graph layout.

The tutorial introduces the fundamentals and state-of-the-art of graph layout. Rooted in a theoretical perspective it introduces design concepts and algorithmic principles of a large number of graph layout methods. It will help beginners to enter the field of graph layout fast and advance their research. Our tutorial includes both course instructions as well as interactive demonstrations, participants can play around with all concepts using the TAURUS website and our library.

Design Sprints for Visualization

Monday, October 23, 2023: 2:00 PM-5:00 PM AEDT (UTC+11)

Carolina Nobre, University of Toronto
Johanna Beyer, Harvard University

Design sprints describe a time-constrained, interdisciplinary process based on rapid prototyping and testing to define goals quickly, validate ideas, and decide on a final design. The well-defined, interactive, and time-constrained design cycle makes design sprints well-suited both for teaching active-learning-centered visualization courses and for creating visualizations in real-world settings. In this tutorial, we will conduct a complete design sprint workshop, showcasing its value both in a classroom setting and for real-world applications. The tutorial contains 5 sections, each with guided active-learning activities. The tutorial starts with a theoretical introduction to design sprints, and then progresses through each of the five stages: Map, Sketch, Decide, Prototype, and Test. Each section will explain the technique, followed by hands-on experience performing the step. We conclude the tutorial with a show-and-tell, where groups can present their final design to all participants.