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DE705 Interactive Data Visualization & DE303 Information Graphics and Visualization

Autumn 2026

Instructor: Prof. Venkatesh Rajamanickam

31 Aug to 18 Sep 2026

Venue: BDes 3 Classroom & Mini Theatre, RBTIC

Course repository Assignments, issue threads, and course materials Contact instructor Prof. Venkatesh Rajamanickam

Course Overview

Information graphics reveal the hidden, explain the complex, and illuminate the obscure. Constructing visual representations of information is not a simple translation of what can be read into what can be seen. It requires filtering information, establishing relationships, discerning patterns, and representing them in ways that help a viewer construct meaningful knowledge.

Recent advances in technology have enabled the creation, recording, and analysis of vast amounts of data. Where data was once scarce, it is now abundant. Computer science has made major progress in handling and analyzing that data, but the methods needed to display and communicate it effectively still require deliberate design training. This course addresses that gap through principles from graphic design, visual art, perceptual psychology, and cognitive science.

Course Objectives

  • Understand core visualization techniques and theory, including data models, graphical perception, encoding, and interaction.
  • Plan data-based storytelling through charts, maps, and diagrams.
  • Build and evaluate visualization systems through practical assignments.
  • Read and discuss research literature in visualization and information design.

Course Contents

  • Information visualization overview and historical perspective
  • Vision, perception, and cognition principles for information visualization
  • Data principles, models, dimensions, and analysis
  • Information taxonomy
  • Visual encoding of data
  • Mapping, cartography, and geo-visualization
  • Visualization tools and strategies
  • Data stories and presentation
  • Short exercises and a mini project in visual representation of data

Schedule

SessionTopicsAssignment or ActivityAdditional Readings and Resources
Day 01Lecture 01: Introduction to Data VisualizationAssignment 1: Visualization CritiqueOn the role of design in information visualization. Moere, A. V., & Purchase, H. (2011). Information Visualization, 10(4), 356-371.
A Tour through the Visualization Zoo. Jeffrey Heer, Michael Bostock, Vadim Ogievetsky. Communications of the ACM, 53(6), pp. 59-67, Jun 2010.
The Value of Information Visualization. Jarke van Wijk. Proceedings of the IEEE Visualization Conference, pp. 79-86, 2005.
Day 01Lecture 02: Visualization Typology; review of Assignment 1Assignment 2: Chart Deconstruction and RedesignVisualization Typology proposed by Scott Berinato.
From Viz to Data.
A periodic table of visualization methods.
Day 02Lecture 03: Data; review of Assignment 2Assignment 3: Comparative VisualizationsOn the Theory of Scales of Measurement. S. S. Stevens. Science New Series, Vol. 103, No. 2684, pp. 677-680. Jun 1946.
Reflections on how designers design with data. Alex Bigelow, Steven Drucker, Danyel Fisher, Miriah Meyer. AVI ‘14 Proceedings of the 2014 International Working Conference on Advanced Visual Interfaces, pp. 17-24.
The eyes have it: a task by data type taxonomy for information visualizations.
Day 03Lecture 04: Data Abstraction;
Lecture 05: Task Abstraction; review of Assignment 3		Visualization Analysis and Design by Tamara Munzner.
Her lecture video of the Data Abstraction chapter.
Her lecture video of the Task Abstraction chapter.
Day 04Lecture 06: Visual Encoding; review of Assignment 3Complete the first 3 assignments, incorporating the feedback from the review discussions and submit by SundayNature Methods Points of View columns on Data Visualization
Day 05Guest faculty Rasagy Sharma
Lecture 07: Using AI to create DataViz: Automating, Augmenting, Amplifying		Assignment 4a: Creating an interactive data visualization using Generative AI
Assignment 4b: Creating skill(s) to augment & amplify data viz process		Data Vizard, a multi-skill workflow for data visualization, by Kenneth & Rasagy.
Collection of data viz about FIFA World Cup made through one-shot prompts & skills.
Reflections from building Data Vizard.
How AI will lead to democratization of data viz (Article on Nightingale).
VIS x GenAI (2025 Archive): Dedicated track at IEEEVIS.
Day 06Review of Assignment 4Assignment 5 (Group): Exploratory Data Analysis and VisualizationYour final deliverable should be a comment to the git issue #59 that consists of 10 or more captioned visualizations detailing your most important insights. To help you gauge the scope of this assignment, see this MIT dataviz course example report analyzing data about motion pictures.
Day 07Guest faculty Arjun Srinivasan
Lecture 08: Interaction in Information Visualization;
Lecture 09: Visualization Systems and Toolkits		Review of Assignment 4
Day 08Lecture 10: Design Hueristics; presentation of Assignment 5Nightingale: What Makes A Data Visualisation Elegant? by Andy Kirk, Sep 2019.
Days 09 to 12Dataviz ToolsActivity: Data Visualization ToolsThis is a collection of some of the many data visualisation and related tools, applications, toolkits, libraries, platforms, and packages.
Another well-curated list of dataviz tools.

Assessment

Assignment 1: Visualization Critique

10%

Assignment 2: Chart Deconstruction & Redesign

15%

Assignment 3: Comparative Visualizations

20%

Assignment 4a: Creating an interactive data visualization using Generative AI

10%

Assignment 4b: Creating skill(s) to augment & amplify data viz process

15%

Assignment 5 (Group): Exploratory Data Analysis & Visualization

30%

Textbook

There is no required textbook for the course. Lecture slides are made available as PDFs for reference.

Reference Books

  1. Bertin, Jacques. Semiology of Graphics: Diagrams, Networks, Maps.
  2. Cairo, Alberto. The Functional Art.
  3. Few, Stephen. Show Me the Numbers: Designing Tables and Graphs to Enlighten.
  4. Fry, Ben. Visualizing Data: Exploring and Explaining Data with the Processing Environment.
  5. Harmon, Katherine. You Are Here.
  6. Harris, Robert L. Information Graphics: A Comprehensive Illustrated Reference.
  7. Helfand, Jessica. Reinventing the Wheel.
  8. Holmes, Nigel. Designer’s Guide to Creating Charts and Diagrams.
  9. Holmes, Nigel. Wordless Diagrams.
  10. Institute for Information Design Japan. Information Design Source Book.
  11. Jacobson, Robert. Information Design.
  12. McCloud, Scott. Understanding Comics.
  13. Mijksenaar, Paul and Piet Westendorp. Open Here: The Art of Instructional Design.
  14. Mijksenaar, Paul. Visual Function: An Introduction to Information Design.
  15. Munzner, Tamara. Visualization Analysis and Design.
  16. Myer, Eric K. Designing Infographics.
  17. Tufte, Edward. Envisioning Information.
  18. Tufte, Edward. Visual Explanations: Images and Quantities, Evidence and Narrative.
  19. Tufte, Edward. The Visual Display of Quantitative Information.
  20. Ware, Colin. Information Visualization, Third Edition: Perception for Design.
  21. Yau, Nathan. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics.
  22. Yau, Nathan. Data Points: Visualization That Means Something.

Contact

You can reach Prof. Venkatesh Rajamanickam via email.