Data Visualisation Bootcamp

An intensive five-week project-based online workshop

Overview

Data visualisation is a cross disciplinary activity that requires us to operate at the intersection of a visual designer, a data scientist, and a storyteller. In that respect it is a craft - both a science and an art. The science involves learning the principles of graphical perception, data sensemaking and cognitive science to better understand how our eyes, ears and brains can process inputs in an effective and accurate manner. The art involves exploring creative and innovative ways to create compelling data-visual-stories that appeal and engage at an emotional and aesthetic level. This workshop is designed for learning this craft of data visualisation.

Objectives

The aim of this workshop is to build a strong foundation for your personal journey in creating compelling data visualisation. There are three main objectives:

  1. To understand the foundational building blocks and design approaches for crafting data visualisation.
  2. To learn these principles through dialogue, exemplars, exercises and feedback in an interactive peer group setting.
  3. To consolidate these learning through application in your own personal data visualisation project.

Personal Project

The main component of the bootcamp is the personal data visualisation project. This is “Bring Your Own Project” (BYOP) - a data-driven project which can anchor and provide the playground for you to apply the learnings during the course. The project review sessions would be used as a structure to help you ideate, share and progress through its application. The possible type of projects (but not limited) are:

Group Sessions

There are 15 group sessions — three sessions per week over five-week — conducted online. These would be delivered with a mix of teaching, discussion and reflections, as well as individual and group exercises. It would aim to cover the following topics.

Week One: Fundamentals

#1 Value & Purpose

  • Explore the visual-wired and the story-wired brain
  • Purpose of visualisation - Expression (record), Exploratory (analyze) and Explanatory (communicate)
  • Semiotics, Signs & Meaning: Encoding & Decoding
  • Medium, Style, Tone and Aesthetics

#2 Layers & Flow

  • The fundamental layers: Data, Visual, Annotation & Interaction
  • Data layer: Data Inputs & Loading, Transformations
  • Visual layer: Marks, Encodings, Coordinates, Scales, Composition
  • Annotation layer: Guides, Grids & References, Titles & Subtitles, Text Annotation
  • Interaction layer: Navigation, Transition, Selection, Highlighting, Filtering, Brushing & Linking, Sorting

#3 Process & Tools

  • The process for crafting data visualisation: The Why, The What, The How, The So-What & The So-Why
  • The tools landscape: Charting-based tools, Grammar-based tools and Canvas-based tools
  • Overview & introduction to select tools for data visualisation

Week Two: See the Data

#4 Wrangle & Explore

  • Data Wrangling: Acquire, Clean & Refine
  • Data Transformations: Reshape, Bin, Sort, Filter, Aggregate, Calculate
  • Finding Data Abstractions: Patterns, Trends, Outlier, Deviations

#5 Questions & Encoding

  • Types of questions answered and visualisations that can be used to represent them
  • Explore a guide to choosing of simple 1, 2 & 3-dimensional representations
  • Learn about visual representations that are best avoided or minimized

#6 Perception & Decoding

  • See the principles of data-ink and chart-junk
  • Understand how visual perception works and what we know about decoding
  • Further guidance in choosing appropriate marks, channels and representations

Week Three: Show the Visuals

#7 Colour & Scales

  • Make effective use of colour
  • Colour for categorical encoding and quantitative encoding
  • Scales for Position, Shape, etc. and Scale transformations
  • Layout & Coordinate Transformations

#8 Composition & High-Density

  • Choosing visual representation for multiple variables e.g. using facets or small multiples
  • Composition Techniques: Concatenate, Juxtapose, etc.
  • Using high-density representations: spark lines, bullet graphs, tree maps etc.

#9 Text, Networks and Geo-Spatial

  • Text Visualisation
  • Network & Graph Visualisation
  • Geo-Spatial Visualisation

Week Four: Tell the Story

#10 Messaging & Annotation

  • Selection of messaging - text annotation and verbal
  • Understand use of typography and annotation within graphical communication
  • Explore design of secondary graph components - trend and reference lines, scales, tick marks, grid lines, axes and legends

#11 Structure & Attention

  • Understand point of view: explanatory vs. exploratory
  • Choose a structure: flow, relationships, grouping or narrative
  • Elements of layout: grids, white space and screen space
  • Understand guiding design principles: compactness, modularity, reveal, focus & guide attention, customization, context aware, lead to action

#12 Storytelling & Narratives

  • Explore the principles of storytelling and narrative
  • Lessons on how stories work from other mediums - oral storytelling, journalism, movies, comics and consulting
  • Building a data-visual-story - understand framing, transitions and flow

Week Five: Engage the Audience

#13 Reactive & Interactive

  • Learn the principles of reactive programming
  • Allowing interactive data-model manipulation
  • Explore common interaction patterns: select, explore, reconfigure, encode, filter, drill-down, connect and dynamic queries

#14 Animation & Context

  • Engagement in context - personal, presentation & participation
  • Use of motion and animation in visual transitions
  • Adapting Visualisation to different usage context & medium

#15 Summary & Forward

  • Emerging trends and context of Data Visualisation
  • "Visualisation alone is not enough" - Ethics, Accessibility, Literacy
  • Way Forward & continuing your learning Journey

Workshop Details

Participant Profile — There are no pre-requisite knowledge or roles necessary for attending the workshop, though prior exposure to handling data (at least using Excel) would make the journey easier for you. Possible roles that would benefit from the workshop:

Number of Participants — The maximum number of participants for the workshop is capped at 12. The small size would enable a more participative environment with group interaction & presentations possible as well as opportunities to have one-to-one learning interactions.

Session Schedule — The group session will be conducted over 5 weeks - every Monday, Wednesday & Friday from 1700 to 1830 IST. You will get a calendar invite for each of the group session to join online. The project review session will be for 30 minutes every week and would be scheduled separately.

Session Logistics — As the sessions would be conducted online - you would require a desktop / laptop computer with a modern browser and reasonable speed internet to attend them. …

Facilitator’s Profile

Amit Kapoor is interested in learning and teaching the craft of telling visual stories with data. He is the founder partner at narrativeVIZ Consulting, where he teaches data-science, data-visualisation and data-stories as tools for improving communication, persuasion, and leadership and conducts workshops on these topics for businesses, nonprofits, and academic institutes. He has also taught data visualisation as a guest faculty in design context at NID, Bangalore and in management context at IIM Bangalore & IIM Ahmedabad

His background is in strategy consulting in using data-driven stories to drive change across organizations and businesses. He has more than 15 years of management consulting experience, first with AT Kearney in India, then with Booz & Company in Europe and more recently for startups in Bangalore. He did his B.Tech in Mechanical Engineering from IIT, Delhi and PGDM (MBA) from IIM, Ahmedabad. You can find more about him at amitkaps.com and tweet him at @amitkaps.