Storytelling in an age of data
Visualizations and explorables
Chan Chi-Loong, V/R
Hi... I'm Chi-Loong
and I do data visualizations for a living.
- What is data viz?
- UX and data viz design
- Data viz in data science
- Data viz: Real-life use
- Community: Visualizing Singapore
Data is important...
...but it ain't worth much if you can't explain why it is important.
DIGITAL STORYTELLING =
TECH + DATA + ART
The confluence of data and new technologies present opportunities to explore how stories are told.
Exploring digital frontiers requires both artists and engineers.
It is a blend of good design, content and technology.
What is data visualization?
Data visualization is a graphical representation of data, and is a powerful tool for exploratory analysis / storytelling.
A powerful, visible use case is media. You see examples in New York Times, Washington Post, Straits Times.
Data Viz Components
Data + UX + Story
Data, which we mine to derive insights and trends.
UX, which is the interactive interface through which we explore the data.
Story, which supplies the context for us to understand why we are exploring the context.
Story Time: Budget
Story Time: GE 2015
So what makes a good data viz?
- Seperation of the data from the presentation so it can be easily updated.
- Not just a data dump, but curated with context within a story / designed with a specific intent.
- Updated automatically if possible with real-time data (via APIs).
- Proper labels, proper proportions. Don't mislead (especially on purpose!)
- Don't overdesign what is necessary to tell a good story.
- Design to go up/down the ladder of abstraction.
Electoral Divisions 2015 website
WTF Visualizations: Visualizations that make no sense
Example 2: Population demographics
Data viz in data science (ML, AI)
...Also known as the unicorn
Visualization in data science
Approaches to doing data visualization
- For exploratory analysis use Excel.
- Buy an enterprise software tool like Tableu, Qlik, PowerBI or Spotfire
- Use a cloud-based tool like Infogram, Piktochart, cartoDB, etc.
- For data science use R or Python. Ggplot2 and shiny for R, etc.
- Use a charting library like Highcharts, Morris charts, etc.
- Or build your own custom charts for web frontend using D3.js.
Data roles: Recap
Where do you fit in for visualization?
As for me
I'm a visualization engineer and I want to build beautiful things.
Because I'm willing to spend the time to get exactly the results I want.
It is a specific kind of UX frontend engineer, except that I go deep into visual / audio / interface libraries
Examples: D3.js, three.js
Data viz: Real-life use cases
Frontend dashboard work
As explorables / calculators / embeddables
As showcase and event pieces
Community: Visualizing Singapore
Started out as a portfolio for my work and a reaction to data.gov.sg in 2015 (compare to dataviva).
To be fair, data.gov.sg is a lot better in 2020, but there is still room for a community site.
- Because in a world deluged by data, data visualizations help us make sense and understand the world better.
- Because the way information is presented can be improved, or seen from a different angle.
Because it is more interesting when we look at the world through different lenses.
Mash-ups of different data sources can yield surprising stories and insights.
If you have an interest in data visualizations or storytelling, join our meetups: Hacks/Hackers SG or Data Vis SG
I'm looking for people to help grow Viz.sg as a community site. Visualizing Singapore one dataset at a time, for all to use. Come talk to me!
www.vslashr.com | firstname.lastname@example.org