The J.A.R.V.I.S. framework for Data Viz

I have always been a huge fan of Iron Man, way before the Marvel Cinematic Universe (MCU) was even a thing. Yeah, I grew up with the comics and 90s cartoons.

‍

‍

‍

In those comics/cartoon, Tony Stark was a bigger asshole than what the MCU portrayed him. But his core drive was always his ability to learn and adapt from both his successes and failures, which makes him a truly formidable hero or villain (in some sense). He has over 60 armors built, each for a different purpose.

‍

‍

‍

‍

And many more... but you get the drift. And if you think about data visualization, it's very similar as we have different tools, different charts, different design styles to put together a piece of information that tells a story. Well, maybe that's why I'm equally passionate about data visualization as I am with Iron Man. Or maybe... I'm feeling extra Iron Man-ish, with a new swanky toy my wife bought for me recently.

‍

‍

But I digress. If you made it to this point, I managed to keep your attention through injecting a little of my personal story into the message. So, I was heavily inspired by an interview article I came across recently, featuring Jayse Hansen - the genius behind all the holographic elements and J.A.R.V.I.S. user interface within the Iron Man helmet portrayed in the MCU.

‍

‍

One of the design principle Jayse touched on was this quote...

For the HUDs, each scene had a very specific message to deliver, like ‘he’s about to target all the aliens’, or ‘Jarvis has just found a tight corner for him to zig-zag through.’

... and it's not unlike how we approach data visualization. Be it an infographic or dashboard, there's always an intended audience with a specific message from you. So thinking from a J.A.R.V.I.S. perspective, our role is to provide key information, without cognitive load, to allow Iron Man (your intended audience in this case) to action upon. Also, did you know what J.A.R.V.I.S. stands for?

‍

‍

I love learning using concepts as I always find it adds a little fun to the whole learning process and helps with long term retention. And so I came up with a fun concept to package the key aspects of data visualization into the acronym J.A.R.V.I.S.

‍

Journey

Think about how your audience will interact with your viz, and reduce as much cognitive load as you can.

‍

Adaptability

Be open to feedback, be willing to try different paths. Use best practices as a guideline, but never feel afraid to break them if you can tell a better story.

‍

Relevance

Showing what is required, not more not less (think along the lines of Data-Ink Ratio). Leverage on common themes, iconography, design choices if it resonates with your audience. Avoid jargons that are not widely known, and if you do use jargons; make sure you add definitions or guidance for your audience.

‍

Visibility

Gestalt principles, pre-attentive attributes, colors palettes, accessibility design, typography... basically anything that helps your visual pop.

‍

Intent

Don't settle for defaults. Every text, color, image and viz should be designed intentionally. Choose the right charts for the right data. Colors especially, should be given to build contrast or accentuate different data points. For the most parts, do try and keep within 4-5 colors so you don't overload your audience.

‍

Story

What's your message behind your viz? That should always be the driving force behind the narrative flow of your end deliverables.

‍

So there you have it.. the J.A.R.V.I.S. framework for data visualization. Hope that was easy for you to remember. 😎