You have seen it before in movies: a darkened room with people working at terminals, the faint hum of some equipment is audible. Suddenly where there was nothing, a glowing red blob appears and starts flashing inside a web of geometric lines. The lines appear to show some sort of floor plan. A block of bright text like from a computer terminal scrolls against the darkness with a needle of light connecting it to the blob. A hero’s face appears lit up by the glow of the floating graphics hovering in free space. Is it an energy leak in sector twelve? Perhaps the aliens have breached the moon base? Science fiction is in agreement that sometime in the future we will get our most important information from three-dimensional holograms.
But how fictional is this scene? We are at the dawn of this kind of technology in the real world. There is plenty of buzz around it, but is there any real benefit to holograms of data besides looking really cool in a sci-fi movie? In the Dow Jones Innovation Lab we set out to investigate questions like this, and with an experimental mindset we figure out how it might benefit the work we do at our brands such as The Wall Street Journal, Barron’s Group, and our Professional Information Businesses.
In this post I will talk about what I have learned from our experiments with holographic data visualization. Specifically, I will explain the thought process behind The Wall Street Journal’s stock market visualization, which is now live as a Concept on Magic Leap World for anyone with a device to try.
Throughout my career creating data visualizations, I have learned that some people are happy to look at tables with rows of numbers, but many would prefer graphic illustration. If you flip through The Wall Street Journal or read digitally, you will come across plenty of data graphics used to illustrate relationships within the data. It is a different mode of understanding than reading an article, and it would be difficult to gain the same insight by describing the data in words.
There is a well defined visual language for charts. The grammar of that language consists of length and area, angles, connections and icons. Color may add another dimension, but there are subtle problems. For instance, comparing the length of two solid blocks is simple, but seeing the difference between a few shades of red is nearly impossible for humans to do accurately. However, the grammar of three dimensional charts is largely undiscovered, which is very exciting from an innovation perspective. There is a new continent full of unknown species of 3D charts out there in the dark.
Some obvious holdovers from 2D are going to be there, but what about walking over a cliff of data? What about getting lost in a data landscape? What if the chart made you feel small, or big or afraid? The medium of paper can communicate only so much. When the medium starts to blend with reality, then the reality of everyday human experience becomes the playground of our communication.
What about walking over a cliff of data? What about getting lost in a data landscape? What if the chart made you feel small, or big or afraid?
For example, a few years ago I published a virtual reality Nasdaq chart for The Wall Street Journal. In that experience, you ride the Nasdaq curve through the dot com bubble growing and then bursting. You see yourself ride up along a path created by the index value. In addition, the width of that path changes based on how volatile the market is. At the height of the dot com bubble the path you are standing on is incredibly narrow, and in virtual reality, you feel like you are about to fall off of a mountain top with nothing to catch you. The feeling in your gut is the data.
Magic Leap is working hard to make the science fiction of spatial computing a reality. It is a cyberpunk-looking headset that you wear. With the device turned on, the world inside the computer appears to break out and take over the real world. Unlike virtual reality, you can see the real world right through the headset. 3D characters will run across your desk, and when they get to the edge of it they fall to the floor.
For the Wall Street Journal Stock Data concept we wanted to show the potential usefulness of spatial computing. There are no gut-turning drops as in the Nasdaq virtual reality project. There are five dimensions of market data neatly packed into an easy to read chart: industry, market capitalization, daily percentage change, average volume and time. If you’re interested in the nitty gritty of how they come together, please read on.
In our experience, we include every equity across the U.S. stock market above a billion dollar market cap. Each stock is shown as a sphere arranged around a circular grid. The size of the sphere represents the market cap. The sector around the chart and the color show which industry the stock is in. The position of the stock in front or back of the grid shows its daily percent change. If it is on the grid exactly the stock is unchanged. The distance to the center of the circle shows the average volume.
The volume measure, which means how actively a stock is being traded, is an interesting example which I will highlight. When you first think about charting around a circle, you naturally tend to think of the center being zero and away from the center being higher values. However, when we tried that, it was clear that was a mistake. For one, there are a lot more stocks that have low volume than high volume. If the center is zero, then all of these low volume stocks are bunched up in the middle of the circle and it becomes impossible to read. When we reversed it then the low volume stocks became distributed around the edge of the circle, with plenty of room to see them all. And now the most actively traded stocks start appearing towards the center almost like they are in “center stage” or in the spotlight. It flips the thinking around.
A lot of the design decisions for this chart were guided by the idea that I wanted to try and animate the data. I had this thought for a radar weather map of the stock market. I wrote a custom back-end to serve the data efficiently, and we built a time-lapse feature into the experience that shows the stock movement sped up over the course of a day. It was total experimentation and I didn’t know what to expect, but it is very interesting to watch. The stocks shimmer and dance back and forth. You can directly observe the volatility. When big news hits you see the entire market swish back and forth like a wave. Ultimately though, I think there is probably a more useful way to visualize the movement that we have yet to try.
Another unique feature of 3D data visualization is that just by moving yourself to a different vantage point, you can get a literal new perspective on the data. In this experience you can try that by walking to the side and viewing the chart edge on. In that perspective every stock which is trading up today appears on one side of the chart, and every stock that is trading down today is on the other side. I suspect that this ability is a simple tool that will unlock a powerful new way to gain insight from high-dimensional datasets. Just by really looking at them in 3D.
I would love to hear your feedback about the experience. What do you think works about it, and what doesn’t work? How would you improve it? This is fully unknown country and our adventure is only beginning.
Images by Roger Kenny. HDR images by HDRI Haven