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Dr. Tyler Morgan-Wall and the rayshader R package
314 Plays3 years ago
Dr. Tyler Morgan-Wall visits the PolicyViz Podcast to talk about 3D and animated 3D in data visualization.
The post Episode #210: Dr. Tyler Morgan-Wall appeared first on PolicyViz.
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Transcript
Dislike for 3D Effects
00:00:13
Speaker
Welcome back to the policy of this podcast. I'm your host, John Schwabish. Now, if you're anything like me, you're probably not a big fan of using 3D effects in your data visualizations. Whenever you see that 3D exploding pie chart, everybody makes fun of it. It gets a lot of critique on social media.
Background in 3D Visualizations
00:00:31
Speaker
But there are times when 3D can be useful. And so on today's episode of the podcast, I am excited to have Tyler Morgan-Wall as my guest to talk about his use of 3D and animated 3D in his data visualization efforts.
00:00:48
Speaker
Tyler created the Rayshader package in R and he uses that package to create what I think are some pretty astounding visualizations. Tyler also has a background in physics, so he brings that background to the development of the package and to his work more generally. So we talk about his work, we talk about his background, we also talk about a run-in he had with Edward Tufti making fun of one of his recent data visualizations.
00:01:11
Speaker
So check out this week's episode of the show. I think you're going to learn a lot. If you're an R programmer, I hope you'll go check out the Ray Shader and the Rayverse packages so you can create your own 3D in useful ways and helpful ways and to help people better understand your data. So here is my conversation with Tyler Morgan-Wall on this week's episode of the Policy Viz Podcast.
00:01:37
Speaker
Hey, Tyler, how are you? Welcome to the Policy Vis podcast. Great. Thanks for inviting me. Very excited to have you on the show. Very excited to be doing a nighttime podcast, not one of my regular things. So I've got my glass of whiskey here. For those listening, you can hear the ice. If you're Steve Wexler, you're mad that I have ice in my whiskey, but I like my whiskey cold. So that's what we're going to do tonight. Tyler, I kind of stumbled
Transition to Data Science
00:02:00
Speaker
upon your work a couple of months ago from this
00:02:05
Speaker
explosion you had this really cool visualization that edward tufty pounced on and we'll talk about that in a little bit but i don't want to spend too much time talking about the negative i want to talk about your amazing work and you know usually for podcasts i'll sort of introduce people and then just go to the tape but i actually feel like you have a really interesting background so maybe you could talk a little bit about your background
00:02:27
Speaker
And then, because I know you have this background in physics, and then just maybe just segue into the data vis work that you've been doing, and how those two sort of merge together, because it's a really interesting combination of skills. Yep, yep. So yeah, I got my PhD in physics from Johns Hopkins in condensed matter, basically superconducting quantum nano devices.
00:02:53
Speaker
Um, so experimental, you know, a lot of, uh, lab work. I really enjoyed working in the lab, but like many people who work in physics, um, I ended up kind of pivoting to data science work, um, afterwards, like the, the quote unquote traditional, uh, path, uh, where it's, it's, it's a lot of, uh, kind of, uh, orthogonal, uh, schoolwork to then end up doing data data science. Right. Um,
00:03:18
Speaker
But in doing that, I had a lot of analytical training, but I ended up working at a place in DC called the Institute for Defense Analyses, which we do a lot of work with the government for data science work and analytical work.
Passion for Cartography
00:03:34
Speaker
And part of that was I was surrounded by statisticians. And when you're surrounded by statisticians, it's inevitable that you end up learning R.
00:03:45
Speaker
So I ended up, so I didn't really have a background in using R and I used some Python in my graduate studies, but I ended up starting to use R and then from there I started building some packages and then I found out, yeah, this is really great, you know, it's really easy to kind of take a package and then produce it so other people can, you know,
00:04:09
Speaker
do reproducible workflows and make it so other people can use your work a lot easier than like sharing scripts or Python scripts or stuff like that.
00:04:20
Speaker
And then at one point, I had just come back from the RStudio conference presenting on a kind of dry statistical package that I'd been developing with my work. And I just had the desire to do something more fun. And I'd always been interested in mapping. And so I decided to try to produce a package that would create maps in R.
00:04:46
Speaker
Um, and that is how I started writing, uh, the race shader package. So that's really interesting that like you went to maps right away. Was there a reason? Like you, you have this, this incredible background, but it's not in cartography. Right. Wasn't maps just like, Oh, maps are great. Maps are cool. Everybody loves maps.
00:05:07
Speaker
Yeah, I mean, part of it was just like I had always really, out of all the kind of areas in data visualization, I had personally just always enjoyed a good map. Sure, yeah. It really was more just that I wanted to learn more about cartography. And I had a very specific sense of what I think I thought an interface to make maps would be programmatically. And part of my desire to write
00:05:35
Speaker
race shader was I originally looked around for something like what I had in my mind, which is basically building up maps based on layers that all of the maps aspects really come from the elevation data.
00:05:51
Speaker
There's a lot of tools like QGIS and a lot of GIS software, which are really complex, powerful tools, but not really have the focus on kind of a programmatic interface. So I really like that kind of reproducible workflow when working with DataViz. I think that's a really important thing to have.
00:06:11
Speaker
And I think it's really good. If tools support the reproducible workflow, I think they eventually become sort of higher quality in that you're less likely to kind of make mistakes along the way.
Evolution of 3D Visualization
00:06:23
Speaker
It ensures a kind of better end product. And it's also, it ends up being, I think, a lot less work for the practitioner. If you have a tool that you can just kind of change the data source and you get an identical visualization now, but just with a completely different area or something like that. And there's nothing really like that for maps
00:06:40
Speaker
that I found, so I was like, oh, I'm going to start building something. And the second part of Ray Shader was the, I'd never really found a tool that was really focused on making beautiful maps. It was mostly focused on sort of putting together maps for, I'm not saying you couldn't make beautiful maps in something like QGIS, but the focus is more on the technical cartography aspect. Yeah, right. Yeah, I gotcha. Yeah.
00:07:02
Speaker
So there was nothing really out there that was really focused on that. And I thought, hey, you know, path tracing or ray tracing, I've seen lots of really beautiful stuff made with that. So maybe if I combine sort of cartography with ray tracing, I would get something really cool out of it. And that was my thinking going into it.
00:07:24
Speaker
And that's kind of where the genesis of the name ray shader was it was ray tracing plus hill shading And and and it ended up being a really boon to ray shader that the ray shader comm was available, right? So you're like the Kleenex
00:07:42
Speaker
of the mapping world. Yeah, when I saw the first person use a ray shader to refer to a map that wasn't made with ray shader as like, Oh, I'm gonna ray shade this. And also, you know, some other thing, you know, some other program, I'm like, Oh, wow, you know, I'm the Kleenex of ray traced maps.
00:08:00
Speaker
so that that was a yeah it was a really good name and sometimes you just like hit on a really good name yeah you don't really realize it and and that can you know really be a boon especially early on right because it was one of those things where i think people just kind of knew right away like oh like this makes maps with some form of ray tracing and it and having a name that kind of
00:08:22
Speaker
tells you what the program does is just, you know, it just really helps I think with from the marketing aspect. Sure. I found is a big part of a successful kind of package for database.
00:08:34
Speaker
Yeah. So I want to come back to this idea of building packages. It is interesting to me that you sort of take this approach of I'm going to build a package that people can install and use as opposed to building out a set. It sounds like at least, correct me if I'm wrong, it sounds like you start on the side of packages as opposed to building out sort of a set of scripts publicly at least, and then getting to a point where people are like, you know, this would be really great if it was a package. And then you build the package. It sounds like you take
00:09:03
Speaker
What I sort of view, and I could be wrong, is the kind of opposite approach or steps to that. Right. Well, that, that I think is the great thing about the R ecosystem is that unlike a lot of programming languages really do kind of work, their bread and butter is kind of sharing scripts, but R has this packaging mechanism built in where that really is just sharing scripts, but in like a.
00:09:27
Speaker
better and more standardized way with lots of checks from the crayon and stuff that makes it much easier for the end user documentation built in. And because I had done this work with my job building packages, I had kind of gotten over that hump of learning how to do that, how to transition from scripts
00:09:48
Speaker
two packages. And because I knew how to make a package, and I knew it really isn't that much of a jump from writing scripts to doing that, then it just to me, it's the first step is, hey, if I'm going to share this with anyone else, I'm going to make into a package.
00:10:03
Speaker
because then it makes it, one, a lot easier to install. Two, it gives it an API. People know how to call the documentation and help files. I can get this great environment of building packaged down websites for documentation.
00:10:20
Speaker
Because I can run a CRAN check, the checks that the CRAN repository they use to kind of ensure the software quality that it runs on multiple systems, I can run that and know that it runs on Macs, Windows, Linux.
Building R Packages
00:10:35
Speaker
It's just a lot of benefits get from packaging that you don't necessarily get from scripts.
00:10:39
Speaker
If you had your way, if you were the our Chancellor or whatever we would call it the God of benevolent dictator, the benevolent dictator of our would you have everyone instead of sharing scripts? Would you have them write packages or do you think?
00:10:54
Speaker
You know, it sort of works the way it is. You know, some people just share scripts because they don't. I mean, you sort of blew by the fact that like you had of all this documentation, you have a help file and you have all these like things like that's not easy to do. Yeah. And it takes a lot of work and time and effort and you're providing that to the community. So like if you had your druthers, would you say everybody should for every script that they're putting publicly should be a package? Given, of course, that they would have to write all this other stuff.
00:11:21
Speaker
Yeah, no, I would say, I mean, so there's kind of like a certain level of how much do I intend for other people to look at this as kind of learning material? Right. Okay. Yeah. And how much do I think of it as a tool? Yeah. So if I look at this as like a tool to create some sort of standardized output, like, you know, Ray shader produces 3d maps, right? And, or, or, you know, Ray render renders 3d scenes.
00:11:47
Speaker
or it's a level of both complexity and kind of the intention. Whereas if I'm just sharing a script to show, let's say, how I made an individual database, like let's say, this is how I made this specific map. But that's obviously, you don't need to have a package for that. This is like, here's how I made this specific visualization. That's the perfect opportunity for sharing a script. But if I mean for it to be a tool for other people to use, then yeah, I think packages are kind of the best way to deliver that to other people.
00:12:15
Speaker
Great. Yeah, yeah, that's great. So let's go to these two concepts really of 3D and animation. So 3D, I think oftentimes gets a raw deal in database, but usually appropriately so when it's sort of that, you know, those Excel 3D
3D Visualization Tools
00:12:32
Speaker
cones, garbage thing. So I just want to sort of just open it up and like, you know, your thoughts on 3D and your perspective on when it's useful.
00:12:43
Speaker
So I think 3D had kind of suffered from a chicken and the egg problem because early on, computationally-wise, we didn't have the computing power in the early 90s to produce real 3D visualizations. I mean, 3D wasn't really a thing.
00:12:58
Speaker
So a lot of the tools we developed on early on, you know, the Excel and the bad sort of 3D visualizations were really these, you know, kind of a 3D bar charts or 3D pie charts. They weren't real 3D in the sense that the data wasn't 3D.
00:13:14
Speaker
It was just window dressing. And I think from years of having only that capability and sort of like a meme of 3D charts are bad kind of permeating database was because the tools only supported in early on bad database. So from that point, tool makers weren't going to put in the effort
00:13:36
Speaker
to support nice data visualizations that are 3D. So if you don't have anyone pushing the tools, then all you have are these kind of poor 3D data visualizations. And I think a lot, for many years, the major tools didn't really support 3D in any real good way.
00:13:55
Speaker
I think in the mid 2000s what happened was people like individual very talented people started using tools like 3D modeling tools and render as like blender to start to create like really kind of striking visualizations. I know one of the first people to do 3D maps I believe was Scott Reinhard of the New York Times and
00:14:19
Speaker
It produced some really gorgeous maps from that. But each one is kind of like an artisanal. The tool is not designed for that. It's a renderer. It's designed for people doing CGI, movie making, 3D modeling. It is not a tool meant for data visualization. It's not built into an ecosystem that supports data very well.
00:14:40
Speaker
So for a while then we had this kind of artisanal period of people being able to build 3D visualizations, but using tools that weren't really meant for that.
00:14:51
Speaker
And I really came in and really wanted to create some tools that would natively within our support producing these sort of visualizations that you only really saw like advanced 3D rendering software like Blender create before and only a couple lines of code. So that was kind of my goal. Originally it was to create maps and actually, so originally it just was to create really cool looking 2D maps.
00:15:20
Speaker
But there was a part where I suddenly thought like, hey, you know, this would be really easy to make 3D. So I sat down and I just made one of these 2D maps that I made with ray tracing and hill shading, these color hill shading algorithms, and extruded it to 3D from the 2D map. And I remember just looking at it being like, oh my god.
00:15:39
Speaker
This is amazing. Literally, I've never seen anything like this before. And it wasn't that complex at the time. It was just like, hey, I'm just mapping this texture onto this 3D surface. But I realized that like, hey, this is something I've only really seen in kind of like a...
00:15:59
Speaker
bespoke, you know, hand drawn diagrams from the USGS. It's actually a very common sort of aesthetic, like a lot of geospatial work is kind of these slices through the earth. But no tools really supported that. So a lot of these things were like handmade and illustrator, or hand drawn. And once I sort of created a tool that could, you know, make these
00:16:23
Speaker
from the data directly, I thought is really cool. And then releasing it to the public in a package form. A lot of other people started using it and started making some some really cool stuff with it as well. Yeah, let me just say give folks a sense.
00:16:40
Speaker
can you give me a ballpark of how much computing power and how long it took for that first that first one to go from like this 2d map to building it up in ray shader like you know when you click go when you click run like i think there's five people listening to this and like well you know my mac can't handle something like this it's building this spinning globe with all this stuff but
00:17:03
Speaker
I've seen your work and I'm sure that's not the case. Can you give folks an idea of what they can expect when they dive into the package?
00:17:11
Speaker
Right. So there's actually two different packages. So Ray Shader kind of, so there's actually multiple rendering methods and that's been half of the difficulty in doing this is, are you developing these packages? I actually have to read a lot of, you know, computer graphics literature to figure out how to like write the software. I mean, I'm doing kind of a double duty with a lot of this stuff. Cause not only am I trying to, you know, prophesize, you know, what, why 3d data visualization is good. Yeah.
00:17:39
Speaker
But I also have to write the tools at the same time. So it's having to do the technical part of writing the tools and then also create engaging visualizations. So it's a lot of balancing that back and forth.
00:17:52
Speaker
But I would say the actual computing power isn't really that high. I think most modern computers have enough computing power to support the basic stuff that Rayshader does, which is creating the sort of basic 3D maps. The hard part is when you use, so Rayshader has a function called render high quality. And that calls Ray render, which is a high quality path tracing renderer.
00:18:18
Speaker
And that can take a while. That's one of those things where an individual frame could take 10 minutes to render. Because it's using advanced, it's basically simulating how light acts through the scene. So it's actually bouncing around with the equivalent of photons and then drawing the scene from those. So it's a very complicated algorithm. So that can take a while. But the normal 3D plots, you can make a 3D plot instantaneously. It's just if you want these really,
00:18:47
Speaker
slick looking ones. Yeah, then then it can take a while. But that's computational work. I would say lines of code wise, you know, we're still only talking like a dozen or two dozen lines of code for even the most complicated things. Like if you look at my GitHub gist page, so the visualization that went viral and reached like the number one page or the number one slide at the top of Reddit and that Tufti tweeted about that was
00:19:14
Speaker
about 40 lines of code and it's not really dense code. You read through it and it really isn't that bad. So computational, I mean, that's something if you really were interested in speeding up, you could always even like rent an AWS server. I've had people do that. They've actually rented like AWS servers with 32 CPUs or 64 CPUs and rendered something really quickly. I just will render something overnight.
00:19:39
Speaker
And like with my computer, like that's, I just take like eight hours, be like, okay, this is my, this is my allocation, 360 frames, 30 frames per second. That means I have, you know, a minute to spend on for frame approximately. Then I just scale the quality of my render down to reach that timeframe and render that. So that's how I do it. Yeah. So I do want to get to this tough thing because I think it's, it's example of a lot of different things, but.
00:20:04
Speaker
clearly, you building the package is built on your your physics background. Did you get the point where you're like, well, the physics here is like not totally perfect. So I'm going to spend a lot more time figuring it out. Or it's good enough. But like as a like at your at your core as a physicist, you're like, Oh, this hurts me to like cut this little corner here. Like, how did you like balance that? Like,
00:20:29
Speaker
Yeah, so there's actually, so the original rendering method that I use, which was just kind of the out of the box sort of more traditional CGI approach that wasn't on Path Tracing, that definitely had some kind of workarounds where you kind of hacked to get something looking
00:20:47
Speaker
physically accurate. Right. There's one one part where I had the shadow that was cast that was just me basically hacking together like a darker version of the background. Okay, yeah, that underneath it wasn't a real shadow. There wasn't any actual lights going on. That sort of not looking kind of quote unquote realistic really motivated me to develop the path racing approach. Because there you can get the things where it looks like you have like,
00:21:12
Speaker
the actual sun is shining down like there you could actually see like this is where the sun's position is the sun's size like you could make calculations based you know for like solar panels you know coverage based on that that right um and the path tracing stuff is actually really it's physically based rendering is what it's referred to as pbr
00:21:31
Speaker
And what's nice about that is so it's a Monte Carlo method that converges on sort of looking physically realistic. If given you take a number of samples as Monte Carlo methods, so you can take a high number of samples, but eventually it all integrates out to looking like it's a photograph.
00:21:49
Speaker
Um, and and the nice thing about that from debugging actually from a programmer point of view is if I render something and i'm like, hey That doesn't look
3D Visualizations in Storytelling
00:21:57
Speaker
right. I can be like oh, it's because I got there's a bug somewhere Yeah, so it's actually easy to debug because i'll just like take a picture of something and see like hey something That shadow looks wrong and then i'll actually go in and be like, oh, it's because well, you know I got some sine or cosine wrong, right and it's in the wrong, you know angle
00:22:13
Speaker
And a lot of my early debugging was like, Hey, this doesn't look right. And they'd be like, Oh, it doesn't look right. Because it's not right. And but now it's actually my, my physicist, the physicist part of me is very satisfied. Okay, physically based rendering really does produce results that are pretty close to reality. And there's lots of, you know, complex integrals related to radiance. And a lot of the techniques actually came from like nuclear physics. And you can actually read the physics back papers, and what that's part of a physics background is
00:22:40
Speaker
you know, interpreting all this. So I'll go back and read these papers to figure out where it's all coming from and be like, oh, okay, you know, this makes sense. And I know as a physicist, I mean, really, like I know economists also kind of have this stereotype where you look at somebody else's field and you go like, oh, I can do that.
00:22:57
Speaker
Like, I can understand this. And I'm lucky in this sense in that because it's physically based rendering, I can actually read these CGI papers and go like, oh, this is physics. So I got you. Even though it's completely different genesis for the field. We can still talk, yeah. Yeah, exactly. So yeah, no, that itch is well-scratched.
00:23:16
Speaker
by this rendering stuff. That's great. That's awesome. Okay, so let's turn with turn to Tufti. So I'm going to just read a little bit from my notes here so people know what we're talking about. So in September, you created this really cool animated map. It showed submarine fiber optic cable network around the world. And so is this just a sort of
00:23:37
Speaker
paint the picture for people. It was this spinning globe, and it had basically lines around it. Hopefully folks sort of get the idea there. And then Tufti put out this tweet. And I'm going to read this tweet for you, and then we don't have to spend a ton of time bashing him, although I'm happy to do that if we want to spend some time. So this was Tufti's tweet. I'll link to it in the show notes so people can go look at it. So Tufti tweets out, discovery of backwards Earth rotation. He puts a little arrow, noble prize.
00:24:05
Speaker
Diameter of each optic cable apparently about 100 miles, exclamation point. On land, drop shadow cable stacks reach far out in outer space. Displays of space junk have same problem. Perhaps thinner lines reduce the massive exaggeration. So yeah, I mean,
00:24:27
Speaker
I guess, I guess I'll just like, I'll just put that out there. And, and, you know, like, what was, I guess first question is like, what was your reaction when you saw him like retweet that? So, so my first reaction was, I've made it tough to criticize my tweet. Like, you know, from that point, it really was like, I looked at it, I just scanned what he wrote. And I, and when I scanned it, I didn't see what I was afraid of.
00:24:53
Speaker
The only thing that I was afraid of was he would tweet something about disparaging 3D visualization in particular, because then that just kind of, there's a lot of people who follow Tufti who think 3D is bad. And I just didn't want to have to fight the battle of be like, oh God, no, I feel like somehow debate Tufti, or at least people who follow him like that 3D is fine. The fact I read that and I did not see anything that was related
00:25:19
Speaker
to 3D in particular. So I breathe the sigh of relief. I was like, okay, he's having some kind of snark about that. Whatever. Thank God. And then and then I kind of read it over a couple times. And I was like, Okay, yeah, a lot of people say like, I had some other data visualizations that had gone viral earlier on where the earth was rotating the wrong way, the wrong way. Yeah, where, you know, apparently, you know, you're not allowed to spin a globe in two different ways.
00:25:48
Speaker
You know, you're contractually obligated, always the cynical way, right? One way and not the other. I never considered this to be a physically accurate representation of Earth's orbit around the sun. You might also notice I had no clouds, you know? I didn't render the moon going in and out.
00:26:09
Speaker
That's right. There's a lot of things that wasn't physically accurate. I'm sure NASA is super pissed about the whole thing. I don't think anyone was looking at this visualization going like, you know, I could really understand this submarine cable map thing, but what planet is this on? Obviously not Earth, because it's rotating the wrong direction. I'm very confused. A lot of people posting like, hey, this might confuse some people, because the Earth's rotating the wrong way. Just like, what are they confused about? Anyway, that's besides the point.
00:26:38
Speaker
I looked at it, so he mentioned the thickness of the cable, which I thought was a little confusing. So these actual submarine cables are about a garden hose thick, which I don't know if you've ever tried to see a garden hose from space, but it's very difficult. I'm sure people would love to have a telescope in space of that resolution, but the
00:27:01
Speaker
Geospatial work mapping is full of abstractions. Yeah. That's a database. We have lots of abstractions. It just more confused me that he would focus on that. Cause I'm like, what is this? To me, it was like, I had a hard time figuring out if this was like, you know, a funny snark thing. I don't, you know, I don't know Tufti that I don't know. He might've just seen this as like, I'm being funny, but, but he, the fact that he used the word drop shadow, I'm like, Oh, he's kind of interpreting this from a 2d perspective. Yeah. This isn't drop shadow. This is path trading. That's like, that's actual shadow.
00:27:31
Speaker
Right. Yeah, it's for shadow. Right. For me, I could see him kind of interpreting it from like the 2D perspective. Yeah. The fact that he used that, the fact that that we have these kind of, you know, abstractions that we use in GIS that might not represent the same, you know, the actual size of things. I mean, people don't complain about, you know, the US interstate system, you know, if it maps of that, you know, the roads being the exact same size, it's, it's a reality that the earth is huge.
00:27:57
Speaker
humans are very small and human scale things are very small. So yeah, obviously, we have to exaggerate stuff. But I would say actually, the big thing that came from Tufti's tweet, the thing I enjoyed the most was really, like the great outpouring from the community of people said like, Hey, what are you doing? Like,
00:28:15
Speaker
Yeah, like at the time, I had like, I don't know, 9000 followers. And, and maybe Tufti looked at that and be like, Hey, this guy's like one 10th of a Tufti because he had 100,000
2D vs 3D: A Cinematic Experience
00:28:25
Speaker
followers. That makes him a fair game. I don't know. But I think a lot of people saw it as like, you know, punching down. But from there, like, so many people came out and I was, you know, working at the time. So I was like, okay, by the end of the day, maybe I'll respond. But right.
00:28:38
Speaker
within like two hours anything that I could have said the community had said all like you know all people had come out and been like you know this this tone isn't great like what are you doing yeah like this is a great visualization but lots of people shared it with like saying like wow this is like I didn't never known yeah this is what you know had ran the internet
00:28:58
Speaker
Which I think is a sign of a good visualization. People have been like, oh my god, I had never known this. And now I realize that this is the infrastructure that the earth runs on for the internet. I didn't really have any negative responses other than people saying, kind of looking the sort of same criticisms Tuffy was being like, I think some people might misunderstand this based on some other things. And I don't think anyone really did.
00:29:21
Speaker
Yeah, I mean, it's interesting, right? Because if your goal with that visualization is, I don't know what the companies are, but to lay if you're working for a fiber optic cable network and seeking to lay new line, then that's not the visualization you want to use for that particular job. Yeah, but if you just want to get this sense of what the world looks like in this sort of hidden layer that we all just kind of take for granted,
00:29:48
Speaker
that visualization, and I hate to say tells a story because I, you know, have a problem with that phrase, the different story, a different whole conversation, but it does tell that story pretty quickly and intuitively.
00:30:02
Speaker
Yeah, no, and I think that's why I kind of hit such a nerve. Like the fact that a data visualization, I mean, I've had some things go viral on Reddit before, you know, some things will reach like the very bottom of the front page because data visualizations, I mean, I don't think most people think about them too much under, but hitting like the top spot, like opening up the Reddit app and like seeing it right at the top, like that's the front page, that's above the fold, whatever the modern version above the scroll or whatever that is.
00:30:31
Speaker
to see that in like the kind of top spot. I'm like, this is really like, like touch the nerve of people being like, oh, wow, that this has made me like understand my world a bit better. Right. Right. So like, that to me is like the the end goal of a good data visualization is to get somebody to understand some data a bit better and really like learn something. And there's kind of like these technical
00:30:53
Speaker
I think a lot of data visualization gets, or criticisms often get caught up in kind of the technical considerations of, you know, what is the best way, you know, a lot of mapping is like projections. And I think in a lot of cases, I would say the negative kind of technical considerations often I think don't come into play if you're
00:31:11
Speaker
tailing like a, if you have a really engaging data set, which I think is what the submarine cable map really was. I mean, this data had been freely available and had been visualized and kind of a flat earth before. I mean, you could see it, there are multiple websites that showed this data, but I think kind of showing it in the sense of more of a kind of realistic view of what the earth looked like in this 3D view kind of made it a little more
00:31:36
Speaker
grounded. It wasn't just lines on the planet. It was showing how we were all connected to this web. I think in a lot of cases, these network visualizations, the abstraction of the lines over the Earth, the fact that with many maps, the lines represented by the countries and the coastlines, you have to be able to separate them to the reader. So moving it to 3D, I was able to actually physically do that. The lines floated above the Earth. So then you're able to see that, and it was
00:32:05
Speaker
uh sort of using this technical trick of 3d to kind of get beyond that sort of like oh what's the data here and what's the point of the visualization yeah um i don't know why this one kind of struck a nerve as much but i i think just generally 3d can create these really engaging plots because it can create like really beautiful visualizations
00:32:26
Speaker
And I think that can really kind of enhance sort of these, even data that not necessarily needs the 3D to like represent it. Because yeah, you could just plot this on a 2D map and it would represent the exact same thing. But seeing it in this 3D view, I think just really, you know, made it that level of engaging that people could like, but actually see it and sort of be like, oh, this is my earth, my planet. I don't know why things go viral.
00:32:52
Speaker
No, yeah, it's impossible to know, but I think you've touched on a few of it. I mean, I think, I mean, I'll just give you like my two cents. Like for me, I think why it struck a nerve. I mean, in the database community, it struck a nerve because of the Tufti thing, but I think more generally it struck a nerve. I think your choice of colors.
00:33:11
Speaker
was something that made it pop. So they were very vibrant, almost fluorescent colors. So I think those popped. But I think your point about there is something about the animation of the globe spinning that in some ways it creates this reveal of this underlying network that we see across the whole world. And if you see it on a 2D static
00:33:38
Speaker
map, essentially, it's essentially lines across this thing. But there's something about that animation as it spins, you're like, Oh, I can track this this bright green line from New York to Berlin to Moscow. And I can see that. And it's, I have to sort of wait for that to happen and sort of reveals itself. And I think that's part of it.
00:33:58
Speaker
Yeah, and that actually brings us to the next point I kind of want to talk about 3D was so 2D data vis I think has a lot in common with a lot of crossover with illustration. So like, you know, a lot of aspects of, you know, art, you know, color theory, and that you need to use when you're doing data vis in 2D. And I think a lot of illustrators are often like very good at vis when they data vis when they get into it. I know, like Allie Torben, I think, you know,
00:34:26
Speaker
She's a very good illustrator and she makes very good data visualization. But I think 3D is interesting because it actually has a lot in common with cinematography. You need to actually use a lot of techniques that cinematographers use in the slow reveal. In this ray render, you actually have to worry about depth of field, where you're focused. You have to worry about lighting. You have to do light design.
00:34:52
Speaker
And it's actually a lot more related to how you film something and reveal something in an actual movie or TV show than just the kind of flat, static nature. Now, you also have interactivity. So those are the two choices you have in 3D, whether you want to make it like a fly through video game style experience where you're flying through the space and revealing it that way.
00:35:17
Speaker
or you can do this animation approach. I think interactivity is a bit harder for technical considerations, just because one, you have to deliver big 3D models to people, and that can be hard from just pure web bandwidth point of view, but also it's just hard because a lot of people don't really work in 3D space that well. I'm part of the Nintendo 64 generation.
00:35:44
Speaker
So I know how to go back and, you know, side to side up and down. But I think a lot of people, and even even a lot of people, you know, my age don't really do well in 3d, because it's, it's, you know, it's hard, you have made lots of degrees of freedom. So interactivity is good in some senses in 3d, but it's actually much harder to implement correctly. Yeah. But movies, I mean, one,
00:36:09
Speaker
it's easy to share a movie on social media. You know, you can embed in a movie on Twitter. All major social media sites support embedding videos, which is why I think animation is really my preferred method of sharing 3D visualizations. And two, then it allows you, the creator, to, sorry about this, tell a story, rather than kind of
00:36:33
Speaker
having the person walk through what kind of story that you think you'd want them to tell. It's much harder than 3D because you just have a lot more places they can go. One of my visualizations that I made this past year was I actually made a VR roller coaster ride. It's sort of a demo proof of concept of the technology where
00:36:53
Speaker
you had a 3D dataset and you could actually, you're taking kind of on like a monorail tour through your data and that kind of bridged the gap in that it was actually just a movie. So for me, I was able to render all the frames, but it was a movie rendered with a 360 view. So if you had VR goggles, you could put them on and then kind of look around as you were traveling through the scene.
00:37:15
Speaker
Right, which kind of splits the difference. I really like that. If you look at a lot of 3D tours through data that like the New York Times have done, it's they've kind of combined squirrely telling the sort of 3D tour where as you scroll, the camera travels.
00:37:30
Speaker
And kind of, I think this element of interactivity with the VR aspect is kind of splitting the difference. And that's kind of as far as I would probably go with it, just because it's like a movie where they can look around. But yeah, generally speaking, I like movies just because it really, the technology is much well supported. It's a lot easier for me to put together. And it's really a lot better for I think the end user, at least for now. Yeah.
00:37:59
Speaker
Well, that's cool. So I'm now eagerly anticipating your next VR R package in 2022. And I'll have to go buy whatever the metaverse decides to put out and let me, let me purchase. Yeah.
00:38:12
Speaker
Tyler, thanks so much for coming on the show. This has been great. Um, really interesting stuff. Um, and I'm glad you were able to brush off the, the Tufti criticism because that can be a tough, yeah, that can be a tough pill to swallow. Uh, when someone like that does that, but I'm glad to see this work. I'm glad to see people using it. I've seen it more and more now. Um, which may be just me sort of having my eyes open a little bit, but, uh, it's really great work. Congratulations. And, uh, and yeah, thanks again for coming on the show. Yeah. Thanks for inviting me.
00:38:42
Speaker
And thanks everyone for tuning into this week's episode of the show. I hope you enjoyed that. I've put the links to everything that Tyler and I talked about in the show notes so you can check out the art packages he created. You can check out the tweet from Tufti and the various responses to that. And just more generally, you can go play around with some 3D. So until next time, this has been the Policy Vis Podcast. Thanks so much for listening.
00:39:06
Speaker
A number of people help bring you the policy of this podcast. Music is provided by the NRIs. Audio editing is provided by Ken Skaggs. Design and promotion is created with assistance from Sharon Satsuki-Ramirez. And each episode is transcribed by Jenny Transcription Services. If you'd like to help support the podcast, please share it and review it on iTunes, Stitcher, Spotify, YouTube, or wherever you get your podcasts.
00:39:27
Speaker
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