Become a Creator today!Start creating today - Share your story with the world!
Start for free
00:00:00
00:00:01
Episode #186: Krisztina Szűcs
209 Plays4 years ago
Data visualization designer krisztina Szűcs joins the podcast to talk about her work and her process.
The post Episode #186: Krisztina Szűcs appeared first on PolicyViz.
Recommended
Transcript
Introduction and Guest Intro
00:00:15
Speaker
Welcome back to the PolicyViz podcast. I'm your host, John Schwabisch. I hope you are well and healthy as we get towards the end of a very rough 2020. I'm really excited for this week's episode. I interview one of my favorite designers in the infographic information visualization space, Christina Suge, who's on the show to talk about her work.
00:00:38
Speaker
talk about her graphics, her process for making her unique, dense, static visualizations. We talk about one of her older projects, Spotlight on Profitability, that I've actually used in my
Christina's Recent Works and Projects
00:00:52
Speaker
classes. I've also featured it in my new book, Better Data Visualizations, that comes out in early January.
00:00:59
Speaker
We talk about her recent projects, a data art project that she built in D3 called Plot Parade. We talk about sort of a fun data visualization project that she did using Tinder data. So we really talk about a whole lot of things and also talk about her process. So if you are working in Adobe Illustrator, if you are maybe leaning more towards the art or design side of the data visualization field or process, this episode is probably really right up your alley.
00:01:27
Speaker
So I'm just going to leave that there and just get right to the interview. So here's my discussion with Christina.
Christina's Background and Education
00:01:33
Speaker
I hope you will enjoy it. Hi, Christina. How are you? Welcome to the show. Hi, John. I'm fine. Thanks for having me. Of course, I am so excited to finally be able to have you on the podcast. I have been a fan for a long time, and I think if I'm not mistaken, we first met last
00:01:56
Speaker
fall in London at the information is beautiful words. Yes, that's right. Yeah. So I'm very excited that I was able to get some time with you to chat about your work. And there's a lot to talk about a lot of great stuff. Folks don't know your work. They soon will after this, after our discussion. So I thought maybe we'd start with having you talk a little bit about yourself and your background and the work you do. And then we can jump right in and talk about some of your past projects that I love and some of your new projects that have just come out.
00:02:25
Speaker
Sure. Okay. So I am based in Budapest, Hungary, and I am a data visualization designer. I mean, in the field since probably 2012. So my background is in graphic design. I went to an art university, so I have a master's in graphic design. And I always loved data visualizations and especially loved maps. I didn't know at that time that they are part of data visualizations or something like that, but I always loved maps.
00:02:56
Speaker
So at the university I was attending to, they always encouraged us to try different fields. So we didn't have one specifications. We tried logo design and brand design and UI design too, and even a little bit of fine arts. So I always wanted to try data visualizations and the university was a good opportunity for that for me.
00:03:25
Speaker
At that time, I entered some of the data visualization competitions that were around. So I just wanted to try myself. If it works for me, if I can do it.
Entering and Winning Data Visualization Competitions
00:03:39
Speaker
And I also wanted to have some kind of a feedback. And I like these competitions because they had the data sets ready. So I didn't need to bother with that one. I find that I am always terrible at gathering data sets because
00:03:54
Speaker
It's a paradox of choice. So I don't know when is enough and when it's good enough. So I love men when I work with a, with a dataset that somebody else created or collected. So I entered these competitions and I also wanted to learn from others because if other people are working on the same dataset and then they are sharing their work, I think that's the best way you can, you can learn much more about the field.
00:04:24
Speaker
So I entered, I don't know, maybe two or three competitions and I won two of them. And this sort of made me believe that I'm good at this and this is a good career for me. So I also liked doing data visualizations, but I also received some good feedback from outside that people also liked my work and maybe I should continue doing this. Right.
00:04:51
Speaker
And I want to talk about that third contest that you lost because I have problems with why you lost that one. But I want to get back to, to the university.
Spotlight on Profitability Discussion
00:04:59
Speaker
So was the university, when you said, I want to explore data visualization, were there classes in areas in and around data visualization about using data or about graphic design that's specific to data or, or did they just say, go try your hand at creating graphic design using data?
00:05:18
Speaker
No, they didn't really say anything to me. So it was kind of free. If I wanted to try something and they could see the value, then they just encouraged us to do it. So we didn't have any data visualization courses or something like that. This was something I was interested in. Maybe there were books around in the university, but
00:05:44
Speaker
Pretty much you could decide what you wanted to work on and what's going to be your profession or your field. Oh, that's interesting. So let's get to these contests because I believe the one that you lost was the infographic you made, the spotlight on profitability. Is that right? Yes, that's right.
00:06:04
Speaker
Okay. So this is one of my favorite exploratory static graphs. It is coming out in my new book. It's in there. So people should go see it on your website and I'll put a link to it. Let's just talk about the graphic first. And then we can talk about the contest because I think as I recall, and it's been a while now, so that was like 2012. Yes. As I recall, a lot of the people in the field were upset about that. So, so.
00:06:31
Speaker
So maybe you could talk, try to describe the graphic for people and also what your thought process was as you were creating that one. Yeah. So this was maybe the second data visualization I ever created. And it was a competition arranged by Info Beauty Awards. And the data set was ready and they didn't say which message we need to convey. So I could do anything I wanted with the data set.
00:07:00
Speaker
And the data set was much bigger than what I ended up visualizing. And yeah, my process was just, I wanted to find something interesting in the data set. So I spent a lot of time on the data set. It was a competition arranged by Info Beauty Awards. And the data set was about Hollywood movies, their profit, their budget, the category genres.
00:07:27
Speaker
whether they want academia board or not and something else. So it was a huge data set actually. And they didn't tell us what was the message that we need to convey. So we could do anything we wanted with this data set. And first I studied the data set. So I tried to find something interesting that might be useful to visualize or that could be something meaningful to others.
00:07:58
Speaker
And I found that some movies have huge budgets. And some movies, of course, compared to the huge budget, movies have very small budgets. For example, animated movies have a huge budget. And usually horror movies, which could be shot by a handheld camera, they have a smaller budget. But compared to that, the profit could be kind of similar.
00:08:27
Speaker
the profit could be much bigger compared to the budget. And sometimes you barely make it to a profitable movie. Sometimes it's much easier. And of course, if you have a smaller budget, it's even more easier to make a profitable movie. Maybe this is just a very dumb way to tell this, but yeah, this is what the visualization is about. And I was collecting this information and I decided that I will visualize the budget.
00:08:57
Speaker
and the profit, so how much the movie made worldwide, each movie. And at this time, I didn't know how to code. So I knew something because I learned action script, and I don't know if you would remember Flash and things like that, but that wasn't something that I could use. So I did the vocal visualizations manually. And by manually, I mean in Adobe Illustrator.
00:09:26
Speaker
So I just created a grid between 0 and 100. And I just draw the circles and the points manually so they could represent the correct data. And this is how I draw the whole visualization. So it was a quite manual process. And because of this, I also couldn't visualize everything because it could have been too much work.
00:09:55
Speaker
The reason that I also just visualize a partial dataset because it just was impossible to do everything manually. Right.
Approach to Visualization and Aesthetic Preferences
00:10:05
Speaker
But as I recall, the graphic that won this particular contest had kind of a dashboard-y sort of feel to it. It was like, here's the movie with the biggest budget. Yeah. And as I recall, yours was
00:10:21
Speaker
kind of bending how we viewed, you know, it was like basically like a new graphic type. It was kind of like a slope chart combined with an area chart kind of thing, because you had the Rotten Tomatoes score on one axis and the budget on the other axis. And as I recall, like people got really, I mean, I know I was really, but I think people got really upset that the award went to something that was very fairly standard.
00:10:46
Speaker
Um, I would say is our, if I recall correctly, as opposed to something that was trying to change the way we look at the data. So, uh, I guess my question really leads into a whole other topic, which is.
00:10:59
Speaker
A lot of your work is fairly dense visuals and using new forms and using new functions. So when you are creating your visuals, are you thinking about using new forms? Are you like how, how, what is your thought process like when you are working with data and you're trying to visualize it? It's funny that you are saying that I have this way of doing dance and static visualizations because I didn't realize this before. So I'm just doing what.
00:11:28
Speaker
feels right for me or what I like, but I never really compare myself in this way to others. So it's interesting because I don't really want to come up with something new, but I like to create something beautiful. So maybe this is because I have a background in graphic design and I always want to create something that could grab the attention of the viewer.
00:11:56
Speaker
I think it's important to make somebody interested in the data visualization and not just because of the data is interesting, but because they find the visual look interesting and maybe that could make them think that, oh, there is some kind of rich dataset behind that I should know of. So it's mainly for grabbing the attention of the, of the URL.
00:12:20
Speaker
But the way you mentioned that all my visualizations are these dense and static, it's mainly because I like those kind of visualizations that have a rhythm. Maybe you can call it pattern, but I like to use the word rhythm. So maybe a small and multiple visualizations when you have almost the same element, but repeated in a slightly different way. So this creates this visual rhythm and it's
00:12:50
Speaker
it's visually pleasing to look at it. I like to find this freedom in my visualizations.
Exploring Plot Parade Project
00:12:59
Speaker
I also found that data visualization is the perfect for that. You cannot go wrong with data visualizations. You have many data points and basically whatever, you will almost always look beautiful if you have enough data. Maybe this is one of the reasons.
00:13:20
Speaker
And the other one is this old visualization is static and dense because I couldn't code at that time. So this was the only option for me to do a static visualization. But nowadays, when I can code, I still do this kind of static and dense visualization. So there are several reasons for that, I think, because
00:13:47
Speaker
I am also doing UX and UI designs, and I also designed the interfaces for my visualizations. So you can think about any filters or buttons or overlays or transitions, maybe also onboarding. So even when I am designing these, I don't like to hide part of the data because I feel like with filters,
00:14:12
Speaker
you always hide part of the data that you want to show. And when it comes to interactive visualizations, it's always up to the user to find what button to press. And I found that I cannot really trust the user that much that they would find it. So I like to put every data point on display at once.
00:14:37
Speaker
I don't want to rely on the user to find the right buttons to turn on the filters or some overlays. I'm just afraid that they will miss something. So it's just an extra step for me to hide. Yeah, that's really interesting. I think your graphic design background allows you to bring something else to the field that many others have, but is somewhat unique. It's also, I wonder if,
00:15:07
Speaker
The fact that you started by not collecting your own data and working heavy in data freed you up to not be like someone like me who came to data visualization more from the data side where I probably, using Excel dropdown menus and Stata package stuff where it's the kind of standard graphic types. And so you sort of get in this box where it sounds like you didn't really have that. You came at it more from the design side where you don't get in these
00:15:36
Speaker
I would suspect like part of design school is not getting into these like boxes of standard form and standard shapes. It's interesting to me talking to people on this podcast about how people come to the field from all these different perspectives and specialties. Yeah, maybe, maybe that's the reason. At the university, we were always working on the same project and we were competing with each other.
00:16:04
Speaker
So we knew that the first thought that you have about how to visualize something or how to do a design is probably what everyone else has. So you need to iterate more or you need to work on the visualization again. You don't need to stay with the first version that you found. You need to think about this more.
00:16:28
Speaker
but I'm also doing the same thing as others. So I'm starting my visualizations with bar charts or line charts or very simple charts, for example, when I just want to understand the dataset, I don't jump onto the design immediately. I always create something normal, I would say. And if the visualization is understandable and interesting in that boring bar chart version,
00:16:58
Speaker
that I can move on to the design part. So there is a certain order I need to do my visualizations. Right. So we've tracked your career from university and trying these contests and how you approach the process and doing a lot of manual work. But now, you have some recent projects that are using D3 and I was hoping we could talk a little bit about those two. So you've got, I thought we talked about two of them. So the first
00:17:27
Speaker
project is Plot Parade, which is a cool data art project. And then you have this other one, Tinder Insights, which I have, I'll say no experience with Tinder. My wife would be happy to hear that too. But we can start with Plot Parade. Really, really interesting. And maybe you could just talk about it and what the inspiration was and how you're building out these visuals. Yeah, sure. So Plot Parade is a personal project of mine.
00:17:55
Speaker
which I just started to learn these three because I started very late and I always feel like I can learn something new every week about these three. So normally when you are creating a data visualization, you always start with the data set and then you find the right visual form for that specific data set. But I wanted to reverse this approach so I was
00:18:23
Speaker
looking at some graphic design blocks or some collections. And I found these interesting graphic designs where I found these visual patterns that I talked about. And I thought that, oh, how interesting this is. I wonder what is the data behind. And most of the time I found nothing because they were just graphic designs, but I could see some kind of data behind.
00:18:53
Speaker
So I just imagined the right dataset behind these graphic designs. And that's why I saved these designs for inspiration. And I guess I was waiting for the right dataset to come along so I could use these designs as inspiration, but it never happened because I always need to study the dataset first and find the appropriate visual form for it.
00:19:22
Speaker
So this is why I decided to reverse my approach and start with the visualization first, and then I designed the data structure for this specific visualization. So these data visualizations that you can use on plot parade, you can enter your own datasets, and these are very simple datasets. So something that you would use in a dashboard, something like
00:19:51
Speaker
that we would require only a bar chart or a line chart. So nothing something complex. But I always found that graphic design is a little bit ahead in terms of design compared to two dashboards. So I just wanted to get those elements from design, typography, spacing, and use them in data visualization.
00:20:19
Speaker
just try if it's possible to visualize these simple data sets in a more beautiful way, sort of using just graphic design. So this is how I ended up creating plot parade.
00:20:33
Speaker
And I always have some new ideas, or I get inspired by other designers' works. And it was a good way for me to learn these three, because I just set these challenges for myself. And I always go into this thinking, oh, I don't know if it's possible to do this. Let me try this. And I forced myself to learn, and I found it very useful for me also to deepen my knowledge.
00:21:01
Speaker
of these three. So I'm just poking around at the project now and like some of these are great. They're like, you know, bar chart overlaid with pictures or, you know, just like a line chart with a nice design aesthetic, but there's boxes here for, for more. So are, is this, is this the sort of thing where you just envision constantly kind of just updating it as you, as you get inspired?
00:21:29
Speaker
Yes, that's right. I've been lazy for a while, so I have some half-finished stuff sitting on my computer. But yeah, I always have new ideas that I want to try. That's probably something that I've never seen before in database. I just want to try if it's possible. And yes, I want to upload more and more as I will find a new time to work on this. Yeah.
00:21:55
Speaker
Well, I love them. I mean, they're great. Um, so I look forward to seeing some more of these. Um, now the other project is a little bit different.
Tinder Insights and Collaboration with Sister
00:22:03
Speaker
Tinder insights data, this tool to track your Tinder data, I guess.
00:22:13
Speaker
Yes, that's right. I have even less experience with this. Although I will say the first image on the website is this really cool flowchart about, I would guess, some imaginary made-up person of swiping and matches. But do you want to talk about this project and where this one came from and how it works? Yes. So I don't really have experience with Tinder either.
00:22:42
Speaker
But this is a project I created with my sister, actually. We always wanted to work together on something, and she's a developer. So we just needed to find the right project. And she's a Tinder user, actually. So the idea came from her because she found that
00:23:05
Speaker
you can get your own data from Tinder. So they are storing everything and you can get your own data and they are going to send you a JSON file with all your swipes and how many times you logged in and your chats. And we've thought that this is a good opportunity to visualize this somehow. Of course, most of the Tinder users cannot visualize their own data.
00:23:28
Speaker
But we created a website where they could upload this dataset and create these visualizations and infographics for themselves from their own data. So I really like these visualizations when somehow you are looking at your own data. And I think it's much more interesting than you are also involved in the visualization.
00:23:56
Speaker
So I really wanted to create something like that when you are looking at your own data and it's much more interesting for you. So yeah, the first flow chart is more like the usual data visualization that I'm creating. And the other ones below are more like these infographics or number decorations. There is a reason we didn't want to make this more complicated.
00:24:22
Speaker
because we are thinking about the average user and how much they know about data visualizations and how much they can read data visualizations. We wanted to keep it very simple and easy to understand. We are also comparing the users
00:24:43
Speaker
to the average. So we are storing anonymously some information about the people who are uploading their data to this website. And we can do these comparisons, like how many times you get a match and compare to women or men. And we are also adding COVID statistics. So we are comparing how Tindale usage have changed before and after COVID.
00:25:13
Speaker
If people are dating more online or less. Oh, interesting. And so then are there visualizations that compare the individual to other people or I guess that the overall average, I guess. Yes. Yes. You can compare yourself to women and men. So we created these two groups because there is a preconception.
00:25:39
Speaker
which might be true or might not do, through that. Vumin has a much easier time on Tinder or any other dating apps because they just need to be on their end. They can just get many dates and while men will have much fewer matches and they need to work more to get more dates.
00:26:06
Speaker
So this is why we wanted to create these comparisons so people can see if this is true or not.
00:26:15
Speaker
And do you ever envision creating sort of separate graphics from this? You're going to, I mean, eventually you'll have some database full of anonymous data with sort of averages. Do you ever envision like creating of our sample? You know, this is a graphic of the average swipes and number of dates and et cetera, et cetera. Yes, that would be very interesting. We still need to have that data set, but yes, eventually maybe we will create something like that, something more complex and something more
00:26:46
Speaker
exploratory visualization. Right. Right.
Interview Conclusion and Podcast Credits
00:26:50
Speaker
Cool. Well, um, I am a big fan of your work of all the complexity that you add. So these projects look great. Um, I'm already a big fan of plot parade. Thank you. Uh, looking around so much fun. Uh, Christina, thanks so much for coming on the show. This has been, uh, this has been great chatting with you and, um, and yeah, thanks for, thanks for coming on the show. Thanks for having me. It's been fun.
00:27:17
Speaker
And thanks everyone for tuning into this week's episode of the show. I hope you enjoyed it. I hope you learned something. I definitely encourage you to check out Christina's website and her projects and her portfolio. Some amazing work there. So until next time, this has been the Policy Viz Podcast. Thanks so much for listening.
00:27:45
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, and each episode is transcribed by Jenny Transcription Services. If you would like to help support the podcast, please visit our Patreon page at patreon.com slash policies.
00:28:20
Speaker
Sleeping at night Eyes took open In a pool of wine I can feel the end So hard to make a mess It's coming
00:29:01
Speaker
Not too much noise