Giorgia Lupi joins the show to discuss her work in data visualization, her journey from Accurat studios to Pentagram, and how she takes a human-centric perspective to working with and communicating data. Giorgia shares her experience with long COVID, explaining how she collected her own data to better explore and understand her illness. She advocates for engaging storytelling through visual design, exploring approaches beyond traditional bar and pie charts.
Our conversation also focuses on her new book, This is Me and Only Me. The book encourages kids to observe and collect data to understand emotions and human questions, using symbols and colors to express emotions. Giorgia hopes the book will inspire kids and adults to be imaginaive, observant, and mindful. We also have some breaking news on this episode because Giorgia is working on another big project, a new book called “Speak Data” that explores data as a language intersecting various fields.
Topics Discussed
- Human-Centric Data Visualization. Giorgia emphasizes the importance of incorporating human elements and context into data visualization to make data more relatable and engaging. She discusses how Pentagram utilizes these principles in various branding projects to create compelling stories with data.
- Impact of Chronic Illness through Data. Giorgia shares her personal experience with long COVID, illustrating how data can be used to convey the profound impact of chronic illness on individuals’ lives.
- Children’s Book Project – This is Me and Only Me. Inspired by her Dear Data experiment with Stefanie Posavec, Giorgia’s new book encourages children to observe, collect, and use data to understand their emotions and human questions. Through the use of symbols and colors, the book aims to make data visualization accessible and fun for kids and adults.
- Upcoming Book – Speak Data. And yes, Giorgia is working on a new book project: Speak Data will delve into the concept of data as a language that intersects with various fields, featuring interviews and insights from diverse disciplines.
Resources
Data Humanism, The Revolution will be Visualized.
Data Items: A Fashion Landscape at The Museum of Modern Art
Books:
Guest Bio
Giorgia Lupi is an information designer. She is a Partner at Pentagram in New York.
After receiving her master’s degree in Architecture, she earned her PhD in Design at Politecnico di Milano. In 2011, she co-founded Accurat, an internationally acclaimed data-driven design firm with offices in Milan and New York.
She is co-author of Dear Data, Observe, Collect, Draw – A Visual Journal and the new picture book This is Me and Only Me.
Giorgia is also a public speaker, her TED TALK on her humanistic approach to data has over one million views.
She has been named One of “Fast Company’s” 100 Most Creative People in Business in 2018, when she also joined MIT Media Lab as a Director’s Fellow. She is also a member of the World Economic Forum’s Global Future Council on New Metrics and recently became a Fellow of the Royal Society of Art and a National Geographic explorer. She was nominated as “one of the names to know in Creative America” by Wallpaper. She is part of the advisory council for the Data Visualization Society.
She has been profiled in the New Yorker among many others, and she recently published a Visual OpEd in the New York Times.
Her work is part of the permanent collection of the Museum of Modern Art, where in 2017 she also was commissioned to create an original site-specific piece.
In 2022, she received a honorary degree in Fine Arts from MICA, the Maryland Institute College of Art. Giorgia is the 2022 National Design Award for Communication Design winner presented by Cooper Hewitt, Smithsonian Design Museum.
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Transcript
00:12 – 00:16
Welcome back to the PolicyViz Biz Podcast. I’m your host Jon Schwabisch.
00:16 – 00:22
I have a very special guest this week on the show, my good friend, Giorgia Lupi.
00:22 – 00:30
You certainly know her name from the Dear Data project, from her work at Pentagram, and possibly from her latest book, a data
00:30 – 00:35
visualization and a data book for kids. This is Me and Only Me.
00:35 – 00:40
Giorgio’s the first guest of this podcast 10 years ago.
00:40 – 00:46
We’ve been friends for a long time, and so I’m so excited to have her back on the show to highlight her new book.
00:46 – 00:54
I invited Giorgia to talk about her work on that book, how she thinks about communicating and working with kids in and around data.
00:55 – 00:57
And, of course, lots of other things that she’s working Jon.
00:57 – 00:59
And we talk about her recent piece in the New York Times.
01:00 – 01:04
We talk about her thoughts around data humanism, particularly as it relates to kids.
01:05 – 01:07
And we talk about all the things that she’s worked Jon.
01:07 – 01:13
The fashion work that she’s done, the data rugs that she’s done, tiles she’s done, illustrations she’s done.
01:14 – 01:20
Giorgia is a force of nature, a force for good in the data visualization community.
01:20 – 01:26
I’m so grateful she was able to take time out of her schedule to join me for this exciting conversation.
01:27 – 01:32
So make sure you check out all Giorgia’s work on her site, on the pentagram site.
01:33 – 01:39
Lots of places to learn more about what Giorgia does and the types of work that she creates.
01:39 – 01:46
And of course, check out her new book, This is Me and Only Me Jon Amazon or Goodreads or wherever you get your books.
01:46 – 01:49
So I’m not gonna waste any more time. This is a great conversation.
01:49 – 01:53
Super fun to talk with George again. So here we go. Here’s my conversation
01:59 – 02:02
Holy moly. The one and only Giorgia Lupi.
02:02 – 02:06
I wish I had a good rhyme for that. Hi, Giorgia. So good to see you.
02:06 – 02:08
Hi, John. It’s really good to see you.
02:10 – 02:16
You know, I was thinking this morning, prior to the pandemic, I was coming up to New York fairly often.
02:16 – 02:20
I felt like I was seeing you, like, every few months.
02:20 – 02:23
We would, like, grab lunch, and then the pandemic hit.
02:23 – 02:25
And now, and now I’ve gotten to see you.
02:25 – 02:30
We’ve talked, like, 3 times in the last couple months for various things. It’s it’s great to see you.
02:31 – 02:38
Loving the stuff that you are working on, and you’ve got a new book coming out for kids, which is super exciting. Yes.
02:39 – 02:42
Do we want to do, like, a Giorgia loopy retrospective?
02:42 – 02:44
Because we were just talking right before.
02:44 – 02:46
You were, like, first guest on the podcast.
02:46 – 02:49
So that was, like, a decade ago.
02:49 – 02:51
So we’ve got a lot lot to cover.
02:51 – 02:58
Yeah. This is pretty exciting. And I you know, you’ve done 20,000,000 episodes in between. You’re very prolific. It’s
02:58 – 03:04
it’s like yeah. I I feel like I’ve talked to, you know, not quite everybody I wanna talk to.
03:04 – 03:06
There’s still some names out there I wanna I wanna get a hold of. But yeah.
03:07 – 03:08
I’m really honored to be back.
03:09 – 03:15
Well, I’m so grateful that you can take some time. So where do you wanna start?
03:15 – 03:20
Do you wanna talk about maybe moving from Accurate over to Pentagram to start?
03:20 – 03:25
Like, because I think when you were last on the podcast, you’re at Accurate, you were running Accurate, and and now you’re at Pentagram.
03:26 – 03:34
And I think people would be curious to hear maybe what you’re working on there and what and and maybe how you’ve, I don’t
03:34 – 03:41
know, maybe how you’ve just changed or evolved in your thinking around data and data visualization over the last 10 years?
03:41 – 03:47
Because I I’m sure you I mean, I know you’ve done all the data humanism stuff, and and and you’ve done everybody’s listening
03:47 – 03:49
to this show knows all of your your great work.
03:49 – 03:58
But but maybe the the thread here would be to hear about how you’ve changed your thinking about communicating data over the last decade or so.
03:58 – 04:02
Of course. Well and, also, maybe let’s not assume that everybody knows who I am and what
04:02 – 04:05
I do. Okay. Alright. Okay. Same. That’s what I love about you.
04:05 – 04:09
Like, the humility is just, you know alright. Go ahead. Go ahead.
04:09 – 04:14
Well, I am Giorgia. And at this point, John, we’re close friends.
04:14 – 04:16
I think we can say we go way back. Yep.
04:16 – 04:20
And I’m Italian originally, but I moved to New York in 2012.
04:20 – 04:22
So at this point, I call New York home.
04:22 – 04:30
And I’ve been working with data in various capacities from a design perspective since a couple of years after I graduated architecture.
04:30 – 04:39
So I’m not a trained statisticians, data scientists, or even, you know, at this point, there are information design courses at universities and data visualization courses.
04:39 – 04:41
I came from a completely different background.
04:41 – 04:49
And so my approach to data, especially at the beginning when with, my partners at Acura, the company that I cofounded, back
04:49 – 04:52
in Italy in 2011, nobody was a data specialist.
04:52 – 04:57
Like, the person that I used to work with, the closest was Simone, a sociologist.
04:57 – 05:05
And so we started to work with data really, asking ourselves questions that are fundamentally about human nature and society
05:05 – 05:09
and relationship and behaviors because he was the one driving the content.
05:10 – 05:18
And we’ve been working on a bunch of editorial projects when we really had the chance to, again, choose the stories and go and find and combine data.
05:18 – 05:27
And, also, on the other hand, because, again, nobody was also using any d three libraries or Tableau or softwares that would
05:27 – 05:34
give us shortcuts to produce data visualization, we also, like, really created what I call visual models from scratch.
05:34 – 05:40
And so you’ll see those data visualizations back then in 2011 that, were very articulate, unusual.
05:41 – 05:43
You had kinda, like, read the legend to understand it.
05:43 – 05:48
And so that’s kinda like the beginning of my, love story with data.
05:48 – 05:55
And more and more in the in the years to to come at Acura, of course, we started to have bigger clients.
05:55 – 06:03
We hired software developers, and we worked more digitally and less manually in a way positioning elements from Excel to Illustrator,
06:03 – 06:08
but really actually, you know, working at a scale in a way, which is something I’ve I’ve loved.
06:08 – 06:17
And but I still think that the approach that shaped my relationship with data is still the one, that I started with, even
06:17 – 06:21
with big data and corporate clients, and, and all of that.
06:21 – 06:28
Now, in I’ll I’ll make it sure, and then we can go in-depth into, whatever you feel it it’s helpful.
06:29 – 06:36
In 2019, I actually had a shift of a career, after almost 10 years at Acura, and I joined Pentagram.
06:36 – 06:40
And Pentagram is a big independent graphic design firm.
06:40 – 06:44
We have offices in New York and London, Berlin, and Austin.
06:44 – 06:49
And Pentagram is absolutely not known for data visualization, but bread and butter is brand identity.
06:49 – 06:57
And so really creating logos and shaping how brands, which are, you know, any kind of company in a way, present themselves
06:57 – 07:04
into the world, reposition themselves where there’s a moment when they have to reach a new audience or change the way they operate.
07:04 – 07:11
Also, Pentagram’s well known for exhibition design, campaign design, titles for movies and shows.
07:11 – 07:14
And so really, like, the more traditional way of communicating.
07:15 – 07:23
And I joined a bit as an outlier, but, like, happily so because I really believe that right now, and that is really what moved
07:23 – 07:31
me, data can become a language that everybody could speak, and it can become a powerful language for brands to express in themselves.
07:31 – 07:36
Because if you think about it, virtually every client at Pentagram work with data and has to communicate data.
07:36 – 07:49
But a lot of the time, data visualization is just an aftermath of branding exercise, together with, honing in on the story,
07:49 – 07:55
together with, honing in on the storytelling aspect that I’ve always been interested in.
07:55 – 08:01
And so we’ve been working campaigns and projects that are true, you know, communication design.
08:01 – 08:07
And and on the other end, I’ve also worked on some fun projects such as a fashion collection that have data patterns on it,
08:07 – 08:14
a data rug, some tiles that have been manufactured really nicely that have data patterns. So, yeah.
08:14 – 08:16
I mean, I’ve been speaking a lot already. I’ll pause here.
08:16 – 08:20
That’s the that’s the past 15 years in a nutshell.
08:22 – 08:25
15 years of of Jordan Libby’s career in 30 seconds. Yeah.
08:27 – 08:29
So there’s a lot we we could talk about.
08:29 – 08:35
So I guess the one so there are two parts of that description that that I found really interesting. 1 is on the storytelling
08:36 – 08:40
piece, and the other one is is on data as a language.
08:41 – 08:48
And I’m curious how you and the folks you work with think about data storytelling. Right?
08:48 – 08:56
So one of the arguments that I’ve made over the last few years is we kinda throw around this word stories with data a lot.
08:56 – 08:58
And, really, at the end, it’s like, it’s a line chart.
08:58 – 09:02
Like, I’m not sure that’s a story the way we would, like, really think about a story.
09:02 – 09:09
But a lot of the work that Pentagram does is is bigger and broader and working, you know, with larger projects.
09:09 – 09:17
And so when you work with folks there who are traditionally have been telling stories, sort of traditional stories, but now
09:17 – 09:22
you’re weaving in the data, how do you have those conversations? What do those projects look like?
09:22 – 09:32
Sure. And as for a clarification, I so Petrem is made of different partners, and every partner has their own set of client, skill sets, and teams.
09:32 – 09:36
So we pretty much function as independent studios. So yeah.
09:36 – 09:43
Long story short, I, most of the time, operate by myself and with my team within the Petrobran platform, but I’ve collaborated
09:43 – 09:52
with other partners for a specific project that benefited from having, say, somebody who’s been doing traditional big branding for universities, for example, and myself.
09:53 – 09:59
There’s collaboration, but, also, I’m very independent, which is, to me, also, the beauty of Pentagram in a way.
09:59 – 10:04
And I would like to really talk about what does it even mean to tell stories with data.
10:04 – 10:13
I think it can be many, many different things as long as the data points themselves are not just crude and cold numbers. Because I think I agree.
10:14 – 10:24
A line chart tells a story, but I think from a design authorial perspective in a way, if you can add and this is my whole
10:24 – 10:29
spiel about data humanism that I do all the time, context, personal details.
10:29 – 10:36
Maybe if you have the opportunity to connect a bigger trend that can look like a line chart with some points in that trend
10:36 – 10:43
that can talk about the individual data points, the human being that is behind that, the particular location of that climate
10:43 – 10:52
change impact in a way or something that is really a little bit more, relatable, to me, that is when we start to talk about telling stories with data.
10:53 – 11:03
And how my practice has evolved, I think over time, I’ve, paradoxically, became less focused on data itself, but really just
11:03 – 11:05
focusing on, okay, I’m primarily a designer.
11:05 – 11:09
My favorite tool or material is data. There’s a power in data.
11:10 – 11:19
But, primarily, it is really about communicating a message, sharing a feeling of, say, for campaigns in a way, we want people
11:19 – 11:22
to relate, say, wow, to want to participate to the cause.
11:22 – 11:30
And I feel that sometimes data can just be the anchoring point to then expand into stories that don’t necessarily have to be data driven.
11:30 – 11:35
And this is really just my evolution, and I don’t think that there’s a right or wrong way to do it.
11:35 – 11:42
But I feel that personally, I thought I’ve been doing a lot of data visualizations my whole career, and I feel like I like now to expand.
11:42 – 11:49
And I mean, if you look at the wall behind me, your listeners will not see it, but it’s, like, full of pure data visualization.
11:49 – 11:56
And I that’s still my passion, But I’d like to think about data in a bit of a broader way now.
11:56 – 12:01
Yeah. And so how do you and your team think about getting those stories?
12:01 – 12:08
This is this is something that comes up a lot when I talk to, you know, quantitative data analysts or scientists or researchers
12:08 – 12:11
who want to do all the things that you just mentioned. Right?
12:11 – 12:18
They they want to enrich their visualizations or their charts with these stories or or experiences.
12:18 – 12:23
And and so how do you practically go about doing that?
12:24 – 12:34
I mean, I feel that I do have, most of the time, the luxury of being together with, the people that shape the story themselves
12:34 – 12:38
and shaping them together in terms of the collaboration with my clients.
12:38 – 12:43
So it’s pretty rare that a client comes to me with a dataset and wants to visualize the dataset period.
12:43 – 12:52
Because in those occasions, I feel, you know, you can try to push to add external data in extra context, and you can try to
12:52 – 12:58
push to make it less of a dashboard, but more of a just for this I’m simplifying for the sake of making myself do.
12:58 – 13:01
What about Crowley telling piece if it’s digital?
13:01 – 13:13
Or before you get to the interactive Tableau map, whatever it is, you have some context and intros and explanations and personal anecdotes or whatever it is. Sometimes you just cannot do it.
13:13 – 13:17
And I feel that it’s also okay sometimes to just have a chart. The chart, it’s what it is.
13:17 – 13:24
But, you know, I I can make a couple of examples of projects where, to me, we’ve been doing true storytelling with data.
13:24 – 13:30
One recent one is an article that I, with my team, published on the New York Times.
13:30 – 13:38
It’s a visual op ed, that is about something personal, which is my journey with, my health, which hasn’t been really kind
13:38 – 13:40
to me in the past 4 years.
13:40 – 13:48
I’ve been, suffering, and now I wanna say I am recovering from long COVID, which is, you know, maybe at this point, people
13:48 – 13:56
know what long COVID is, but are there health consequences that might take many forms and shape and degrees of severity following a COVID infection?
13:56 – 14:02
Most people right now, you know, get COVID, don’t even think about it, and they get back to their lives and they’re fine.
14:02 – 14:05
But for some of us, that hasn’t been the story.
14:05 – 14:07
And so I’ve been battling with physical limitations,
14:10 – 14:17
continuous flowing of symptoms of different kinds 247, pretty much for the past 4 years, and really then introducing myself
14:17 – 14:25
with health care, doctor’s appointments, cans, lab tests, therapies, injection, infusion, different medication, treatments.
14:25 – 14:28
And, of course, I’ve collected a lot of data about it because this is what I do.
14:28 – 14:36
And at some point, looking at the long COVID stories that were out there, I decided to try and publish something because the
14:36 – 14:44
stories that I saw, and I think this is important in terms of what data can do, the story that I saw published were, you know,
14:44 – 14:52
very moving, but at the same time, you would just read a blog post or an article and you’d read a list of 10 symptoms, 15 symptoms.
14:52 – 15:01
And I think that for a healthy person, these might have felt like, well, okay, I’m tired as well after work. Sure. I have addicts too. Okay. Yeah. Sometimes I’m nauseous.
15:01 – 15:06
But that is so far away from the experience of living 247 with a chronic illness.
15:06 – 15:14
Like, the term fatigue doesn’t even start to describe the crushing impossibility to move your body that happens.
15:14 – 15:19
So long story short, I with all the data that I collected smartwatch, they were all off,
15:27 – 15:33
but also the nuanced qualitative symptoms that I was experiencing every day, my visualization, and all of that.
15:33 – 15:42
I thought that telling a story that could be a complete account day by day of my 4 years, could, really shine a light onto
15:42 – 15:43
what it means to live with this condition.
15:43 – 15:54
So I think the power of storytelling with data sometimes can really just actually shine a light on the granular versus the aggregate. Right.
15:54 – 15:56
You can link it in the in the show notes. Yeah.
15:56 – 16:00
Yeah. I absolutely will. And I wanna ask you about that piece since you brought it up.
16:00 – 16:07
I mean, I can imagine a lot of people and a lot of people do collect their own personal data about lots of different things.
16:07 – 16:12
And a lot of people would present it as a bar chart or a line chart. Right?
16:12 – 16:15
I’m thinking about, you know, the sort of folks that I work with. Right?
16:15 – 16:17
Other economists and social scientists, right, they make a bar chart.
16:18 – 16:25
But the way you presented that information was these little, I guess, paintbrush strokes sort of thing.
16:25 – 16:32
And and I’m curious what you would say to someone who looks at that and says, oh, I’ve collected my health information or
16:32 – 16:36
my exercise information, but, you know, my instinct is just to create a bar chart.
16:36 – 16:39
But but what would you say to someone who says, yeah.
16:39 – 16:41
I’d make a bar chart, but I wanna be more creative.
16:41 – 16:47
I wanna I wanna engage people the way you were able to engage millions of people with that piece.
16:47 – 16:53
I’m I’m guessing you wouldn’t recommend everybody go out and get a degree in design. But, like, what would you yeah.
16:53 – 16:59
Like, what would you say to someone who wants to make something engaging but doesn’t know how to get started?
16:59 – 17:08
Totally. I mean, I think that, honestly, not everything needs to be necessarily engaging to a point that you’ve never seen something like that before.
17:08 – 17:16
I think, personally, the reason why I decided to go for this painted brush language is I’ve been thinking about what do I
17:16 – 17:20
want this piece to do, and I’ve had the opportunity to do it in The New York Times.
17:20 – 17:25
And so, of course, the visibility was has been pretty, like, wide in a way. Yeah.
17:25 – 17:32
And my main goal in a way was actually to make people feel something, which it’s a lot it’s in a lot of my projects.
17:32 – 17:41
And I feel that because my story was so personal, but I hoped that it could, first of all, make the people that could see
17:41 – 17:48
that are suffering from long COVID or any other chronic illness feel seen and understood and, not so alone.
17:48 – 17:53
Because the experience of a chronic illness is the most lonely thing to me that you can think about.
17:53 – 17:56
In general, health scares or health problems.
17:56 – 18:01
As much as you have family around you and all of that, it’s it’s the only place because your body fails you.
18:01 – 18:08
You are so uncertain in terms of what’s gonna happen in the future. You’re not yourself anymore. So, you know, this this aspect.
18:08 – 18:13
And I wanted people to just, you know, feel seen and recognized and validated.
18:13 – 18:20
And on the other hand, I wanted for people that didn’t know what long COVID was to, for a second, try to immerse themselves
18:20 – 18:26
in the world of constant daily litany of elements to your body.
18:26 – 18:27
Right.
18:27 – 18:35
So to me, like, the language of these repetitive paintbrushes that actually start with the piece in a way that it’s not even a data visualization.
18:36 – 18:43
You start to see colored paintbrushes that are interacting with the text and highlighting the symptoms that I’m describing in different colors.
18:43 – 18:49
So you start to understand that a paintbrush is probably a symptom, and a different color is a different kind of symptom.
18:49 – 18:54
And then, you know, slowly, you build this calendar of, like, never ending scrolling Right.
18:54 – 18:54
Yeah.
18:55 – 19:01
Of days in a way. And I feel that I decided for that language because of my goals in a way.
19:01 – 19:10
And so that long explanation that I gave is to say, I don’t think that necessarily everybody needs to paint other times, having
19:17 – 19:24
having a, graphically rigid geometric bar chart can also be the solution.
19:24 – 19:32
Because if you wanna communicate a certain level of trust, rigor, institutional knowledge, I don’t think that a paintbrush
19:33 – 19:39
is probably the best way to do it because it does communicate evolution, nuance, uncertainty, imperfection.
19:40 – 19:43
So I guess if I have to really abstract it.
19:43 – 19:48
I’d really suggest really, truly ask yourself what is that you wanna communicate?
19:48 – 19:56
What is that you Jon people to feel and to understand, and then trying to experiment and see if, you know, going to be out
19:56 – 20:01
of the usual ways of depicting data can be helpful.
20:01 – 20:07
I think that, like, maybe people depict me as somebody who hates bar charts and pie charts. I I don’t.
20:07 – 20:09
Like, you know, I’m nothing against it.
20:12 – 20:15
Yeah. You have the the early work in Accurad.
20:15 – 20:20
I always whenever I I think of your early work in Accurad is always, like, stuff that’s, like, at a 45 degree angle. Right?
20:20 – 20:23
These are really intricate big, big, big
20:23 – 20:28
I still remember at a Visualization, you were speaking after me.
20:28 – 20:36
And, you were making your examples, and at some point, you were talking about a problem that you have with the clients or whatever or, like, a challenge. And then Yep.
20:36 – 20:45
You feel the screen of the next slide with tilted small multiples of w w g l d. What will George Loopy do?
20:45 – 20:49
And I am so happy about that, and the audience was laughing.
20:49 – 20:51
And this 45 degrees in you, again. Yeah.
20:51 – 20:55
There’s 45 degrees. Just a lot of them, 45 degrees. Yeah. Alright. Yeah.
20:55 – 20:59
That was that was a fun talk. Yes.
21:02 – 21:10
So there there are 2 things I wanna talk about, but I I think maybe we switch gears to talk about your latest project because Yes.
21:11 – 21:20
It’s interesting hearing you talk about stories and now having a kid’s book coming out, you know, you know, the next couple of weeks.
21:21 – 21:24
Because when I think about stories, that’s my first thought. It’s like, okay.
21:24 – 21:28
So how would my kids or any kids think about, you know, what is a story? Right?
21:29 – 21:38
And so and and and, of course, just for folks who don’t know, your project, with Stephanie Posavic, the Dear Data project,
21:38 – 21:46
There is for folks who don’t know, there is, like, a little mailing list of people who are working in doing Dear Data, and they’re mostly educators.
21:46 – 21:49
And I always find it fun to find, like, an email show up. It’s like, hey.
21:49 – 21:53
I’m a teacher in Austin, Texas, and I’m doing Dear Data with my with my,
21:53 – 21:54
with my class.
21:54 – 21:58
And I would say, like, yeah, 90% of the emails that show up are educators.
21:59 – 22:06
So I guess my question is, like, where did the idea for the kids book come?
22:06 – 22:08
What was the what was the inspiration for it?
22:08 – 22:12
And and and for folks who don’t know, like, what is what is the book about?
22:12 – 22:19
Yeah. So the book will be out in a couple weeks, and it’s called This is Me and Only Me, and it’s a collaboration with my
22:19 – 22:23
coauthor, Maddie, Gardner, who also has been working with me at Pentagram.
22:24 – 22:33
And she was a preschool teacher before becoming a project manager, so it’s been really lovely to work with her, as somebody that really knows and understand, kids.
22:33 – 22:36
So the book is a book a picture book for children.
22:36 – 22:42
And if I have to take a step back, I would say that definitely, you know, the origin of all of these was Dear Data, which
22:42 – 22:51
is, an experiment that Stephanie and I have done with extensive personal data collection for 52 weeks, mailing data postcard
22:51 – 22:54
back and forth every week from London to New York and New York to London.
22:54 – 23:00
We’re really in 4 in 52 weeks, we’ve explored pretty much everything about ourselves.
23:00 – 23:07
And so noticing our behavior, our thoughts, our environment, what makes us happy, what makes us sad, and pretty much painting
23:07 – 23:11
a portrait of the other person through this only layer of data.
23:12 – 23:19
Then people got excited, as you mentioned, educators, wanted to experiment with kids in terms of, like, making them observe
23:19 – 23:26
reality through this data lens, which, again, it’s not only how many time a day or certain things, but, like, qualities and
23:26 – 23:31
human questions related to it such as what was I feeling, what was the context, and why.
23:31 – 23:41
And on the other end, also using it as a tool for creativity, being a little less afraid of the white page and working with quantities and numbers and symbols.
23:42 – 23:49
So the second, iteration of your data also was a journal called observe, collect, draw that Stephanie and I published in,
23:49 – 23:57
if I remember correctly, 2017 or 2018, couple of years after their data, really because we got so many requests of, like,
23:57 – 23:59
teaching workshops and how can we do it.
23:59 – 24:03
And so we did this journal that made this kind of observation actionable.
24:03 – 24:13
There is exercises and gridded pages for you to fill in with symbols of your own, making sometimes or suggested by us, and that got pretty popular too.
24:13 – 24:19
And I think that really, honestly, from that time on so it’s been, like, a bit of an idea that was in the back of my mind
24:19 – 24:21
for the past 5 or however many years.
24:21 – 24:25
I always thought, you know, this will be such a nice story for a picture book.
24:25 – 24:33
And my idea has always been pretty simple, starting with inanimate object of any kind, whether it’s a circle or rock, anything.
24:33 – 24:35
I didn’t even think about the visual language then.
24:35 – 24:48
And then the more this entity observe things around them and about them, the more this becomes this colorful portrait that makes this human being feminine.
24:49 – 24:51
So that was just really the origin.
24:51 – 24:58
And then, you know, long story short, I talked about it with Maddie, who has much more knowledge about children than I do.
24:58 – 25:03
I I don’t have children, and I also have not, you know, grown up with children around me. I’m an only child.
25:03 – 25:08
My parents were both only children, so there’s no nephews, nieces, anybody. You know?
25:08 – 25:09
Right. Right.
25:09 – 25:18
And so we collaborated really in in in really figuring out what can be, some aspects of collecting data that can really resonate with kids.
25:18 – 25:26
So pretty much the ball starts with a a hollowed circle that has a black outline, and it starts by saying this is me and only me.
25:26 – 25:33
And you flip the pages and you start to see that it starts to add these colored symbols on the days when I’m happy, different
25:33 – 25:41
symbols on the days when I’m sad, and going on and on and starting to add more details, interacting with people, observing
25:41 – 25:48
also the feelings in them that might be a little confused if you don’t stop and actually acknowledge and name them.
25:48 – 25:54
And really, in the end, building a beautiful portrait of what makes you you. So it’s a pretty simple idea.
25:54 – 26:00
In the end, I hope it’s it can and something that might inspire not only, young kids, but, you know, I’ve always wanted to
26:00 – 26:04
make this book that adult feel like, oh, this is interesting too.
26:04 – 26:14
Right. But what and what’s interesting about the way you describe that book is I do you view it as a data book or as a data vis book for kids?
26:14 – 26:18
I Jon. To the point that we don’t mention the word data until the very end.
26:18 – 26:24
The last page is a bit of an explanation that said all that you’ve seen so far can be called data.
26:24 – 26:34
But I think that this is an invitation to observe, and it is an invitation to actually also start to like yourself for who
26:34 – 26:39
you are and the things that make you you. And, I mean yeah. No.
26:39 – 26:46
I really don’t see it necessarily as a data book, and I have been very opposed when some publishers suggested that in the
26:46 – 26:51
end, we add some activities because to me, invitation, it’s it needs to be inspiring.
26:51 – 26:59
I’ve already done a journal and a, like, kind of, like, classroom kind of a book, and I’ve been really pushed back in, yeah,
26:59 – 27:03
in making it become a database book. I really want the story.
27:04 – 27:07
Yeah. That’s what it sounds like. I’m I’m very excited to get my hands on it.
27:07 – 27:14
So did you and I’m excited to hear that that Maddie is a was a preschool teacher because I think that brings in like, that
27:15 – 27:26
to to your point from earlier, like, that’s the experience that you need to understand who you’re communicating with and communicating, you know, for. But have you tested it?
27:26 – 27:29
Like, did you bring it into classrooms or give it to kids?
27:29 – 27:34
I’m sure with other things that you’ve written, you know, you send it out to people to, like, peer review and that sort of thing.
27:34 – 27:38
But, like, for kids, did you, like how did you do that?
27:38 – 27:45
We did. We did do some sort of, like, informal, very anecdotal testing around that and our publisher also.
27:45 – 27:51
So the publisher is Korayini, is an Italian publisher that I really love working with.
27:51 – 28:03
They are the original publisher of all Bruno Munari’s book, and they’ve been publishing these beautiful books, that are artistic, poetic, and design oriented.
28:04 – 28:13
And the editor that has been working with us is very, you know, she works in children’s book a lot, and she’s been very helpful too.
28:13 – 28:17
And, you know, we’ve tested it with the kids around us that could, you know, give us, some feedback.
28:17 – 28:27
And I think what I’ve liked to observe is how so the the book is not illustratively, figurative in a way that the all the
28:27 – 28:32
representations are animals or flowers or things like that. Everything is abstract.
28:32 – 28:37
And, the maybe the concern that I had in the beginning is, you know, will kids relate?
28:37 – 28:42
But turns out that at least in our little experience so far and, again, the book’s not out publicly yet. Right.
28:42 – 28:46
So we’ll we’ll see what, parents and children think.
28:47 – 28:52
But really is that with this abstract way, like, every time that you go back, you can see different things.
28:52 – 28:59
And there’s, like, little anecdotes, as you go through the book that make you explain what you know, that actually have you
28:59 – 29:02
understand what is that symbol, what is this other.
29:02 – 29:09
And and I think that in the end, that abstract representation could be just really a way to foster imagination even more and,
29:09 – 29:12
hopefully, something that kids wanna get back to.
29:12 – 29:16
It’s almost like the difference between, you know, a written book and a movie.
29:16 – 29:23
And sometimes you want a movie because you’d like to just see what the author thought in terms of what does that character have to look like.
29:23 – 29:25
That’s another kind that you also wanna imagine.
29:26 – 29:39
Right. The way you describe it also feels to me very consistent with your, I mean, your general approach to to data, and particularly with the data humanism.
29:39 – 29:47
I mean, it sounds like what you’re trying to accomplish with this book is to get kids to not to get kids, but to encourage
29:47 – 29:53
kids to feel comfortable with themselves, comfortable with other people, and sort of kind of, in some ways, kind of, like,
29:53 – 29:59
see people behind the data for you know, I’ll use that term loosely in this context.
29:59 – 30:03
Is that, like do you feel like that’s where you need to start with, like, with kids?
30:04 – 30:11
Well, I again, I think I don’t have kids, so I’m not necessarily the best person to to talk about that.
30:11 – 30:17
But, you know, I I was a kid myself, and I was a bit of a nerd kid just collecting stuff and you know? Yeah.
30:17 – 30:25
But I also know that if there’s something that kids really have that maybe we all lost, it is the power of imagining.
30:25 – 30:34
And so I think that the imagination of what every kid can see in those symbols and how they can actually translate it to things in their lives.
30:34 – 30:41
And I feel that the inspiration of saying, you know, oh, I had never really paid attention on what’s happening on the bus on my way to school.
30:41 – 30:51
And, you know, this is really an invitation to observe in very different areas of your life, even the one that seems the most mundane. And I feel that Mhmm.
30:51 – 30:58
The record relation with your data and something that I can’t stop thinking since Stephanie and I almost 10 actually 10 years
30:58 – 31:04
ago at this point started the project is that we always and this is has nothing to do with designer data.
31:04 – 31:05
It’s really have to do with life.
31:05 – 31:16
We tend to remember and look forward to the big grandiose event, and instead, like, the beauty of the daily details of the
31:16 – 31:18
most mundane things just, like, get lost.
31:18 – 31:27
And when you learn to pay attention I mean, now, I don’t wanna sound like a meditation mindfulness, you know, preaching or anything like that.
31:27 – 31:35
I think that learning to open your eyes and as opposed to going about your life with a spotlight onto what you’re thinking,
31:35 – 31:38
but really just shining a lantern Jon what’s going around you.
31:38 – 31:43
It’s such a useful way to sometimes go about your life.
31:43 – 31:50
And I think it’s something that has helped me and has been helping me even with this illness to try and think about it’s very
31:50 – 31:52
easy to point my focus, for example.
31:52 – 31:58
And this is an extreme situation, but I feel that everybody might feel like that for other aspects of their life. It’s very focused.
31:58 – 32:05
They just it’s very easy to focus on what’s wrong on my body, what I can’t do, what are my symptoms right now, what is the
32:05 – 32:10
fear that I have about whether I’m gonna pay for this later or whatever it is that’s going on.
32:10 – 32:17
But instead, if I stop and every time I remind myself I’m here in this room, there’s all these beautiful things around me,
32:17 – 32:23
today is the day where I’ve been able actually to accomplish x, y, and zed as opposed to thinking about what I don’t have.
32:23 – 32:25
I mean, does it cure my illness? No.
32:25 – 32:28
But it makes everything a little bit more bearable.
32:28 – 32:35
And, again, this is an extreme example, but you have to really learn to pay attention, which is something that they should teach in school, I think.
32:36 – 32:40
Yes. Patience and gratitude. Yeah. I think that would be really helpful.
32:41 – 32:47
If you were the, I don’t know what they call it in in New York, but if you’re the superintendent of the New York City Schools,
32:48 – 32:56
would you and you can model it on the Giorgia loopy corpus of works out there.
32:56 – 33:02
Do you think that your projects kinda work together in sort of a data data curriculum?
33:02 – 33:08
Like, I like I would say I don’t have the book yet, so I’m I’m, like, waiting. So yep. There it is. Yeah.
33:08 – 33:15
So, like but I can imagine the way you’ve described that book, it feels like it’s for the for the youngest for the younger kids. Right?
33:15 – 33:17
The I don’t know if what you have in mind.
33:17 – 33:20
Like, 3 to 6, 3 to 7, something like that.
33:20 – 33:23
Thinking more like 5 to 10, perhaps.
33:23 – 33:24
Okay. So 5 to 10. I mean,
33:24 – 33:26
like, I think, like, 4 to 8, perhaps.
33:26 – 33:37
Yeah. Right. So then those, like, 8, 9, 10 year olds are in the, age group where they can start doing, like, the early deer data stuff. Right? So that’s like observe, collect, draw.
33:37 – 33:45
And then you get a little bit older and you have, like, the teenage kids who could do, like, the deer data stuff the way you
33:45 – 33:47
and Stephanie did it where they’re collecting their own data.
33:47 – 33:54
Like, if you could build that curriculum, do you think we’d have a population of young adults who are more data literate?
33:54 – 33:57
Do you think they would just be more creative?
33:57 – 34:01
Do you think they’d just be more able to observe the world around them?
34:01 – 34:03
Where would that, like, high school graduate be
34:03 – 34:04
if
34:04 – 34:05
that was their that was their curriculum?
34:05 – 34:11
That’s a really interesting way of thinking about it, and I feel let’s say that my ambitious has never been to completely
34:12 – 34:14
heal the 1st grade to to to Right.
34:14 – 34:15
Yeah. Yeah.
34:15 – 34:16
Yeah. Whatever. You know?
34:16 – 34:18
I was giving you more things to do. That’s all.
34:18 – 34:20
Yeah. No. No. But it’s interesting because it’s true.
34:20 – 34:22
I think, you know, this is me and only me.
34:22 – 34:30
It’s just an introduction to being inspired by who you are and what’s around you and also, of course, starting to make you
34:30 – 34:37
think that not all the stories needs to be completely figurative or I maybe I’m missing a word in English, like, really representative of reality.
34:38 – 34:47
And that there’s an element of visual going out there and thinking about something different that can happen. And, then you’re right.
34:47 – 34:49
Observe, collect, draw can start to be exercises that can
34:57 – 35:04
collected into symbol, and then there start to be lengths and colors for categories and sizes and positioning on the page.
35:04 – 35:06
And so I you you know me, Jon.
35:06 – 35:13
I’ve never been, like, a didactic academic teacher, and I think that that is a little bit of my way of teaching, just making
35:13 – 35:17
you think about how you could do those things, and and then you learn by yourself.
35:17 – 35:25
And I feel that Dear Data, maybe it’s that more poetic, oh, I can be very creative with data.
35:25 – 35:33
And if these people send each other postcards, maybe at this point, I can write a love letter with data or build a sweater
35:33 – 35:35
knit a sweater that has data in.
35:35 – 35:38
So I think that that is a little bit more like, okay. And now you can expand.
35:39 – 35:45
Now I don’t even know if I mentioned it, but I am co authoring another book that maybe is part of the next step.
35:46 – 35:49
This is gonna be out in 2025, so I don’t speak a ton about it.
35:49 – 35:52
And it’s like I love, working with, co authors.
35:52 – 35:56
If you if you if you haven’t, you know, seen the the trend.
35:56 – 36:03
And I’m working with my, dear collaborator at Pentagram, strategist Philip Cox, who’s I’ve been working with me, at Pentagram
36:04 – 36:06
for, you know, the longest time since I joined.
36:06 – 36:08
He’s been with me and is fantastic.
36:09 – 36:17
And we are working on a book that is called provisional title, speak data, which is, for the first time, a bit of a textbook,
36:17 – 36:25
and it’s filled with interviews with people that are not necessarily data expert, but artists, metheologists, health care,
36:26 – 36:32
practitioners, and people in all different fields that tangentially have touched upon data.
36:32 – 36:40
So it is a way to actually start to think about data as a language that can touch every aspect in a way of the world that we’ve moved in.
36:41 – 36:47
And it’s a little bit more of, let’s say, we’ve been thinking about it like a guide that if you don’t know anything about
36:47 – 36:50
data but wanna have a dinner conversation that is informed.
36:51 – 36:52
Yeah.
36:52 – 36:55
So, yeah, there’s there’s that too. So I think I’m coming to people.
36:55 – 37:01
You’ve got you’ve got, like, the world according to Giorgia, like, all the way through K to K to 22.
37:02 – 37:10
It’s not often there’s breaking news on the on this podcast, but, I’m glad to have, like breaking news. Yeah. Breaking news. Yeah. Well, that’s that’s really exciting.
37:10 – 37:17
I mean, I I think, yeah, altogether, I can see this sort of thread that pulls I mean, obviously, pulls through your work,
37:17 – 37:25
but just on, like, helping kids as they age, as they grow to think about their own data and their own identities and and and
37:25 – 37:29
then the world around them in the sort of broader broader way.
37:30 – 37:38
And to hear you speak about, you know, your own, health issues over the last few years, like, with this patience and gratitude
37:38 – 37:43
for what can be as opposed to what is sort of bad and negative. Yeah.
37:43 – 37:46
I think it’s a it’s it’s really exciting.
37:46 – 37:54
It is. I’m, yeah. No. I mean, you know, John, I feel like we’ve never or, like, maybe nobody ever thinks that they are prolific
37:54 – 37:57
enough or that they are accomplished enough or productive enough.
37:57 – 38:07
But I think maybe if I pause, at least I know that I have been putting out pretty much all the ideas and thoughts that I had.
38:07 – 38:09
Now are they helpful for the world? I don’t know.
38:09 – 38:13
But at least I know that I’m trying to sort of, like, keep experimenting.
38:14 – 38:21
And one thing that I feel that I mean, maybe you look at my work and it looks all the same, but I’ve kept from the beginning
38:21 – 38:29
really wanting to experiment with new challenges, new mediums, new type of data, new outputs, new type of clients.
38:29 – 38:38
I don’t think that I’ll be fulfilled if I kept doing the data editorial data visualization for the maybe time newspaper like I’ve done. You know? Like, I feel Yeah.
38:38 – 38:42
Really, to me, expanding and even going out of my comfort zone.
38:42 – 38:46
I mean, now I’m a partner at the branding agency. I’m working on branding project. It’s fun.
38:46 – 38:48
It doesn’t necessarily always have data in it.
38:48 – 38:58
When I can, we we do use data, but I’m even learning how to just get completely out of the comfort zone of having numbers to visualize, but really Right.
38:58 – 39:04
Checking messages and how do they translate into a symbol that has no data points behind it. So
39:04 – 39:11
Yeah. Yeah. I mean, I think that’s that’s part of the what in my experience of having done this now. Right?
39:11 – 39:17
So, episode 1, you were on and now episode I don’t even know what number this is. 260 something.
39:17 – 39:22
Like, you know, there’s been an evolution in the field and the evolution of the way people have approached data, not just
39:22 – 39:29
from an individual perspective, but the way we get data now, the way we the tools we use, the platform for use.
39:30 – 39:38
So I think it’s it’s really interesting to see people evolve and and change in their approach to data and their approach to visualization.
39:38 – 39:47
And now, like, in another year, we’ll have the entire Giorgia loopy, like, literature to take us all the way through from from birth to young adulthood. Exactly.
39:47 – 39:49
And then I’ll retire.
39:51 – 39:54
Then you’ll need to write a book like Data Viz for retirees or something like that.
39:54 – 39:57
You need to, like, you know, help people get ready for retirement.
39:57 – 40:00
So, Giorgia, thanks so much for coming on the show.
40:00 – 40:02
It is always great to see you.
40:02 – 40:07
Congrats Jon the new book and the forthcoming book. I can’t wait to see them.
40:07 – 40:14
I will put links to all the stuff that we’ve talked about, all the dear data stuff and the data humanism stuff and pentagram
40:14 – 40:17
stuff, so people can can reach out and find you.
40:17 – 40:19
So again, thanks so much for coming on the show. Always.
40:20 – 40:22
Thank you, John. It was so fun. Such a pleasure as always.
40:24 – 40:28
Thanks for everyone for tuning into this week’s episode of the show. I hope you enjoyed that conversation.
40:28 – 40:30
I hope you’ll check out all of Giorgia’s work.
40:30 – 40:36
I’ve got links in the show notes to the many things that we’ve talked about ranging from her your data book all the way to
40:36 – 40:43
her new book, This is Me, Only Me, and a range of other projects and products that she has worked on over the years.
40:43 – 40:50
Before you go, as you’re tuning out, as you’re getting ready to move on to your next podcast, if you could just take a second
40:50 – 40:53
to rate or review this show on your favorite podcast provider.
40:54 – 40:58
You can also check out the video version of the show over on my YouTube channel.
40:58 – 41:04
And as always, check out lots of great content when it comes to your data visualization work over on my website policyviz.com.
41:05 – 41:10
So until next time, this has been the PolicyViz Podcast. Thanks so much for listening.