Lauren Klein joins me to talk about her new book, Data by Design, co-authored with a team of student collaborators. Over more than a decade of work, Lauren set out to place the history of data visualization in its full historical and political context, going well beyond the familiar “great men” narrative of Playfair and Snow. We talk about how she chose which historical visualizations to feature and redesign, the ethical questions that come up when working with data about the transatlantic slave trade and Indigenous mapping, and what it actually took to track down high-resolution scans of centuries-old charts. Lauren also shares what she wants readers, especially working data visualization designers, to take away: that visualization is only as powerful as how, and by whom, it’s put to use.
Resources
Data by Design (book) | dataxdesign.io (free online companion) | Data Feminism, with Catherine D’Ignazio | Lauren Klein at Emory
Guest Bio
Lauren Klein is Professor of Data & Decision Sciences and English at Emory University, where she directs the Emory Digital Humanities Lab and the Atlanta Interdisciplinary AI Network. Before moving to Emory, she taught in the School of Literature, Media, and Communication at Georgia Tech. She is the author of An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020) and coauthor (with Catherine D’Ignazio) of the award-winning Data Feminism (MIT Press, 2020). With Matthew K. Gold, she edits Debates in the Digital Humanities, a hybrid print-digital publication stream that explores debates in the field as they emerge.
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Transcript
00:01.88
Jon
Hi, Lauren. Good to see you again.
00:03.95
Lauren
Hey, John. Yeah, been a minute.
00:05.99
Jon
Yeah. It has definitely been a minute. It has definitely been a minute. um how is Georgia, how is the kickoff to the semester?
00:16.28
Lauren
um It’s good. It’s exciting. It’s exhausting. You know, all the things that happen in week one of classes, which is when we’re talking.
00:22.78
Jon
Yeah. Yeah.
00:23.76
Lauren
But yeah, no, so far, so good.
00:26.08
Jon
Are you, how many classes are you teaching now?
00:28.45
Lauren
I’m teaching two.
00:30.15
Jon
Okay.
00:30.30
Lauren
um And I have this funny appointment. So I’m half in a data science department and half in an English department.
00:34.61
Jon
Right.
00:35.64
Lauren
And so I joke that I live in a natural experiment, but it’s totally true. So like one of my classes is like…
00:39.89
Jon
Yeah.
00:41.93
Lauren
this It’s supposed to be the introduction to NLP, natural language processing for data science students.
00:41.100
Jon
Heh.
00:46.28
Lauren
And so that class is like, here’s how AI works.
00:47.14
Jon
Yeah.
00:49.23
Lauren
And then in my English grad seminar, it’s like.
00:49.77
Jon
Right.
00:51.71
Lauren
AI is terrible.
00:52.86
Jon
Yeah.
00:52.61
Lauren
Let’s learn all the ways in which AI is destroying society.
00:56.89
Jon
Oh, wow.
00:57.97
Lauren
So.
00:57.36
Jon
Yeah, don’t get them all in one room together, that one.
00:59.69
Lauren
Well, I do.
00:59.79
Jon
B.
01:00.36
Lauren
i let I let my seniors, I let my data science undergrad seniors enroll in my grad seminar as a capstone seminar.
01:00.50
Jon
Bad or good? Yeah.
01:07.38
Jon
oh
01:07.100
Lauren
And it’s actually, it’s really good to have. students with technical knowledge. in dialogue with really theoretically
01:16.95
Jon
Yeah.
01:17.15
Lauren
rich grad students. like Usually the data science students are like, oh my gosh, they they they use so many words. They have so many things to say. And the grad students are like, oh my gosh, we just, we said we wanted to like make this map.
01:26.06
Jon
of
01:29.81
Lauren
And then they just.
01:30.85
Jon
Let’s do it.
01:30.89
Lauren
They did it.
01:31.82
Jon
Love it.
01:32.32
Lauren
Yeah. Yeah.
01:34.23
Jon
That’s awesome. All right, bringing people together.
01:35.30
Lauren
Yeah.
01:36.48
Jon
um
01:36.43
Lauren
Yeah.
01:37.47
Jon
which is kind of what you’re doing in the new book, like bringing lots of people together. You’ve got a whole crew. of co-authors and students and collaborators on this one so um it it looks great um i’m waiting for my hard copy i’ve got the digital version which is not going to be i i’m you know mit does have a nice reputation of good like solid
01:57.18
Jon
quality book so i’m looking forward to um to holding on to it so um data by design can you start us off like what is the goal what is the message what do you want people, like, what is that core thing you want people to know when they. go to Amazon for. for shopping.
02:14.61
Lauren
Oh, my gosh. So this you can tell this is the first time that I’ve ever talked about this book because the answer is that I don’t have one answer to the core thing that you want people to know.
02:21.62
Jon
Okay. That’s fine, yeah.
02:23.15
Lauren
But I will say like there’s sort of I was thinking about this and. One of the reasons why it’s hard to answer is that this is a really long project. I worked on it, I say a decade, but if I’m being honest, it’s probably something like 12 years.
02:35.89
Lauren
It’s as old as my oldest child who just turned 13, which I know because there’s a picture of her in a baby Bjorn outside of the first archive that I ever went to on my first day of research for this project.
02:37.95
Jon
Mm.
02:44.63
Jon
Wow.
02:47.37
Lauren
um But I sort of, I put it aside and came back to it and put it aside and came back to it. And kind of each time my goal changed, I think in a good way.
02:54.66
Jon
Mm hmm.
02:54.77
Lauren
So like the first time. It. was a pretty clear goal. um I just wanted to place the history of data visualization in its historical and philosophical context.
03:06.22
Lauren
I thought that that had not been done before.
03:06.95
Jon
Mm-hmm.
03:08.88
Lauren
You know, we’ve got, and if you look at the histories of visualization, who writes them, it’s generally statisticians, which is fine. Great. Like I love that, but they’re not trained historians. And so one of the things that.
03:18.73
Jon
Yeah.
03:19.64
Lauren
I can do for my background in the humanities is. broaden the context. through which we understand the emergence of the field. So that was like. you know, goal number one, but then.
03:29.90
Jon
then
03:30.61
Lauren
I wrote Data Feminism with Catherine and I put…
03:32.47
Jon
Right.
03:33.16
Lauren
this book aside and one of the unexpected pleasures of that book was that People actually read it?
03:40.49
Jon
ah Always satisfying.
03:40.45
Lauren
You know, in the humanities, you don’t expect people to read your your books, you know.
03:43.75
Jon
Right. Yeah.
03:45.42
Lauren
um but It was really exciting to think about. Are ideas impacting practice? And so when I came back to it after Data Feminism, I really pushed myself to say.
03:52.13
Jon
Mhm.
03:56.59
Lauren
like how does this history change what we do now?
04:00.19
Jon
Mm-hmm.
04:00.22
Lauren
And so if you look at the book, there’s now at the end of each chapter, like bullet point takeaways. that We have a set for people who look at visualizations and interact with them and then a set for people who design them.
04:10.71
Lauren
And I really pushed myself to ask, like, OK, how does learning about the 18th century or, you know, the weird life that William Playfair had, you know, how does this change how we like.
04:17.29
Jon
Yeah.
04:21.19
Jon
Yeah. Yeah.
04:23.82
Lauren
you know design time series charts today. like really and really And sometimes it was obvious to me, and sometimes…
04:25.88
Jon
Right.
04:29.02
Lauren
it was tricky so anyway so that was the sort of the second time and so
04:31.83
Jon
Mm hmm.
04:32.28
Lauren
I really did want to. sort of And I do want to change and enrich how people design visualizations today.
04:39.33
Jon
Mm.
04:39.13
Lauren
And then the third thing, you know when you’re writing a book, a book book you know this actually it began as a website and will eventually again become a website but one thing that happens when you write a print book is that you send it off to the press and then you don’t see it for like a year because it’s getting you know routed and they do legal clearance on the images and they copy edit it and like and whatever and so when it came back to me and copy edits it was right in like the first or second month of the second Trump administration where
04:54.16
Jon
Yeah.
05:08.98
Lauren
higher education was just getting attacked right and a left and words were getting banned and professors were getting fired. And then there was also the sort of undercurrent, which we would become a…
05:16.05
Jon
Mm hmm.
05:20.06
Lauren
major tidal wave of AI, which was threatening. from a different angle, kind of sometimes the same angle. um
05:27.26
Jon
Mm hmm.
05:27.48
Lauren
you know what it is that we do in universities. And so it became really important in the end to really stake a claim for the value of. research, and in a particular of humanities research, which is often perceived as
05:37.78
Jon
Mm-hmm.
05:42.73
Lauren
Abstruse or narrow or irrelevant and certainly slow. I mean like i just told you how long this book took um but i think it really matters and so
05:48.61
Jon
Yeah. Yeah.
05:53.82
Lauren
The last pass I did through the book, mostly in the intro and in the conclusion, or I guess the… preface of the epilogue there’s like sort of end front matter and matter right um was to really be explicit about what i thought the political stakes were of the project and why this kind of work matters and
06:02.37
Jon
Yeah. Yeah.
06:08.98
Jon
Mm hmm.
06:12.54
Lauren
I believe it. you know And now when people say, like why did you write this book? Now I say, well, it was to show. why what we do is It really matters in the world. It matters for the future. It matters if we want to have better ideas about how to get out of this mess.
06:25.62
Lauren
We need people spending 12 years writing books about the 18th century. You know, I mean, we also need activists and we also need.
06:29.20
Jon
right
06:31.89
Lauren
organizing and we also need unions and policy and all these other things but we do need people saying like Let’s think really hard and deeply about how we got here.
06:40.84
Jon
Yeah. So I want to come back to some of these. um what people can learn from. uh william play for or what people can learn from these graphics and the I mean, really going back to the early 18th century right even before that um in the in the in the preface at least you go back even further so i want to come back to to some of that in a bit but um let’s talk about the before we do that let’s talk about the the
07:08.10
Jon
the book itself so um You have, I believe, if I if i counted right, 11. collaborators slash co-authors and I’m curious from an author perspective like was that Harder?
07:23.17
Jon
or easier. than like working with just catherine like what what was this sound, it sounds to me the way you just described it and the way it’s sort of written up in the book that it sounds like this was.
07:34.81
Jon
Kind of a… book that grew out of a practice with lots of students.
07:39.95
Lauren
Yeah. Yeah. I mean, like to answer the question, to it like it’s both easier and harder. Right.
07:45.18
Jon
Mm-hmm.
07:45.15
Lauren
So. It is challenging in that most of my… collaborators as you just said are students and the i don’t know like who’s listening and how long ago they were a student.
07:57.32
Lauren
But the student lifestyle is very different than the lifestyle of a middle-aged mom.
07:58.37
Jon
ah
08:02.94
Lauren
academic like me you know and so like I’ve got my to-do list I’ve got my schedule I’ve got my calendar and I
08:03.43
Jon
Yeah. Yeah.
08:10.32
Lauren
I’m very clear about what needs to get done. And I think when you’re an undergrad, when you’re 18 years old, you’re like, oh no, I have a midterm tomorrow. You know, like that is my all consuming priority or like, oops, I stayed up all night and now I need to sleep all day.
08:17.80
Jon
Okay.
08:20.52
Jon
Yeah.
08:23.58
Lauren
You know, and these are normal things that. should be happening to college students but one of the things actually like one of my proudest one of the things I’m most proud of over the course of this project is I think that I learned how to be a really good project manager of students.
08:39.23
Jon
Hmm.
08:39.30
Lauren
you know like I really learned what… ah realistic chunk of a project was to Sort of. delegate to different people depending on what their sort of
08:48.68
Jon
Right.
08:51.27
Lauren
constraints were and sort of where they were at that that point in the semester. Um, I feel like I figured out a good meeting cadence. We have good asynchronous communication. Um, I really feel like, and that was a skill, like, you know, like you don’t learn that in grad school, you know?
09:04.66
Jon
no right yeah
09:04.85
Lauren
So I really like, I’m actually, I feel like we. Like I figured out how to make it work and I hope that. the other authors on the project the student authors would agree um but sometimes it was tricky right because sometimes it’d be like look i need to go you know like
09:13.91
Jon
Mhm.
09:18.54
Lauren
I need to get a job when I graduate. So I’m just like out for the next three months because I’m interviewing in New York City, you know, and like you need to be like, OK, that is your prerogative.
09:23.38
Jon
Right. Right. Yeah. That’s right.
09:28.17
Lauren
And then you’re like, oh, no, no one can prototype my visualization for me.
09:27.74
Jon
Yeah. Yeah. ah yeah that’s right yeah
09:33.82
Lauren
Yeah. um sorry so like so that part was a little bit harder but the other thing you know and i think about this um
09:34.99
Jon
Yeah.
09:39.67
Lauren
you know, now, cause I’m like, oh my gosh, like there are a lot of moving parts. Would it just be easier for me to just write the thing that came out of my brain, just me by myself, but it’s very lonely. And sometimes you’re like, oh, I’m stuck here.
09:49.31
Jon
Yeah.
09:51.04
Lauren
I don’t know. what to do and there’s something really nice about having sort of like a built-in real-time
09:53.48
Jon
Yeah.
09:58.36
Lauren
feedback committee where you can be like it does this make sense?
09:59.76
Jon
Mm hmm.
10:01.35
Lauren
Is this where we should go?
10:02.24
Jon
Right.
10:03.19
Lauren
And people who are not just invested as readers and friends and colleagues who you can bounce ideas off of but people who are legitimately invested in the project because they’re part of the project like that’s that’s really nice you know so I definitely feel like
10:13.11
Jon
Right.
10:16.63
Lauren
it will be a transition moving back to even smaller collaborations.
10:20.69
Jon
Yeah. Well, it it is.
10:21.11
Lauren
um in the future
10:22.39
Jon
it I mean, the the book is really interesting for lots of reasons. but But one reason I found interesting just on the visualization side is. You don’t just… take a set of graphics and talk about the historical where they were.
10:36.89
Jon
in that moment in time and who created them and why and how and what the impact was but you also take time to redesign some of those Going back to the original data, I’m thinking of the… the slave trade.
10:50.61
Jon
um graphics in the in the first chapter. um And so I could imagine. that conversation about what the design should look like.
11:01.77
Jon
Um… is certainly easier with more people. Um, and presumably you can just say to the students Go build the thing and we’ll talk later.
11:13.90
Lauren
I mean, like, yes and no, right? I mean, I think it’s super, it’s super interesting because I feel that oftentimes I have a very clear. sense of what I want a thing, not as much what I want it to look like, sometimes I do, but like what I want it to do.
11:27.07
Jon
Mm hmm. Hmm.
11:28.72
Lauren
and often And I’ll sort of come to the students and be like, here’s the data. here’s sort of what I think we should do with the data or the kind of thing that I want to show.
11:37.90
Jon
Mm-hmm.
11:38.27
Lauren
And then the question is like, well, how do we show it? And then the interesting conversation comes between like on the team, I have people who are getting their PhDs in visualization in a computer science department.
11:49.33
Lauren
um Shout out to Xiao.
11:49.45
Jon
Mm-hmm.
11:50.80
Lauren
I have people who are getting a PhD in English. Shout out to Margie.
11:57.49
Lauren
Margie Adams, for example, is very familiar with sort of theories of the archive and how you deal with sort of the damaged evidence of the past, in particular with respect to…
12:05.34
Jon
Mm hmm.
12:07.43
Lauren
slavery. and There’s a huge body of work that is very theoretical. about
12:12.31
Jon
Right.
12:13.29
Lauren
what you should and shouldn’t do with that information and who should and shouldn’t do things with it, right? And then you have someone like Xiao who’s… been instilled in sort of. best practices in visualization design and
12:25.75
Jon
Mm hmm.
12:26.49
Lauren
the goal of clearly communicating a single, you know, like there’s, you know, and there’ there’s almost sort of conflicting disciplinary perspectives.
12:34.07
Jon
Yeah.
12:34.35
Lauren
And. everyone is bringing their own perspective to the table. And then my job is kind of to try to merge those perspectives so we end up in a place where we all either see what see what we believe.
12:51.63
Lauren
visualized or were sort of converted to the other perspective.
12:52.93
Jon
Mm-hmm.
12:55.62
Lauren
And I think it goes in both directions, right?
12:57.53
Jon
Yeah.
12:57.45
Lauren
Where I think. you know And for some people. especially dealing with a lot of this 18th century data, which sometimes is of things traded.
13:08.03
Lauren
um but other times is of people who are traded right like there’s very much uh
13:10.85
Jon
Right.
13:13.57
Lauren
pretty core principle held by a lot of people in the humanities that just is like You don’t touch that. That’s irredeemable data. right? Like there is nothing good that could come out of trying to
13:21.21
Jon
Right.
13:25.06
Lauren
re sort of re and plot.
13:27.37
Jon
Mm-hmm.
13:27.46
Lauren
these numbers that were the first step in the process of turning people into. saleable goods right like that’s just a dead end um and many people in the field like that is a like no one will question you if you say that but just so like you’re right yes and to to a large degree like i
13:34.46
Jon
right
13:40.65
Jon
Mm.
13:43.45
Lauren
I feel that very deeply.
13:45.34
Jon
Mm hmm.
13:45.52
Lauren
um And then on the other hand, you have people like, of which I’m also a part, right? Which is like, you can always learn something about data. Like visualization is so cool.
13:52.64
Jon
Yeah.
13:53.44
Lauren
There’s gotta be something. that we can do with this that is generative, that lets us understand.
13:56.89
Jon
Mm hmm.
13:59.45
Lauren
this. really troubling time. with a little bit more nuance that makes us pause and think that sort of inflects our own choices going forward. And so that was that was sort of what I was trying to do with that particular visualization. was and Yeah. yeah
14:15.33
Jon
Yeah. I mean… it is It is an interesting question to think about. how And maybe you didn’t have this in your group. But. how people might disagree about i mean not just Yes or no the binary question But even as you get deeper into the design aspect.
14:34.41
Jon
At what point? Because you talk a lot about. power and hierarchy and you know who who sort of writes the history and i can imagine within any subset of people working on a visualization like the ones that are in the book saying we shouldn’t do this or we should do it this particular way. And I mean, I can imagine tensions and emotions getting pretty high.
14:53.68
Lauren
Yeah, you know, I mean, I will say like our group is a pretty good group. And I think part of the benefit of working on this project for a really long time is that we were almost never in a rush, right?
15:02.16
Jon
Mm.
15:03.88
Lauren
And actually, I do feel this as someone who does a lot of of work across. technical spaces and I like I write for technical conferences and then I also write books that take 12 years right like I do think one of the values in humanities scholarship in general is that there’s never a conference deadline you can always push things I mean it’s both ah a feature and a bug right but like
15:11.34
Jon
Yep.
15:21.49
Jon
Yeah. Yeah, yeah yeah yeah
15:24.32
Lauren
You know, if you haven’t yet come to consensus, you can be like, well, we haven’t reached consensus. We’re not done yet. Right.
15:29.47
Jon
Mm-hmm.
15:29.19
Lauren
And I will say that. um we I would say that the… Not as much in that chapter. And there was that we did a chapter on indigenous that has to do with indigenous mapping.
15:41.14
Lauren
And that was the one that I think was a little bit harder for the group because we had and no indigenous team members.
15:41.35
Jon
Mm hmm.
15:47.45
Lauren
And if there’s like one thing that you know about indigenous data sovereignty, it’s like you must do this.
15:47.62
Jon
Hmm.
15:50.51
Jon
Yeah. Yeah. Right.
15:52.16
Lauren
in collaboration with and led by the people whose data you’re working with.
15:53.67
Jon
Yeah. Yeah.
15:56.71
Lauren
And. it was that I left the chapter for last. It’s the middle of the book, but it was the last one I wrote. and um Because I knew that if you were telling sort of a counter history of data visualization, there needed to be.
16:09.56
Lauren
space held to tell the story of indigenous mapping practices because they are so robust and everywhere and are the obvious counterpoint to these sort of
16:12.72
Jon
Mm hmm.
16:17.87
Lauren
dominant accounts that we’re getting, but you know, the team was what it was. and
16:22.42
Jon
Right.
16:22.95
Lauren
you know I really believe in taking people’s perspectives and experience seriously. um And I think. Probably had I started the book… from the beginning.
16:35.01
Lauren
Later, I might have been a little bit more intentional in who we had brought into the project. But because my collaborators were students who sort of showed up their first year being like, I heard about your research group on the internet.
16:40.11
Jon
Right.
16:45.65
Lauren
Do you have a job for me?
16:46.44
Jon
Yeah.
16:46.92
Lauren
You know, like I didn’t.
16:47.72
Jon
Yeah.
16:48.13
Lauren
you know I mean, I hire students.
16:48.68
Jon
You didn’t go choose people. They kind of chose you.
16:50.01
Lauren
I didn’t go choose people, right? Like they, you know, it’s a, it’s an educational context.
16:51.48
Jon
Right. They chose you. yet
16:53.41
Lauren
They chose me, right?
16:53.87
Jon
Right. Yeah.
16:54.87
Lauren
um
16:55.05
Jon
Yeah.
16:55.77
Lauren
And so for so for a really long time, you know, we were like. Is this… what do we do with this chapter should we you know like There was data.
17:06.15
Lauren
there There is geodata, you know, like we we all know how to make a map, you know, like we could do it.
17:08.45
Jon
Mm-hmm.
17:11.43
Lauren
And some people thought, you know, like, should we try it? Is there a way to? Maybe we can sort of reclaim it in some way. And then other people were like, absolutely not. Hard no. This is my red line and we should not cross it.
17:23.97
Lauren
and um
17:24.87
Jon
Hmm.
17:25.69
Lauren
You know, we even, we… we sketched a lot of things. As you say, we, Tanvi, the sort of the main art designer who went to art school on our project, who begins her processes a lot just by sketching.
17:36.87
Lauren
Like she would sort of sketch things out and then bring them to the group and be like, I don’t want like. And we’d be like, these are beautiful. And she’d be like, I don’t think I don’t want to use these. Like, no, we’re not going to use this design because this doesn’t feel right to me.
17:45.16
Jon
ah Right.
17:47.75
Lauren
um And so we really had to work through what. ah an ethical path. through that chapter would be. where all of us could feel comfortable.
17:59.38
Lauren
signing our names to. the end product.
18:01.29
Jon
Mm-hmm.
18:02.10
Lauren
And I feel like that’s the…
18:02.83
Jon
Right.
18:04.88
Lauren
Like for me, that’s always the question. It’s like when this is out in the world, if you’re on a podcast, you’re standing up in front of a room and someone says, why did you do this?
18:13.30
Jon
Yeah.
18:13.57
Lauren
Like. You need to have an answer.
18:15.26
Jon
you you’re Right.
18:15.80
Lauren
And the answer could be…
18:15.82
Jon
You need to be able to defend it.
18:17.41
Lauren
You need to be able to defend it. The defense could be like…
18:18.78
Jon
Yeah.
18:20.16
Lauren
I’m not sure that this is the best thing that we could have done, or maybe I would have done it differently, but you can’t just stand up there and be like, oh, good question.
18:22.57
Jon
Yeah.
18:26.52
Lauren
I never thought about that, right?
18:28.17
Jon
or Or you can’t.
18:28.41
Lauren
And so I wanted.
18:29.35
Jon
Okay. Well, I mean, I don’t know how you how you feel about this, but How I would guess that you can’t get up there and say, well, I actually think we did the wrong thing here. Right? Like that.
18:42.34
Jon
I mean, it seems like, you know, you kind of have ah as a as a collaborator, as a co-author, you kind of have ownership of it.
18:42.54
Lauren
Like, yes and no.
18:48.48
Jon
And I get that there are disagreements, but. you know before the thing goes out in the world i think you sort of either implicitly or explicitly say This is what. We’ve agreed on.
19:00.20
Jon
Like there’s a little bit of like, like that’s not, let’s not.
19:00.26
Lauren
Yeah, and I would say yeah
19:03.39
Jon
Let’s not. Let everybody behind the curtain. to all of our disagreements on things. Thanks.
19:07.100
Lauren
Yeah, that’s exactly it, right?
19:09.18
Jon
Yeah.
19:09.13
Lauren
It’s like you never want to be in a situation where you need to throw someone else on your team under the bus.
19:13.39
Jon
Yeah, yeah, yeah.
19:13.66
Lauren
right? like I think it’s like you know like it’s like, if my name is attached to this, can I describe this collectively and be like, we discussed this, we thought we thought about this or the other thing, and in the end, this is what we decided.
19:14.43
Jon
Right.
19:20.18
Jon
Yeah.
19:25.45
Lauren
And interesting, interesting like Catherine and I did this too.
19:26.09
Jon
Yeah.
19:27.41
Lauren
like The last thing that we did before we sent Data Feminism to the printer was that there were a couple of sentences where we’d gone back and forth and the two of us had different ideas. And like the last thing we did was to go through them one by one and be like, if my name is attached to this sentence.
19:37.14
Jon
Mm hmm.
19:42.57
Jon
Mm-hmm.
19:42.59
Lauren
you know, is this okay? right
19:44.31
Jon
Yes.
19:44.67
Lauren
And.
19:45.05
Jon
Right.
19:44.100
Lauren
If it’s not, then we we had to dial it back or say something different. But, you know, if it’s like, well.
19:49.16
Jon
Right.
19:50.52
Lauren
like maybe I wouldn’t have quite used those exact words, but it’s fine. You know, like then that’s kind of, you know.
19:54.64
Jon
Right, you’re right. Right.
19:56.61
Lauren
and I think that’s really important.
19:56.78
Jon
Or, or… Yeah. Yeah. And also to your, I mean, I think to your original point, like someone asked you the question and say. Well, this may not be the best solution, but this is what we…
20:07.05
Jon
fought. at the time or even now is. I mean, is there ever a best? I mean, especially with some of the content that you’re talking about, right? Like, I don’t know if there is ever a best solution to using data about selling people.
20:22.30
Jon
Right. So you like.
20:22.83
Lauren
Yeah.
20:24.25
Jon
you know, it’s it’s a solution. It’s a solution to a bad. Bad data set, I guess, might be the… way to put it i don’t know
20:32.97
Lauren
Yeah, but I mean, I guess in a way that sort of, I almost feel like one to one of the…
20:32.93
Jon
um
20:37.92
Lauren
main contributions that I wanted to make. which is another thing that comes from the humanities which is the fact that like In the humanities, if you study history or if you study almost anything,
20:51.45
Lauren
A lot of it is bad, you know, and just because
20:53.51
Jon
Mm-hmm.
20:54.95
Lauren
Things were bad in the past doesn’t mean that you can’t learn from it or that you learning more about it makes you bad.
20:59.25
Jon
Right.
21:02.18
Lauren
right? And I almost feel like in certain tech spaces, when people are confronted with
21:02.50
Jon
Mm-hmm.
21:08.19
Lauren
evidence of a thing that is bad. there’s sometimes an impulse to be like, oh i should just walk away right like that’s it’s untouchable like that that’s such a terrible thing i it’s so separate from me and where i am either because of
21:15.34
Jon
Mm hmm.
21:22.55
Lauren
time or like who I am or what job I have or whatever like let’s just leave that over there and
21:29.13
Jon
Mm hmm.
21:29.88
Lauren
You don’t really have that choice in the humanities, because if you want to be able to learn something new about the past, you need to You need to sit with like, I mean, this is what Donna Haraway calls staying with the trouble, but like you need to sit, like sit with some really heavy stuff.
21:42.58
Lauren
And then ask yourself what you’re going to do about it. and
21:45.42
Jon
Yeah.
21:45.88
Lauren
you know both in terms of… technology and just in terms of my sort of humanistic scholarly practice. I am really someone who… likes to push myself to ask like how do I go through like how do I move forward
22:01.54
Jon
Mm hmm.
22:01.57
Lauren
um And I feel like in like I’m but having a lot of soul searching. about this with respect to AI right now, because the people like the on the people on the side of refusal, like full-on refusal.
22:12.15
Jon
Mm hmm.
22:12.19
Lauren
I. I understand that. Like, I understand and respect.
22:14.35
Jon
Mm hmm.
22:16.46
Lauren
that stance and I’m asking myself, like is AI the limit case for my general ethos, which is like there’s got to be a path.
22:23.33
Jon
Yeah.
22:25.05
Lauren
Like even if it’s narrow. There’s got to be a path through.
22:26.90
Jon
Yeah.
22:28.75
Lauren
And i I don’t, I mean. at least once a day with some new ridiculous headline and like, like maybe not, you know.
22:35.49
Jon
Yeah. Right, right. Um, Okay, so I want to ask about… um the visualizations in the book and i i wanna ask two questions of you so you can sort of pick. But I also wanted to say that. I think ah your book and my Better Data Visualizations book, as far as I know, are the only data viz books when they include the Menard.
22:58.02
Jon
Napoleon Marchograph, also include the top panel. on Hannibal’s march to the Alps. So I was very satisfied to see that because I don’t think most people know. that that menard graphic is like the way tufty shows it’s sliced off it’s like sliced half that page is lost so i was really happy to see that um okay so
23:17.91
Jon
I want to ask about. Like the conceptual thing and then the and then the practical piece, which is how did you go about choosing the visualizations you did choose to include and redesign in the book? And then also… because I’m actually in the process of doing this now. like What was the… um process of getting the high resolution images to include in the book because that is not as always as easy as it sounds.
23:43.82
Jon
Just like go download the Playfair thing and you’re good to go. So maybe you can start with like why these particular graphs and then we can talk about the the practical piece of it.
23:53.90
Lauren
Yeah, so it’s such a good question. um i would So each chapter has sort of a core image. And if you think of and the reason why that.
24:00.23
Jon
Mm hmm.
24:01.92
Lauren
is true is because in the humanities when you write a book the structure of the book is that there are four or five chapters And each of the chapters has a central text or image or artifact or whatever.
24:12.64
Jon
Yeah.
24:13.63
Lauren
And when I.
24:13.59
Jon
Yeah.
24:14.49
Lauren
conceived of this book I was only, I was in my second year of being an assistant professor. Like I, I didn’t know that there were other ways to do things.
24:24.94
Jon
Mm-hmm.
24:24.92
Lauren
And I had actually thought this would be the first book I would ever write. It would be the book that would get me tenure. And pretty shortly after that, i it became clear that there was no way I was going to finish that in time.
24:33.72
Jon
Yeah.
24:34.12
Lauren
so i had to so So I think you know one of the interesting things is I wrote the i rewrote the introduction. towards the end. And I rewrote the introduction. as a more mature scholar.
24:46.56
Jon
Mhm.
24:46.58
Lauren
And as I was writing it, I was like. Oh, I wish that I could do this all again and make the chapter is all like this.
24:51.56
Jon
Hmm.
24:54.06
Jon
Mm hmm.
24:54.05
Lauren
um But on the other hand, I do think that there is value and there’s especially value for people who are not familiar with that. form of research. to see what you can do with. one thing.
25:07.22
Jon
Mhm.
25:07.03
Lauren
Right.
25:08.04
Jon
mm-hmm
25:07.93
Lauren
Like you can get a lot of meaning out of a single.
25:08.77
Jon
For sure.
25:11.29
Lauren
image and so i actually so i go back and forth um
25:12.24
Jon
Yes.
25:15.63
Lauren
But that’s, it is what it is. But like how I picked them, you know, some of them were images that I. knew I wanted to talk about. you know i knew i i I sort of felt like I had to talk about Playfair because that’s where I started.
25:29.22
Lauren
And that started as the first chapter and it moved to the second one because I…
25:29.40
Jon
Mm-hmm.
25:33.19
Lauren
At a certain point, I didn’t want the book to be so. connected to this dominant history. um But I just felt like there was so much more to say about. Those charts then. people had said.
25:44.40
Jon
Yeah. Right.
25:45.31
Lauren
um Same thing with the Elizabeth Plummer Peabody charts. Those are probably the first charts that I saw. that like blew my mind that I’d never seen before.
25:53.27
Jon
Hmm.
25:53.54
Lauren
And I thought they were so weird and beautiful and captivating and I had no idea what they meant.
25:58.57
Jon
Yeah.
25:58.60
Lauren
um And so I knew I wanted to talk about those. um You know, i the the other ones. You know, like you sort of…
26:09.94
Lauren
you do some thinking about what you think the important… strains of the argument are and what the images are that can help you tell that story.
26:21.24
Lauren
the best.
26:22.69
Jon
Mm hmm.
26:22.93
Lauren
And for me, They have to be images that are visually striking. um that can sort of stand on their own as images.
26:33.25
Lauren
they need to be able to sort of expand when you place them in the context of their time. There needs to be sort of new things that you learn when you say like, who was making this?
26:40.37
Jon
Mm hmm.
26:43.93
Lauren
What was going on around them? How does this connect to? the broader political forces that were playing out at the time like that needs to you you sort of need to either see that in the image or see how the image changes when you know that.
26:56.78
Jon
Mm hmm.
26:58.02
Lauren
um And then I also thought a lot about… who was making the images and what perspectives those people might have brought to their own practice. like you know i’m not gonna lie you know if you look at the heroes of Data visualization, it’s all…
27:18.28
Lauren
mostly British Scottish and some French dudes you know
27:22.37
Jon
Right.
27:22.74
Lauren
um
27:23.02
Jon
Right.
27:23.61
Lauren
you know, and like. There’s a lot more people in the world making visualizations all the time um who are not.
27:27.04
Jon
Yeah. Great.
27:28.17
Lauren
you know, like from that pretty small, isolated geographic area. In this project, you know, again, it could have been. It. It never was going to be a visual history of like everyone who ever made a visualization in all places of the world because
27:40.72
Jon
Yeah.
27:42.99
Lauren
I believe in disciplinary expertise and my own expertise is the sort of Anglo-European 17th, 18th, 19th century.
27:49.31
Jon
Mm hmm.
27:50.02
Lauren
So i like I know a lot about that.
27:50.96
Jon
Right.
27:52.21
Lauren
But even within that space, I was like.
27:52.39
Jon
Yeah.
27:54.82
Lauren
I want to be very intentional about sort of shifting the spotlight onto these different types of people who are representing different constituencies. who were making visualizations at that time.
28:06.08
Lauren
That’s why there is the chapter about Indigenous mapmaking where I focus on
28:06.68
Jon
Mm.
28:11.18
Lauren
a Beothuk woman named Shana Dithit who made these really interesting and fraught series of maps in and the late 1820s. It’s why I have a chapter on Du Bois but I actually don’t talk about Du Bois as much as I talk about his students because I feel like that’s really the
28:25.12
Jon
Mm hmm.
28:27.07
Lauren
untold story of those charts. um In a way, I actually feel like it’s a little bit tricky.
28:29.46
Jon
Mm-hmm.
28:32.57
Lauren
like It’s convenient that we now know about Du Bois’ charts because he’s another great man who just sort of gets slotted into the like hero narrative.
28:37.02
Jon
Yeah. Yeah.
28:38.72
Lauren
And it’s like, no, he like he had a whole bunch of students who probably actually, a whole team, you know?
28:39.47
Jon
Yeah. A whole team, right? Yeah.
28:44.08
Lauren
um and And likely the only reason why he was able to…
28:44.47
Jon
Yeah.
28:47.26
Lauren
make all those charts in time. was because he had a whole team of people working on it together, right?
28:50.98
Jon
Right. Did you as you were sort of sketching out or outlining? the argument and the structure of the book. Um, Did you find that?
29:02.76
Jon
You… it You had… um an idea of the visualization or the or the creator. That would. be the best representative for each one? Or were there ones where you had like Du Bois?
29:16.95
Jon
Playfair. The slave map, the this the the slave map, like all those are kind of like. Um, you know, kind of like in the back of, I think, your head, my head, like, you know, if you’re thinking about these things, these are the ones that kind of pop up, right? Were there ones that you ended up using in the book that you, you know, kind of discovered in the process of? of writing and and developing the the the project.
29:42.38
Lauren
Yeah, there’s um there’s a whole bunch. like I ask myself that question a lot. and in many you know in many ways my focus on sort of the people right next to the founding fathers is kind of how I was trained to do my own scholarship you know and I think it’s I’m a artifact of my own time you know in
29:54.75
Jon
Mm hmm.
29:58.94
Jon
Yeah.
30:02.67
Lauren
I went to grad school in. like the 2000s, the first decade of the 2000s.
30:07.30
Jon
Mm-hmm.
30:08.79
Lauren
And that was like the first wave of the corrective to dominant accounts.
30:09.25
Jon
Mm hmm.
30:12.92
Lauren
And so what we were taught to do was like.
30:13.34
Jon
Mm-hmm.
30:14.89
Lauren
Look in the room. of the famous people and see who else is in the room right and now multiple generations later people are like we don’t even care about that room like that’s not where the decisions were like
30:18.99
Jon
Mm hmm.
30:24.77
Lauren
you know we’re we’re all interested in this other place right but anyway so i feel like my impulse my personal impulse.
30:25.33
Jon
Yeah. Yeah.
30:30.79
Lauren
is to That’s sort of how I approach things. But there were these people who I encountered over the course of my research.
30:33.20
Jon
Mm-hmm.
30:37.41
Lauren
Where I was like, oh. If I were starting from scratch, would I have focused on them? And one of them, for example, is france Francisco de Caldas, who’s this Colombian naturalist who Alexander von Humboldt essentially stole the idea for the…
30:42.68
Jon
Yeah.
30:50.40
Lauren
chimborazo mountain diagram with the elevations like
30:53.60
Jon
Oh.
30:54.24
Lauren
literally stole it from like they were roommates um when they were both doing their naturalist voyages and Kaldas has these sketches in his notebook that predate Humboldt
30:54.29
Jon
Yeah. Yeah. Huh?
31:05.64
Lauren
um that are exactly the same.
31:07.57
Jon
Hmm.
31:07.49
Lauren
and called us he he they’re in pencil with watercolor they’re incredibly beautiful um They’re held both in Colombia and also in Madrid. And.
31:17.29
Jon
Mm hmm.
31:18.11
Lauren
Like. no one knows about this guy.
31:20.59
Jon
Right.
31:20.50
Lauren
And I’m like, if we’re going to valorize, they’re like, Alexander von Humboldt. as this person who fused you know naturalism and visualization, biological data, like, like He literally stole this idea from this other guy.
31:33.70
Jon
I stole it. Yeah.
31:34.83
Lauren
you know like he literally and the they at like the We have the receipts, as they say, right?
31:35.45
Jon
Right.
31:38.68
Jon
Yeah. Yeah.
31:39.39
Lauren
And so like, there could have been a chapter on that, you know, I really feel like the one missed opportunity that even would have been. um in line with my sort of my general view, I don’t have a chapter on Florence Nightingale. I feel like that would have been a really good way to get into the close connection between statisticians and the eugenics movement.
31:59.14
Lauren
And she sat uncomfortably close to that.
31:59.61
Jon
Mm-hmm.
32:02.32
Jon
Mm-hmm.
32:02.16
Lauren
And I feel like that story has not been told. And then there’s also like, I, you know, most of the archival research I did. was in the United States on the East Coast and archives that I knew from my own training.
32:12.39
Lauren
And so they just have.
32:13.02
Jon
Yeah.
32:13.87
Lauren
all these obscure Sort of. mid 19th century. big giant charts that are so weird you know and most of them
32:23.17
Jon
ah
32:24.29
Lauren
like Most of them are about like our great country. like A lot of them are about the founding, about the presidents, about wars.
32:29.78
Jon
Mm hmm.
32:31.69
Lauren
um And, you know, there’s. like totally bizarro and illogical and also fascinating like vines and snakes and
32:39.24
Jon
Yeah.
32:41.99
Lauren
you know whatever um And I wish that I had pushed myself a little bit more to. uplift some of them. and And for a while, actually, of the million times I rewrote the intro, one of the ways that I so tried to start it was just to pick three of my favorite Totally Weirdo charts and just be like…
33:00.61
Jon
Mm hmm.
33:01.02
Lauren
You could start with this one. Here’s a reading of this.
33:03.00
Jon
Yeah.
33:02.97
Lauren
You could start with this one. Here’s a reading of this.
33:04.22
Jon
Yeah.
33:04.38
Lauren
You could start with this one. But then I felt like it was almost. too arbitrary. Right. And I did because sort of anchoring like.
33:09.85
Jon
Yeah.
33:13.06
Lauren
Really trying to say there’s an established history here, like major geopolitical events were happening. At the time that…
33:21.62
Jon
Right.
33:22.56
Lauren
data visualization or a sort of modern European-centered data visualization was emerging that were totally…
33:26.17
Jon
Modern yeah. Right.
33:31.05
Lauren
the running in parallel courses with
33:33.68
Jon
Mm-hmm.
33:33.97
Lauren
what we only have taken to be just the… charts themselves. Like, it was so important to me that I be able to present sort of like overwhelming evidence that this was the case that
33:43.91
Jon
Yeah.
33:44.25
Lauren
I found myself re reverting to the. images that had the richest, most powerful evidence attached to them, which tended to be people who are already to some degree, like central.
33:52.23
Jon
Right.
33:56.39
Lauren
to these stories.
33:56.37
Jon
Sure.
33:56.83
Lauren
So a person like Playfair, a person like William Clarkson.
33:59.29
Jon
Yeah.
33:59.69
Lauren
that’s it
34:00.12
Jon
Well, it just it just leads to the the to the sequel to the book. That’s all.
34:03.77
Lauren
Right.
34:03.75
Jon
You’ve got, you know, another 12 years to write the the right the next one.
34:03.97
Lauren
I know. I know. Oh my God. Oh, my God.
34:08.05
Jon
um So I do want to ask about getting the the images. And this may be only… ah Maybe no one else really cares, but I’m always curious about this. about this part. So.
34:20.63
Jon
Um, What was that process? like I mean, I’m guessing some of these are relatively easy to get from online. library catalogs. you know at least you know a lot of the stuff that i guess library of congress they have a lot of the stuff but like Um,
34:36.34
Jon
How many… Did you have to go to like the original source and. find it and scan it or photograph it like what what was that What was that? process.
34:47.87
Lauren
Yeah, I mean, so… This project is so old that my first images from my first archival research trip, I took with a digital camera because I don’t think I had a smartphone.
34:57.24
Jon
Huh?
34:57.92
Lauren
And so I actually have these images and I had a Zotero database.
34:58.98
Jon
Whoa, wow.
35:03.06
Lauren
And so when I first went, I would take these pretty rough. images of everything that I saw and attach them to the metadata entry from the light from the library the archive and then take notes and if there was a pdf version if there was a book i was so i had this big
35:11.69
Jon
who
35:18.14
Lauren
personal database. um And so with some of those archives, you just need to go back to them and say. Like, hey, here’s the catalog number. Could you scan this for me? And it does take some weeks or months and you usually need to pay them.
35:28.28
Jon
Mm hmm.
35:31.10
Lauren
I mean, the thing is, I i knew from having done a…
35:31.93
Jon
Yeah.
35:35.24
Lauren
you know, old school monograph. Like this is the process that all. historians use.
35:40.04
Jon
Yeah.
35:40.52
Lauren
um And I knew it would take time. And I, for the most part, accounted for that. But there were definitely a couple that fell through the wayside where we thought we had high res versions or a lot of things that would happen. There were so many different.
35:53.32
Lauren
versions of a lot of these charts and we’d sort of have this placeholder image and I’d sort of forgotten that it was a placeholder and then I’d be like oh we can’t use the third edition because I’m actually talking about the first edition and then or like the other thing is because a lot of these are hand tinted or um
35:55.36
Jon
Yeah.
36:04.84
Jon
Yeah.
36:09.78
Lauren
you know even like early lithography the colors change and in some cases or they just fade and in some cases i was like Oh, I really want. the version of the chart that this archive has, like the Peabody charts, for example, um I ended up using the Internet Archive version of them, even though I have incredibly high res scans from the library company in Pennsylvania, just because the Internet Archive colors are so much better, you know, at least like in the year 2026.
36:23.71
Jon
Mm-hmm.
36:33.76
Jon
oh yeah
36:35.82
Lauren
I don’t know. Like… which library they got them from but their preservation methods um either
36:39.59
Jon
Yeah.
36:42.24
Lauren
before the book got into their control or after just meant that like I liked it better and there’s an image on the back cover of the book
36:47.51
Jon
Right.
36:49.65
Lauren
um where we were gonna swap it out with the higher res version and then in the end i was like i don’t i don’t want to i like the other ones i like them better no but i mean i guess like but it’s a long way of saying that And I actually think it’s important for people who don’t deal with old stuff to know is like you feel like everything is out there on the Internet and you feel like the.
37:09.91
Lauren
image that you download is going to be fine. But…
37:12.83
Jon
Yeah.
37:13.91
Lauren
there’s so That’s not true, actually. And there are a lot of situations in which you need to go to a real expert who’s…
37:16.38
Jon
Yeah.
37:22.79
Lauren
you know an institution even that has devoted its work to the preservation of these and of these original artifacts. And actually in one of the um
37:30.58
Jon
Right.
37:32.89
Lauren
I think in the Playfair chapter, we actually include an image of the high-res scan that we got from the library company of the specific version of the Playfair chart, including like the color bar and the geo-rectifying edges on the side, because I sort of wanted to make the point that…
37:43.77
Jon
oh
37:46.80
Jon
Yeah.
37:47.88
Lauren
like It’s not like we just press download from Wikipedia. you know like
37:51.92
Jon
Right.
37:52.36
Lauren
there was a person who we who
37:52.87
Jon
Yeah.
37:54.60
Lauren
carefully put this in their very high-tech scanner and sent us a
37:55.95
Jon
Right. Right. with the white gloves and the and the whole thing.
37:59.83
Lauren
Yeah.
38:00.55
Jon
Yeah.
38:00.82
Lauren
Yeah. Well, no, you’re not supposed to use white gloves, actually, because apparently it makes your fingers too clumsy.
38:01.36
Jon
um
38:05.23
Lauren
And they’ve discovered they’ve done studies and they discover that. If you balance out like human oils as long as your hand are clean versus the clumsiness that happens if you try to touch books and gloves, it’s actually better to touch it with your oily fingers.
38:16.37
Jon
Yeah.
38:19.76
Lauren
than a clumsy white glove because you’re less likely to crack the pages.
38:19.93
Jon
Wow.
38:23.42
Jon
Okay, so now I need to go back an episode in in Widow’s Bay and tell the ah the librarian in that in the historical society not to use the…
38:24.55
Lauren
Yeah.
38:32.87
Jon
The glove set.
38:32.90
Lauren
Oh, that’s on my watch list.
38:34.43
Jon
Yeah, okay.
38:34.31
Lauren
I’m only just catching up on my shows now that the book is at the printer.
38:37.40
Jon
right as that right as the semester starts you get to catch up on shows so okay um
38:40.89
Lauren
Peace. I sometimes watch them on the treadmill.
38:43.90
Jon
Oh, there you go. Okay, there you go. Okay, so I have… um a couple of Um, sentences I pulled from the book. And I want to read them to you, and I just want to get your…
38:56.85
Jon
You know. more insight onto these, um because these are the ones of many that that just struck me that I was highlighting as I was i was reading. um Okay. All right, so here we go. So here’s the first one.
39:09.15
Jon
By placing each map or chart that we encounter in its particular context, we absorb a fundamental truth that visualization is only as powerful as how and by whom it is put to use. Um,
39:20.01
Jon
So I just want to get your… Expanded thoughts. on that Because i think I think that’s a good…
39:23.69
Lauren
Okay.
39:25.99
Jon
For me. a ah really good encapsulation of the book.
39:29.39
Lauren
Yay. that’s my that’s like my the like the nut like That’s like the sentence that I, that was from the intro.
39:33.87
Jon
There it is.
39:35.87
Lauren
And when I wrote that, I was like, that’s it.
39:36.47
Jon
Okay.
39:37.99
Lauren
That’s what I want to say.
39:38.47
Jon
Okay.
39:39.86
Lauren
So i it makes my heart fill with.
39:40.01
Jon
Okay.
39:42.25
Lauren
ah I don’t know, relief? leisure and relief no but like but that i mean but but really i mean that’s like that’s really i i believe that so strongly and i hope that people who read the book will
39:46.93
Jon
Yeah, yeah. Okay, good.
39:55.86
Lauren
come to see how this is true, right? It’s like anyone can design a visualization of anything for any purpose, but… you know It is. real i it It is like a fundamental truth, I think, that…
40:10.12
Lauren
You only activate the power of visualization when you ask yourself like. Why am I doing this? What are my goals here?
40:15.81
Jon
and
40:16.42
Lauren
Who am I designing this for? And if you and if you do answer those goals. You can be incredibly persuasive and you can make an… a incredibly captivating image and if you don’t like you’re missing out or worse you might
40:30.43
Jon
Yeah.
40:31.45
Lauren
convince the wrong people or convince people of the wrong thing, right? um and so yeah so that thank you thank you for that that’s my favorite oh That’s my favorite sentence in the book, I think.
40:37.73
Jon
Okay. All right, awesome. Great. Star that one.
40:41.09
Lauren
Okay.
40:41.58
Jon
Okay, here we go. Number two. This is maybe a little out of context because it starts with the… a ah word but but That’s okay. Okay. But from the charts in this book will emerge evidence of the opposite claim, that complete objectivity is an illusion, that context and power always enter in.
40:58.63
Lauren
Ooh, you’re a good reader because this is a sentence that I tweaked in page proofs, which they hate you to do because like the, you know, the type is already laid out and they’re like, don’t add a word that bumps it to the next line.
41:04.59
Jon
They hate it. They hate it. Yeah. Yeah. You got to worry about reflow and.
41:10.39
Lauren
I know, I know.
41:10.56
Jon
Yeah.
41:10.99
Lauren
But I, I actually, I. I struggled over this because what I was trying to say, what I believe is to be true is like. Nothing is truly objective because things are all created by people in a context and you need to take that context into account.
41:27.96
Lauren
You can be looking at data, but someone scoped the data collection.
41:29.05
Jon
Mm-hmm.
41:32.81
Lauren
you know Someone decided what you’re counting and what you’re not. you can be looking at a chart that is trying to show you Only what matters. But someone decided. what they thought matter is there like when the you know the x axis should start in and like those are the things that i mean You know, like you’re never looking at.
41:50.13
Lauren
something that is just outside of the conditions that created it.
41:56.32
Jon
Yeah.
41:56.35
Lauren
However, I’m very sensitive to the fact that we live in a world in which people don’t believe in science and knowledge and expertise.
42:08.51
Lauren
And the word that I added at the end was complete.
42:13.34
Jon
Mm-hmm.
42:13.08
Lauren
objectivity because initially, and I think rhetorically, it sounds better to say that objectivity is an illusion. Um,
42:19.06
Jon
Hmm.
42:20.14
Lauren
But I really didn’t want this to be misinterpreted as… like anti-science or um somehow a view that it was pointless to not pursue objectivity and this is something that comes from like feminist science studies but this is the idea that we of course are always pursuing the goal of objectivity but it’s almost like an asymptotic goal right like we’re never going to get everything.
42:32.34
Jon
Right.
42:43.04
Jon
Mm-hmm. Get there. Yes.
42:45.05
Lauren
but we can always learn more. right and sort of the more you know
42:46.84
Jon
Mm-hmm.
42:48.88
Lauren
the more you can either you can assess the objectivity of what you know, and the more you can sort of create conditions of sort of composite objectivity. Because you’re saying like, oh, now that I understand about the person who was collecting the data, then I understand like.
42:56.73
Jon
Mm hmm.
43:02.42
Lauren
why they chose this and not that. And then I can go find that other thing that was missing and bring it in. And then I’m have more, a more objective perspective, you know? um So anyway, so yeah, so that that like it’s a tricky line.
43:13.98
Lauren
I think that it is true, but I I worried about saying it because I because of the time that we are in.
43:22.20
Jon
I see. Okay. Um… I see that but I still… to me, it rings it rang rings true. So, but I get the point about where we are in this moment in history, but. but Okay. Okay, one more for you. um And this one I think is from chapter one.
43:42.52
Jon
So this one rang true to me, especially because in the book that I have coming out later in the year, we really focus on the people behind the data. and this really had Had your book been out a few months ago, I would have… quoted this in my book, but um ah my proofs are.
43:58.77
Jon
basically done. So, okay. All right. ah More basically and more profoundly, these diagrams, which which I think are referring to the slave ship diagrams, these diagrams remind us that before there is data, there are people, people who contribute to the production of data and people who themselves become data, not always with consent.
44:16.76
Lauren
Yeah. I mean, this is another, um, I you’re not. Like every time you read over your book, you’re like, oh, God, I really like this is the thing that people are going to read.
44:22.23
Jon
Yeah. All right, all. Yeah I know I know
44:26.06
Lauren
And my name is on it, you know? And like, I was definitely at that moment.
44:27.33
Jon
I know.
44:28.94
Lauren
So this is, it’s making me feel good because this is another line that I like. I mean, so this is a line where I was trying to, so with the the example here is. both historical visualizations of the data of the slave trade. that were designed in their own time Amen.
44:42.76
Lauren
in order to try to convince people to get on the side of abolition but then also um our project team, as we were discussing earlier, decided to take that same dataset or related dataset and see what we could do with it in the present.
44:54.53
Jon
Mm hmm.
44:55.15
Lauren
Um, But I think what I was trying to do here is to say, you know This lesson that there are people behind the data and you need to think about what they contributed to the data, whether they wanted to contribute to that data.
45:08.72
Lauren
And I mean, both like people who collected the data, but also who themselves might have just been counted. Right. um Like it’s not just a lesson that applies to.
45:14.03
Jon
Mm hmm.
45:17.10
Lauren
the worst of historical circumstances like what i did what i was hoping was that and what i try to do throughout the book is to say we’re looking at these incredibly resonant examples because they’re very powerful examples But the lessons apply to everything, right?
45:32.43
Jon
Mm hmm.
45:32.08
Lauren
like even when you’re just like making a like you know plotting the like what viz did i make today like my strava data recorded my jog today in the park right you know like there’s always like any chart that you’re looking at always has people behind it and
45:40.60
Jon
Yeah.
45:43.72
Jon
Yeah. Right.
45:50.18
Jon
Yeah.
45:51.54
Lauren
you can always learn something when you ask yourself like
45:53.95
Jon
Mm.
45:55.73
Lauren
who made this, who’s in it, who’s being counted. who’s not being counted. You know, like I, you know, I think a lot about like like the Strava heat maps, you know, which I use all the time, but it’s like.
46:06.86
Lauren
Those are made by people just like me.
46:08.83
Jon
yeah Yeah, right.
46:08.72
Lauren
You know?
46:09.99
Jon
Right.
46:10.35
Lauren
Well, now AI.
46:11.06
Jon
Yeah.
46:11.01
Lauren
Actually, they replaced him with AI, which I’m really grumpy about because they’re not they’re no longer made by people just like me.
46:12.02
Jon
No, yeah. Yeah. ah
46:16.03
Lauren
But yeah, no but I mean, that’s the point, though, is it’s like, you know, you the the the question is prompted. by an example where you can’t not ask that question.
46:26.18
Lauren
right?
46:26.51
Jon
Mm-hmm.
46:27.22
Lauren
And that’s why I began with that one.
46:27.91
Jon
Right.
46:29.29
Lauren
But the point of the book is to say. just because it’s not necessarily an obvious question to ask of any chart. Doesn’t mean that you shouldn’t ask it. And actually, I think that. It gives you better ideas about how to design visualizations.
46:40.01
Jon
Yeah.
46:41.74
Lauren
differently and more truthfully and more creatively if you’re thinking about how your data came to be. so
46:49.14
Jon
Yeah.
46:49.34
Lauren
Yeah.
46:50.79
Jon
Terrific. Okay. I love it. I think that’s a great place to to end on. I wanted to ask. Um, what I mean, obviously people can get the book wherever they get their books. um But there is an online.
47:03.34
Jon
companion. right Or there’s an online version of the book, I think. um that people can sort of play with the visualizations.
47:08.02
Lauren
Yeah, there’s an online version.
47:10.10
Jon
Yeah.
47:10.41
Lauren
Yeah, it’s dataxdesign .io and we’re in the process of updating it for what I hope will be the final time. It contains like a condensed version of the text that’s in the book.
47:23.11
Lauren
um It’s probably like 30 % shorter.
47:23.17
Jon
Okay.
47:25.26
Lauren
And so.
47:25.90
Jon
Okay.
47:26.68
Lauren
It. is a little bit faster paced. There are some details that I ended up cutting just because no one likes to read a long thing on the internet. But very crucially, it has interactive versions of all the visualizations.
47:35.01
Jon
Yeah.
47:38.03
Lauren
So the book is mostly screenshots or things were redesigned from the web to print, but this was a native web.
47:38.02
Jon
Right.
47:44.90
Lauren
project. and so some of the coolest things like we do a lot of scrollytels and like zooms and simultaneous text and image especially in a lot of the process parts so people can check it out it’s free
47:46.08
Jon
Right.
47:51.88
Jon
Mm-hmm.
47:57.63
Lauren
And. And it’s teachable. that’s what i wanted that but I wanted that one to be teachable.
48:02.01
Jon
Yeah. That’s great.
48:02.91
Lauren
Yeah.
48:03.49
Jon
um And where, if people want to… get you on their podcasts, or if they want to join your lab for the next 12 years for the next book, what’s what’s the.
48:13.14
Lauren
Yeah.
48:15.74
Jon
What’s the best way to get in touch?
48:18.22
Lauren
Okay, so be careful what you wish for speak coming from someone who took like nine years to get a PhD.
48:20.14
Jon
Yeah.
48:22.93
Jon
Yeah.
48:26.15
Jon
Yeah.
48:26.31
Lauren
I’m online. ah not Not very, but like… sort of, um, elkline .com. Uh, I work at Emory university. My email is there.
48:36.72
Lauren
And of course, like the last thing to ever be updated is my lab groups website. It exists from like 2015. Um, but it does have probably, hopefully like a working email address.
48:47.90
Lauren
so
48:48.56
Jon
Okay. awesome well i’ll put those on the show notes people can check it out Lauren, congrats on the book. It looks great. um And I’m sure it’s going to do great. And yeah, thanks for coming on the show.
48:59.48
Lauren
Thanks for having me. I’m so excited for your book too. I’m going to go pre-order it now.
49:02.17
Jon
no thanks yeah
49:03.50
Lauren
Yay!
49:03.65
Jon
Yeah. Thanks a lot. Okay. Thanks.