In this week’s episode, I chat with Dietmar Offenhuber about his new book, Autographic Design and the concept of autographic data analysis. Dietmar stresses the significance of recognizing the material origins of data and the influence of extraneous variables. He advocates for a qualitative approach that pays attention to data traces, which can uncover deeper narratives. In our conversation, we explore what is meant by autographic design and urge a wider lens on data to grasp multifaceted problems thoroughly. Additionally, Dietmar’s work underscores the interplay between qualitative and quantitative methods, emphasizing the role of subtlety and conjecture in data interpretation to bring a more nuanced understanding of the stories behind the numbers.

Topics Discussed

  • The Material Context of Data Collection. We dive into why understanding where and how data is collected is paramount for accurate analysis. We talk through a number of examples in Dietmar’s work and book.
  • The Impact of the Third Variable. We explore how the introduction of a third variable can dramatically shift the interpretation of data and data visualizations. We discuss the importance of being vigilant for these variables to avoid erroneous assumptions.
  • Unintentional Digital Traces. Our conversation uncovers the value of unintentional digital traces that we leave behind and how they can be a gold mine for analysts.
  • Qualitative Meets Quantitative. We discuss the need for blending qualitative insights with quantitative research and how they can complement each other to provide a fuller picture of analysis.
  • The Speculative Nature of Data Analysis. We address the inherently speculative aspect of data analysis, highlighting the fact that, despite the numbers, much of what analysts do involves informed guesswork.
  • A Call for Collaboration. The discussion opens the floor for collaborative efforts, emphasizing that the best results often come from pooling knowledge and expertise across different fields.


Guest Bio

Dietmar Offenhuber is a designer and urban planner in the College of Arts, Media and Design at Northeastern University in Boston. He was educated as an architect in Vienna, Austria before receiving a MS and PhD at the Massachusetts Institute of Technology. His research focuses on the relationship between data and design in social contexts. Dietmar is the author of the award-winning monograph “Waste is Information” (MIT Press) and has published books on urban data and accountability technologies. His new book “Autographic Design – the Matter of Data in a Self-inscribing World” examines material visualization practices and the production of evidence.

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for the spring, summer, and fall semesters. Welcome back to the Policy Biz Podcast. I’m your

01:26 – 01:32

host, Jon Schwabisch. Have Have you ever thought about different ways of working with data and

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what data means in different contexts? So how you might download data from some website or some

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resource, or how you might actually collect data in running your own survey or through a Google

01:44 – 01:49

form, or how you might see data out in the world and the number of cars that pass by your office

01:49 – 01:55

on on any given day. Well, in this week’s episode of the podcast, I talked to Dietmar Offenhuber

01:55 – 02:02

about his new book, Autographic Design, The Matter of Data in a Self inscribing World. It is

02:02 – 02:09

a fascinating look at how data can be different. The way we think about data, the way we work

02:09 – 02:14

with data, the way we visualize and communicate data. And what you’re gonna hear in this week’s

02:14 – 02:20

episode of the show is just a really unique take on what it means to collect, analyze, and work

02:20 – 02:25

with data. And I think if you can think about data in sort of a different way and take this

02:25 – 02:31

into your everyday work, even if you are downloading data from the Census Bureau or the World

02:31 – 02:38

Bank or the IMF, wherever it is. I think we can take a more holistic and truer sense of what

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data means in our day to day work. So here is my interview with Dietmar Offenhuber, the author

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of the new book, Autographic Design. Dietmar, good morning. How are you? Good to meet you.

02:52 – 02:55

Hey, John. Good to meet you. I’m, glad to be on the show.

02:55 – 03:02

This is this is great. I’m very excited. There is this whole sort of move around data physicalization

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these data, and I had recently had some of the editors from the making with data book on the

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show. And then I think Sam Huron was at a talk with you, and I saw, like, the piece of your

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talk on autographic design. I was like, woah. Woah. Woah. There’s more, and it’s like a different

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angle on it. So I’m very excited. Thank you so much for sending me the book. I was telling you

03:23 – 03:28

earlier before we started, I I moved it to my Kindle so I could read it. And I took all these

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notes and had to move it back to my desktop so I had it in front of me so I could, like, you

03:32 – 03:36

know, copy, like, highlighted text into other things that I’m working on. So I wanna talk about

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the book. I thought we would start with with introductions, you know, where you are, what you’re

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doing, what you’re working on, in addition to autographic design, and then we can we can talk

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more about the book.

03:47 – 03:56

Sure. Sounds good. Perfect. So, I’m yeah. Dietmar from my background is in architecture. I,

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but I, you know, studied architecture in the nineties when the field was in a big crisis because,

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you you know, computers will disrupt everything. And nobody actually believed that architecture

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actually will exist, in 10 years. So at that point, everyone was, you know, all my colleagues

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were doing all kinds of things on the Internet and, with digital form experiments and so on.

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And then I actually also dropped out to work for Oselektronika, which is like an institution.

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But at some point, I decided that I I actually wanna finish and I wanna, you know, work more

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on cities and urban environments. So I finished up and then did a, PhD in Boston, on on urban

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planning and urban studies. So this has always been my interest, having this kind of, you know,

04:46 – 04:56

art visualization, cities, and and data. Mhmm. Yeah. Now I’m teaching and, department chair

04:56 – 04:57

at Northeastern University.

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And you’re teaching in the urban planning department?

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As well. So Northeastern has this thing where they always have these dual appointments where

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you are appointed in 2 places. And one of one of it is, yeah, public policy, which is the planning

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Right. Program and, art and design. And at art and design, I I’m mostly in data visualization

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and Right. Design theory. I do wanna get to the book, but

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So do you have students who are in both of those programs? Do you see them balancing between the 2?

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I mean, absolutely. So it’s we we have this PhD that focuses very much on interdisciplinary,

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modes of research and, you know, students do visualization and urban studies or Yeah. You know,

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game science and mental health and things like that.

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Right. Right. Wow. Kind of the way you need to be these days, like interdisciplinary work. Yeah.

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Okay. So let’s talk about the book because I think for me, I think I’m probably like probably

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like most people. You see the title Autographic Design, just those words, and you’re like, what?

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But then you see some of the images that are in the book. You’re like, oh, okay. This is something

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I wanna dive into about. So let’s start with defining autographic design for folks, and then

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we can kind of make our way through. Yeah.

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Yeah. May maybe I should give a little bit of history because, like, I’ve been working on the

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topic for a long time. And, originally, we called it, indexical design focusing on this kind

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of semiotic theories. But that, you know, people got really, you know, like, what what is that

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supposed to mean? And it’s also I found it a little bit too limiting to only look at it from

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a semiotic perspective. Mhmm. So, autographic design as a field didn’t exist before, but the

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term autographic has been used by several theories such as, Matthew Kirschenbaum, who who, you

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know, distinguished between allographic and auto graphic arts. The ones that are really focusing

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on material traces and the others that are purely based based on, you know, data on the score,

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let’s say, musical composition and Mhmm. And so on. So the word autographic means self writing

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or self inscribing, and many things inscribe themselves in the environment. You know, think

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about tree rings or traces in the snow. We can look at them as visualizations, as a record of

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what has taken place. And the goal of autographic design is now to treat these traces as as

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data and make them legible as visualizations. And, you know, those could be either traces that

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already exist that only need to be properly framed through design operations or also to create,

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the conditions that let new traces to emerge. You know, so if you put a trace of substance in

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the water to see, you know, where the the streams are going and things like that.

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Right. So it’s it’s interesting because I think a lot of it feels centered around the environment

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and living things. But reflecting back on the very beginning of this interview, thinking about

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urban design, a lot of people describe cities as living, breathing entities. So how should folks

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think about data having these traces when it’s not necessarily a living thing like a tree or,

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you know, a a water system, but it is something that humans maybe have built, but it has these

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this sort of still living feature

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to it. I mean, I don’t really distinguish between whether something has been, you know, human

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made or whether something is, you know, natural environmental. But, you know, if if if if you

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distinguish maybe that’s a useful distinct distinction to distinguish between the symbolic world

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where you only have abstract information versus the physical world. And in the physical world,

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regardless of whether to talk about what humans have made or or natural phenomena, you know,

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as as Matthew Christianbaum says, there are never 2 things that are exactly alike. You know?

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Yeah. Everything, every process leaves countless traces. But in the symbolic world, of course,

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we can have, you know, perfect copies of a digital file and so on. But of course, you know,

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the digital file is also in physical trace at some point. You know, like, if I drop the hard

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drive, I will lose.

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So could you talk about just to maybe, for folks who are listening or or watching, an example

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of a of a project that you think sort of embodies this idea of of traces? Mhmm.

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I mean, since, you know, I’m I’m looking out the window here and I see a little snow now in

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Yeah. Boston. And, over the last 10 years, in I think this started in New York with, Clarence

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Eccleston, Street Films director. And, they they started recording vehicle traces in the snow

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as a way of advocating, for more space for, pedestrians and cyclists. They’re basically making

10:41 – 10:47

this argument. I mean, look. You know, if if the cars are driving as they should within the

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speed limit, a little bit more careful because it’s snowing, then they don’t need so much space.

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They rarely come close to the sidewalk. There’s so much space that could be recaptured. Yeah.

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And so so so this is I mean, of course, you know, physical traces in snow have been already

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used by urban designers more than a 100 years ago or described in books, such as Camillo Sitti

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wrote about snow to figure analyze traffic. But but the the argument here is slightly different

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because today’s transportation planners, you know, they work with data. They work with, GIS

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models and so on. And in order to join that discussion, you’re supposed to be able to master

11:35 – 11:43

these tools and use all these advanced abstract forms of representation. Right. But what what

11:43 – 11:48

these guys are doing is the opposite. They are basically just pointing to a natural trace and

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say, explain this. You know? Yeah. So they’re basically shifting the conversation, Jon their

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own experiential territory.

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Mhmm. When I started reading your book, I came into it with, in the back of my head, the sort

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of data physicalization literature and also a bit of the data art literature. And I think there’s

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a pretty strong overlap between those 2.

12:14 – 12:14

Mhmm. And

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so can you I think that example does a really good job, but maybe for for folks who aren’t sort

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of as familiar with these concepts, maybe distinguish between these different concepts or different

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projects that people are pulling together.

12:30 – 12:35

Sure. So, I mean, first of all, I don’t wanna be territorial here because I think data physicalization

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and data art are very often autographic, and there are a lot of artistic practices that focus

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on metreality, on physical Yeah. Faces and so on. But but I think the the biggest difference

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is this underlying idea of data, what constitutes data. And data visualization and physicalization,

12:58 – 13:03

they start with this with a data set. You you know, you can’t do anything if you don’t have

13:03 – 13:11

a data set. You’ll then translate it into something that can be, you know, contemplated. But

13:11 – 13:16

autographic design is different because it ends with data. You you start with the phenomenon

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itself, and, you you make it legible. And as you do this, you end up with something that, you

13:25 – 13:32

know, comes close to a digital data set. So you are preparing the phenomenon in a way that it

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it can be, you know, made legible as data. Right. So, I mean, I can also say that in many autographic

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visualizations are measurement devices or vice versa. You know, if you think of a seismograph

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or a meteorological instruments, they make the process of measurement experiential Mhmm. And

13:57 – 14:03

also accountable more accountable than, let’s say, digital sense that it just gives you a number,

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at the end, but you don’t have any context for that number.

14:06 – 14:15

Right. I guess the struggle I have with the data physicalization work that people do is it feels

14:15 – 14:24

more exhibitory, where it is often I collected my data Jon my habits, or I have this data and

14:24 – 14:29

I made a sculpture or I made a this, or I made a that. And, you know, sometimes it’s interactive,

14:29 – 14:34

but but a lot of the examples that you see out there are, you know, the kind of one that you

14:34 – 14:39

you don’t see a lot now is people, like knitting a scarf of weather patterns in their in their

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neighborhood. But but the autographic design seems feels different to me, and maybe it’s because

14:45 – 14:50

of of the data piece, but it I don’t think it’s that simple. I don’t feel like it’s that simple.

14:50 – 14:51

Maybe it’s just a feeling.

14:51 – 14:59

Yeah. No. I mean, I think what I I started just with an observation of how all these controversies

14:59 – 15:06

in in our world today Mhmm. How do they present themselves if you look at, you know, climate

15:06 – 15:12

change or misinformation or, you know, environmental pollution, environmental justice, and those

15:12 – 15:18

kind of things. It’s rarely about the interpretation of data. It’s not that someone creates

15:18 – 15:23

a visualization and then someone else says, well, but, you know, this visualization is is not

15:23 – 15:29

correctly, you know, emphasizing this aspect, which, of course, can also be the case. But very

15:29 – 15:36

often it’s about the origin of data. You know, people would say, well, that data is not valid

15:36 – 15:42

because and, you know, if you think about data collected by amateurs, that’s very often the

15:42 – 15:48

response. Oh, you didn’t use these these instruments. It’s not, you know, how how do I know

15:48 – 15:55

if I can trust the data? So what I observe is that a lot of these activists or or citizen scientists

15:56 – 16:07

use kind of autographic methods just to, put the data collection process itself to debate rather

16:07 – 16:14

than the interpretation in terms of visualization. But, of course, there’s only one part of

16:14 – 16:21

it because the other part is then how do you discuss the results. And and I think this is maybe

16:21 – 16:28

where physically physicalization and autographic design are, again, a little bit more similar.

16:29 – 16:35

Because what what I see as the the biggest advantage of data physicalization is, like, you put

16:35 – 16:40

something on the table. You talk about it. You have a kind of a conversational situation. You

16:40 – 16:57

can explore it together. And it’s not so much about, you know, brushing discussion, and and

16:57 – 17:03

and and focusing on that. And, yeah, this is, I think I mean, as an educator, I also see just

17:03 – 17:10

students are always gravitate to to these analog modes of of of collecting data. And and it

17:10 – 17:13

has that appeal because it, like, you know, grounds the experience.

17:13 – 17:17

Do you think that’s because I mean, I I totally agree with you. I mean, I I think there’s something

17:17 – 17:25

about the tangible, you know, at least in the, you know, touching the the marble in the in the

17:25 – 17:32

column or the block to build the thing. Do you think that is inherently our nature, or is that

17:32 – 17:39

have something to do with sort of a pushback against the digital world in which we’re all in,

17:39 – 17:40

like, all the time?

17:42 – 17:46

I mean, it’s very interesting question, and maybe it’s a little bit of both. I mean, one of

17:46 – 17:53

my favorite papers from long, long time ago was Andrew Vander Moore’s against the tyranny of

17:53 – 18:01

the pixel. This was, I think it’s almost, like, 20 years ago now. So this this sentiment that

18:01 – 18:12

the screen is limiting us is is very old. And but but I I think part of that sentiment is also

18:12 – 18:20

the way how we make sense of things. I mean, for me, this very big revelation was, during COVID

18:20 – 18:25

when suddenly everyone became paranoid about touching things. Mhmm. And that made us realize

18:25 – 18:33

how much we actually touch things. Yeah. Yeah. And, so we we we started that autographic, research

18:33 – 18:41

project where we are trying to understand how people are touching data sculptures or data physicalizations

18:42 – 18:48

in order to make sense of them by by covering those with a kind of a powder that that registers

18:48 – 18:58

traces of of touch. So so, I think and and the answer is not simple. I mean, people touch and

18:58 – 19:05

physically engage with information in so many different ways. And maybe that’s that’s the path

19:05 – 19:13

that is a little bit in the in the nature. Yeah. You know, Barbara Tuetsky and other, psychologists,

19:14 – 19:20

talk about how gestures are so much part of our thinking. They’re not just a presentation or

19:20 – 19:23

something like we we think with our hands.

19:23 – 19:24


19:24 – 19:30

Whether we are sketching or whether we are, you know, touching or Yeah. You know, fidgeting around.

19:30 – 19:37

Right. Right. But but the other part of it, you you you sort of alluded to it, I I think is

19:37 – 19:46

kind of embedded in this is a in some ways, a rethinking of what data are or what data Yeah.

19:46 – 19:52

And and how and so so when you work with either your colleagues or with students, like, what

19:52 – 19:53

are those conversations like when you are discussing, like,

20:01 – 20:12

Yeah. I mean and maybe this is a result of, our, you know, just the success of digital technology

20:12 – 20:18

that when we think about data, we think about, like, digital file or spreadsheet or something.

20:18 – 20:18


20:18 – 20:26

But, someone who works in the social sciences or, you know, works with collects data from interviews,

20:27 – 20:34

We know that it’s a little bit more complicated. And, there are there are many different forms

20:34 – 20:41

of data that people use in their daily practices or scientific or professional contexts that

20:41 – 20:50

are not like, digital records. And, you know, you you you can if you want if if you want definition

20:50 – 20:57

of data, you can go all in the, you know, philosophical realm and just say, okay. Yeah. Kind

20:57 – 21:02

of the minimum difference between two things and 2 states and so on. But that doesn’t really

21:02 – 21:08

help you that much in your practice. And in your practice, it’s very contextual. You have archaeologists

21:09 – 21:18

for whom, a artifact that they pulled out from the ground is data. So, so you you don’t necessarily

21:20 – 21:28

rely on the translation into some form of symbolic record. Even though you could define data

21:28 – 21:35

that way, you could say, okay. It’s a it’s a record, but it’s not a universally agreed, way

21:35 – 21:41

of defining data. And the way how I define data is really through these environmental traces.

21:41 – 21:45

They are, for me, a material form of data. Mhmm.

21:46 – 21:51

So there’s the very interesting sort of conceptual nature. And I will say, for me, I think I

21:51 – 21:56

read the introduction of the book maybe, like, three times because I read it twice to start

21:56 – 22:01

to sort of get my head around, like, what are we talking about with autographic design? Then

22:01 – 22:07

I read the rest of the book and, you know, it it does put the theory sort of into practice.

22:07 – 22:11

You see all these different projects. The car is driving in the snow is, like, a a great example.

22:11 – 22:16

I I that one I have I have, like, that whole chapter bookmarked. But then I went back again

22:16 – 22:22

to sort of, you know, kinda crystallize it in my head. And so so my my question is for, I think,

22:22 – 22:27

for probably most people listening to this, I’ll certainly put myself in this bucket of working

22:27 – 22:33

with, as you mentioned, digital data, spreadsheets, databases. How should we think about this

22:33 – 22:37

concept of autographic design in our day to day work?

22:38 – 22:43

Mhmm. So there there are many different ways how we can, I mean, on the one hand, it’s it’s

22:43 – 22:51

really just an invitation to think about data differently? And this has very, very real implications,

22:52 – 23:00

because as I also explained in the book, digital data are also autographic in some sense. You

23:00 – 23:08

know? If you have Jon the one hand, you know, seismograph with the chart drum, the data is the

23:08 – 23:16

trace on the on the chart drum. On the other hand, you have, let’s say, a digital device that

23:16 – 23:23

writes a data on some storage medium. Mhmm. It’s conceptually the same thing. There are just

23:23 – 23:30

a couple of more steps involved, in the digital form. So so the digital dataset is also autograph

23:31 – 23:37

is also a literal physical trace. This is not just a metaphor. It’s it’s a literal trace. Yeah.

23:37 – 23:44

And why do we then need the concept of autographic design if everything is a trace? Yeah. But

23:44 – 23:53

but for me, the answer is that, it it allows us to, look at data differently. It allows us to

23:54 – 24:00

analyze things that we otherwise would not be able to analyze. So this has very practical implications.

24:01 – 24:05

In the book early on, I gave this example. My dogs have seen a squirrel.

24:09 – 24:11

There’s there’s a trace right there. Right?

24:11 – 24:20

I mean yeah. Yeah. They’re very excited about this. So, just to give you an example, I early

24:20 – 24:26

on, I have this, you know, it’s a popular data set, the the taxicab data set from New York where,

24:26 – 24:32

you know, you have, millions and millions of pickup and drop off points as as points. And if

24:32 – 24:40

you just plot them all, on a on a plane, you you see, unsurprisingly, a map of New York that

24:40 – 24:47

is very accurate. But then you notice that some area a little bit blurry. And, people usually

24:47 – 24:54

have a hard time explaining this, but, of course, you know, it is it is just the the GPS signal

24:54 – 25:05

that is, interfered by tall buildings. So you you have to understand the material background

25:06 – 25:12

of how GPS works. Mhmm. And then suddenly, you have a third variable. You know, it’s no longer

25:12 – 25:18

just x and y. Suddenly, you have information about the height, about the three-dimensional shape

25:18 – 25:26

of the, of the city, which has inscribed itself in kind of unintentional ways. So now if I’m

25:26 – 25:31

a, you know, let’s say, very traditional data analyst, I would, you know, remove all these because

25:31 – 25:37

they are not accurate, and I I want a certain threshold of accuracy in order to get a good,

25:38 – 25:46

you know, result for my analysis. But, if I look at those as physical traces, I will, you know,

25:46 – 25:51

I can get additional things out of it such as the three-dimensional shape of the city. And there

25:51 – 25:57

are many, many examples like that where we have all these latent, unintentional, accidental,

26:00 – 26:07

traces that are inscribed in our digital data. So so this is, you know, like, a very, forensic

26:07 – 26:12

perspective, but I I think it’s it’s very useful. And and a lot of people in the data field

26:12 – 26:14

are very attuned to this.

26:15 – 26:25

Yeah. Well, it it is interesting because it is not like we are we being, you know, sort of your

26:26 – 26:32

your your average practitioner. Right? It’s not like we are I guess, the autographic design

26:32 – 26:37

to my mind is not so dissimilar from the work that we do every day and the work that we see

26:37 – 26:43

every way is just is like a different perspective on interrogating our data. Right? I think

26:43 – 26:49

about you you talk, I think it’s kinda towards the middle end of the book on the early, in the

26:49 – 26:54

early part of the pandemic with the, with the with the flatten the curve. I mean, we all saw

26:54 – 27:00

that graphic, and that that has traces all around it. Mhmm. But maybe that’s not how many people

27:00 – 27:06

sort of think about data when they get started. They don’t have that perspective.

27:07 – 27:13

Yeah. I mean, the pandemic had so many examples of this. So there was this at one point. The

27:14 – 27:22

the case counts were kind of capped, just because the fax machines that were still used to,

27:23 – 27:28

transmit the the numbers from the previous stage just couldn’t handle more couldn’t handle more

27:28 – 27:34

paper. So we have this kind of, you know, materiality again inscribing itself into the datasets.

27:35 – 27:42

And Yeah. So there there’s this so this is this one maybe what what could be called it, like,

27:42 – 27:48

a different state of mind about data that pays more attention to the material context of data.

27:49 – 27:58

But then Jon the other hand, like, to be very, practical in terms of the how this can be used.

27:58 – 28:06

If we go back to the bicycle activists in New York Mhmm. For them, autographic strategies are

28:07 – 28:16

a very, yeah, straightforward way of making claims about evidence. And it’s kind of interesting

28:16 – 28:23

because you’re asking the recipient or the viewer to piece it together yourself. You you just

28:23 – 28:30

lay out things. You don’t tell them the solution. You you give them different parts. And this

28:30 – 28:35

is, I think, also what is a third thing that is maybe really useful for database practitioners

28:36 – 28:42

because traces are about stories. You know, you’re we make sense of traces Mhmm. By kind of

28:42 – 28:48

hypothesizing what may have caused them and then putting things together from various angles.

28:48 – 28:54

So there’s always a trace narrative. So there are these kind of I don’t wanna be, like, you

28:54 – 29:00

know, positivistic and say, okay. Those traces are evidence. Yeah. Yeah. You you cannot, you

29:00 – 29:06

know, dispute that. In in reality, it’s very rhetoric. You know? Like, it’s it’s very rhetorical.

29:06 – 29:15

You are, guiding the your listener to your viewer, through these kind of trace narratives. Mhmm.

29:15 – 29:20

It’s also interesting because one of the arguments I’ve made in other projects I’ve been working

29:20 – 29:25

on is is for and you mentioned this earlier about qualitative data, data, but I’ve been making

29:25 – 29:30

this argument quantitative researchers or analysts of which I would consider myself. Certainly,

29:30 – 29:37

my training background is in quantitative methods need to be more qualitative in in in some

29:37 – 29:42

ways to actually talk to in in my line of work, right, talk to people and talk to groups and

29:42 – 29:46

communities to find out what the actual experience is. The data don’t always tell the full story.

29:46 – 29:52

And I think, for me, that’s where I’m sort of pulling in this this concept of autographic design

29:52 – 30:01

that it rounds out the a fuller story of what it means to, again, in my line of work, what it

30:01 – 30:07

means to be, you know, need programs to support food and security or to support people with

30:07 – 30:14

disabilities. There’s a broader story and only a broader perspective on data can we really understand these issues.

30:15 – 30:20

Yeah. Because, you know, someone has to come up with metrics how to measure food insecurity

30:20 – 30:27

and things like that. But it manifests in so many different ways. And and in each way in each

30:27 – 30:34

station, there are probably some kind of traces or indications that we can point to and then

30:34 – 30:40

that we can investigate. And, you know, I I don’t wanna put this into a kind of a dichotomy

30:40 – 30:45

between qualitative Jon quantitative. Because, like, you know, a qualitative course is about,

30:45 – 30:52

okay, what is it trying to figure out? What’s going on here? What what is the mechanism? What

30:52 – 30:57

is the story? But then a kind of a quantitative quantitative view also gives nuance because

30:57 – 31:04

it’s it’s no longer just categorizing things, but you’re showing intensities and degrees, different

31:04 – 31:11

degrees. You differentiate that very well, and that is also part of, autographic design. We’re

31:11 – 31:19

trying to Right. If you look at, all those chemical tests where, you know, piece of paper changes

31:19 – 31:24

color and then you have a scale and you compare it to, like, what is the color, which number

31:24 – 31:30

does that correspond to. So it’s Yeah. It’s all about measuring, quantities as well. Yeah. But

31:30 – 31:38

I think, ultimately, it it is this very speculative component that is I find very interesting

31:38 – 31:46

where you Yeah. Never basically treat data as just as a plain fact, but it’s always about this

31:46 – 31:50

possibility. You know? Like, what could have happened here and what could that mean and all

31:50 – 31:57

these different ways, how how, you know, those data could have been.

31:57 – 32:02

Yeah. Yeah. That’s a really interesting way to to to think about how the data could have been.

32:02 – 32:09

Yeah. So I wanted to just to just before we wrap up, I wanted to ask about maybe some of the

32:09 – 32:15

work that you’re doing now on autographic design, any, experiments or or studies that you’re

32:15 – 32:20

doing that are you you know, you’ve written this book on it, but actually, you know, doing a

32:20 – 32:21

kind of project around it.

32:22 – 32:33

I mean, for me, just doing very modest art design projects, was a way to also, further my thinking

32:33 – 32:38

about it. So it was not just a illustration. I say, oh, look. This is an example of what I’m

32:38 – 32:45

talking about. But this helped me clarify a lot of things. And, just right now, there are 2

32:45 – 32:53

different lines. One thing is really looking at plants as as visualizations and then, you know,

32:53 – 33:04

working with plant biologists. And I I think this was a, method that was brought up in the maybe

33:04 – 33:14

eighties or nineties by NASA scientist, Jack Fishman, using, plants as Jon indicators of, like,

33:14 – 33:24

a ground level ozone, which is a gas that is harmful, for pretty much all living beings, and

33:24 – 33:32

it also hurts, plants and you can observe it on plants. So, they’ve been putting together visualization

33:32 – 33:39

systems that consist of plants that are sensitive to ozone and different degrees. So beans and

33:39 – 33:45

tobacco and all kinds of things. So I’m interested in these kind of community practices of monitoring

33:46 – 33:54

environment, natural plants. There’s something at the door. So so and this is something I’m

33:54 – 34:01

still doing, especially looking at local impacts of climate climate change, to to figure out,

34:01 – 34:06

like, how does the environment change? Because we yeah. You know, the climate itself is an abstract

34:06 – 34:13

concept that Yeah. You know, I mean, narrowly speaking, climate doesn’t really exist in the

34:13 – 34:18

environment because it’s kind of average. But, what what exists are the kind of the local impacts,

34:18 – 34:23

and and we’re just trying trying to figure out the way how we can talk about those in a more

34:23 – 34:31

general way. And and so, this this is more kind of work where I’ve I’ve done some of, you know,

34:31 – 34:39

a project that I called ozone tattoo where I’m, creating almost like a map legend on plants

34:39 – 34:47

that show how kind of this kind of ozone damage and impact looks like. And this is something

34:47 – 34:57

I’m still doing with, you know, community groups and and biologists. And a second line of work

34:58 – 35:07

that I’m working on with Laura Perovich and Denise, who’s with, environmental, who’s experimental

35:07 – 35:15

psychologist. Here, we’re looking at how people use their sense of touch to make sense of data

35:15 – 35:22

physicalizations. And here, the autographic part is mostly a method of registering touches because

35:22 – 35:31

it’s it’s actually haptics. It’s a surprisingly still a very difficult topic for digital technology

35:32 – 35:37

even though in the nineties you had the first haptic interfaces, but, you know, they’re always

35:37 – 35:47

very fragile Yeah. And very limited. So, we are using basically a a tracer powder to to register

35:47 – 35:56

this that we can photograph objects Jon the UV light and fluorescence. So this is this is kind

35:56 – 35:59

of a very, analog way of registering

36:00 – 36:06

touch. Really interesting. So Autographic Design is the name of the book. Where can folks find

36:06 – 36:12

you if they wanna learn more, if they have an idea for a project, if they’re a community group

36:12 – 36:16

in Boston, they’re like, this is the guy we need. How can folks,

36:16 – 36:24

Yeah. Please reach out to me. I’m I’m easily findable Yeah. On the Internet. And, yeah, always

36:24 – 36:32

happy to to collaborate. And, I’m also just interested in also seeing what people are doing

36:32 – 36:38

that is somehow related without, you know, me making any claims about this. Yeah. I’m just curious. That’s

36:38 – 36:43

great. Dietmar, thanks so much for coming on the show. Really appreciate it. This was, fun and

36:43 – 36:48

congrats on the book. And, I’ll share all the notes for folks who Jon to read more and, yeah.

36:48 – 36:50

Thanks again for coming on the show.

36:50 – 36:51

Thanks, Sean. It was a pleasure.

36:52 – 36:56

Thanks everyone for tuning into this week’s episode of the show. I hope you enjoyed that interview

36:56 – 37:01

with Dietmar, and I hope you will check out his new book, Autographic Design. I hope you’ll

37:01 – 37:06

also head over to the PolicyViz website to check out all the show notes and all the links that

37:06 – 37:11

I put in there so that you can explore this and related work to your heart’s content. And while

37:11 – 37:12

you’re at it,

37:12 – 37:13

just take a moment out of your day.

37:13 – 37:18

If you wouldn’t mind, to go over to your favorite podcast provider and leave a rating or review

37:18 – 37:24

of the show. It helps me bring in new listeners, help me find more and more guests. So until

37:24 – 37:29

next time, this has been the Policy Biz Podcast. Thanks so much for listening. A number of people

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helped bring you the Policy Biz Podcast. Music is provided by the NRIs. Audio editing is provided

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