Kenneth Field is a ‘cartonerd’ with a Bachelors degree in cartography and PhD in GIS. A former academic who grew tired of admin, he ditched his 20 year career, moved to the US, and talks and writes about cartography, teaches, and makes maps at Esri. He has presented and published an awful lot. He blogs, tweets, after 8 years as Chair is now Vice-Chair of the ICA Map Design Commission, and did a 9 year stint as Editor of The Cartographic Journal. He’s won awards for maps, teaching, kitchen tile designs and his book, Cartography. He recently taught a MOOC to over 100,000 people on Cartography. He is co-founder of longitude.space and mappery.org. He snowboards, plays drums, and is a long-suffering supporter of his home-town football/soccer team Nottingham Forest.
Ken and I talk all things maps in this week’s episode–why he loves them; his favorites; his least favorites; and how we should think about them.
Featured image from the Swiss Society for Cartography SGK.
Kens’s book, Cartography
Ken’s blog, Cartonerd
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Hi, welcome back to the PolicyViz Podcast. I’m your host, Jon Schwabish. I hope everyone’s well, I hope you’re having a good kickoff to the fall. Apologies for the lateness of this episode, I decided to go camping with the family last weekend and that took precedence, because sitting around in open campfire is quite lovely even in Western Maryland where it was a little bit cool but we did have a good time. Anyways, I’m excited to be back and have a new episode for you. This time we’re going to be talking about maps. I’m really excited to have Kenneth Field on the show. I saw Ken speak at the Tapestry Conference last year. He gave an amazing talk about maps. He has an unbelievably great book, it’s like the treatise on maps, cartography – I’ll link to both of those in the show notes. You should really check out the book. I mean, it is a tome, but it is a beautiful book, and it really does walk through everything you really need to know about data driven maps. So Ken and I talk about this stuff that he’s working on now, the biggest challenge with data driven maps, his favorite map, his least favorite map – we sort of try to cover the broad range of what’s going on in the world of cartography all in one 30-minute conversation or so. So we try to pack a lot in. Before we get to the episode, just a quick note. If you’re interested in supporting the podcast, please leave a review on your favorite podcast provider, iTunes, Stitcher, Google Play, even Spotify now, the show is now on Spotify. If you’d like to support the show financially, please head over to my Patreon page, I support the show on my own with my handful of folks who are graciously supporting me and I’m really thankful that they take the time out and their funds to help me pay for transcription services and audio editing and web services and all the things that are needed to bring this show to you.
Also, if you are interested in attending a data visualization workshop, I have two public workshops left this year, I will be in Denver in early November and I’m teaming up with the University of Minnesota IPUMS’s team – if you don’t know what IPUMS is, you should check out the show notes page and you can learn more about it – it’s a combination workshop where I teach data visualization, they talk about how to use, download, and analyze the data from the IPUMS’s tool. So you really sort of get all the things you’ll need to download, analyze, and visualize your data. And then later in November, I’ll be in London to team up with my friend Stefanie Posavec who will be doing another one of our data design workshops in London. That week I’ll also probably be attending the Information is Beautiful Awards, I will also be giving a talk for SAGE Ocean, and both of those will be announced very shortly. I’m sure the Information is Beautiful Awards folks are about to announce their plans for their award show, and SAGE Ocean will soon put the announcement up for the talk that I’ll be giving there in London the week before Thanksgiving. And then I come home and I’m taking a few weeks off, we’ve got some big family events coming up here at the Schwabish household in Northern Virginia.
So anyway, back to the show with Ken Field, I hope you’ll enjoy this interview, I really enjoyed talking to him. I really enjoy learning more about maps and I hope you will too. So here’s my interview with Ken.
Jon Schwabish: Hey Ken, how is it going, how’s the wine down to your summer?
Kenneth Field: Hi Jon, yeah, doing good, beautiful weather out here, yeah.
JS: Lovely. It’s like in the high 90s here, and it’s like walking through soup when you go outside.
MB: Yeah, I mean, we’re in the 90s pretty much permanently over here until it hits triple figures for a Brit, that’s kind of a difference to sort of gray, cold, wet. I did 40 years of that, now I think I am going to do 40 years of this, and then on average [inaudible 00:04:00].
JS: Yeah, on average you get that [inaudible 00:04:02].
JS: So I’m excited that we are able to chat, I really like your talked from Tapestry last year, and I think I bought your book on my phone as you were talking. So I want to talk all about the book and about maps, but maybe we’ll just start by having you talk a little bit about you, your background, what you’re doing now, and then we can we can chat about some maps.
MB: Okay. I’m glad I found out finally who the person was that bought the book, that’s great, thank you. So that was fun, Tapestry was great. I like to challenge myself by going to conferences and events that are a little outside of my normal bounds. They’re sort of groups that you normally go to, and I guess that’s really characterized what I’ve always done. So I’m an ex-academic, I spent 20 years in the UK as a lecturer, principal lecturer, and leader of various GIS and cartography courses at different universities, and that was fun, that was great. I loved helping students develop their skills, and it’s so fulfilling to see some of them now in the industry doing great stuff themselves. I just sort of – the truth of the matter is I just got a little bored of all the bureaucracy and admin like a lot of academics do, and I had an opportunity to move out to Sunny California and kind of do an academic job at Esri, the GIS company in Redlands, Southern California, and have all the fun of being an academic and writing about maps and teaching and workshops and helping people who use the software make better maps. And I got to do all without having to grade course work and sit in endless committee meetings and bid for funding moneys to support some obscure piece of research that would never really get done. And yeah, I’ve been here eight years now, and I’m loving it, it’s great.
JS: That’s great. Is your role there to direct research and then train people both on general cartography skills and also in the tool itself?
MB: Well, you saw, I’d love that to be the case. But the truth of the matter is for a mapping company we have maybe, I don’t know, probably a dozen cartographic experts, people who would call themselves cartographers, and I guess I fit within that that bunch of people. But there is no sort of cartography unit, there’s no fundamental mapping core group of people. We’re kind of spread out throughout the company. I actually work on a team that’s responsible for the development of one of our core products ArcGIS Pro, and I work on what’s called the Map Authoring Team. So my job title is senior cartographic product engineer which is kind of, you know, I’ve never engineered anything in my life, and we have great developers who actually build the software. But what I do, along with a lot of others is help direct what they need to be building, and to define what map makers and cartographers want to be able to do with the software and how they want to be able to use it. And I guess, I’m sort of colloquially referred to in-house as the resident cartographer which sounds a bit tempery to me, but you have to – who’s next, who’s the next resident cartographer!
JS: Yeah, right, who’s the next guy, yeah, I was looking over your shoulder, yeah.
MB: But it’s good, because I can send help. I also get to – a lot of what I do in terms of making the maps is done really primarily to test the software to try to test it to destruction. So there’s a lot of testing that goes on in-house on small datasets and it’s a tick box thing, it passes the test, therefore the software is fit for purpose. But what I try to do at the same time is throw several gigabytes worth of stuff at the software and see if it passes those sort of tests, the tests of making a real map and going through a lot of the pain points that people would have to in the real world. And then the side aspect to that is obviously I can publish the maps, I can talk about them, I can explain how they were made and what the tips and tricks were, and in that way, it generates sort of educational products and stuff to support people in their own work.
JS: Right. Are most the people that you work with making those really data intense maps or is it on the other side of the spectrum where it’s not as data heavy, smaller data?
MB: I think at a company-wide level, it’s everything. I mean, the software supports national mapping agencies doing topographic reference sheets all the way down to just a small new shop who’s just got some interesting data about something, and they’re trying to create an interesting web map. And that’s sort of product range I guess falls across the entire spectrum. I tend to dabble in a bit of all of that stuff; sometimes, I’m keen to make a nice looking topographic map and to explore those sort of cartographic challenges; and other times, it’s like, how weird and wonderful can I corral this dataset into some bizarre visualization just as an experiment sometimes, perhaps just – I joke around here that I’m a bit of a 3D skeptic, but I’m forever trying to challenge myself to put data into a 3D view mode just to see whether it offers anything different or whether 3D brings something new or gives us new insights to something. So I can sort of shapeshift a little bit between the sort of mapping tasks that I take on, and what I’m really grateful for is the freedom and flexibility to basically pick my own tasks. So if a new dataset appears on the scene, I’ll grab it – let me see what I can do with it. I sometimes have challenges with some of our other guys here like John Nelson and we take down the same dataset, right what are you going to do with it John, what am I going to do with it, and let’s see how different people can approach the same thing. And that to me has always been a fascinating part of the job is you give a dataset to 10 different people and you will more than likely as not get 10 different outputs, 10 different maps, so maybe not even maps.
JS: Yeah. You have this great book on cartography and obviously spend your days working in and thinking in maps. What draws you to maps? I don’t actually know how I mean that question, but it’s not like people are like, oh I’m a bar chart person, I like bar charts. You know maps are sort of like this kind of separate thing because they are so complicated and there’s all these different representations. So what draws you to trying to unlock the mystery and the magic behind maps?
MB: What a great question! How long have we got? I mean, I think…
JS: I’ll just let you go. [inaudible 00:11:14] my headphones, I will come back in a little bit and see if you are still talking.
MB: You can grab yourself a coffee. So I can look at this on a couple of different levels. If I think about it personally, I grew up around maps, my father was a geologist and the house was full of these really bizarre abstract maps, like, what are these things, these geology maps. We’d go out and he’d knock bits of grey lumpy stuff off a cliff and then he’d go back into the university and suddenly it’s this bizarre multicolored thing on a piece of paper and it’s, well, how does that work. I think I was always enthralled with them, I enjoyed geography and art and technical drawing and so on at school, I looked for a degree course at university that would give me the opportunity to basically take those loves further forward, and that’s – by the way, I really wanted to be a surgeon, but I was terrible at chemistry, I never knew you needed chemistry to be a surgeon, but there you go. And then I felt architecture, but it’s like a seven-year course – I said, no, no, no, I want to earn some money before that. So these practicalities, and I found a course called cartography in the UK at Oxford Polytechnic as it was and it seemed to me to be a great way to spend another three years basically just doing what you enjoyed, and I kind of fell into it. I fell into the teaching aspect of it because just about the point at which I graduated, this thing called GIS came along and basically killed professional cartography. So those old office drawing labs, they all sort of went. So I fell into teaching and just ended up trying to infuse others to have that same passion.
So that’s on the personal side. I think on the why do people love maps question and why is it so interesting, I think, basically, they’re pieces of art. I think people always gravitate to art of some form or another, whether it’s film, music, painting, whatever it is. But even within each of those genres, we all have likes and dislikes. Some people like heavy rock music, some people like rap, two very, very different forms of basically the same thing. And you can see that parallel in mapping, you’ve basically got data that you can create something visual out of, and it creates an interesting visual system and an explanation of that data. And you can have very, very different representations of the same data which yields different impressions, different interpretations, and again, neither of which may be correct or incorrect but they are facets of the same visual conversation, and that’s me, it’s always interesting. So every day you come to work and you’re basically – you can create a new map. You’ve got a blank screen or a blank piece of paper – what are you going to come up with today.
Do you still work with pen and paper when you’re designing a map, even if it’s ultimately going to be on [inaudible 00:14:25]? Are you working in an analog world first to sketch out ideas?
MB: Yeah, I do. Maybe that’s a function of my age a little bit. I come from a hand-drawn cartographic era, that’s what I did in my university days, drawing and photographic film and negatives and print plates and all the other sort of stuff. And still now, I get a piece of paper out if I’m thinking of a new map and I just jot down ideas, sketching them not very well, but just visual ideas. I guess some people would do that digitally, some people might naturally go straight to digital, but I still think sketching out and wireframing and getting a whiteboard and just messing about, it’s a great way to think, and that’s where I think the art and cartography is. And what a lot of current maps, I guess, might be missing is that sort of time that you spend drafting and sketching and thinking rather than just going straight into your favorite software, dragging the data in, hitting a few buttons and seeing what the software can do. I prefer coming at maps, well, what do I want it to look like, and then how can I crack the software to make it do that, and it doesn’t always work.
JS: Yeah, but it’s interesting, and it doesn’t surprise me given that that’s where you started your training. But it is interesting how – it sounds like you take a bit more of… If you thought about making a data map and split into sort of a design side versus a data-driven side, it sounds like you start by coming from the design side a little bit more than the data side, and then move it together.
MB: Possibly. But I mean, most of the maps I make are data driven in the sense that, if the data changes, I can switch the new data in and re-render it and it’ll work. I was never one of these people who are satisfied with pulling data into something like Illustrator, making the map and saying there it is, because two weeks later it’s out of date and you’ve got to start again. But I think what that that kind of training did for me, and let me be clear, I wouldn’t want to go back to those days whatsoever. I mean, three months to make a single choropleth map is not fun, but what it made you do was really think very, very hard, because you’ve really only got one chance to do it, otherwise you’ve got to do two months’ worth of work again, and the cost of materials and time meant that you really didn’t have opportunity to screw up, you had to get it right, or as right as you could. I guess now, it doesn’t matter if you mess up inside your software, you just sort of [inaudible 00:17:23] you need that layer to rerun it or do something else again. So I think the element of time that has been compressed massively these days, I mean, it gives us wonderful opportunities because we can experiment and we can try things out and we can do all sorts of things and there’s no real great harm or cost involved. But yet if we’re setting out to make the map the best we can make it, that time spent sketching and thinking and working stuff out, I still think it’s critical, even though the technology is now massively improved and allows us to be much more rapid in our map making.
JS: Yeah. When I talk to students about maps, I sort of couch the whole thing or frame the whole thing as two competing instincts, I want to get your take on this. So on the one hand, people love maps because they are familiar, they see a map of the United States and they recognize it, and they can find themselves on the map and we know that people like to find themselves. But on the other hand, the data maps are not always the best way to actually show the data, so you have these distortions, the example that I always like to show which you have a bunch of these on your website is the electoral college where a lot of the big states and square miles don’t actually have a lot of people in them. So they’re not particularly important for the electoral college, so this is my perspective is that there’s this tension that people like maps but they are not always great at showing data, and to adjust one of those things, you have this offset on the other one. So I’m curious about your take on that and sort of an extension to that question is when you’re teaching people about how to make map, how do you start and frame this whole discussion about making data-driven maps?
MB: Yeah. I mean, you’re spot-on. I think there is a tension and I think it begins with the fact that we’re often making maps for people who have very little experience in how to interpret those maps. So they really rely on familiarity which is why you get a lot of the same type of maps a lot of the time. And talking about election maps, you will get a choropleth, you get the red-blue choropleths, you get the maps that people are familiar at looking at, hopefully, because that means they’ve got less of a barrier to interpret them correctly. So the problem comes then when you’re trying to use a dataset that’s a little bit obscure maybe or you’re trying to make a point that’s a little bit hard to tease out of the data and then maybe there’s nuance in the map that is difficult to find. So sometimes you exaggerate it, you modify the map to tell that story, you do things cartographically to really punch out that message and sometimes that can really knock people off balance because they expect one thing and then they’re challenged visually to try to see something they’re not familiar with and try to interpret it. So how do I start telling people how to do this effectively is it’s basically just to impress upon them, there is no right and there is no wrong way to make the map. So you’re making the map based on all sorts of choices and constraints which create this sort of soup, and out of that soup you’ve got a create – you’ve got to sort of pull out the map that is going to do that particular job for that particular user group, for that particular set of conditions and environments, and for that particular message and so on and so forth. And sometimes it might not be the map you think you’re going to make, and that’s okay. So it’s a perpetual challenge, it’s a perpetual tension, and I think the best thing that anybody making maps or data viz in general can do is step back from it and have an appreciation that the person that’s going to read that is going to read it a particular way. And we can mess around with graphics and graphic signage to tap into people’s sort of subconscious perceptual and cognitive characteristics, things that we know that the brain does that people aren’t necessarily aware of, but nevertheless that’s what it’s doing, and that’s how it’s making you read something. And we can do that and we can do that objectively or we could do it to make a persuasive map. We could play with those things in lots of different ways. But to be aware that that’s what we’re doing and to maybe step back from the map and ensure that you are meeting the objective you want for that particular user group. And experiment, because it’s very unlikely that the first map you make is going to necessarily be the best. I mean, there’s sort of maps I would default to as a quick and dirty test, but I’d probably try something different. And then there’s a whole spectrum of maps from the very simple to the obscenely complex and they can work in different ways, a proportional symbol map that’s going to go lovely in a report. But not on the cover of a book or a poster. You want something that’s a little bit more impactful. So you might go for something just a little bit more challenging visually.
JS: So when you’re going through that process, are you thinking about both the projection of the actual map and then to all these other classes of cartograms and objects and things we can put on the map because the projection thing is something that I kind of ignore, because it seems like a rabbit hole that I just don’t want to get into, but I suspect that it’s something that you and other people that you work with take it really seriously, and so how balance these two and make these decisions as you progress through a project?
MB: Well, I mean the projections issue is interesting. I think people are frightened about it because it’s fundamentally about [inaudible 00:23:36] and I balk at that, I don’t want to get involved with all of that. Well, I mean, the beauty these days with most software packaging is you don’t have to worry about it, you have to make a decision about which is the most effective projection to act as a scaffold for your map, and that’s what it is, it’s the scaffold, it’s the framework. And without a correct framework, it doesn’t matter what you’re going to show, you can make a real mess of it. I mean, fortunately in the US, you’ve got a size and shape that just works well with Albers equal-area projection, which – and, I mean, I know you have to move [inaudible 00:24:13] a little bit in Hawaii and so on. But it just works, it’s a nicely balanced shape, it works great in landscape. And crucially for data it works as well. So whenever you’re making maps of population based data, the fundamental issue is you need an equal area projection. And without that, you are going to introduce all sorts of visual issues into the map that make interpreting it a lot harder, and it will force people into seeing the map the way in which the data actually doesn’t support, it’s just that the projection has morphed it into something that says something slightly different.
So I guess, I mean, it’s important, particularly with smaller scale maps. The larger you go, as in, the smaller area, if you’re just making a map of a town or a city [inaudible 00:25:07] projections are irrelevant largely because it doesn’t matter. But if you’re making maps at a country or a continental scale or a global scale then they matter very much. I guess, I’d be foolish not to comment on Web Mercator at this point, because everyone loves to hate it. I mean, I would counter that, there is nothing wrong with Web Mercator. I mean, from a technical point of view, it made a lot of sense to go down that route for making web maps way back when – not so way back when [inaudible 00:25:44] it’s only 15 years or so. But they don’t support every type of mapping that you might want to publish on the web, and this isn’t so much a problem of Web Mercator, it’s a problem of people not being willing to just go the extra mile to change the projection to suit the map that they’re making, and pretty much every major mapping platform allows you to do that now. We’ve gone beyond having to be forced to use Web Mercator for data maps and really they should be consigned to history now. If you’re going to make a data map with Web Mercator now, you’ve frankly just been a little bit lazy these days. So Web Mercator is fine if you want to navigate the globe in a canoe. That’s its purpose. That’s why it was made, for navigation, but it’s not for showing population data and so on.
JS: You mentioned the Albers projection at least for the United States. Are there other projections that you think people should use or maybe don’t get the attention that they deserve?
MB: Not explicitly. I don’t have a favorite projection. I don’t go down…
JS: Do most cartographers have a favorite projection?
MB: I think some would say they like things like the bond projection which is the heart-shaped one, but they’re really just curiosities, you can’t do anything particularly useful with those. I think rather than saying which projection is good and which is not so good, I would just scrape off a layer, it’s not about trying to find a projection, it’s about employing the special property of a projection. So properties such as equal area or conformality where angles are equivalent across the map, these properties are what drives the projection’s purpose and its usefulness to you. So I’ve got a colleague here called Bojan Šavrič was one of the authors of the viral hit, the Equal Earth projection from last year, and he’s also created a tool called Projection Wizard. If you just Google Projection Wizard it’ll pop up. And it’s great, because what it allows you to do is just zoom into a part of the world you’re interested in mapping and it will give you choices for that part of the world at that particular scale and say here is your best projection for mapping data for equal area; here is your best projection if you’re doing, let’s say, an aeronautical chart or something else. So it’s not difficult to just select an appropriate projection these days. So it’s not really about a favorite or least favorite, it’s about selecting the special property of a projection that makes most sense to you.
JS: Your book is massive, It’s like a tour de force of maps. And so I want to ask you two quick questions before we go. So I want to know, maybe you don’t have specific answers for these, but do you have a favorite map of all time and a least favorite map of all time, either yours or other’s?
MB: Okay. By the way, thanks for constantly bringing the book up, that’s supposed to be my…
JS: You see what I am trying to do here.
MB: Yeah, that was supposed to be my job I think.
JS: I can do it.
MB: Yeah, it is a monster, and I was privileged to be given the freedom and flexibility to basically just write the book I wanted to write and that was a wonderful opportunity. So my favorite map, my all-time favorite map is Harry Beck’s 1933 London Underground map. Some people might even call it a diagram. It’s a schematic map, it does a perfect job of showing the routes in and around London, simple lines, horizontal, vertical, 45 degrees, color coded, symbols for stations, that’s it, job done. It’s the basis for every subsequent metro map. I mean, we can go into the history and we can basically prove that Beck didn’t invent the schematic map but that’s by the by. I think he was in the right place at the right time to capture a sense in a mood of graphic design in London in the 1930s and that map fitted very nicely into that overall aesthetic that was being pushed at the time. I hate the current map. So it goes to prove that an idea from the 1930s if you just keep persisting with it and basically just keep adding more data and adding more lines and adding more colors and adding more information, you end up with a complete mess. So it’s not that I like the London Underground map, I mean, the current one. The current official one, I think, is an awful piece of work, it’s just way too cluttered. But yeah, that classic 1933 original one is my favorite. And you could argue that if Beck was making the map of today’s massively more complex network, he may not even have taken the approach that he took because it doesn’t necessarily suit the purpose of today’s map.
JS: Since you had mentioned the teams and technologies, how much you think his decision-making was driven by the technology he had at the time?
MB: Well, I mean, he was an electrical draftsman and his job was basically creating schematics of electrical wiring diagrams. So you can see that he obviously, literally, quite literally, drew from his experience the technology that he was used to using and made a map that made sense to him. You’d maybe do it differently today if he was starting from scratch. My least favorite map, just to finish off that, really hard question. There isn’t a map I dislike particularly. But there is a map type that I dislike and that’s any map that seemingly goes viral across social media when it has absolutely no qualities whatsoever. It’s the map that’s nonsense. It’s the map you look at and can see holes in it, you can see problems, you can see the way in which the map readers have been tricked into thinking it’s great. And unfortunately, before you know it, half a million people have said, hey, this is the best thing I’ve ever seen in my life, and then it just goes crazy from there. And some little corner of the internet with the cartographer going, excuse me, this actually isn’t a very good map, that doesn’t wash. So that’s my – and of course, the converse is true. I’ve seen people make some absolute wonderful work and no one ever sees it. It doesn’t cause even the slightest blip. So it’s not really that there’s a map I like. It’s really that this is environment of today’s rapid sharing, uptick kind of world and how that doesn’t – it doesn’t necessarily equate to the quality of the piece of work the people are upticking. It’s just stuff. There’s a lot of noise. There’s some great stuff within it, but there’s a lot of noise. The one map I do dislike is my own. I made a map in 2009, a map of Irish surnames, and I hate it. It’s one of those things I did for a particular reason and a particular time in my life, and it comes back every single year around St. Patrick’s Day, and I look at – it’s just like that, it’s like that bandwidth, that one classic single that they come to hate, because they’ve got to play every gig. And they desperately want, they had fans to listen to their super cool new work that they spend ages crafting. Now, they want to hear the classic.
JS: Yeah, they want to hear that one [inaudible 00:34:07] is a good sign.
JS: [inaudible 00:34:09]
MB: Wow! And it was a lot of comfort today. [inaudible 00:34:14]
JS: I should try to get [inaudible 00:34:17] into every episode of the show, that should be a new goal. Well, I will put links to all this stuff on the show notes so people can check it out, including your site and your book and the projection wizard. I am sure people would like to play around with that too. So thanks for taking the time and chatting with me.
MB: Yeah. No problem. Have fun. Thanks.
And thanks to you for tuning in again this week. I hope you enjoyed the show. I hope you learned something. I do hope you will check out Ken’s website, he’s got a lot of great tutorials and a lot of great examples on the page. Also check out his book, it’s linked on the show notes page, check it out, it is an amazing book that will help you improve the way you use maps in your data visualizations. And if you would like to support the show please consider leaving your review, please consider going over my Patreon page or just give a shout-out to the show on Twitter, Facebook or your favorite social media platform. So until next time, this has been the PolicyViz Podcast. Thanks so much for listening.