Alberto Cairo @albertocairo is the Knight Chair in Visual Journalism at the University of Miami. He's also director of the visualization program at UM's Center for Computational Science. He's the author of The Functional Art: An Introduction to Information Graphics and Visualization and The Truthful Art: Data, Charts, and Maps for Communication . He also writes regularly about visualization in his personal blog . He has been director of visualization at news publications in Spain (El Mundo) and Brazil (Globo magazines,) and he's currently a consultant for companies such as Google and Microsoft. Cairo also organizes two annual conferences, the Digital Humanities + Data Journalism Symposium , and VizUM.
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Rosemary Pennington: Journalists are swimming in data coming from governments, nonprofits, think tanks and other agencies. There's data available to help contextualize almost any story a reporter might want to tell. How to present that information to audiences in a compelling and understandable way is something many newsrooms are struggling to figure out. It's also the focus of this episode of stats and stories where we explore the statistics behind the stories and the stories behind the statistics. I'm Rosemary Pennington. Stats and Stories is a production of Miami University's departments of Statistics and Media Journalism and Film and the American Statistical Association. Joining me in the studio are regular panelist John Bailer chair of Miami's Statistics department and Richard Campbell chair of Media, Journalism and Film. Today's guest is Alberto Cairo the Knight chair in visual journalism at the University of Miami Florida, where he teaches courses on info graphics and data visualization. He's also the director of the visualization program at UM center for computational science and the author of 2016s, the truthful art, data charts and maps for communication Alberto, thank you so much for being here today.
Alberto Cairo: Thank you for having me.
Pennington : In addition to your work as an academic, you spent time creating graphics and data visualizations for newsrooms in Spain and Brazil. So I'm just kind of wondering how did data visualization become what seems to be a passion for you?
Cairo : It all happened by happenstance. Back in 1997, I graduated from a journalism program in Spain and my plans originally were to work in radio. I always loved radio, so if I had followed that career probably I would be doing podcasts today. But then in the last year in 1997 I was not a very good student. So that year I couldn't find a good radio internship. I did some internships in radio before but in 1997 when I was about to finish my B.A. I couldn't find one and one of my professors at the University of Santiago de Compostela in Spain, I knew that I can…I can draw a little bit so if you ask me to draw something you know, a cow or a dog or something like that I can sketch it out. I'm not a great artist but I can sketch things out. So she knew that I could draw and she got a request from a Department of info graphics of the local newspaper who were seeking a student who could do both journalism, but who could also do graphic design in an info graphics department. I didn't know anything about infographics at the time but I got that internship by basically by happenstance and thanks to this professor. I learned to do graphics in the newsroom both pictorial graphics and data visualizations and I stayed in the field until this day.
John Bailer : One of the things that people often debate about is the idea of what is an info graphic versus what is data visualization. Tell us what your perspective is on those topics.
Cairo : So a data visualization is simply put the visual encoding of data. You begin with data and a spreadsheet or data set of any kind and then you encode those numbers or you map those numbers on to spatial properties of objects, like the length, the height, the position, the angle etc. to generate the different kinds of graphs or data maps that we use nowadays to represent data. Another method of encoding besides height, length etc. is shade of color, for example, which is widely used in data cartography. So that is what data visualization is, in my opinion. There are many different issues but for me data visualization again is the visual representation of data. And then, info graphics is a broader term or a broader field. An infographic, or the way I like to call them, news graphics is the visual representation of information not necessarily just quantitative data. But any kind of information in visual form and then also it is the combination of these visuals with text in some sort of narrative structure. So an infographic can be both pictorial, think about for instance…I don't know…the visual representation of the inner workings of an airplane or a visual reconstruction of catastrophe of a hurricane or a visual explanation of an earthquake, right, in which you do a cutaway…a 3D cutaway of the terrain to show how the earthquake works. That's an infographic or a pictorial visualization, right? Not data visualization but still a pictorial visualization. But then infographics can also include data visualizations. So a news graphic, a narrative piece that combines text and visuals can also include data visualizations like you know bar graphs, line charts, pie charts etc. on different kinds of data maps as well.
Richard Campbell : Alberto, I know you write right that infographics, data visualization should be both functional and beautiful. But there are a lot of statisticians and journalists out there who…that would have a hard time caring about the beautiful part of that. So how do you sell that to a hardnosed statistician or journalist…
Bailer : Hey, I'm looking for the beauty in the visualization…Richard, come on! Come on! Don't sell us short!
Campbell: I get my stereotype from you John!
Bailer : Oh come on! I'm deeply offended.
Campbell: That's just a joke.
Bailer : OK.
Cairo : Well I have found that many of the statisticians actually have a very well developed aesthetic sense.
Campbell : Ha! That is true of John I would have to give him that.
Cairo : There is always a but though, but they don't apply that much when they design graphs, unfortunately.
Cairo : They have a very well developed sense towards, for example art, and very good taste. But then they don't bring that to the design of the graphs. I'm not talking about every single statistician. But having worked with, you know, many communities, what you mentioned is absolutely true. I think that scientists, statisticians, business analytics people etc. need to care a little bit more about the aesthetic component of data visualization, caring a little bit more about good typography, good color, good composition, good use of white space and margins etc., to increase the readability of graphics. So the aesthetic component of graphics and the functional component of graphics are actually intertwined, they cannot be separated. Graphics that deliver the information clearly and well are usually graphics that look good. When I talk about beauty in my books, I don't talk about, I don't refer to the decoration of graphics. What I do…what I talk about when I describe is elementary visual design, like principles of graphic design, we should never be an afterthought when we design a graphic both the function of the graphic like designing graphics to fulfil some sort of purpose in a clear manner and presenting that information in an elegant way and in a compelling way go hand in hand. They are not…they cannot be separated.
Bailer : What suggestions do you have in terms of in terms of improving practice?
Cairo : Oh I have many.
Cairo : Do you want me to talk to journalists or do you want me to talk to statisticians and scientists because…
Bailer : Yes.
Cairo : Depending on the audience I give different advice.
Bailer : Let's answer first for the journalists and then second for the statisticians.
Cairo : Okay. So for journalists in general, and visual designers in general, I think that we need to focus a little bit more on creating graphics that are not just spectacular and fun and attractive and click-baity, but graphics that are deep, and graphics that deliver information that is actually useful for people. And I am…I know that I sound unfair because there are many many many journalists out there in my opinion that are doing a great job at designing graphics that basically fulfil this goal. But I remember myself like five, ten years ago, creating graphics that are where, you know, they were OK, but you know, they could be a little bit more rigorous, they could be a little bit deeper, they could have used more research, they could have done a better job but you know including the advice of different sources. So that rigor that part of that comes before designing the visualization. It is very relevant obviously and then also for journalists and designers perhaps thinking a little bit less again about creating graphics are a spectacular again but caring more about the clarity of the graphics not trying to be you know super innovative all the time but trying to be clear first and then if you can be clear then you can experiment with new graphic forms. I am a great advocate for experimenting with graphic forms, with novel graphic forms but only if we can only present the information clearly and compellingly. Again, all these things, all this advice that I'm giving here is advice that I would have given myself not that long ago.
Collective : Yes.
Cairo : So that's for journalists who are graphic designers, who want to practice data visualization. And then for statisticians, scientists, business analytics, you know, IT people etc. who produce graphs all the time and data maps…care a little bit more about, you know, again, the visual design and care a little bit more about making your graphics not only clear but also elegant and well-presented and beautiful. I mean attractive you know, improve hierarchy for example, visual hierarchy. I have seen for example tons of quarterly reports from clients of mine who produce quarterly stuff all the time to inform their internal audiences about the performance of their company and whenever I see pages full of graphs in those kinds of documents they look really flat because everything looks the same there's no hierarchy whatsoever, all fonts are the same size, all fonts are the same style, there is no style, right? We need to include style. Style is an important component in developing a good visual style. So good hierarchy, good margins, good use of whitespace, better use of topography and color etc. All those are things that I believe scientists in general, in the broadest sense of the word, could put some effort on. It's not hard, and again, it's not an afterthought. It's a very relevant element of a successful data visualization.
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Pennington : You're listening to Stats and Stories where we discuss the statistics behind the stories and the stories behind the statistics. The topic today visualizing data and information. I'm Rosemary Pennington. Joining me are panelists Miami University statistics department chair John Bailer and media journalism and film department chair Richard Campbell. Our special guest is Alberto Cairo Knight chair in visual journalism at the University of Miami, Florida. Now Alberto you were talking a little bit about sort of what journalists and designers need to keep in mind and sort of things that statisticians or maybe scientists need to keep in mind but I am a journalist, Richard is also, you know, formally a journalist, you have worked as a journalist. There's a stereotype of our field that we get into this field because we are scared of numbers. How would you sort of encourage, you know, a journalist who, maybe is uncomfortable dealing with data and who is, also has this, added sort of thing about sort of creating those infographics that are beautiful as well as sort of readable. How…what would you say to those people who are kind of timid or worried about sort of diving into this field? What would you say to them to encourage them to do it?
Cairo : I think the first step is to become friends with statisticians who can communicate well. That would be the first thing.
Campbell : We've done that.
Cairo : John is one of those.
Campbell : Yeah.
Cairo : You need to become friends with statisticians who are willing to explain to you, in terms that a lay person can understand, what principles of statistics really mean. So what lies behind all those with scary looking formulas and calculations and mathematics etc. The mathematics looks scary but in many cases they are just plain arithmetic. It's a matter of…it is more important, at least in the beginning, when you start learning a little bit about statistics, understanding the principles is much more important than understanding the possible deep math that lies behind. Both things are important but these things can be understood. So becoming friends with a statistician, or, if there is no statistician around that you can become friends with, there are great books out there that you can read to at least get started and get the ball rolling. Like recently, Naked Statistics you have Bad Science, Ben Goldacre, who is both a statistician and a medical doctor, you have How not to be wrong by Jordan Ellenberg who is a mathematician but who can communicate really well with non-mathematicians. So any of these books or all of them if you have the time to read them all will give you a…they will not give you a foundation in statistics, this is obvious, but they will give you a broad understanding I believe of how to avoid the most common kinds of mistakes that we see in the media every single day, right? Like correlation doesn't mean causation or the most common ones right or what the regression to the mean is, right? You don't necessarily need to be able to calculate a regression to the mean but it's understandable. It is something that anybody can understand on a conceptual level. So all these books help with that and then after you take that first step you realize that this, it's not magic. I mean, it's logical. It's rational thinking and then is when you are ready I believe to start you know digging a little bit deeper into the professional literature of statistics. So you know you can start reading basically real reading, Stats 101 books and or again talking more to your statistician friends who can recommend great books to you, there are online courses that anybody can take, data science, introduction to data science courses in places like Coursera and other places right? So those are great ways of getting into the field and start losing the fear because as you said, that's right. I mean journalists in general I heard it sounds like a cliché to say that journalists get into journalism because they fear math but it is not a cliché.
Pennington : Right.
Cairo : I heard that in college. Yes I want to become a journalist because I want to write, right?
Campbell : Yes.
Cairo : And I still get that from my students. Last point that I would like to make in this answer, my introduction to data visualization and infographic course and our data journalism course, are both mandatory for all our journalism students. And some students getting to those classes with a little bit of fear of what those classes are going to offer, then they realize that they are not that hard because again this is not magic but some of them, a few of them get this reaction, they say you know "oh! I want to be a writer, why do I need to learn all this stuff?" Well you need to learn it because if you're going to become a writer or a reporter you're going to face numbers on a regular basis. If you don't have a working understanding of what those numbers mean, what are you going to write about? So it's a really important idea to put inside our students' brains I believe.
Campbell : Alberto, can you think of stories, and this is speaking to the journalist in you, that aren't being done because journalism doesn't quite know how to tell that story or visualize that story because the numbers seem complicated or just too big to get our heads around?
Cairo : Good question. So I believe that, it is, speaking in general terms, most things related to artificial intelligence and machine learning and deep learning are still those stories are still to be told well, right? So I'm talking in a very general sense then we can go we can go into the specifics because not all journalists are the same so…and not all news organizations are the same. There are news organizations that are well equipped to deal with very complex stories and large amounts of data I'm thinking of organizations such as ProPublica in New York or The New York Times, The Wall Street Journal, The Washington Post these organizations either have statisticians on staff or journalists who are very well versed in the statistics and then they have great sources in academia who can help with very complicated data. So I am not that concerned about you know big stories, worldwide stories that even if they involve the management of large amounts of data I am much more concerned about stories at the local level. Because smaller news organizations, local and regional news organizations often don't have the luxury of having a statistician on staff or a web developer or data visualization designer who knows statistics, right? So in that cases we may find ourselves in a situation in which these organizations are shrinking, they are laying off more and more people every year and there may be many, many local stories that are not being told, just because these organizations don't have the muscle and I don't really know what to do about that but it's something that concerns me quite a lot actually.
Bailer : That's something that you know Richard has talked a lot about as well and certainly he is involved in some projects, you want to mention those…
Campbell : We have an initiative that I worked on during my leave last year was a report for Ohio project. To address the problem of shrinking staff particularly in rural communities or even in inner city communities where there are stories that are not going they're not being reported I mean mostly because we don't have the staff to do that in fact we have now a national partner report for America there's just an article in Pointer today about their organization and they want to use us as one of their sites on a regional level to get more reporters hired in these areas that you know, we tend to call a media deserts now where they just don't have information and nobody's telling these stories.
Cairo : Penelope Abernathy's term …
Campbell : Yes you're exactly right though you're you identified the problem it sounded like you had read our report.
Cairo : Well, I mean I haven't but I would love to know what I mean when I when if you send it to me but I mean it's pretty obvious, right? I mean I see it locally in Miami. Even if Miami is a well-covered area we still have the Miami Herald which is much smaller than it used to be we have the Spanish stations: Univision … Telemundo, we have you know the Miami News times. So we have plenty of organizations down here but still, the super local stuff feels not covered well enough. We have a special election for example going on here, I barely hear about that in local media, right? And you know who knows how many, you know, corrupt politicians get away with this stuff that they are doing just because there are not reporters who are able to you know, download data sets or FOI a request that they can analyze and discover these covered things that maybe worth, you know, worth putting under the public eye. We don't know but that's something that really worries me. Because who's going to do that job if the news organizations are gone? It's not about the New York Times, it's not about the Washington Post. Those organizations are going to survive I believe in the long term. A nonprofit organization like the Texas Tribune or ProPublica etc. are doing great job and they need to be praised but there are many things that they cannot cover. Who are going to be the ultra-local ProPublica's in this country?
Campbell : Yes.
Cairo : Or anywhere in the world for that matter.
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Pennington : You're listening to Stats and Stories. Our discussion today focuses on information and data visualization. Our guest is Knight Chair in visual journalism at the University of Miami Alberto Cairo. Alberto, we were talking a lot about the problems around local reporting and you mentioned the fact that you know data visualization and these info graphics are a really compelling way of telling stories, an important way and as I was listening to you, I was thinking about the fact that a few years ago when The New York Times published snow fall that seemed to be like this moment when journalists were like oh! We have to do data visualization now. We have to do something really big, loud and exciting with information. Are there are local examples, are there smaller examples that you can point to that you think are going to be good examples of the way smaller newsrooms are doing this kind of work that you think smaller newsrooms around the country could also sort of pick up and carry, and I know the Charleston Mail orGazette I think…what was that…I can't remember the name of the paper, won an award for their reporting on the opioid epidemic and it was through very simple info graphics. Are there other examples you can point to for people listening for ways of these newsrooms that are struggling to be able to do this?
Cairo : Absolutely. I mean there are plenty of examples out there. There is still tons of courageous journalists that produce great work with very few resources and still you know, managed to put out great projects. The first one that comes to mind is the Tampa Bay Times which won a Pulitzer award a couple of years ago thanks to a project titled "Failure Factories", I believe that's the title of the project "Failure Factories" which is an exploration, a data driven exploration of how increasing racial segregation in school systems lead to worst performance in those school systems. It's a very compelling story it's a great investigation and it's a great example of how to produce that kind of work with just you know two or three reporters one of them very well versed in visualization and one or two that are just traditional you know shoe leather reporters, and how, you know working together they can produce this kind of great work. The Miami Herald is doing great work down here in my opinion as well also with shrinking resources again they are unfortunately they are not the newspaper that they used to be many years ago not because the reporters are worse but because there are fewer reporters and designers. But they still put out great stuff on a regular basis, they do investigations. For example one of our adjunct professors here at the University of Miami, is Nicholas Nehamus, who is one of their investigative reporters he's also a computer assisted reporter. Here we still use that term. You know, if you remember that term?
Campbell : Yes.
Cairo : You have computer assisted reporter which is basically the precedent of the journalism or data reporter. So he does a lot of Excel analyses and he focuses on real estate but he also does stories about many other, many other things so those are the examples that come to mind immediately but there may be there may be I mean there are many others I believe that inThe Truthful Art I mention are probably by The Seattle Times and I don't I mean there are many out there and some of them are showcased in my book, in both my books and my website.
Bailer: So you mentioned some guidance to the journalists that want to know more about you know build up their skills in statistics. I mean a question for the stat community is what would you recommend in terms of building up not just the sense of aesthetics and design which I think your books are a couple of great examples of doing that but also just in terms of the narrative part of the story you know I think that sometimes you find that the people that are building some of the visualizations and have the technical skills to do such displays are not necessarily good at the narrative that complements it.
Cairo : Yes I completely agree and I understand why that happens. Sometimes when I do talks or conversations like this one I sound sometimes like I am bashing scientists because they don't communicate well but there is a reason for that. There is a core, key difference between how journalists approach "stories" quotation marks in there and scientists approach stories. So journalists approach stories in a way that always strives to simplify, find the main take away, transform that main take away into the headline and then try to simplify things no matter what, right? And scientists, and statisticians in particular are more about the nuance and the exceptions, for good reason, right? So as scientists may tell you, Well, I think that the main takeaway of the research project that I'm conducting is such and such. But here are the nuances, here are the exceptions, here are the limitations, here are the things that we still need to do research about blah blah blah and they do it for good reasons, that's what science is about. You always open the door to continuing doing research in the future so no scientific truth is ever permanent. It is always subject to change, right? So I think that there is a way though, to establish dialogues between journalists and statisticians and this podcast is a great example to learn from each other. And the point that I like to make in my talks that are open to the public, therefore I have both scientists and journalists in the news in the room is that as journalists, we need to learn to think a little bit more like scientists in the sense of you know always incorporating the nuances, always incorporating the uncertainty of the data into our stories particularly when the uncertainty is crucial to understanding the story the exceptions the counter-arguments etc. and then you know whenever we deal with data particularly we manipulate this data, always releasing the data and explaining the methodology behind the manipulations of the data. That's what scientists do and some news organizations are already doing that Propublica for example whenever they publish a story they publish the methodology of the story not just the story right and on the other hand scientists and statisticians, I believe should learn a little bit more about narrative techniques and graphic design and this sounds like anathema to some scientists and statisticians, but I'm going to quote a statistician. All right so there is a famous book titled Statistics as Principle Argument by Robert Abelson. So Abelson used to teach statistics at Yale University and statistics as principal argument is a book about statistics, obviously. But in the prologue of the book he describes narrative techniques he says well, a statistics argument is a rhetoric based on data you're trying to persuade someone of something right you just use data for that you use sound science and statistics for that but still it is the rhetoric. Therefore in the prologue he says whenever I teach statistics, and whenever I am teaching my students to use statistics, they tend to get a little bit lost into the methodology right, they start thinking about what methods should I use here, what techniques should I use here…and in the prologue he says no no no stop just one second right if you were to report your argument or your paper in the newspaper what would the headline be. So what is it what is the elevator speech over here? Begin with the elevator speech with the headline and then talk to me about the methodology, and exceptions, build an argument around it, talk about the limitations but always begin with the main takeaway because that's what journalists always do. We begin with a headline and the lead of the story.
Bailer : Great advice.
Pennington That's all the time we have for this episode of stats and stories with Alberto Cairo, knight chair in visual journalism at the University of Miami Florida. Thank you so much for being here. Stats and stories is a partnership between Miami University's departments on statistics and media journalism and film and the American Statistical Association. You can follow us on Twitter or iTunes. If you'd like to share your thoughts on our programs, send your email to firstname.lastname@example.org and be sure to listen for future editions of stats and stories where we discuss the statistics behind the stories and the stories behind statistics.
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