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Episode #19: Chris Ingraham
145 Plays9 years ago
In this week’s episode, I’m happy to welcome to the show Chris Ingraham from Wonkblog at the Washington Post. We talk about good and bad data, interesting and unique data, and his process for writing and pulling together great stories....
The post Episode #19: Chris Ingraham appeared first on PolicyViz.
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Transcript
Introduction and Sponsorship
00:00:00
Speaker
This episode of the PolicyViz podcast is brought to you by Socrata. Socrata is a global leader in software solutions that are designed exclusively for digital government. They deliver unprecedented data-driven innovation and cost savings for hundreds of public sector leaders and millions of their constituents around the world. Socrata's digital government solutions are being deployed for a wide array of strategic and mission-critical government services that empower citizens while enhancing their quality of life. To learn more about Socrata, visit www.socrata.com.
00:00:37
Speaker
Welcome back
Guest Introduction: Chris Ingraham
00:00:38
Speaker
to the Policy Viz Podcast. I'm your host, John Schwabisch. This week I'm here with Chris Ingraham, reporter for The Washington Post. Chris, welcome to the show. Thanks for having me, John. Thanks for being here. We're going to jump right into it because there's lots of good stuff to talk about because I think
00:00:53
Speaker
Well, I think probably everybody's a big fan of the work that you're doing over the post. Really enjoy the post that you're writing for Wonk blog. So maybe
Chris Ingraham's Career Journey
00:01:01
Speaker
I'll start by asking you to briefly sort of give the listeners your background a little bit, because you and I met before you were at the post, so maybe folks would be interested in where you came from.
00:01:13
Speaker
Yeah, back in the nonprofit days. Yeah, my background is all over the place. And you've probably run into this with people in this field that you talk to having backgrounds that are just all over the place. I was a liberal arts major. I worked as a technical writer. I worked as a web marketer. I did all kinds of stuff. I started doing the Data Vis stuff in DC. I worked at the Pew Research Center for a while.
00:01:34
Speaker
spent about two years there doing web stuff and they had a need for this is like two thousand seven two thousand eight two so i need to people even know what charts were back then i don't think you got the notion that we should be doing more visual chart so i just started doing that because i had some design background.
00:01:54
Speaker
From there, I went on to Brookings to do data viz stuff full time. And that's where I got, cut my teeth doing more interactive coding and development. And this was like, so this was like 2011. So this was right in the transition when like flash was going away and like people were trying to figure out what they could do in the browser without flash. So that was a pretty kind of strange and interesting time from a data viz standpoint.
00:02:21
Speaker
And then I came here to the post in, let's see, 2014. Right. And so now at the post, you are, at this point, I think exclusively writing for Won't Block.
00:02:32
Speaker
that's
Joining The Washington Post
00:02:33
Speaker
correct that so i actually i came in through the graphics department at the post they actually they wanted somebody with some data background to do to do graphics for all of their blogs basically in the kind of be detailed out to various blogs uh... but when i came in that actually happen to be read the moment when the prior one blog crew they all departed and left to found box dot com so all of a sudden they have this big need for
00:02:59
Speaker
just, you know, graphics and stories and everything for Wonk Blog. So I started out there and it worked out really well and so they just kept me at Wonk Blog full time. And so these days I'm doing doing probably more just straight-up writing and reporting than I am doing, you know, traditional graphics and even coding stuff.
00:03:15
Speaker
Right. So you and I are both inside the Beltway. So for those listeners who are outside the Beltway, who may not be as familiar with Wonk blog, how would you describe the goals and the content that you guys are posting?
00:03:31
Speaker
Yeah,
Data-Driven Analysis at Wonk Blog
00:03:32
Speaker
that's a really good question. That's a question that we pose to ourselves, I think, on at least a weekly basis. We're essentially, we're a policy block. So we write about, you know, policy and ideas that are kind of in the national conversation about politics, you know, Ben Carson's tax plan or Donald Trump's immigration plan to the extent that he has one. So we're talking about policy, but we're trying to do it. And I think this is more of a recent development, more from a data driven standpoint.
00:04:00
Speaker
So there's a question idea in the news for me specifically and for a lot of other one blog writers to the first question we have is well is there any data that speaks to this and is there any data that speaks to this given claim that this candidate is making or that you know that you know people are debating so that's kind of the bread and butter of what we do and
00:04:21
Speaker
And we also spend, and this applies again to me a lot, is we're just looking for interesting data and interesting ideas, interesting research that can be highlighted. Basically anything from kind of a quantitative standpoint that we can
00:04:38
Speaker
that says something interesting about the world or politics or what have you. I want to come back to the lighter stuff and the unique data, but first talk about this idea of bringing data to talk about some of the bigger issues of the day.
Shift to Data in Political Reporting
00:04:58
Speaker
So I hear this a lot from bloggers who are in your area, folks at Vox, folks at FiveThirtyEight, but how does that differ from the rest of the posts or the other blogs that are going on? It seems like a lot of those stories should also be rooted in data.
00:05:15
Speaker
Yeah, you'd think so. And I think newsrooms and I think media groups in general that are becoming your typical beat reporter and politics reporters have become a lot more comfortable with data in general over the past few years. And it's hard for me to accurately look at this because I've been so steeped in this over the past few years, but it didn't always used to be that way, I don't think.
00:05:38
Speaker
You know, I think a lot of that changed in the last election cycle with FiveThirtyEight and with this sense of, you know, getting past, you know, pundits' gut instincts and gut feelings to, you know, putting some actual quantifiable data. Or the other, the leg of that, too, is just political science and social science and not necessarily
00:06:00
Speaker
you know finding a chart to assess a given claim but seeing well you know there are people who have been studying this in academia for you know dozens of years now and so what do they say and so it's we're trying to provide a bit more in-depth coverage and in a lot of the situations of of campaigns and policy ideas and big policy debates and so i imagine now every time i visit uh... any newsroom i sort of have uh...
00:06:27
Speaker
sort of like the Hollywood version where everybody's going to be yelling at each other. But of course, it's a little bit different than that. It seems to be quieter. But at the post, at least, it's sort of a huge, at least one of the floors that I've been on is just sort of a huge room. So is there a lot of collaboration or sort of working across the different platforms?
Breaking Newsroom Silos
00:06:45
Speaker
It seems like if you're doing some data work, let's just take one of the, you know, any candidate's tax plan and you're really digging into the data, you've pulled it.
00:06:54
Speaker
from Brookings and from Urban and from all the different places that are talking about it. Are you working with reporters who are maybe working on a cover story for A1? Are you sort of providing information to them and back and forth? Or are they sort of siloed off?
00:07:09
Speaker
That's a tricky question in any organization. I think newsrooms, and I think I certainly experienced this in non-profits too. There's still a lot of balkanization and silos. This is true in non-profits I worked at.
00:07:24
Speaker
I'll say here that they've been actively trying and trying very hard to break down some of these barriers. And one of the interesting things that we're doing here is we have, I mean, in addition to people like myself, guys like Philip Bump, who does stuff similar to what I do with a strictly politics focus.
00:07:42
Speaker
In addition to those, the posts, like most newsrooms, we have an entire huge graphics department that does absolutely amazing data-driven work, both static and interactive. And one thing that they're doing now is they're, at least with Wonk Block, we're taking graphics artists and developers and embedding them with Wonk Block for a couple weeks at a time to get them directly with us, and they kind of have that.
00:08:06
Speaker
Nexus between graphics and between stories and that's kind of the idea is we're trying to Try we want to get the entire newsroom thinking more visually I think And I think that's one way that we're experimenting trying to do that, right?
00:08:22
Speaker
But yeah, I mean it is tricky. I mean sometimes, you know, sometimes the inevitable happens where I'm working on a story and like somebody in the education department, if I'm working on education data, somebody in the education department is working on a similar story. You know, and that happens anytime. But it's, I think we've rarely
00:08:38
Speaker
I can't even think of one where we run into a situation where like two people inadvertently wrote the exact same story more or less. Like even dealing with the same data set, there's so many different ways to go at it. And you know, with one blog, we're a blog. And so, you know, a lot of time I'm just trying to do something really short and quick. Like for instance, with this, there was this big education data release over the weekend, right? You're probably familiar with it.
00:09:00
Speaker
I'm also interesting new higher ed data and there I mean there's like there's I mean you could You could get yourself busy for a year doing yeah that and writing stories off of it I kind of wanted to familiarize myself with it and so I just did a really tiny slice of it I just looked at some salary data
00:09:15
Speaker
among Ivy League colleges. And I just did a really short, punchy post that was two charts and maybe 350, 400 words of text. And that's kind of like a lot of our bread and butter. And that's going to be very different from what the folks in our education department do, where they're writing a traditional A1 story, they're diving in, getting really deep into the context of the data behind it, any controversy behind releasing it, what it all means, etc., etc.
00:09:38
Speaker
Right.
Engaging Data Stories
00:09:39
Speaker
All right. So this is good. This is a good segue because I want to talk about some of the lighter stuff that you do because I think, well, I don't know. I don't know. I'd be curious if I grabbed a random sampling of your readers, what they sort of what they sort of thought. Yeah. Yeah.
00:09:56
Speaker
Aside from the heavier stuff of my reading, it seems like you try to find the unique off the beaten path data that maybe it's hard to find or maybe people just haven't used it. Then you also do these fun things that are, here's a map of the United States of county level map and guess what I'm plotting or here's a line graph and guess what I'm plotting.
00:10:18
Speaker
What sort of drives you to do that sort of thing and how do you feel that it fits within this sort of larger walk blog goal of data-driven research and storytelling?
00:10:33
Speaker
Yeah, so I definitely, I mean, yeah, as you've noticed, I love doing more lighthearted stuff. And, you know, I think it's just, it's fun to do as a writer. And I think, I think one of the things about data in general is that it, you know, data communicating with numbers, it's similar in a lot of ways to communicating with words. And, you know, when you're
00:10:53
Speaker
writing a story, you can write a serious story, you can write a sad story, you can write a light hearted story. And there are ways you can do the same thing with data. And I think that's something that I've been trying to explore is some of the more light hearted interesting stuff, like, you know, a map of every goat in the United States, which actually exists, like the USDA has data for this. And so a lot of this is
00:11:13
Speaker
And in terms of how this fits into the broader wonk blog goals, I think a lot of what we're trying to do is just explain the world that we live in. And the fact that the US government devotes time and energy to take a census of America's farm animals every five years in itself is really interesting. Just the fact that this happens and then also what those numbers look like, those are also very, I think there's just a natural curiosity.
00:11:41
Speaker
Like a lot of these, it feels like sometimes you'll have a conversation at the bar when your three or four drinks in and somebody's like, well, I bet there's more goats in my hometown than your house. Stupid questions like that that people talk about every day, but that nobody thinks there is actually an answer to. Well, in a lot of cases, there are answers to. Digging those kind of things up is really interesting. I look for stories and data and findings that surprise me.
00:12:09
Speaker
It struck me as, oh, wow, I did not know that or I would not have guessed that.
Curiosity-Driven Data Exploration
00:12:13
Speaker
And that drives a lot of what I decide to write about. So are you starting with the question, like, do you have to go out to the bars every night to have three or four drinks and come up with a fun question? Yeah. I'll pitch that to my editor and see what he says. Yeah. And so a lot of so sometimes I'll start with a question.
00:12:33
Speaker
So for instance, I'm working on a project right now. This past weekend in the DC area, the weather was absolutely gorgeous, as I'm sure you're aware. And I'm like, man, I could get used to this. And then I thought, well, where in the country is the weather like this most during the year? And so now I'm working on a project and getting climatological data. And I'm trying to find, OK, so I'm trying to create a thing where somebody types in a given range of temperatures between 60 and 75 degrees.
00:13:00
Speaker
looking at county level map, which are the counties that have the most days or the average temperature? So a lot of it, it's like stuff like that where the stuff it starts from a question that I have. But some of it, and I'm aware that this kind of
00:13:15
Speaker
breaks one of the cardinal rules of a lot of storytelling with data. But a lot of it, sometimes I'll just be poking around the internet and I'll find a really interesting data set. I'm like, wow, I did not know that this exists. This is inherently interesting to me. And so I'm just going to write on it or chart it or make something with it and take it from there and see if other people are interested too.
00:13:38
Speaker
So yeah, so I can imagine some people might be offended by that less poking around. But on the other hand, it's one of the ways that it's just something that's piquing your curiosity, right? And that's, that's what all of this is kind of about is using data to answer the
00:14:08
Speaker
But, you know, in news in general, this is not just like a modern development, like even back in the day in the 70s and 80s, like there were, you know, newspapers had the comic section and the horoscopes and there was always this goofy, lighthearted stuff. And I think if you can be goofy and lighthearted and also methodologically rigorous and have like, you know, some some interesting, you know, serious numerical grounding to what you do, I think that's a real sweet spot in terms of
00:14:19
Speaker
serious or the fun questions.
00:14:34
Speaker
Just showing people how numbers and how quantifying the world, it can be, it can solve curiosity gaps and it can also be really entertaining too. Right, right. Okay, so when you come up with some of these questions that may be a little, even if they're not sort of light hearted and they're not sort of on the fun side, but they require some unique or hard to find data, do you have
00:14:59
Speaker
a process that you go through or is it literally just starting to make phone calls and searching the internet to sort of try to, you know, just try to find something that will answer that question? Yeah, I
Finding Unique Datasets
00:15:11
Speaker
mean a lot of it's just plain old like Google searches and phone calls.
00:15:17
Speaker
Developed like I've got a series of like go to data sets and sources that I always check first Like I do a lot of criminal justice stuff And so there are some certain criminal justice databases that have been proven to be really useful and then I turn to time and time again One of the more interesting things that's happened in the last year or so is just it's so much of the data on Policing and crime is so bad because at the national level it's all voluntary and it all goes to the FBI
00:15:42
Speaker
that a lot of places just started crowdsourcing it and just started making it themselves. So there's a lot of really interesting crowdsourced databases popping up. And you know, with that kind of thing, you always have to be worried about like quality. Like, is this a legit data set? Like, is this, you know, this is like some guy sitting in his basement, like, you know, like, is, but is he being like, you know, it's not peer reviewed or anything. So you have to be careful with that.
00:16:06
Speaker
One of the more interesting data sets I found recently was this database that's basically maintained daily of mass shootings in the United States, and it's maintained by a Reddit community. And of course, Reddit is an online community with all sorts of
00:16:24
Speaker
various individual communities interested in different things, and one of them just happens to be interested in guns, and they track, via news reports and news stories and police platters, the number of mass shootings that happen on a daily basis in the United States. So there's a lot of non-traditional data sources coming up in the past years. It's an opportunity and a challenge, because you have to make sure it's vetted, but it's also telling us a lot of things that we weren't able to know before. Yeah, yeah, interesting.
00:16:52
Speaker
Yeah, really interesting. OK, so before we close up, so two quick questions.
Challenges in Data Visualization
00:16:57
Speaker
So as someone who does sort of quick turnaround, data vis and using data regularly, so what do you think is the most egregious data visualization error? And then perhaps relatedly, the most egregious statistical error, kind of in your field. So the data visualization errors, you know,
00:17:20
Speaker
You know, a lot of people yell at pie charts and the non-zero lines. But you know, is there anything that you see or that you've created where you look back and you're like, God, that was just really wrong. Or things that you've seen that other people are doing that you're like, no, stop doing that.
00:17:35
Speaker
Yeah. Well, I mean, and this might be kind of getting at both of the questions, but there's, this is going back to questionable data. And I'm sure you probably saw Jacob Harris's thing that he wrote recently about how companies are like just kind of peddling all these random data sets that they, you know, and so I get a lot of pitches like that. I get a lot of these weird pitches that are like, I don't know. It's from like, it's from these random websites. Like, I don't know. And I'm just making this up like bestrestaurants.com or something wherever they're like,
00:18:03
Speaker
Well, we saw that you wrote about marijuana the other day. Did you know that there are like 2,000 marijuana rehabilitation centers in the US? And here's a map of them. I'm like, why is bestrestaurants.com pitching me a marijuana map? What is going on here? And so that's a questionable thing. And I try to be wary of those. So this is like the new version of direct mail.
00:18:26
Speaker
It's like direct data visualization mail to people who can get their message out there. Yeah, and some of it's really useful. Some of the countries are companies like Uber and Trulia, they have actually really interesting databases that you want to get, but there's also just this weird subset of spammy domains and companies that you're like, why do they exist and what are they trying to sell? I don't understand.
00:18:53
Speaker
I don't understand the connection between restaurants and marijuana policy.
00:19:13
Speaker
I think one of the biggest pitfalls with just numeric data reporting in general is just being afraid of the data and not doing enough of it. I don't know how many news stories, like traditional news stories that I've seen from various outlets in the past year where they're reporting on numbers or they're talking about something quantitative, where the data is out there and it's very easy to find, but there's no charts, no links to surveys, no nothing.
00:19:38
Speaker
I think we still need more numerical literacy in newsrooms and in the general public. And we're getting there, you know, with places like Wonk blog, and in the past year the rise of places like FiveThirtyEight and Vox, they're all doing a great job of getting people used to
00:19:55
Speaker
different data types and different data sources. I mean, I remember when I was at Pew, like 2007, 2008, I wanted to do a scatterplot of something and everyone was like, oh boy, do people even know how to read a scatterplot? Like, what is a scatterplot? And like, those questions don't even happen. Like, you know, everyone's like, oh yeah, scatterplot, this is cool. So I think that rising numerical literacy is a good thing, but we need a lot more of it still. Yeah, I agree. This is great. Well, I think we have to wrap up. Thanks so much for being on the show. It was really interesting.
00:20:24
Speaker
No problem, thanks for having me. And thanks to everyone for listening, really appreciate it. We'll be back in a couple weeks with another guest. In the meantime, be sure to hit me up on the site if you have questions or suggestions and be sure to rate the show on iTunes and of course subscribe to the show on your favorite podcast provider and we'll see you next week. Thanks so much.
00:20:57
Speaker
This episode of the PolicyViz podcast was brought to you by Socrata. Socrata is the global leader in software solutions that are designed exclusively for digital government and provide benefits for hundreds of public sector leaders and their constituents. The company's customers, among others, include the cities of New York, Chicago, San Francisco, and Los Angeles. To learn more about Socrata, visit them on the web at www.socrata.com.