[00:00] Data journalism is a collaborative field with journalists growing into better reporters
[00:10] with the help of practice and partnership.
[00:12] In this episode of the IRE radio podcast, veteran reporter, editor, and computer programmer
[00:19] Ben Welsh joins to talk about his journalism career and how he got to where he is today.
[00:26] As the founder of Reuters News Applications Desk, where he is currently an editor, Welsh
[00:30] has gained a multitude of tips and tricks for data journalism that he will share with
[00:35] you throughout this episode.
[00:37] Additionally, we discuss his personal site that archives his various data in investigative
[00:43] journalism panels and resources.
[00:45] This is Nakyla Carter and you're listening to IRE radio.
[01:05] So the first thing I want to say is just when did you know journalism was your thing and
[01:09] then how did you nurture it to be the person you are today?
[01:12] Oh man, we can go way back with this, I'm getting old.
[01:17] I never set out to be a journalist.
[01:18] It wasn't something I did much in high school or a career goal I went into college with.
[01:24] I was an undergraduate at DePaul University in Chicago, Illinois after growing up in Eastern
[01:29] Iowa and kind of stumbled into journalism accidentally.
[01:33] I had a job answering phones in the communication department as part of kind of one of these
[01:37] work study programs to make a little money while I was in school and that kind of thing.
[01:43] In that job I was entrusted with some very important responsibilities.
[01:47] One of them was pinning up flyers on the bulletin boards around campus about upcoming events
[01:52] that the department was running.
[01:54] So I was often the first person to see the notice of new things happening.
[01:58] One day I was pinning up the flyer and I noticed that it was an advertisement for an internship
[02:03] with two journalists who were taking up residency at the university, Carol Marine and Don Mosley.
[02:09] They were looking for a student to join them.
[02:11] I was pinning in, I thought, "Hey, that sounds cool."
[02:14] It sounds a lot cooler than this job pinning up flyers on bulletin boards.
[02:19] Because I was the first person to see the flyer, I suspect I was the first person to
[02:23] apply.
[02:24] I never asked how many other people applied, but I ended up getting that internship despite
[02:29] being ridiculously unqualified and began my journalism career, as it was, as the grunt
[02:36] assistant to this producer and correspondent team who were doing weekly television pieces
[02:42] and newspaper columns and some long-form documentaries.
[02:46] I got into journalism as an accident and pretty quickly saw it was a lot of fun.
[02:51] It was a great way to engage with the world and learn about it and was also a challenge
[02:56] and maybe something I could do.
[02:58] I think that was amazing because I think it's important to understand that everybody's
[03:02] plight into journalism is completely different.
[03:04] It's always interesting to hear how did you get started there.
[03:08] You talk about how you kind of got into the journalism realm.
[03:11] How did you start doing more so data type of things?
[03:14] I was, as I said, pretty unqualified to work in this journalism office I was working in,
[03:20] but data and the work that I do now today quickly found me in a public records request.
[03:27] We got a tip that a local suburb of the city had.
[03:31] The tip was that a local alderman had been bid-rigging some legal contracts in this city
[03:38] to rack up some money for himself and his allies.
[03:41] To check it out, we filed a public records request asking for a list of every legal contract
[03:47] or fee that was paid out to the city, to this particular law firm.
[03:51] It was my first FOIA ever.
[03:54] After a few weeks or months, I can't remember exactly, finally in the mail came a big long
[03:58] printout, a computer printout.
[04:00] This is like a 1990s or '80s style one where it's an accordion sheet of paper, dozens of
[04:05] pages connected by the little tear strips on the outside.
[04:09] It was all the legal fees, but they were spread out in this dot matrix style across a lot
[04:13] of paper.
[04:15] We initially had the question, "Well, how the heck are we going to make sense of this?"
[04:18] I honestly don't remember or don't know where I got the idea, but I thought, "Hey, what
[04:24] if I type it all into a spreadsheet?"
[04:26] It kind of came to me.
[04:27] I sat down there.
[04:28] It took me a day or two to go through it all and double and triple check it.
[04:32] We arrived at kind of a pretty big number, a big enough number to justify the story being
[04:37] on the news.
[04:38] We kind of got our little scoop, our investigative piece, out of the tip, the FOIA, and the data
[04:43] entry.
[04:45] With that, I kind of was hooked, one, I saw the data was kind of a shortcut to getting
[04:50] to work on really cool stories, more than just kind of the run of the mill stuff, things
[04:54] I found exciting.
[04:55] Hey, as the guy who could sit down and figure out the tech, it might be a niche for me or
[05:00] a place for me to be the guy who fills that gap and helps make those stories happen.
[05:05] Those two things kind of got me going on it.
[05:07] I wanted to go further down that road, so I went to the University of Missouri and was
[05:11] a graduate assistant at IRE NYCAR, where I really got to focus on not just faking it,
[05:16] but actually learning how to do these skills, learning how to code, learning what real analysis
[05:20] was, getting a lot more practice.
[05:23] That set me off onto the path I still am today, now more than 20 years later.
[05:28] On that respect, I think that you'd grow so much as a data journalist by obviously knowing
[05:32] the practical experience, but also talking to people and collaboration and learning other
[05:39] people's tips and tricks.
[05:40] So I have to talk about your website, PowerWire, because I was like, this is amazing.
[05:44] I wish I had seen this last year.
[05:46] But yeah, like what made you want to compile all that information?
[05:50] Because it's not something that you're required to do, but it's amazingly helpful.
[05:53] Well, you know, it's nothing that happened overnight.
[05:55] It's the accumulation of kind of years and years of chipping stuff together.
[05:59] But you know, for me, the annual IRE NYCAR conference is really just kind of an opportunity
[06:04] to challenge myself and for all of us in our community to come together, to say, what do
[06:10] we want to teach each other?
[06:11] What's important?
[06:12] What have we learned in the last year that's worth passing on to other people or that we're
[06:16] excited about or that we want to share?
[06:18] You know, and I look at every year's conference as kind of that type of moment or opportunity
[06:23] and try to drum up new stuff.
[06:25] And I've, you know, been doing it long enough that I kind of got a little playbook for it,
[06:29] a little routine, and I've just been adding, you know, incrementally more and more of these
[06:34] kind of lessons that I put together with other people who helped me, by the way, of course.
[06:39] And it's become, you know, over time, this collection.
[06:43] And do you have any favorites or any talks that you have that, you know, you look forward
[06:47] to saying?
[06:48] Because I know some of them you repeat and some of them you tweak and things like that.
[06:51] But is there ever one where you kind of are like, I wish that something like this existed
[06:55] when I first got started?
[06:56] Well, I don't know if I have a favorite child, so to speak.
[07:00] To me, the best thing about it for me, there's a lot of great things about it.
[07:03] I love coming together with peers and people I respect to help create the classes and that
[07:08] sort of formative experience of us collaborating to really take an idea or a technique that
[07:14] hasn't really been fully fleshed out and trying to put it on paper and get it across.
[07:19] Like, that creative process is really stimulating and always rewarding to me, and that keeps
[07:24] me doing it.
[07:25] And then, you know, the conference itself is a great experience, but, you know, maybe most
[07:29] of all is the thing that comes out of putting it on the web and just kind of having a little
[07:33] bit of faith in the world or giving it out there is I am just often stunned to hear from
[07:39] people on the other side of the planet who I've never met, never will, who will reach
[07:43] out and say they learned this or that just based on a resource that we put on the web,
[07:47] not really knowing what would happen with it.
[07:49] And there's something that is kind of magical to that, that is a hit I keep chasing or that
[07:56] I just love, and it really reminds me of my own formative experiences on the internet
[08:01] as a teenager in the 90s, you know, I'm old enough that, you know, I remember life before
[08:05] the web and as a kid in rural Iowa, its arrival was a big deal.
[08:10] And the internet was really my kind of gateway to the world and such an exciting, stimulating
[08:15] place to learn and connect and to still have experiences like that 30 years later with people
[08:21] in Ukraine or Brazil or wherever else is just, it's the magic of technology that I find so
[08:28] rewarding.
[08:29] You know, I'm learning about your plight to where you are today and you went from not
[08:33] knowing that journalism was something that you even were interested in to creating an
[08:38] entire news applications desk.
[08:40] How did you know that that is something that that newsroom needed and how do you operate
[08:45] in that position?
[08:47] Not sounding too grandiose or self-assured, I think we are entering kind of a new era
[08:53] of data journalism in kind of the commercial space, commercial media, which is I think
[08:58] one of industrialization and specialization.
[09:02] You know, when I started out at the LA Times in 2007, the whole idea of putting data on
[09:07] the internet on a newspaper website was still a pretty new one.
[09:11] We weren't the first to do it for sure, you know what I mean?
[09:13] But in our context, it was definitely new, and I think a lot of what was going on even
[09:18] at the leading news organizations then was really experimental.
[09:21] You had really small teams of people kind of goofing around trying to make things happen
[09:25] on the web, often totally separate from their mainline newsrooms.
[09:29] You know, it's good to remember that it was that 2008 election was probably really the
[09:33] first one where you had really widespread live election results on newspaper and news
[09:38] organization websites.
[09:40] When Obama was first elected, they did, there was examples of that before, but the really
[09:44] kind of first like widespread publication of it was that time.
[09:49] And it was really kind of an experiment that was then wildly successful.
[09:53] And I think there's been many other examples since then running up to coronavirus trackers.
[09:59] And you can go down the list of all these different ways that taking data directly to
[10:03] the audience in the form of dashboards and databases and visualizations that aren't traditional
[10:09] stories, you know what I mean?
[10:10] That has gone from an experiment to really a widget or a product that we want to manufacture,
[10:16] you know, inside the metaphorical assembly line or factory of your newsroom.
[10:22] And so it's my view as we enter, as we want to go from experiment to mass production,
[10:28] we need to, you know, institutionalize, specialize, and really ramp up how we are organized to
[10:34] create these widgets, you know?
[10:36] And in my view, that means making a news desk, which is its own little assembly line in the
[10:40] factory that focuses not on the kind of battleship investigative reporting projects, not necessarily
[10:48] on kind of one-off graphics to accompany traditional text stories, but instead on these data products,
[10:56] whatever you want to call them, that are incredibly popular with audiences and are also, it could
[11:02] be Capital J journalism as well, right?
[11:05] And so this news application's desk is our attempt to name something that does that.
[11:10] I don't know if I love the name, if you have a better name, I'd love to hear it, but that's
[11:15] what we mean.
[11:16] Basically, that's what we're trying to do here at Reuters, is to create a group of people
[11:19] who just focus on making that type of thing.
[11:22] I think that's amazing, especially because, like you said, we're moving towards a time
[11:26] in data journalism where I like to say that people almost expect data to be in the story.
[11:30] That's become way more normal, and so I think it's amazing that you guys are thinking about
[11:36] this.
[11:37] Yeah, I think we can't forget that.
[11:38] I think because data journalism grew out of the investigative reporting tradition, or at
[11:43] least a large part of it did, there's many streams and strands, there's not one way.
[11:47] But the IRE/NICAR tradition is really one that stems back to investigative reporting,
[11:52] which is really what I was trained in and what I love and respect, and I've done a lot of
[11:56] it in my career, but the justification for that type of work, for the investment, for
[12:01] the dollars to be spent to fund it, is typically one that's based on prestige and public service,
[12:08] which are two of the very high call-ins of our profession, but in a time of decreasing
[12:14] resources and brutal disruption to the economic model that supports journalism, it can be
[12:19] difficult to justify jobs and investment in data journalism if it's strictly seen as a
[12:25] prestige project, so that's bad news, baby.
[12:28] But the good news is, and I think we often undersell this good news, is that these data
[12:32] products I'm talking about, your live election results or your coronavirus tracker, these
[12:37] are, yes, they are public service, and yes, they ought to be seen as prestigious.
[12:41] They have won some of the highest awards, but they are also popular, right?
[12:46] I think last year, Reuters.com, the most popular thing all year, were the live election results
[12:52] done by our team in London, led by John McClure, and the most popular thing in the history
[12:57] of the Los Angeles Times, where I used to work for the most read piece of journalism
[13:01] in the 100-and-whatever-year history of the LA Times, was its coronavirus tracker, and
[13:06] I suspect the same is for the New York Times and many, many other news organizations, and
[13:11] I think we shouldn't sell ourselves short.
[13:14] We're making things people want.
[13:17] A lot of people say journalists and math don't go together, or a lot of journalists aren't,
[13:22] I guess, set up naturally to do data, stuff like that, but what is your advice for someone
[13:26] who wants to get into that realm of things?
[13:29] It is a hot commodity right now, and it's an amazing skill set to have.
[13:33] Well, then, that's your advantage.
[13:35] You know what I mean?
[13:36] If other people are avoiding it and you're willing to take it on, that's going to give
[13:40] you the edge, that's going to give you the front foot, and I think you should not listen
[13:45] to people who are discouraging you to not go down this road if it's where you want to
[13:49] go, because, as you just said, we know it's where things are headed, and we know that
[13:53] it's valuable, and so don't be afraid to have the confidence of that and surround yourself
[13:59] with people who agree with you and find mentors and role models that'll help you move down
[14:05] that path.
[14:06] It's a lane that's wide open.
[14:08] What are some things that you live by when you're doing data analysis and news application
[14:13] creation?
[14:14] I don't know if I can rewind.
[14:16] What would I tell younger me?
[14:17] I mean, I've studied harder in high school, you know what I mean?
[14:21] I don't know.
[14:23] I don't have any regrets or any big thing like that.
[14:27] There's reassurance, I think, we all need when we're young and that I needed like everyone
[14:31] else, which is if you work hard, it will pay off.
[14:35] I've seen that in my own life, and I've seen it in many others, and I would just encourage
[14:39] people to ... I almost said lean in.
[14:41] I won't say lean in.
[14:42] I'll say work hard and be a good person and it'll work out.
[14:48] That's what I would tell myself because I was a very nervous, young, country kid in
[14:51] the city.
[14:52] As far as the work we're doing, I mean, to me, you got to have high standards for yourself
[14:58] and you can't cut corners and you got to do the work.
[15:02] I think that that means coming in every day like you got something to prove, not being
[15:07] afraid of challenges and realizing that by pushing through them is how you're going to
[15:12] do something you're proud of.
[15:14] Don't be lazy.
[15:15] It's the same message maybe, but it's really what I believe.
[15:18] I think it's all about progress and push and not giving up.
[15:23] I have to ask some things.
[15:24] Do you prefer Python or R?
[15:26] Why?
[15:27] I'm definitely a Python person, but I respect R and really about the results.
[15:33] I think there's a lot of great and talented people who work in R, but Python is obviously
[15:38] superior.
[15:39] I agree.
[15:40] I wholeheartedly agree.
[15:43] And then I wanted to ask, what is your favorite data journalism memory?
[15:46] Something that if it's a story or maybe an interview or just something that happened
[15:50] where you're just like, yeah, this is the career for me.
[15:52] Well, there's that first story I told you earlier where I kind of had the spark of the
[15:56] light bulb went on.
[15:57] This could be something for me.
[15:59] To me, the most powerful moments are often, and maybe it does go back to those investigative
[16:04] pieces, but when statistics and data lead me to someone's doorstep or to somewhere in
[16:09] the world and help both me, the journalist who's trying to figure out the story, but
[16:15] more importantly in the moment and maybe in the cosmic sense, the people who lived the
[16:20] story helped them better understand what the heck happened to them in life, particularly
[16:25] if it was something bad.
[16:27] I did a whole series of stories about the local 911 system in Los Angeles where we uncovered
[16:33] a lot of systemic flaws and how emergency care is delivered, how the fire department
[16:38] is run.
[16:39] And some of the most powerful memories they had is where the statistics would tell us,
[16:43] well, there's this kink in the system.
[16:44] There's this inefficiency, there's this problem, and it could be having really bad effects
[16:48] out there in the world.
[16:49] But then we followed the data, individual calls out to doors and knocked on them to
[16:53] see what really happened in this case or that case where the data says something maybe went
[16:57] wrong.
[16:58] And what we found often is, yeah, it did go wrong.
[17:00] And so there's this way in which you kind of discovered a story based on a spreadsheet.
[17:05] But then also there's this powerful moment of connection with the person on the other
[17:10] end of the journalistic exchange where you help them understand why something bad happened
[17:17] in their life and help them be part of an effort to describe and share that with their
[17:22] community so that maybe it can be fixed and it doesn't happen to someone else.
[17:26] And to me, those moments of where statistics and shoe leather and the kind of connection
[17:31] with a subject come together are kind of these magical moments that data does make possible
[17:37] because when you don't just go off your own bias or instincts, when you let the math and
[17:42] science lead the way, you can have these powerful moments of discovery.
[17:46] And they're not the same as Albert Einstein and E=MC squared or whatever.
[17:51] But they are powerful.
[17:52] And so I struggle to describe it and contextually it would be almost impossible to give you
[17:57] every detail of what that was really like without writing a novel or something.
[18:01] But like those moments of discovery and connection where statistics and shoe leather meat are
[18:06] intense.
[18:11] To access Ben Welsh's site and his resources, be sure to check out p-a-l-e-w-i-dot-r-e.
[18:20] You can also find the link in the description of this episode.
[18:24] Reporting for IRE and Nightcar, I'm Nikkyla Carter, and this has been an episode of the
[18:29] IRE Radio Podcast.
[18:31] Doug Meggs edited the script of this episode, and we are recorded in the studios of KBIA
[18:37] at the University of Missouri School of Journalism.