Claire McKay Bowen on the Role Federal Statistics Play in our Daily Lives

On the latest episode of Data for the People!, Claire McKay Bowen discusses the role federal statistics play in our daily lives, strategies for communicating the value of government data, and her vision for the future of data sharing and data privacy. 

Bowen is a data privacy expert who is currently a senior fellow at the Urban Institute, an adjunct professor at Stonehill College, and a board member with the Association of Public Data Users (APDU). Last year, she co-authored a series of blogs for APDU about the manifold ways federal statistics inform routine decisions for Americans, how federal data is like the “forgotten egg” used to bake a cake, and what educators can do to teach K-12 students the origins and importance of U.S. federal data. 

Bowen also discusses a recent article she wrote for the Journal of Economic Perspectives titled "Government Data of the People, by the People, for the People: Navigating Citizen and Privacy Concerns." 

The Data Foundation is currently reviewing submissions for the People’s Data 100, an initiative to recognize federal datasets providing the greatest value to Americans. The conversation with Bowen is part of our broader effort throughout 2026 to spotlight the strategic data infrastructure that powers daily life in the U.S., from protecting public health to enabling scientific discovery to safeguarding taxpayer-funded benefit programs.  

In the spirit of the initiative, learn more about the AirNow system that supports the Air Quality index provided by BreezoMeter on the iPhone's weather app. AirNow is a partnership of the U.S. Environmental Protection Agency (EPA), the National Oceanic and Atmospheric Administration (NOAA), the National Park Service, NASA, the Centers for Disease Control, and tribal, state, and local air quality agencies.

Want to be part of a national community that promotes policies that enable government data to be high-quality, accessible, and usable? Join our Data Coalition: https://datafoundation.org/pages/join-the-data-coalition

The Data Foundation is a 501(c)3 nonprofit, nonpartisan think tank. All contributions may be tax deductible. We appreciate all charitable contributions towards fulfilling our mission to make democratic society better for everyone by championing the use of open data and evidence-informed public policy. Donate: https://datafoundation.org/supportus

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Transcript

SPEAKER_00 0:07

Welcome back to Data for the People, a new podcast from the Data Foundation that focuses on the invisible infrastructure that powers daily life for Americans and the changes in Washington that could enhance or limit its use. I'm your host, JP Wogan, and we're here with Claire McKay Bowen, a data privacy expert who is currently a senior fellow at the Urban Institute, an adjunct professor at Stonehill College, and a board member with the Association of Public Data Users, among other affiliations. Welcome, Claire.

SPEAKER_01 0:39

Oh, thanks for having me.

SPEAKER_00 0:40

So back in November of 2025, I came across a blog that you co-authored with Aaron Williams, a data scientist and colleague at the Urban Institute, titled A Day in the Life with Federal Government Data. And I love this blog because at that exact time I was thinking about ways to better capture the story of federal government data and what it means in concrete terms for people, for companies, for organizations. And here in this blog, you and Erin detail more than two dozen federal data sources that inform and enrich our daily routines, plus, by my count, something like another dozen or so data sources that support significant like decisions like where to send your kid for daycare. And of course, this blog was part of a series you penned for the Association of Public Data Users. So I'd love for you to talk a little bit about, well, I'd love for you to give some of those examples for our listeners. But first, would you mind talking a little bit about what inspired the series and feel free to explain the forgotten egg analogy, which I really enjoyed in one of the blogs.

SPEAKER_01 1:49

Yeah, it's so I will just say that it this all started thanks to Erin when we were discussing like how we can contribute to the conversation. There's been, of course, a lot of talk about like what's happening with our federal data and the infrastructure, the federal statistical system, but there was like always the same voices talking to the same people. And so the conversation that we had was how can we go beyond the usual voices and reach out to a different group of people? Because like if you're talking to the same folks, like they all know federal data is important. It's the people who don't know it's important. And that was the inspiration for that. And so that's why we kind of introduced like this forgotten egg analogy that you just pointed out, because it is like everybody sees the cake, but they don't think what's the ingredients inside of it unless you tell them, right? And so that's that goes into exactly why we need to talk about this and like why people don't know where federal data is, is is like unless somebody specifically told you or you had a firsthand experience about federal data, like you just right, you just wouldn't think about it. I mean, that's human nature. Like, unless somebody points out something to you, you're just gonna go on live thinking, like, well, that's it. Or maybe if you're curious, but that's pretty rare. Actually, recently I was talking to my friend who she's the breadwinner of their household. She's the one who goes to work. But she was talking about how her daughter came up to her and says, like, dad is so cool. He bought me X. Isn't dad great? And it was one of those moments where she thought, like, you do know, kid, that I am the one who brings in the money to buy that thing, right? But I know this is a very simple example, but we we're all children. And unless somebody told us like that money that dad used to buy the thing that you wanted came from mom, right? Like you would not make that connection at all, right? Again, like imagine all of us are children. And then, like, even taking like a step further, thinking about like why is it that we don't learn about federal data or why it's really important? Like, do we actually teach that at all? No, right. Like, if you go through K through 12, if you even talk about data, it's like very high level or it's like data viz, because that's really accessible, which that makes sense, but really there's no part in there that we say, like, where does data come from? How do you collect data? Where is data stored? How do you access that data? How is it transferred? What is the infrastructure behind data, right? Like that ever, that's never taught. It's always not a standard. And then you think, well, what about post-secondary education and maybe going to college? Same story, right? I meet a lot of students, and I teach this one summer course, it's for professional master students. It's on data analytics, it's focused on security, privacy, and ethics of data. And we go through the whole life cycle of it. And that's the usually the first time that they ever hear about how is data actually collected or are collected, and what are the impacts about asking questions a certain way on the form or not asking questions on the form or anything like that. That's their first exposure to it. And at this point, they are getting their master's degree. And that's because I put the extra effort into teaching that to them. And if that doesn't happen, then like where else? Right. So we need to, I as a society to like think about like how we approach this, especially with AI coming into place, right? So some people think, oh, is this actually important? Do we need to teach this? And the answer is yes, because we are going to be thinking about more and more about our information, how it's being used for something that's very much in people's faces. So I think this is like a really crucial and really poignant time to be talking about our federal data or and private data and how it's being used for these algorithms and pointing that out to it.

SPEAKER_00 5:42

Going back to that blog and the two dozen or so federal data sources that are informing decisions and enriching a person's life in routine ways. What are some of your favorite examples from that blog that maybe people wouldn't think about?

SPEAKER_01 6:00

I mean, I'll give you kind of the typical boring one and then one that's like more personal to me. So the boring one is that I mean, Google Maps, right? I think that's one that lots of people use and would be very much like, oh, this is very useful. I use it all the time to go explore a new city or even just see what the traffic is like or anything like that. And they all think that data belongs to Google, and some of it is refined by Google because they have those little Google cars that go around, but it is powered by Census Bureau data. And without it and other government data that goes into it, you would not be able to use Google Maps like you do. And I got to experience this firsthand when I went to go visit my mother in South Korea this last fall, where I didn't know this until I opened up my phone trying to figure out like where is my mom's house? And the the address got put in, but there was no turn-by-turn direction. You could only know that there was a bus that maybe was kind of close by, but it wouldn't give you more information than that. Just like here's the local bus or here's the local train station and the times and the next things going, but there is no direction around. So it was very interesting to navigate Korea without it. And it's actually one of the few countries that doesn't provide the data. And so having to go through that is like, oh, okay, well, this is obviously one of my favorite data sets because this is something I use all the time, especially because as a runner. So that goes into like the more fun, maybe less boring, is that I really appreciate the fact that the National Park Service and like Department of Transportation and like all these other places collect information on like where people are traveling and where open spaces should be, because I live in New Mexico and I love running on the Bosque because where I'm at is like it's really hilly and mountainous. And so sometimes I have to like, because I'm a serious runner, I try to hit certain kind of workouts and hit my intervals. And that's really tough when the terrain is very much up and down. And I say up and down, I'm over at 7,500 feet. So, like, just to give you some context there about like it's really mountainous where I'm at. And so being able to go to this place called the Bosque, where it's a nice open space, it's paved, there's a dirt portion for it, and it goes for miles. It's great for training. And that's something that is a resource that the city of Albuquerque decided to invest in and using federal data to determine that and know that's a need.

SPEAKER_00 8:29

I was curious how long it actually took to research the government data sources that link back to those different parts of your daily routine. And I I can talk a little bit more about why I'm asking this question, but I suspect it's not always like you know it top of mind, or it's really easy to find. Did it take some work to figure out which federal data sets kind of connect back to these things that you're refer uh describing in the piece?

SPEAKER_01 8:56

Yeah, some of them were easier and they didn't take very long because like either I knew a top of mind or I knew what to look up, but some of them were really tough. And I think that's an indication of like what we value in not only as a society or what we value in research specifically. So you would think, hey, wouldn't researchers be good about citing where the data comes from? And they're they're not. Like it's it's really tough.

SPEAKER_00 9:21

Connect back to these things that you're describing in the piece?

SPEAKER_01 9:25

Yeah, some of them were easier and they didn't take very long because like either I knew the top of mind or I knew what to look up, but some of them were really tough. And I think that's a indication of like what we value in not only as a society or what we value in research specifically. So you would think, hey, wouldn't researchers be good about citing where the data comes from? And they're they're not. Like it's it's really tough to actually like if you go through some papers, some of them don't give the right credit of where they got the data from. Sometimes they'll say a name and you're like, okay, great, but where do I find it? And there's no proper citation for it. And that is the same for public data for certain like amenities that you use. It's not like a lot of like, let's say, financial institutions say outright that they use certain data sets, like the Department of Transportation to know like where the roads are going, or Census Bureau data to know the demographic information to figure out like, should I put an ATM here? Should I put a bank here because of like the growing number of people are coming to this one city, or the way that the traffic flow is, or things like that. It's like they're not going to advertise that. So you have to dig in a little deeper. So I will say it took, I mean, I'm trying to remember how many, it took a few hours to dig into some of them. Like I kind of drafted like what would be my typical day and what, or maybe some other things that people would do, and then try to see if I could research and find all the data sources that impact all those things. And like to your point, some of them were easy and some of them were just hard, and for the reasons I pointed out, and many others too, but those are the ones that come at top of mind.

SPEAKER_00 11:01

So I had this instructive experience. The data foundation is currently, we have this initiative called the People's Data 100, where identifying federal data sets that provide the greatest value to Americans, you can define value how you like from public health, environment, economic prosperity. And I decided I should walk the walk. If I'm you know posting on social media, writing in our newsletters, please submit nominations. I should submit one myself. I wanted to do one that felt authentic to me. So I was trying to find a federal data set that informed the air quality data that I get on the weather app on my iPhone. So I looked on the weather app on my iPhone and it says the air quality index comes from something called BriozoMeter. So then I looked on Briozometer's website, it takes me to an EU program that uses BrizoMeter, although Briozometer was also purchased by Google, I think, in 2022. And both on Google site and the EU site, it's not obvious. You know, I'm able to determine that there are governmental monitoring stations in the US that are providing data to BrizoMeter, which then gets it's one layer of information that gets combined with other layers of information and some modeling that takes place, but they don't actually say which government data sources. So, you know, then I thought, okay, well, I'm gonna see if I can, if I Google it, what if I if I consult with Claude? I asked a couple friends, one who worked used to work at NOAA, someone used to work on climate change issues for USAID, and I thought this would be really easy to establish that it came from a specific agency. Eventually I found some subpage where it was uh an Air Now federal data system, and that's a partnership across many agencies, including EPA and NOAA. But I I thought it was interesting that the Breezo Meter doesn't advertise it very well. Air Now itself doesn't advertise it. But I wonder how many other cases there are like this where there's a private data product that is built in part on public data, and there's not an incentive to advertise what federal data sets are helping make this data product available to people.

SPEAKER_01 13:27

Yeah, I think that goes like exactly what I was saying about like, oh, you it it gets really tricky, right? So doing that everyday life with federal data, I run into the same same issues. And like you said, there's no incentive. Like you see Google Maps, they don't say like thanks to the US Census Bureau for the sh the shape files that they use for doing the turn by turn or anything like that, or thanks to NOAA for this contribution for when I go to underground weather is the app I use for for weather, right? Like they there's no thanks to the blank. And it's actually a project I give my students or a homework assignment, is that after we have a discussion, I say, like, okay, well, now go find how a federal data set helps your community and talk about it and like why it's important and how you get it. And some of them really struggle, right? Just for the same reasons, but that's a part of a homework assignment. And then hopefully they learn why it is important and why it's front and center. So it goes, I think this goes full circle to like the earlier points like why people don't know. It's like we don't advertise it, we're overwhelmed with a lot of information already. So if not in our face, we're never gonna know. And so it's nice to actually had a couple of students who were originally from Canada, another one from France, and they talked about the data sets there because I didn't specify that it had to be a US data set. I said it had to be a government data set. And one of them is really into hockey, which I can guess which country that was, and talked about like the Canadian tourist industry and like StatCAN and like how that was the decisions to like build certain facilities for their the hockey stadium. And I thought that was really interesting. But he said, like, I didn't think about this until this assignment to go through and discuss these things.

SPEAKER_00 15:13

I want to switch gears here and talk a little bit about your research focus on data privacy. You wrote a paper in the Journal of Economic Perspectives with a title that could not be more appropriate to discuss on this podcast: government data of the people by the people, for the people, navigating citizen privacy concerns. And full disclosure, I had not seen this paper when we came up with the name of our podcast, but obviously great minds think alike. I really appreciated the framing and explanation about how you think about the public's relationship to data with the phrases data of the people, by the people, and for the people. Would you mind walking listeners through what you mean when you say data of the people, data by the people and data for the people?

SPEAKER_01 15:59

Yeah, happy to. I mean, I came up with this phrase because I was like presenting on something and then somebody had a QA. And I just was like, well, because okay, so backing up on the the talk, it was uh a discussion about the importance of of data. And somebody made this like, well, why should we even be like talking about this? And it just struck me so hard. I was just like, this is so important. This data is of the people because it's your information, it's being collected. You're part of this data because we need to know who is in what place. If we need to go rescue them in case of like emergency evacuations, like I think of my my mother-in-law living in this remote area of Idaho where there is no cell service and we need to know that she's there so we can go rescue her because she is an hour and a half drive to the nearest big city. And so it is of the people for that reason, many others, trying to get other kind of resources out there. It is by the people because it's your taxpayer dollars that funds these data sets. I think people don't realize that like your taxpayer dollars is the ones that fund for it. So, like, you should then make sure that it is for the people, is for you. It's for our communities for the reasons I just said, like rescuing, I would want you to arrest my mother-in-law. Please rescue her if there was ever a flood or a forest fire because she's in Rome, Idaho. But it's also thinking about making sure we have the green spaces, right? I'm thinking about more nature here, but then it's also making sure we have hospitals and police stations and other services provided for our communities. That's what the federal public data sets are for. And they trickle down to our local communities. It's essential for that. That's why people just don't realize, like, we just have it, right? So once it's gone, that's when we'll realize how important it is.

SPEAKER_00 17:49

I love that. And it's similar in intent to why we named our podcast Did for the People. I think part of what I was trying to do was convey the idea that these federal data sets are public goods in the same way that maybe public roads or libraries or schools or fire stations are. But we're frequently describing it as this invisible data infrastructure because there isn't the same physical manifestation of public data. I don't know what this would look like, but I can't think of public data vehicles or buildings or personnel. It's not like there's a public data uniform of a public employee that I would recognize and encounter every day. And in the context of the past year, when budget cuts have resulted in reductions in workforce and capacity in federal data and evidence, I'm thinking through how one articulates what is lost or in the future could be lost when these kind of abstract, largely invisible data sets go away. Do you have any thoughts about? We've already talked about a few ways that you're trying to get that story out, but is there anything else that you're doing or you think folks who care about this issue should be doing to make data infrastructure visible?

SPEAKER_01 19:00

Yeah, making it visible. That's it's really tough. I'll try to keep this concise, but obviously I get really passionate that I talk too much. That's my problem. The the thing is that it involves people, involves tools, and involves regulations. But I also think it involves like we need to change the way we talk about research and communicate with the public. We need to shake things up a little bit. Like it's good that you have this podcast. It's one way to reach out to people. It's glad that people are doing data visas. So going to like the people and tools right here, that's very broad buckets, but kind of in line about the way we can communicate with folks. Like what we did before in past generations is not the way we should be communicating now, right? I've been talking with my nieces and nephews, and it's like everything's on Instagram and TikTok, right? And it's a different kind of style on how you communicate. And that's what they're what they're seeing. And so I think we do need to change up how we reach those audiences. It's the whole like you make short little blips, you you try to do a quick video. Maybe I found out memes are no longer cool. Like I put memes in my course notes and it resonated initially when I first started teaching. And this last year, this last summer I taught my class. The students were like, Yeah, memes are not in. And I was like, Oh, crud, I gotta, I gotta do something different to capture my students' attentions, right? And so this goes into like, we need to evolve with the times. And unfortunately, that costs money and time, right? Like, people don't want to, like, oh, we have another thing we need to do. But if you really want to break through the noise, that's what you need to do. So getting people on board on this, and then probably think about the tools to do that in the vehicles of, like you said, uh, I do think blogs are still good, but I think everybody's now writing blogs, just like you said, everybody's doing podcasts. So you got to figure out the mix of things that's gonna work with you and resonate with the audience as best as you can. I said regulations, and that's just kind of a broad thing because I think there's different things that different people can do. And so when it comes to regulations, we still need the people who are digging in the technical details and informing the public policy makers about what's really important. There is some new proposed legislation through Lori Trahan about updating the privacy act. And I really appreciate one part, which is when we talk in data privacy and the and the broad techniques and tools you can use, they call it privacy enhancing technologies. And when sending a letter to her through the American Statistical Association and the Association of Public Data Users, we kind of stress that, like, well, it's not just the technologies because you think about like a computer or simulation or like this, like all these like really fancy tools, like super multiparty computing, differential privacy, like all affederated learning, right? But you still need to put techniques in there because the simple things are still really important. So saying that, like just doing something simple like suppression, which is removing a person from the data. Set because they're too identifiable, or rounding up values, or grouping up people. Those are very simple techniques that could still work really well. And that goes back to the tools and people I just mentioned, because some people are not trained to do this really fancy super multi-party computing, or they don't have the tools to do it because there's not what I sometimes tell people, there's not enough bikes on the road. So you don't need to build a bike in order to ride it. But unfortunately, we're in the space where there's not enough bikes for people to ride. And then training the people to learn how to ride a bike. Because again, we're all children at the start, like I said in the beginning. Like we're just all kids and we're trying to learn what's going on. So it comes back in the full circle of again, like thinking about how we can reach out to people and train up people. It's the tools to get to those people with all the different things and maybe implementing the endpoints that we want and then thinking about the regulations that kind of support those people and tools.

SPEAKER_00 22:55

So you're already getting at this a little bit, but in that journal of economic perspectives paper that had the nice framing about of the people and by the people and for the people, you begin actually with a similar structure to that blog on day in the life with federal data, in the sense that you're detailing daily routines and how your use of different digital technologies results in private companies having a lot of information about you and your habits and even maybe major life events like if you get married, they they might be able to know that from the registrations in a race that you did for a triathlon. I understand you were recently asked at an event whether, in light of these ubiquitous apps and all the data that these companies have, if data privacy is dead, and what is your answer? Is data privacy dead?

SPEAKER_01 23:44

Yeah, I thought that was really interesting when the person said, like, hey, I think data privacy is dead. Like, what is your response to this? Like, what are we going to do forward? And there, there it's multifaceted. So we'll we'll just go to the right. The punchline is like, we need to not focus on it being dead now. We need to figure out what we can do in the future. And that goes back to what I just previously said. It involves like how do we train up people and get people involved and excited or push certain legislations and then the tools to empower those people to use the data in the right way and thinking about how we can think about privacy and then it's the regulations because what it doesn't matter how strong people are to like to code things up, to make those tools, to get everything together. We still have a lot of data privacy laws that don't all speak to each other, like FERPA and HIPAA, Tau 13, TAL26. And I'm naming all these things, and it's because we have all sorts of federal data laws that govern different kinds of data sets, let alone the fact that every locality up to the state level has different privacy laws and they all all speak to each other. So sometimes you can have somebody down the hall and you're in the same agency, but because you work on different data sets, they might not be able to speak to each other. So that gets really tricky. And so the future has to be about for data privacy is to tackle all these issues and think about that future. Because if we don't try to do anything now, we lose ground and that's gonna impact the future generation. So that's why I think about a lot is like how am I gonna help that next generation and how we keep moving that needle forward. It gets even deeper if we want to about like what do you mean by privacy being dead, right? Because some people are like, well, the federal government always has a lot of information on me. Like that's invasive of itself. But then some people don't know that data brokers, those who collect data from third-party private companies, it's a multi-billion dollar industry, and not realizing that how much that is driven. And so that goes into like, well, then what can you do about your privacy and what does that privacy mean to you? Because I bet if we asked all the different people, they all have different definitions of privacy and what that means. That goes all into say that we need to think about how we can properly govern it and who do we trust to govern it and to use it in a safe manner. So again, going back to that my theme of people, tools, and regulations, we got to figure out like how all those three things can come together and govern our information in a way that we feel that our data is being used responsibly. And that's actually the kind of the vision statement or impact statement or however you want to say for the group I'm in, that we say like everyone being responsibly represented in data.

SPEAKER_00 26:24

You know, there's so much discussion right now about data removal or data, you know, harder to find data. What about if you if you were Queen for the day and could commission new federal data collection activity? Is there something you wish that the government collected data on that it doesn't right now?

SPEAKER_01 26:42

That's a really tough thing because we do collect a lot of information, a lot of things, and you can piecemeal them together. I think one of the big things I would say is like making sure they're all linked together properly and collected in the appropriate manner. So it's not quite what you're asking, but I would say if we're gonna do a new federal data collection activity, I want to be like, can we all agree on how we define blank and then move from there? Because we all have different terms for the same thing. So for instance, I'm learning more about children's services data and they have different definitions for ant. Like that's crazy. Like, how do we have different definitions for ant? Right. So just like, can we just have a standard across all these federal government agencies on like how we define very basic things, let alone the fact that there's like if we can't define ant, what happens when you're trying to think about neglect? Right. That's a very broad term. Some people are like, well, obviously, we know what neglect is. And it's like, no, there's different qualities or quantities of that, right? And that's really important in order to help our children. And so that goes into the point of like, if I were queen for the day, I would just fix how we are collecting data and how we're defining it and how we're standardizing it. Because that's actually one of the biggest problems right now is that like the silos of data sharing between within the state, across states, and then states to federal, some of it's just because they literally don't speak to one another properly. And so it's just that much harder to make sure that data sharing happens. And then if there were those sharings, like would I link any of them? And I think one of the ones I think would be really powerful and it's kind of more closer to home for me, is thinking about our educational like longitudinal data systems data. So they're called SLDSs or state longitudinal data systems. They're usually like pre-K to K. They can have post-secondary, they can have other kind of links. It depends on the state, because it's for 40 states in the District of Columbia that has these data sets. So not all 50 or the territories, but it's a vast majority, but they're all different variations of quality. And so I would very much would like them to be all the same quality and then link them to certain programs. And what gets closer to home is like, I think it would be great if it could link to like foster care or other like children's services or human services data. And it's close to home because like my mother's adopted, and she was actually one of 11 kids because my grandparents were crazy, and they decided, like, in addition to the four kids we have, we're gonna adopt seven more. And just imagine, like, they they kept adopting kids because they were all having really bad conditions. And I keep thinking, like, well, if we had better data and we knew what was going on, then like we could save more kids, like my mother.

SPEAKER_00 29:34

So better data standards, better data definitions, and then linking those data sets once we come to some agreement about definitions and standards. That on its face seems like it should be achievable. I'm sure that there are many obstacles and it's like every everything in life, it's harder to do. But I hope we get to see that vision come to fruition. Claire, thank you so much for talking with me today.

SPEAKER_01 29:58

Yeah, thank you for having me.

SPEAKER_00 30:01

Thanks again to our guest, Claire McKay Bowen. In the episode description, we'll provide links to the blog series that Claire co-authored with Aaron Williams on the role of federal statistics in our daily lives. I'll also link to Claire's article in the Journal of Economic Perspectives titled Government Data of the People, by the people, for the people, navigating citizen and privacy concerns. As always, thanks for listening to Data for the People, a podcast from the Data Foundation. If you liked this episode, please subscribe and leave us a review. We're available wherever you listen to podcasts. Learn more about the podcast and the rest of the Data Foundation's work at datafoundation.org.