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Bridging Data Gaps: Nancy Organ on Making Data Visualization Accessible for All Ages
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In this final episode of the season, I welcome Nancy Organ to the show to discuss her new book Data Visualization for People of All Ages. Nancy’s book aims to make dataviz accessible to everyday readers. Our conversation highlights the importance of not altering data simply for aesthetics but to facilitate understanding. We also explore balancing creativity with informed design choices, and suggest alternatives to traditional graphs, such as infographics, timelines, flowcharts, and diagrams.
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Transcript
Welcome and Reflections on Season 10
00:00:12
Speaker
Welcome back to the Policy Vis Podcast. I'm your host, John Schwabisch. This is the final episode of season 10 of the Policy Vis Podcast. Thank you so much for tuning in. I hope you've enjoyed this season. I have talked to so many.
00:00:28
Speaker
Great data visualization and presentation practitioners and researchers and analysts. I hope you've learned a lot over the last few years. Over the next couple months, take some time. Catch up. Relax. You're on the beach. You're hiking. You're hanging out with friends. Throw in your headphones. Throw on your AirPods. Listen to a couple of episodes. Catch up.
00:00:50
Speaker
so that you can be ready for the fall where I've already got folks lined up for another great season of the show.
Introduction of Guest Nancy Oregon
00:00:57
Speaker
But on this year's season finale of the show, I love saying there's a season finale, by the way, because I get a break from all the work. But on this final episode of the season, I have a special guest, Nancy Oregon, author of the new book, Data Visualization for People of All Ages. We talk about what that means, what it means for
00:01:18
Speaker
kids to learn about data and data visualization and how we can engage them and the different challenges of teaching data visualization to five-year-olds and 65-year-olds. We talk about Nancy's process for writing the book. We talk about the challenges about teaching data visualization and we talk about how we think schools and education programs might integrate data visualization
00:01:44
Speaker
into those curricula. So there's a long good conversation here about the new book. I hope you'll check it out. It's really, I think, a great book to help you learn the fundamentals of data and data visualization. And so I hope you will check it out at the CRC press site at Amazon or wherever you get your books.
00:02:01
Speaker
Now, just a couple of things before we go for this season. First off, I want to thank everybody who has listened to the show, all of my guests that have come on over the last nine or 10 months. And of course, everyone who's helped me build the show from sound editing to the YouTube channel to creating the website and all the content. This is not an easy show to put together.
00:02:23
Speaker
It sounds easy. I'm sure you're listening to it like, oh, this is just a breeze. There's a lot that goes into this show all the way from scheduling to recording to editing to all the materials that go out when the show is produced along with the newsletter where I write up a little bit about each and every episode.
00:02:41
Speaker
That's first thing, second thing, if you wouldn't mind, please take a moment to rate or review the podcast on your favorite podcast provider. That might be iTunes, it might be Spotify, or it might even be on the Zencaster website where I do a lot of the recording. The podcasting market is kind of interesting how it's evolving, but I think iTunes and Spotify are the primary places. So if you wouldn't mind, please take a moment, leave a rating, leave a review. If you don't want to do that,
00:03:07
Speaker
Head over maybe to Amazon and leave a rating or review for one of my data visualization or presentation books. There's better data visualizations, there's better presentations, there's elevate the debate, and of course my new book, Data Visualization in Excel. Okay, with that out of the way.
00:03:23
Speaker
I'm going to head over to my interview with Nancy Oregon. I hope you will enjoy it. I hope you'll learn a lot. Again, thanks so much for tuning into the show. Have a great summer. And here's the final episode of this 10th season of the show. My interview with Nancy Oregon, author of the new book, Data Visualization for People of All Ages.
Nancy's Journey and Book Inspiration
00:03:43
Speaker
Hi, Nancy. Great to see you. Great to meet you. I guess, like... Great to meet you. Right? In person. For real. At the same time. Yeah.
00:03:53
Speaker
as opposed to like endless emails. And I'm sure like attending the same thing simultaneously that we did early. Yeah. Totally. Smallest world. Smallest world. Yeah. Especially the date of his world, right? Like the smallest world. Absolutely. So thanks for coming on the show. Great new book.
00:04:09
Speaker
Thank you. Data visualization for people of all ages. We have our matching, our matching copies. And your poster in the back, right? You've got like the date of his theme in the back. Mine is a little bit more effective than that. So I'm excited to chat with you about writing a date of his book for all ages. Like, you know, thinking about everybody.
00:04:32
Speaker
But maybe we can start with intros. It's a little easy for you to be like, oh, I did this, this and the other. But maybe sort of talk about, you know, where you started and how you got to the point where you're like, there needs to be this book and I'm ready to write it. Totally. Great, great, great.
00:04:51
Speaker
Well, um, I'm Nancy. That is true. Start the present tense. So more than anything, I'm a database practitioner, which means that my career, my days are dedicated to using data visualization to help people share what's the most important to them.
00:05:10
Speaker
I say all the time that my job is the fun part of so many scientific and analytical pursuits because I get to take the end result or, you know, that's a little hand wavy. We work on it the full trajectory, but I get to make it impactful and actionable and pretty and fun and expressive. So yeah, my job is the fun part. My academic background, though, was in statistics and actually started my career in medical research.
00:05:40
Speaker
but obviously medical research uses quite a bit of visualization so that's kind of where i got my first exposure and then when i realized it's this marvelous confluence of technical thinking and creativity and relationships and expression i decided to focus solely on that and and have this ability to
Challenges in Writing for All Ages
00:06:02
Speaker
interact with so many different fields. And like I said, so many different things that people care about. Yeah. Yeah. So that's, that's what I'm doing now. But as far as why write a book and why
00:06:20
Speaker
set out to do something so absurd as to write something for everyone. It's like, what's more canonical than the expression of like, you can't please everybody? And then just say, oh, but I can. Who am I to say? But I did. I did say that. And I think we did a pretty good job, we being myself and my fabulous editors to our Muzner and Alberto Cairo. I think we've done it or as close to
00:06:48
Speaker
doing it as possible. So why? I had this, it was a couple years ago, it was during the pandemic, right? So we had a lot of time alone with ourselves. And I had just taught a class at the University of Washington. And I had just recently been working at Microsoft with so many brilliant adults.
00:07:13
Speaker
And I realized in this like flash of light that I'm spending all of this time, either at work or teaching or wherever, explaining to adults these very fundamental concepts of data visualization, even if it's their own work or it's, you know, just part of their day-to-day routine. Right. And I saw this gap. I was like, wow, these brilliant people.
00:07:38
Speaker
are using this tool without ever having truly sat down or had the opportunity to learn what they're doing, to learn what it means to visualize. We've taken math classes. We've taken grammar classes. People have learned how to code. People have taken science classes. We've learned everything peripheral to data visualization while using it. But we haven't sat down and learned what does it mean.
00:08:04
Speaker
to visualize. And if I'm teaching them, who's teaching their kids? So, you know, a quick Google at the time right now, we're lucky over the past two years, more content, more resources for young people have started to emerge in the database space. But at the time there was very, very little and certainly nothing in mainstream circulation. So I said, okay, well, who's teaching them? No one. What if that's me?
00:08:35
Speaker
What if we go for it? So we did. And I felt like it was important to reach everybody in one go because you and I may have our bookshelves full of Datavis textbooks. I think that is both statement, a minority of people. And so with the operating assumption that most people will only ever read one Datavis book.
00:08:59
Speaker
Can I get that book, that one book that's going to be in someone's house? Can I make something where a grownup on Wall Street feels cool having it on their desk and a fifth grader in North Carolina feels cool having it in their backpack?
00:09:21
Speaker
Yeah, I don't know if that fifth grader is ever gonna feel cool. I mean, there's the rare fifth grader feels cool with a data book in her backpack, but I get your point, I get your point. So how do you go about trying to find the sweet spot in not just the style of the writing, right? Cause you can write differently for the fifth grader versus the 30 year old.
00:09:46
Speaker
but also in the examples you use. So we were sort of, as we were talking before prepping for recording, I was talking about how like the first example in the book is on ice cream. Now everybody gets ice cream. And so that I see is like for all ages. Now had you started the book with like per capita GDP or like, you know, government funding for a program, like that's clearly for the 30 year old, right?
00:10:14
Speaker
But how do you sort of think about threading the needle to kind of meet the needs of both? Totally.
00:10:22
Speaker
Um, yes, ice cream is for everybody and I stand by this. And I actually love, I love this. I think it's just such a funny little quirk of, of people that, um, the ice cream example has come up in a couple of conversations. Like even when I started writing it, right? We sat down as the, as a team, we're like, is this too, is this too young if we're going for all ages?
00:10:45
Speaker
But everyone knows ice cream. So my compromise there was to instead of having kind of simple traditional flavors to make more interesting flavors, right? Like horchata flavored ice cream and red velvet or pumpkin pie. So I made, I use my local Seattle ice cream shop as inspiration and say, what would they do? What kind of interesting flavors would they have?
Creative Freedom in Data Visualization
00:11:08
Speaker
Because I go there, right? And I'm not getting the
00:11:11
Speaker
the typical strawberry chocolate vanilla. I'm getting the whatever, you know. Right. Okay, so now before you go on. So that was how I solved that. Before you go on, before you go on. So what is this? Just for the Seattle people. What is this ice cream shop that you like to go to? Oh, Frankie and Joe's.
00:11:29
Speaker
Okay. All right. Good to know. All right. 10 out of 10. Next time I'm in Seattle, I'm just going to mark it down. I would say I've had a bad habit of having ice cream for dinner. That's not a great place to do that because it's very rich. So I would keep the conventional order in that case, but that's my only word of caution with respect to ice cream.
00:11:49
Speaker
All right, so this is this is good. So so folks are sort of getting they're getting a little bit of the like literally Seattle flavor from this from this conversation. So that's totally yeah. Okay, great. Absolutely. So right, so the examples, that's the kind of one way that I dealt with the tone. Another thing that really inspired me was Reddit. Have you seen the subreddit explain it like I'm five?
00:12:15
Speaker
Uh, I don't believe I have. Okay. So there's a sub, there's a subreddit, right? There's a page on Reddit where people ask questions and they can be simple or complicated. And they say, I just don't understand this. Can you explain it to me as if I were a five year old? And that's so delightful and magical to me. Um, because if you can explain something complicated in simple terms, that's when you truly understand it. And most things.
00:12:43
Speaker
It's not that they are too hard to understand. It may just take, you may just need some more time to understand it, right? Things are complicated, but everything is solvable. Everything is made of small pieces that taken bit by bit can be digestible.
00:12:59
Speaker
So I use that as kind of inspiration motivation to say, all right, well, I think we can tackle almost anything in simple terms. And if I'm having trouble explaining something in simple terms, that doesn't mean stop. That just means take the complicated part of it and break that down further. Yeah. Yeah. So that's why I mean, the first chapter is what is data? Like, let's start from the very atomic unit of data visualization. Let's assume nothing.
00:13:27
Speaker
and go there, right? We all learned to speak. Yeah, yeah. No, you need to be able to kind of speak that basic language.
00:13:36
Speaker
Again, thinking about all ages and most data viz books don't do this. There's not a more on sort of like the date of like how to process data, how to work with data, where to get data. That probably is like that's several books. But did you think about kind of the intervening stats of definition of data? Then there's the, how do you get it? How do you work with it? How do you analyze it? And then here's the visualization piece. I mean, I don't think there's many data viz books that sort of fill in that. The whole thing. Yeah, the whole thing.
00:14:05
Speaker
I did think about it. I decided to not go there. So this is purely visualization in the sense of what we revealed at the end and what practitioners know as
00:14:19
Speaker
just encoding information onto something perceptible. Not even just visual, perceptible, right? I have the chapter on sound and touch too for that exact reason. This is more than just, this is not a taxonomy, a practice of taxonomy where you take, oh, this concept needs this type of graph. This is, this type of data can be shown with any number of different encodings. It can be abstracted in any number of ways. That's what visualizing is.
00:14:46
Speaker
We can put all the pieces together later, and that's really part of it. But at the crux, you're just mapping your encoding. So I focused on that. We have to stop somewhere. I also very intentionally didn't include any visuals that are statistically focused. There's no box plots. There's no violin charts. There's no ROC curves. You stay away from those.
00:15:15
Speaker
Because those are ultimately also just little blobs of encoding. You can get there once you know what visualization means. And same with data collecting and analyzing.
00:15:30
Speaker
beyond the scope. And I had already doubled what I had contracted to do. So I needed somewhere. I had the same experience when I wrote my book for them, too. I don't know. Maybe they just underestimate what we're going to write. I don't know. Yes. You mentioned having worked with and taught folks and done work as a freelancer. Have you worked with kids? How did that work inform how you wrote the book and the circular piece of getting feedback and going back and forth? Totally. Yeah.
00:16:00
Speaker
Personally, I had not worked with kids before writing this. So I fully admit that. I will defend though. I have been a kid. So I know that that experience is not all of it, right? I'm not parented. I have not been a school teacher, sure. But constantly present in my mind throughout this book was what would 10 year old Nancy have
00:16:25
Speaker
wanted to see, what would she have understood? Where would she have gotten hung up? Where would she have been more curious? Where would she be impatient? And now I need to give the payoff a little bit sooner because you're losing focus, because it's a lot to take in. So granted, that's an audience of one, but as special as we like to think we are, I know that's true for myself. Ultimately, that is limited. If it works for one 10-year-old,
00:16:53
Speaker
Yeah, my hope at least was that that would resonate with more Yeah, and there's also very intentionally not an age number put on here, right? Because things you know, everyone's different and maybe for some people they just won't be interested in it until they're 15 or 65 and Somebody may love it and just soak it up at five, right? Who might say right? I don't want to I don't want to impose any
00:17:23
Speaker
assumptions on people. Right. But my target audience was 10 year old Nancy. Gotcha. And then at the end of each chapter, there's, you know, it depends on the chapter, obviously, but there's, you know, at least a couple of pages, maybe up to five or six pages, depending on the chapter of exercises. And in your head, was that for the 10 year old Nancy? Or was that for 65 year old Nancy? Or for again, for like everybody?
00:17:52
Speaker
Sure, sure. That was, I made them, you know, the solutions are in the back, right? There's no, you can just look up what the answer is. Yeah. So I didn't, I wanted something where, you know, maybe someone learning independently, a young person, an adult, whoever could kind of test their understanding there in a very low stakes kind of accepting way, right? All the solutions say, Oh, you could do this a variety of way, but the important thing here is that you understand this component.
00:18:22
Speaker
But it's also, I wanted to make sure that I didn't rule out classroom usage. I know there's a full gamut of complexities to getting new material in school systems, but having no exercises would pretty much eliminate that possibility altogether. So I wanted some exercises where in an education environment,
00:18:46
Speaker
the teachers were equipped with something they didn't have to think about, think of it themselves. So that's for, you know, it's there if you need it. But I don't think any of there's no like new content revealed in them that would prohibit continuing through. Yeah, you didn't just get through it.
00:19:04
Speaker
The other big thing I wanted to ask about was, uh, your take on database rules. So I noticed you have a section on like bar chart should start at zero and you have a thing on like, and then there's a, there's, there's a section on like 3d, like be careful.
00:19:21
Speaker
And then you have a section at the end, like a chapter at the end that's like, here are ways to kind of distort or mislead. But my read of the book is that, you know, we're sort of similar in this way that there aren't really rules. It's a creative medium. And so, so I guess, I guess if I were to sort of distill that down to one question, like, what is your philosophy on data vis rules versus kind of like loose guidelines?
00:19:50
Speaker
Sure, sure, sure. Just like it's a wild, wild west and go wild. I love this question. And it comes up almost daily in my practice, right? Because everyone wants to be, for the most part, and Alberto had this in his book, How Tarts Lie, right? A very strong emphasis on most people don't mean anything bad, right? Most mistakes, most lying in visualization, even though we get a really bad rap for being misleading.
00:20:19
Speaker
I would say most of it is really well intentioned. So that's why I call the chapter Whoopsies, instead of something more sinister. Yeah. I think the only real rule is don't lie. Don't be dishonest. And that includes don't be unintentionally dishonest, you need to know how that can occur accidentally, so that you don't
00:20:43
Speaker
Right, like the bar charts is a great example. I can totally understand and I'm sure I've done it before starting a bar chart, not at zero. But once you realize why that's a whoopsie, they say, Oh, this actually is misleading. That's not what I mean to do. That's not that doesn't align with my intent here. So always fall back on what's true. Right? I have a little mantra at work.
00:21:08
Speaker
That is, we do not edit data for aesthetic purposes, right? So if you have an outlier or something that is inconvenient in your visualization and it makes it look less cool, you have my full sympathy, but we need to hold ourselves to that. We do not edit data for aesthetic purposes. We don't lie, right? Essentially. Other than that, I think knowing
00:21:33
Speaker
Like knowing the rankings of encodings, right? Oh, certain codings work better or worse for different types of data. And this is measured, right? This is just based on our minds and our perception systems. That lets you maintain a little bit of creative liberty, but also kind of guide you in what's a good choice. Because there are situations where you want to say, look, this could be objectively the best.
00:21:58
Speaker
length, position, whatever, but I need something fun for whatever reason. And so you want to bend, you want to kind of say, I see that. I respect that. I'm going to go with something that maybe is less good, but is way better ultimately, because it's fun and people pay attention to it. Or you have a wall of bar charts and you need a way to distinguish one concept from the other. Right.
00:22:25
Speaker
I think that's great. I think it's great. I don't think there's any need to be overly severe in that sense, as long as you're not lying and you know why you're making that choice. Right. One of the things that I struggle with is, and I see this a bit in your book, but I see it certainly the case in my book and many other books, is
00:22:48
Speaker
A lot of the books focus on the classic graphs. I think your book, my book, there's a handful of others that sort of push like there's lots of other stuff that people don't know about. But then there's like more of the like infographics design things like and even not like an infograph, but like a timeline or a flowchart or just a diagram like it gets into this like
00:23:10
Speaker
Yeah. Like there's not even like a bar chart. Okay. So there's a standard. The bars go left to right and blah, blah, blah. And like, but it has a structure. Whereas like a timeline, you know, a line bar or a circle or a multiple, like, so how do you like, like within the book or just in your, in your work or when you work with people, when you're teaching, like, how do you think about some of these diagrams sort of give that introductory, um,
00:23:36
Speaker
Yeah, kind of the same.
Effective Diagram Creation
00:23:38
Speaker
Let me, let me, I'm trying to distill my questions down. My head is still not here, but like if, um, CRC press was to come back to you and say, this is great. We want you to do a sequel. Um, we don't want you to do data visualization for people of all ages. We want you to do data diagrams for people of all ages. I know I'm sort of throwing this like brand new book project, this brand new question at you right now, but like,
00:24:02
Speaker
How would you think about those like basic guidelines of kind of visual types that are essentially super freewheeling? They're not like almost no structure to them. Right.
00:24:18
Speaker
Gee, I think, well, it's not the fun answer, but I might say I'm the wrong person for this. Right. I mean, that's totally fair. I mean, that's totally fair. I mean, I, I certainly like wave my hand at this question when it comes up and I'm just like, Hey, if you go to, I don't know, timeline storyteller.com, or if you go to then gauge, you know, these other sites and you look at timelines, there's like,
00:24:42
Speaker
a million options right away so like I can't give you really like really rules of thumb even because but it's something I struggle with a little bit because I think a lot of people do you know like an org chart is a pretty common thing that people make and they want to make them look good and so but like right it's kind of hard to like give them yeah in the basic right
00:25:05
Speaker
It's true because they also are everywhere, right? Anybody who's worked in any corporate environment or has seen many of these infographic, just chart based things. I think the, so A, I don't know how to write a book on that because I just, I like you and it just isn't, I guess I think too structured and how I think, but even with,
00:25:35
Speaker
even outside of that being my comfort zone.
00:25:40
Speaker
I think we can dissect a lot of these charts and still see this language of encoding. They still inform each other, right? You have a flow chart that's everywhere, you know, it's going all over the place, but there are some, you know, some of the ribbons that are thicker than others. That means something. You've chosen to make some areas, one color, and perhaps there's a gradient between them. That means something. And so even if, even if I'm not the right person to tell you how to make a great
00:26:09
Speaker
which I will reiterate, I think there are great infographics and I appreciate them. It's just not my area. I do think they are very close cousins, right? There's a lot of, they inform each other, I think. Yeah. Yeah. It's kind of interesting to think about what an underlying structure
00:26:29
Speaker
of kind of the diagram world is. And I'm just thinking about like, as we're talking, I think about like my kids, right? Like my daughter makes, my daughter's in high school and making like for her like biology classes, like she's making flow charts all the time, right? And so I think they're,
00:26:49
Speaker
Yeah, I mean, this might be where you and I have to write the book together because only two people who don't know what they're doing can write something that will help people. Yes, yes, yes. I would say I did address networks, which was a great learning opportunity for me as well, because I just had never really sat down and explained it like I'm five. How do you explain networks to someone?
00:27:13
Speaker
who is a complete blank slate in the world of networks. And that was really interesting and a funny thing to fit in, right? Because connection is not really an encoding, but it also definitely is. Right, right. For sure. And I also really wanted to include it because of so many, because of all Sankey diagrams that I've come across in my lifetime.
00:27:39
Speaker
And they are confusing. They are cool. They are cool and wiggly and confusing. And so just for the sake of humanity, like, well, maybe we would all benefit if we had sat down to think a little bit more carefully about what these mean. Or selfishly, just so I have an excuse to also think about them carefully. Well, I mean, that's the thing about writing and teaching, right? Like you really learn the content when you have to do it. Yeah.
00:28:07
Speaker
Um, so I wanted to ask before we finish up, um, I'm pretty sure I know what your answer is going to be, but do you think data, this data science should be part of the K-12 curriculum?
Data Visualization in Education
00:28:20
Speaker
And then of course, if so, like what should be cut? Now we're right at the end of the school year here in Virginia and my kids for those classes were like.
00:28:29
Speaker
their exams, the AP exams are done or whatever. They're just like watching movies. So they could, they've got several weeks. They could do it right now, but okay. But just generally speaking, like, you know, do you think database should be core part? And then what would you sort of push out?
00:28:44
Speaker
Where do you trade? Well, firstly, I will say I was raised by a public school science teacher. So I know firsthand just the pressures and restrictions and constraints that they're under. So let it be known, this is not something that we can just dump on teachers as an addition and hope that it works out. That is, no, strongly disagree. That said, of course, I think that it should be
00:29:14
Speaker
part of the curriculum. It should be in the water as soon as we can possibly get it there. Because it's not just one skill, it's thinking abstractly. And there's no lower bound on that being useful. Like I think anybody who's who's going to remember the journey of learning visualization
00:29:37
Speaker
and probably relate to this feeling of it just changing the way you see the world. It's this full other tool that lets you understand and appreciate and communicate information. Yeah, of course we need that. And I think something special about it is that even though I put it in one book, you've put it in one book, it's...
00:30:00
Speaker
Visualization is omnipresent and it is a helpful learning tool in so many disciplines that, I don't know, maybe we don't need to teach it in its own dedicated class. Maybe we don't need to swap out math content for visualization. The first bar charts I saw were in a history class, right? And you see them in biology. You see timelines, you know, oil prices over time. Can we integrate visual thinking, visualization,
00:30:29
Speaker
more pervasively instead of having it be one chunk of time. That seems valid to me. So the short answer is I don't know, but we cannot if we don't have the resources available. And also we can't teach what we don't know. And so that goes back to all ages, right? We have a lot of work to do to get everybody on board.
00:30:59
Speaker
Yeah, and so I don't know. I wish I did. I'm with you. I mean, for me...
00:31:05
Speaker
In my thinking, I think it's a little easier at like the older ages. And I'm sure I'm gonna ruffle a bunch of feathers with the next sentence. But like, I think there's a, in math at least, there's an overemphasis on calculus in high school, especially in the later grades. Like, you know, I mean, look, I have degrees in economics and like, I don't use calculus anymore. Like in my day to day, right? Like most, like who needs calculus in their actual work. It's like engineers and economists and that's kind of it, right?
00:31:35
Speaker
I would substitute statistics and probability for that maybe first. But at the younger ages, which is where I think to your point, you need to get to fourth, fifth, sixth grade is where you need to start. And in my experience, my kids learned,
00:31:53
Speaker
It's kind of interesting actually like in our schools they learn bar charts line charts pie charts and histograms were like, oh, there's like a core graph type now histogram is I guess a bar chart but like, right, so there's something but I think, you know, it is like everything's a trade off and like you said, especially
00:32:13
Speaker
certain states, what teachers can and can't do is like pretty strict. So, um, so it's, so, and yeah, like you said, like they're already overburdened. They already have to teach a lot of stuff and you know, so it's, it's certainly hard, but, um, but we can continue having the good fight. Yes. And, and I think there's room with, yeah, we can, we, we, we shall. There's room outside of the classroom too. Right. You know, there's, um,
00:32:40
Speaker
just activities after work or in the summer, like like Gulrez's book, right? Yeah, where he's just doing activities with his kids. That's right. That's great. That's a possibility. Home schools are a possibility. You know, like science camps, I think. Yeah, I mean, there's a ton of coding camps now, right? Like there's coding camps. Yeah, I mean, it's out there for sure.
00:33:01
Speaker
Yeah. Do you know those little, I don't know if you have them where you live in your neighborhood. There are like little mini libraries that people put in front of their house. Yeah. The little lending libraries. Yeah. Yeah. Yeah. I've been putting copies in them. That's so good. Kind of my like guerrilla marketing, but they're disappearing. I think there's a demand. I go back and it's not there the next day. So I put another.
00:33:27
Speaker
So I think there is an appetite for it. I don't have a camera. I don't know who's taking these books. But someone is. And I think a lot of it is that people don't realize that visualization is a full discipline.
00:33:50
Speaker
Like what your kids are learning? 100%. Visualization is bar charts and pie charts. Right. And like, how often have you heard the joke? Oh, no, 3d pie chart, right? Yeah, you could, you could write on an index card, like the sentences that you just hear over and over. And that would be the extent of common knowledge. I think people don't know that it's there. And so if we can also just get that switch flipped, like, oh, it is there. And it's not rocket science. And it's actually,
00:34:18
Speaker
very inclusive to different ways of thinking and people and personalities.
Sports and Data Visualization
00:34:23
Speaker
And if we're not judgmental, right, if we're a little open minded to it, not being too strict. Yeah, I think that will
00:34:34
Speaker
Yeah, I totally agree. I think it's also interesting when I think about like the sports world, because there's so much data in sports. Like NHL has this new thing called NHL edge, which is like, deep data dives, like super like where the players shoot on the ice, right? And they have this new website and like, but I think would
00:34:53
Speaker
My guess is when people go to that site and they see what you kind of have is like the ice rink it's an image of the ice rink kind of it's like a basically heat map of the ice rink right and my guess is if you said if you ask people about that is that a date of visualization they would probably say they probably say no
00:35:11
Speaker
Right? Because it's not a bar chart or a line chart where that's what people think of, right? Absolutely. And it's broader than that. Yeah. Interesting. Yeah. Yeah. So I'm not a hockey person. The heat map that you're describing, what kind of gradient is it?
00:35:29
Speaker
It's gray. It's gray. Okay. It's a sequential for every team and every player. And I don't know if they made this decision because they just didn't want to have to deal with different hex codes or like, but like for every player, every team, when you select and it changes the map, it's a light to dark gray, uh, sequential color ramp. Um, which I find.
00:35:53
Speaker
the page doesn't look as vibrant, right? You would think like, if you pick the Seattle Kraken, you would get like a really cool green or blue. If you pick the Washington Taps, you get like the red color, but everything is the same color.
00:36:08
Speaker
But it's not the jet palette. It's not rainbow. It's not rainbow. It's not rainbow. So I don't. Yeah. So they've got that. But, um, it's kind of interesting, but my guess would be that most people like instinctually wouldn't say, Oh, this is like a really cool database or even a dashboard, even though that's really what it is. Um, because it's not like bar chart, line chart, bar chart. And for better, for worse, whatever that is. So.
00:36:34
Speaker
Um, all right.
Connecting with the Community
00:36:36
Speaker
Well, Nancy, thanks so much for coming on the show. New book. Thank you. DataViz for people of all ages. Um, before we go, where can people find you to ask you questions, connect with you. Oh yeah, that's a quick, I have such a quiet social media presence. I am most active on LinkedIn. Okay. Uh, if that's, if that interests people, um, yeah, that's your best bet is LinkedIn.
00:37:04
Speaker
Great. Sounds good. Well, you can get that flood of connection. I'm a little bit analog. Yeah, that's fine. You get that flood of connection requests on a website. All right. Thanks so much for coming on the show. This was great. Really great meeting you and Jamie. Thank you. Thank you so much.
00:37:21
Speaker
And thanks everyone for tuning into this episode of the show. I hope you enjoyed that. I hope you have a restful
Season Wrap-up and Listener Engagement
00:37:27
Speaker
summer. I hope you take some time out to spend your summer with friends and family. Head on over to the beach, do some swimming, do some relaxing, do some reading, and do some listening to your favorite data visualization podcast, the Policy Viz Podcast. So thanks again for listening. Have a great summer. Until next time, this has been the Policy Viz Podcast. Thanks again for listening.