 Hello, everyone. Welcome. I'm Matilda McQuade. I'm acting Curatorial Director at Cooper Hewitt. And welcome all the graduate students and others who are here this evening. And just a warning, this is being recorded. And tonight's event is presented by Parsons School of Design, and the Cooper Hewitt Master's Program in History of Design and Curatorial Studies. So we have students here as well as others who are interested in all the the lectures that Ellen has organized with curators from Cooper Hewitt, as well as as well as designers. So tonight's event is Visualizing the Pandemic. And unfortunately, as the last lecture of our series, Graphic Design Histories, all of these lectures have been organized by Ellen and part of the, as I mentioned, the seminar as part of the Master's Program. So this has been a great series, and we hope we'll have more to come in the future. So stay tuned. And the series or this particular program tonight is really a celebration also of a current exhibition up called Design and Healing, Creative Responses to Epidemics, which was organized by Ellen, with Julie Pastors here today as and Curatorial Fellow, Elizabeth Sanders, who is a student in the graduate program. So congratulations to you both, to all of you for a fantastic exhibition. So they all helped create it with Mass Design Group. So I am going to turn it over to them, and they will talk more about the topic of tonight. So just a reminder to put your questions in the Q&A section down below. And at the end, we'll have some time to cover some of those questions. So thank you speakers. Turn it over to you, Ellen. Thank you so much, Natilda. To help make this program accessible, we're going to be describing the visual content of tonight's presentation. And let's start by introducing ourselves. I'm Ellen Lupton. I'm a white woman with blonde hair, a dark sweater and glasses. Hello, I'm Elizabeth Sanders, a white woman with long brown hair, and I'm wearing a checkered black and white turtleneck, and I have glasses. And hi, I'm Julie Pasteur. I'm a white woman with very short blonde hair and a black sweater. Thank you, Elizabeth and Julie. It's great to see you. COVID-19 might seem like a strange topic for a talk about graphic design history. But I assure you, this is going to be a history talk. Together, we will walk back to the early months of the pandemic and experience how COVID-19 was living and changing through data. During each heartbeat of the pandemic, data graphics have focused our attention on the present. They tell us what is happening now, often right in our community. But data graphics also create a record of history. And they are designed, in part, to predict and control the future. Tonight's talk builds on Cooper Hewitt's exhibition, design and healing creative responses to epidemics. A recurring theme of our exhibition is visualizing the invisible. Artist Sam Stubblefield used a medical device to create a light and soundscape based on brain waves from over 100 participants. The exhibition explores diseases like TB, cholera and COVID-19 and their impact on design and public health. At the end of this rather dark and stormy yet optimistic exhibition, you can relax in our beautiful breathing space, designed by Sartak and Sahil in New Delhi, India for Cooper Hewitt's glorious conservatory. So please come to the museum and visit us and relax in this beautiful space designed for healing. Let's try to understand data graphics by walking through the most basic elements of graphic design, dots, lines, color and humans. Data graphics show what the eye can't see. Dots on a map help us see geographic patterns. In 19th century London, Dr. John Snow used maps to help found the field of epidemiology, which studies how diseases arise and spread. At the time, many scientists believed that cholera was caused by squalid living conditions and the faulty habits of the poor. Dank crowded spaces as shown in this print were concrete conditions that doctors and scientists could see. Medical illustrations showed the visible effects of disease. Here, cholera has turned a vibrant young woman into a blue and disheveled ghoul. The illustration has a kind of moral undertone as well, making health with purity and virtue. John Snow had a different idea. His map shows the water supply in London neighborhoods. Water back then was provided by different companies represented here by a big blue blob and a big pink blob. Now, if you drank water from the blue blob, you were going to get cholera. And if you drank water from the pink blob, you would stay well. And if you happened to be in the overlap between the two, an unfortunate then diagram, then you were going to get sick. So John Snow's map showed that water, not bad habits or smelly air caused cholera. His most famous map shows a cluster of cholera cases around a particular water pump in London, the Broad Street pump. Houses affected by cholera are marked in black on the map. Mapping diseases remains a crucial tool for public health. Let's take a trip to the area near New Orleans, known as Cancer Alley, where mapping has been used to show connections between illness and air pollution. It's my pleasure to introduce my colleague, Elizabeth Sanders, a Parsons Cooper Hewitt Research fellow who worked on our exhibition. Welcome, Elizabeth. Thanks, Ellen. Hundreds of chemical plants and oil refineries are located along the river. This photo shows smoke billowing from one of these many facilities. Since the 1960s, these river parishes have been inhabited by black Americans. One fourth of the population lives in poverty, more than double the national poverty rate. This picture shows a small house with a neat front yard, an industrial structure looms behind it. This map of Greater New Orleans shows redlining. The federal government ranked neighborhoods as good or bad risks for housing loans. Black neighborhoods were marked in red, preventing investment and home ownership in these areas. This practice caused generational gaps in wealth, health, and education. Redlining embodied in these pernicious data graphics is the heart of systemic racism. Residents here suffer from many chronic diseases such as asthma, cardiovascular problems, and cancer. Local activists are fighting to clean up the region. In 2019, ProPublica published an interactive story about this polluted area. This photo of the industrial riverfront features a beautiful pink sunset filled by smoke. Dots on the map show the location of existing and planned facilities. Each point represents a facility along the river. New facilities are still being built and planned, despite the known risks. Shades of pink show levels of toxic particles. Research by the GRIST in 2020 showed that the high level of air pollution in Cancer Alley Parishes is associated with higher death rates from COVID-19, revealing the unequal impact of the pandemic. Thanks, Elizabeth. The Johns Hopkins University COVID-19 dashboard is the world's most widely cited source for global COVID-19 data. So how did this tool, which is unmatched by any other data instrument come into being? Well, it was created by Lauren Gardner, a Hopkins engineering professor who started tracking COVID-19 in January 2020, right at the beginning of the pandemic, with her graduate student and Sheng Dong, working in their modest faculty lab. Citizens and everyday people like Gardner and Dong, not government agencies, repeatedly took the initiative to track COVID-19. Journalists, designers, teachers, engineers, even high school students led the way. The JHU dashboard aggregates global data in one place. We can scroll through case counts in countries and regions around the world. And we can look at line graphs showing change over time. But above all, we look at the maps. The red dots on this map show COVID-19 cases. As we zoom in, the data becomes more local. Soon, precise numbers appear with each dot. Imagine Jon Snow having access to a tool like this, allowing us to view the pandemic at the scale of the entire globe, and then come up close to communities and villages. My colleague, Julie Pasteur, is going to talk about how Cooper Hewitt is collecting new material during the pandemic. Thanks, Alan. So in September of 2020, Cooper Hewitt launched a responsive collecting initiative, seeking to document the many momentous events of our times. Staff volunteers and trustees submitted over 100 nominations for new designs that address racial justice, the 2020 election, the climate crisis, and more. Shown here are some examples, including masks, PPE, and a portable kit that enables bystanders to treat opioid overdoses. Some of the works that we were collecting were born digital. So Alan is going to tell us about this piece, how the virus got out, and how Cooper Hewitt is documenting it for our permanent collection. Great. Yeah. So this piece by the New York Times uses an innovative format for interactive journalism. And in fact, it's the same format that was used in that ProPublica piece earlier that Elizabeth talked about. And so how it works is that text boxes appear on the screen, and a reader scrolls, you know, down through a document and activates these text boxes at their own pace, right, reading at their own pace. And each text element also triggers a video to play a short video. So in order to document this interactive work for our collection, Cooper Hewitt made a very lengthy and detailed screen capture and video of a user moving through the piece. To include this in our exhibition, we made a much, much shorter clip from that longer video. And I'm going to play a bit of that clip now. For accessibility, I have narrated the clip, explaining visually what's happening and also speaking more briefly about the content that appears on screen. March 22, 2020. Many of the first known cases clustered around the seafood market in Wuhan, China. A map shows the train station and seafood market. Four cases grew to dozens by the end of December. A cluster of red dots quickly expands. The departures from Wuhan accelerated over the next three weeks. Green dots move outward from Wuhan. Thousands of people were infected. Red dots move among the green dots. Two days later, the authorities locked down Wuhan. Travel across China nearly stopped. But local outbreaks were already growing quickly. Red dots explode in Chinese cities. As the outbreak moved across China in early January, international travel continued as normal. Thousands of people flew out of Wuhan to cities around the world. Green dots flow through a map of airline routes. Over 900 people went to New York every month. In the US, where testing has lagged, President Trump suspended most travel from Europe. The virus will not have a chance here, he said. But by then, the virus had a secure foothold. Red dots cluster across a map of the US. When you connect two dots, you get a line, and that's one of the most basic and fascinating principles of graphic design. In this graphic by the Atlantic, a series of dots becomes a line that swells and shrinks over time. Each dot conveys data through its size and location and color. But so does the line taken as a whole. This piece was designed by visual journalist Scott Reinhardt for the New York Times. And Scott is here with us tonight. We're really excited to be able to talk with him in the Q&A. The graphic shows how wealthy New Yorkers fled the city during the spring of 2020, like Dukes and Duchesses fleeing the plague in the Middle Ages. The line weights express the relative numbers of people going to different places. It looks like the thickest one is Miami. Welcome, welcome, welcome us to Miami. And how do we know where these people went? The data was collected by looking at change of address requests that had been filed with the New York City Post Office. So all that junk mail went to Miami, too. Lines are especially valuable for showing change over time. A line graph, sometimes called a fever graph appropriately enough, connects a series of dots. There are many ways to draw the line or smooth it out into a curve. And that smooth line helps us to see a trend over time to see all that individual data turning into a story that we can understand about things rising and falling. This line shows the shape of a real cholera epidemic in 1849. The jagged blue line rises exponentially. As the bacteria infect more hosts, the blue line falls as immunity halts the spread. And this line graph should look familiar to all of us. It's actually a bit older than you might think. The CDC introduced the concept of flattening the curve way back in 2007, 15 years ago. A tall purple mountain shows an uncontrolled epidemic. No social distancing, no masks, no vaccines. A low wide hill stretches out in front of the mountain, showing the potential benefits of intervention. And this theory was put into practice very early in the pandemic. And this version of the graph was designed by Rosamund Pierce, for the economist in 2020, and became the basis of hundreds of interpretations. Flatten the curve became a kind of banner, a signifier for the pandemic and our attempts to control it. It became shorthand for the many interventions that were put into place. And it became essentially an icon. And you too can download these icons, these are all from the noun project. And sometimes important details are missing, like this one doesn't have the flat curve, just the tall curve. So that wouldn't be good. This one removes the dimension of time. So both curves are just compressed into the same space. When the goal of flattening the curve is actually to delay the peak of the pandemic, and not simply bring it down. And here's what the curve really looked like. So we're looking here at the drawing of the pandemic, the first year of the pandemic, from the New York Times, and I'm superimposed over that line drawing, the purple curve, the flatten the curve graphic. And we can see that at the beginning of the pandemic, in those early months, it did seem like we were flattening the curve. And indeed we were those interventions were helping to bring the numbers down and delay the peak. But then after that optimistic summer, the pandemic roared ahead and reached its, you know, ultimate catastrophic peak in the winter of 2021. So we can see that the pandemic, the shape is not as simple as flatten the curve. The pandemic has multiple peaks and valleys. It's a a living wave, right, not a single curve. And when Omicron occurred in the winter of 2022, the graph had to be rejoined, because the peak was now well over double what it had been a year before. So the first winter peak, which had looked so insurmountable, right, the height of the mountain, now looked very small, next to the new mountain of Omicron. I'm going to show you another interactive graphic from the New York Times, which covers the map of the United States with small red triangles, triangular dots, we could call them. And each triangle grows over time, representing the intensity of different outbreaks in different regions. And there is a slider at the top of the graphic that allows one to replay history to move back and forth between across these early months of the pandemic. And color is very important. We've been seeing a lot of the color red tonight. And so we're going to talk a little bit about color. And I'm going to ask Julie to start the conversation by telling us a bit about this famous medical illustration, which is in the Cooper Hewitt collection. Alyssa Eckert and Dan Higgins created this 3D medical illustration at the CDC in January 2020. So right at the very beginning of the pandemic, they designed it in just 10 days, working with scientific images, 3D rendering software and their own sense of artistry and imagination. The red-spiked ball inspired thousands of interpretations appearing on countless websites and warning signs, soap bottles and hand sanitizers. You can see it shifting and changing like a living thing as we scroll through this search window. It became an icon. And some interpretations are basic Bauhaus. Some are a little bit scary or other worldly. Some are very scary. Some are actually kind of likable. Oh, poor virus. So cute. And this one actually looks like a clock, which happens to be in our collection. This is a 1949 clock by George Nelson. It's a circle spiked with polished wooden spheres. Okay, Julie. So as I understand, a virus has no visible color. And if it did, we wouldn't be able to see it because they're so microscopic. So why are the spikes red? Well, similar to how the maps we were looking at showed those spikes in red. This illustration was designed to warn people. And red has an emotional function. The CDC wanted people to take this new threat seriously. Yeah, so color codes are widely accepted around the world to trigger a response. Note how the GHU dashboard uses color. Red signals the number of cases. Yellow signals the incidence of cases in a population. Green is vaccinations, which are good. White indicates fatality rates. White represents death in many cultures. White is spiritual, marking loss with points of light. This New York Times map uses yellow and red, our favorite colors of warning and danger to track COVID-19 hot spots in the US. This map is from November 2020. And we can see that the lighter yellow tones feel less urgent, a warning, but less urgent. Deep bright red tones show intense danger. And notice that in this map, many regions have already reached their maximum intensity. Now let's look at the map one month later. Okay, so this is November. By December, the situation is far more dire. And so the designers at the New York Times have to change the color scale and add purple to it. They can't just change the value of red because people rely on this data and it would be very confusing to them. Suddenly red took on a different meaning. So let's take a walk back through history. At the museum, we started taking a screenshot of that hotspot map every week. The animation I'm about to show you tracks a single year of COVID-19 from fall 2020 to fall 2021, right when our exhibition opened. So we have this intense autumn, intense winter. Meanwhile, a vaccine is visited upon the land. And the map starts to fade back. It becomes pale and yellow. And people take off their masks. Remember this last summer? How optimistic we were? How wonderful it was to plan to return to life as normal. And then Delta came. And Delta spread its purples and reds across the map. I've continued to take these screenshots after our exhibition opened. And so let's take a look at 2022. We're going to see a similar pattern, the intensity of Omicron. But then it just fades away. And it goes back to this pale yellow, like we saw a year ago. So that's what the spring look like a year ago. And this is what it looks like now, history repeating itself, history returning. Julie, I want you to tell us about the very different use of color in the work of policy map. Yeah. So policy map compiles geographic data that's used by journalists, by universities, governments, think tanks. And the designers are very aware of these emotional connotations that we have with color, and they reject those loaded colors to avoid stigmatizing any group that's represented by their data. So this map that we're looking at shows racial or ethnic groups in Chicago. And you can see that neighborhoods in green have predominantly black populations. And when you overlay data, you also see that these neighborhoods have a lower life expect expectancy, which is shown in white. Dark purple shows high rates of hyper tension. And such illnesses are associated with higher mortality from COVID-19. And early in the pandemic, we had the privilege to interview Maggie McCullough, who's the founder and CEO of policy map. We'd like to share a short clip from our conversation. One of the things that COVID has really brought to the forefront is that health and disease and, and healthy lifestyles really are impacted by where somebody, somebody lives. CIP code really does play a large part in the health of a person. And so when we set out to map COVID data, it became very clear that these, where you had these heavy rates were also communities, communities of color, communities where people didn't always have great access to healthcare in the first place. They were communities that had high rates of different types of chronic conditions that made them really vulnerable to dying from COVID where they to catch it. And they were communities where people had jobs that didn't allow them the luxury of working from home and staying safe, but they were having to get on the bus and go to work mapping has a real dramatic way to bring that home for people because they do know like the zip code that they live in. And they know the intersections of the streets and their neighborhoods and when you zoom in on a map, you can say, Oh, I know where that is. Wow, what is going on? And this connects back to a point Elizabeth was talking about earlier with redlining and how that was used to harm populations of people. And this print by Amanda Williams imagines reshaping Chicago's history of redlining. The ghost print is an image of a redlined map created by the Federal Housing Authority. People living in the red zones were denied housing loans. This policy enforced poverty in these areas. And to create her new map of Chicago, Williams cut out pieces approximating each zone, and shook them up breaking up the human bias into a random mix. This and this print was recently acquired by Cooper Hewitt and is on view in our exhibition Dora Lois Selects. All these dots and lines and colors represent human lives and human suffering. Back in August 2020, we interviewed Scott Reinhard, a designer and visual journalist at the New York Times. Scott was one member of the team publishing COVID-19 data. The team worked in continuous shifts like in a hospital. These were frontline workers performing their service from the isolation of their homes and apartments. I'm going to share a short excerpt from our conversation with Scott. And this excerpt reveals the intense labor required to track the pandemic. I think when many of us see these maps and graphs and dashboards, we think of just computers grinding away. But actually all that data has to be located and sorted and collected. And systems have to be created to deal with it. And it's a profoundly human task. It's a task with great cost to the people doing it. So here's a short clip about two minutes long from our conversation with Scott. This is an outbreak that started at zero cases, right? And it started with a literally a Google spreadsheet where they were just starting to track each individual case as it came in. So when I showed up in March and it was less than a thousand, it was a Google spreadsheet. And there was just four of us in New York, London, and Hong Kong updating this tracker 24 hours a day, seven days a week. And so I just went into it and it was like a month and a half straight of work, no time off. And as those cases are scaling, eventually it broke the Google spreadsheet because we're at 60,000, 70,000 cases. And the impact, I'll probably keep referencing this, but the personal impact of just seeing, updating in the morning and then going back in the afternoon to do the update. And there's 3,000 more cases and just the holy shit. So as we were building this, or starting to maintain and update these trackers in the background, they had a development team that are building more robust databases that could actually handle the amount of data being piped in, as well as at that time, they're building a data collecting team that includes people tracking all the press releases from health departments, but also there's a really, really robust team of developers that are working at scrapers, so that we're constantly, constantly scraping data from everywhere as much as we can. And so deeply close to these numbers and they haven't really become abstract to me. It's not like I'm just hitting a script and publishing and it hasn't become automatic. Thank you, Scott. The last piece that we're going to share tonight is an interactive graphic published by the New York Times on the occasion of 100,000 COVID-19 deaths in the U.S. Today, that number is almost a million. Small gray and black figures scroll upward on a pale gray background. Some have names. 100,000. Toward the end of May 2020, the number of people in the U.S. who died from the coronavirus passed 100,000. Den mother for Cub Scout pack nine. Manager of the produce department. Tavern owner. Nurse to the end. 100,000. Thank you all so much for being here tonight and thanks to anyone in the audience who has contributed to this work. Graphic design was not at the edges making comments about the pandemic. Graphic design was keeping us alive. It was making visible what could easily be denied. We do have the wonderful good fortune to have Scott Reinhard here and he has, he can't stay very long so we're going to start by asking Scott a few questions. And Scott, it's really great to see you and I guess my first question is how are you doing? Oh, thanks for having me Ellen. It's really nice to see you and I appreciate being here. How am I doing? Yeah, I'm doing okay. That was 15 months of work for me before our systems got kind of robust enough to be a little more automated. And so I've since moved on down to things I've been mapping the war in Ukraine. But yeah, this was really interesting to take a look back at this. And can you tell us anything about how you understand the pandemic now looking back? I mean it was just such a wild time to be at the beginning of it and to see it as being so immense and yet it kept getting bigger and bigger. Yeah, yeah, I mean there were a few times like the ones we pointed at too were like the scale. We had to change the color scale, you know, and those were those really felt like momentous times, you know, at least from a graphic design perspective. And I was doing like the print map every day for that too. So I was like trying to solve that puzzle in black and white in a way. But it's been so interesting to have had that perspective of, you know, I came back to the times in March 2020 to work with the graphics desk. And so like I said in that clip, you know, we started from a Google spreadsheet. And this is a kind of a normal project, the normal type of project. It's like just reporting and then mapping and, you know, but as it grew and the scale grew and then the scale grew, to have that perspective of seeing it turn from this Google spreadsheet into almost a piece of infrastructure, you know. And like the times we want to pull surprise and public service for this, that was part of that effort. And you know, it was. It really did turn into this piece of infrastructure that we really rely on, I think, in a way. And some of the pieces that you did were more journalistic and more storytelling. So the piece about the people fleeing New York. Can you tell us what inspired you to do that and kind of your role in creating that graphic? Yeah, absolutely. Yeah, and you're absolutely right, right? The I'll say like the limits of data visualization, right, is we're talking about humans, but at a scale that I think runs into the bounds of form and graphic design, things like that. And so the other thing we do obviously is report and show like the human impact and how the pandemic changed how we live and where we live and things like that. And so for that particular piece, for that particular piece, we got, received basically a data source of like how people left, right? And trying to solve that problem of like where are people going? Yeah, the question is, well, how do you show that? Where do you show that? Where do you get that information? And so that, yeah, it was like you mentioned it was postal data. And you know, I love arrows. You know, arrows are so useful. They really, you can show so much, right? You can show the where, but the how and the how many and things like that. And so it, I like when I do these graphics, I, they have to exist in so many areas, right? They exist in print. This one ran on A1 above the fold, but then also we'll have to exist at the size of Poch's Champ at the top of the time, you know, at the top of the paper, whatever. And you know, it's one of those things where at first glance I want the reader to understand at least what's going on, but I think I always dig in a little bit further, but it has to, has to be punchy and understandable and engaging in a way. So yeah. Yeah, that's sort of scary, but also a little bit funny. Yeah, so I have one more question for you, which is, can you tell us a little bit about what you're doing around Ukraine? Yeah, absolutely. So I, so a lot of what I do with The Times is, is cartography related. And so in December, I started reporting on the buildup of Russian troops around Ukraine. In, in December is mostly in Russia, and then that kind of moved to Belarus. And so I was working with reporters in Ukraine and in New York. And so there was a series of maps we did kind of every few weeks, we're just like showing the buildup, showing the buildup. And then obviously when the invasion began, I've, I've been working kind of nonstop on, on mapping the, the developments of the war in Ukraine. And so kind of, if you're in The New York Times on the maps page, there's like, we have kind of a long page of, I don't know how many maps we have at the moment, maybe 50 plus at the moment. But so I've been heavily involved in making those maps and showing, you know, how the war has progressed and, and kind of evolving how we're showing that as well, because that's a constantly changing situation. So that's, that's my focus. Bad things happen. You're the guy. I guess so, yeah. Sorry about that. Thanks so much, Scott. We really appreciate what you've done for the world. Yeah, I appreciate it. Sorry, before Scott maybe signs off, there's a couple, there's a few questions in here. Oh, great. And, and the first one may be interesting from your standpoint and also from Ellen's who's a graphic designer. This week, Dr. Fauci has reportedly said that the US is no longer in the pandemic phase. How do you anticipate these next stages of COVID will be presented graphically? Any thoughts? Everything will be yellow and green now. I mean, it's interesting that from the beginning, right, Scott, the color has been used to signal alarm. And there is even critiques, you know, from the, the right side of our political spectrum saying like, why are they using so much red? Why this is JHU dashboard? Why is it always red? It's making people scared. So I think that the message coming from on high is to bring it, bring it back and make people less scared. What do you think, Scott? Oh, man. Yeah. I mean, oh, it's, it's a good question. And, you know, I think it's, well, I'll just say from the beginning, it's tricky, right? Because we didn't know the scale that this would, you know, go to. And so I don't know if I have a good answer to that question, to be, to be honest, but it's, it, we want to be appropriate to the, to what we think is, is the kind of appropriate level of we, we should be aware of this, you know, and, and as we've kind of seen that changes. But like, you know, the pandemic feels like it's going away, but it's also kind of not like we're, if we look at the, the chart again, like, we're at a similar level that we were in March, April, May of 2020. So, you know, I think, you know, as we've done, and I think as we'll continue to do, it's just like assessing where we're at, where things might go, and just building a system that can anticipate that and be flexible enough for that to happen. You know, it's less about just like reacting to exactly what's happening right now, but it's really kind of thinking about what has happened, what is happening now, what might happen, and just building systems that are flexible and kind of robust enough to allow where things might go. I mean, the same thing kind of has been with our working in Ukraine as well. It was like, we don't know exactly what's going to happen. News is news and things change all the time, and so you have to just like be flexible enough and have systems in place and just, and anticipate things, but, but maybe that's why I don't have a totally solid answer, because it's just that kind of like that range of allowing for things to happen and being ready for it. Thanks so much, Scott. I appreciate that. There's another question. I'd like to hear more from you about the connections between graphic design and other areas such as medicine, epidemiology, etc. In this work involving information design, how does that connection, that conversation, go on? How hard can it be? So I don't know if it's, you know. Well, yeah, it's very interesting. So Florence Nightingale, who founded modern nursing, also founded statistical graphics, and she created a very famous diagram that is, you know, somewhat contested now by historians, but very influential diagram that showed that British soldiers in the Crimean War, which was a proxy war with Russia, were dying more from infections that they acquired in the field hospitals in Crimea than they were dying from their wounds. And Florence Nightingale was there. She was on the ground, a frontline worker, and she advocated changes in hospital design and was able to really make those changes become policy through her use of these graphics, which showed this, you know, death by infection problem that was caused by the really miserable conditions in these hospitals. So the relationship between data graphics and medicine is just, it's essential. I mean, think about the heartbeat. Think about vital signs, right, when you go into any kind of pre-op room, right, your vital signs are there on a monitor. That's all data visualization. It's just really essential to the field and people like John Snow and Florence Nightingale really pioneered public health by using graphic design as a tool. That's a great, great question. And then two more questions. One, first of all, this person wanted to thank you all for the wonderful lecture. Data has become more important than ever. The data shows that access to resources is a critical factor during the pandemic. How can we possibly increase the accessibility and make the data understandable to more people in the future? Scott, do you have any answer for that? Yeah, I mean, maybe no concrete answers, but it's really, I think, being thoughtful. It's really thinking about who the audience is, what the data is that we're showing, and just always questioning, does this make sense? Like, is this, what are limitations of readers or people who are going to be accessing this data? And it's just kind of always kind of striving to do better. Like, I see a kind of a question here, I hope not to jump ahead, but like about like dots and lines and, you know, these, you know, in terms of representing humans and things like that. Like, I think, like, you know, data visualization has been around for quite a long time, as like the foreign site in Yale, but like, I also think, like, in a way, like, some of these questions, like, aren't totally answered. I think, I think the scale of the pandemic, as well as just like other, the scale of other things that data visualization is trying to cover, I think we run into the edges of that sometimes. And I think, like, you know, I think constant, like a constant dialogue, critical dialogue, like things like this, and like talking about this. There's been really good discussions around a lot of the work that we've done, a lot of critical feedback, and things like that. And I think that's like really important. And because like a lot of these, in my opinion, like open questions and things that we really grapple with and really think through and are really thoughtful about it, and it's, it's, it's, it's unanswered. And that's like, that's what the work is. It's really trying to, every time we try to, you know, publish something, I think we are trying to just do a little bit better and try to answer these questions, make them more accessible, more understandable, a bit clearer, you know, like, right off the bat and in a bit richer. And so that, so that, so that these concepts and like these large vast amounts of data that hadn't been available to us prior, are, can, can make more of an impact, can kind of sink in in a way that, that's just we haven't had access to before. So it's, it's just, it really is an ongoing process. And it requires like a really like a lot of thoughtful dialogue and questioning and in critical discussion. Yeah. Yeah. And I think often that the dots and the lines do the best job. Yeah. Because they are so, so accessible to our perception, right, to see those patterns revealed can be very powerful. I see a question about math education and the low level of math education. Does that influence how we represent data? Are there some formats that are easier than others for people to understand? Like I know the mathematics of the epidemic curve is like not conventional steps of 10, but you know, is jumps. I don't know. Yeah, I feel like if you see that graphic and you can kind of feel it in a way, like that kind of like transcends knowledge of math or kind of math education, I think it's like if there's a visceral connection to those graphics, that's what's important. I think that data graphics do have that power. Of course, they can, they can be manipulated. I have a question for my wonderful colleague, Julie, who's been so involved in our collecting of this material at Cooper Hewitt. Julie, what do you think is the most exciting piece that's been collected during the pandemic at the museum? I think that's a tough question. We've acquired a lot of really good things and it's been wonderful to see suggestions from so many people across the museum. Away from information graphics, one of the things I was most excited about was during the 2020 U.S. Open, Naomi Osaka, when she was playing her games, wore face masks and each one was emblazoned with the name of a Black person who died at the hands of police. This was right at the time of peak demonstrations for Black Lives Matter against racial injustice in this country and also at a time when it was very clear, you know, the data was showing us that Black Americans were disproportionately dying and as a result of COVID-19 and that's a simple graphic statement that makes an impression about humans really, really quickly and Naomi Osaka donated all seven of those masks to our collection and one of them is on view and design and healing. Yeah, it's really a treasure for the Smithsonian to have such a unique artifact of our time. And I have a question for you, Elizabeth. You are a graduate student in design history in the Cooper Hewitt Parsons MA program. How is your work as a historian informed by this kind of research? Well, I was really lucky because I really started my graduate degree a part of the show. That was like kind of the first thing I did starting off the two years and it was really influential specifically because it started to get me to think about, you know, how pandemics and epidemics really affect intersectional identities and how, you know, it really influences systemic racism just, you know, makes a lot more intense. And so the work that I've been doing in my thesis, which I'll hopefully be submitting in October, is really looking at public space which really became a contentious and freeing space in the pandemic and sort of looking at neocolonial practices in public space. And I've also been looking at displaced populations and sort of their interactions with it. So yeah, again, it was a really wonderful and influential project work on and it definitely helps kind of me find my voice as a design historian. So thanks to you. Well, I hope that maps and visualization will play a role in showing the movement of people and changes in space. So we're going to conclude the evening. It's been very meaningful to share this space with you. If you're interested in this topic, please join us next Friday for a panel discussion called safer spaces about how designers and doctors are creating more beautiful and healthy buildings and cities in the age of COVID-19. I'll put a link to that event in the chat as well as to Cooper Hewitt's two amazing books about redesigning healthcare. Thank you again so much to our panelists and to our live cart captioners. Thank you for what you do and to Matilda and all of you for supporting Cooper Hewitt. Thank you so much.