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- I wanted to welcome everyone. My name is Jennifer Frazier. I'm a scientist and curator here, and the person who with much help organize this event and I wanted to officially welcome you to the Visualise Conference. Thank you so much all for being here. For the next two days, we're gonna be focusing on the use of data visualizations in informal learning settings. We're gonna be talking about what we've done, what we've learned and where we need to go next. And we're gonna be getting a lot of ideas, inspiration and feedback from not only each other in the informal science field, but outside experts from related disciplines. So before I really launched into talking about the conference, I wanted to introduce Rob Semper, who's our associate executive director. He is responsible for all of the educational programs here. And after getting a PhD in physics, he joined the Exploratorium in 1977. So I'm not saying that to make Rob feel bad. I just think it's about credibly. It shows you the order of magnitude, like how much impact Rob has had, because in that time, he's overseeing so many programs here, led countless grants, and he's been a huge supporter of our work in visualization, not just in the last decade, but beyond. And because of Rob's huge contribution to the informal science field, he's recently also been nominated to serve on the inter agency governmental panel on science, technology, engineering and mathematics or STEM Education, which among other things will be advising on the federal STEM five year strategic plan for STEM education. Phew! Okay. So anyway, without further ado, Rob for a few remarks.

- So I realized we designed this theater with stairs at either end, but everyone always comes up over the top of the stage, so we have to refurbish. Anyway, it's my great pleasure to welcome you to the this conference, to this meeting, to this workshop, to this confab, on a really critical topic on visualization. The notion of data visualization's been an important part of what the Exloratorium been about, almost from its very beginning. And as I was reflecting on that work and my interest, I realized that my first brush with this was building an exhibit in actually 1979 on we had to Centennial Weinstein's birth, and we built an exhibit to show black body radiation and his development of the quantized light, and had to visualize data from a physical exhibit that actually showed the black body curve or our planks curve. My joy was actually showing that once the Victor Weisskopf, famous physicist who said he had never seen that. This is the guy who started everything else. Actually had never visualized the data coming from that kind of experiment. So it was exciting for me. But it sort of started this whole notion in my mind about the importance of visualization. From our perspective, we been sort of in that world for a long time. Most recently, we got engaged with that, with sort of our work in wired periods, looking at how to visualize data, actual data that's being taken around the bay, and how to present that to the public where they get a chance to start to look at it. But this visualization is an important feature, way beyond sort of us here at the Exploratorium. Is clearly becoming critical in terms of the public experience in the way science is done in these days. And it's become a topic of interest, not only in from the scientific perspective, in the public sector, but also in the STEM education field perspective. And like Jen says, I'm on this panel, and one of the pathways in the federal STEM strategic plan turns out to be called Computational Literacy. And in that is digital literacy, computational thinking, and digital teaching and learning, and we've through all of that, is issues that I think are really about visualization, and about how to actually visualize data. So this is very timely, which gets to the point, why is this conference now? And I think, as Jen is gonna talk about the conference itself, it seemed like a good point in time to say, okay, we know that science is really now more and more about data. Visualization data is both scientifically important, but also, from the public's perspective important. It's probably a good time to take stock of where we are now. It's probably a good time to understand what we don't know as well as what we know, and so I think about what we should think about for the future. And so my message to you all professionals in this field, one form to another is always to remember that from a public perspective, their literacy in terms of dealing with visualization of data is actually fairly limited. And it's because we don't actually teach people very much about how to do that. If you look at the K12 system, the out of school system, it's really amazing how little attention is paid to that, compared to mathematics, functional analysis, that sort of thing. So we have a big road to go in terms of relating this world of complex data visualizations, to a public that actually is not schooled and how to look at things. And that can be one of the big agenda items we have. So in terms of welcoming, I would like to encourage you to realize that this is a great group of people, it's been carefully assembled, you already have know each other, but you probably haven't all been in the same room at the same time. And so this conference is a chance for you guys to actually talk to each other, to explore the space, and to really start to move further on this agenda for the field, about how to look at visualization in formal science education. So have a great conference, I hope to join you in different parts as my duties permit. But have a great two days at the meeting here. Thanks.

- Thanks, Rob, for the... Okay, you're officially welcomed now. All right. So to sort of ground us in why we're here, I wanted us to step back, 10 to the 21 orders of magnitude. Or if you're a biologist, a cell biologist like myself, step in about 10 to the minus eight. I actually was trying to think, "Well, how do we really like ground why we're all here?" And to me, this iconic sort of assembly from "Powers of 10," by Charles and Ray Eames, to me sort of reflects in some ways why we even first started to get individualization at the Exploratorium. And that is, if you think of all of the realms, the different scales of the natural world, very few of them are actually able to be perceived by us directly. So this isn't everything from the movie, and I wish we had like the music, But if you think about it, it's like, oh, I could see the wrinkles on my hand. Or if I were in a hot air balloon, I guess I could look down on some people having a picnic. But really much of the rest of the natural world is not perceivable by us with any of the senses that we have. And so for us to engage with those scales, we need tools. This was not done by Charles and Ray Eames. This was done by the biologists myself. So you can tell the graphic design qualities dipped a bit. But basically, we need tools to be able to engage with these other realms. Whether they're radio telescopes, whether it's X-ray crystallography, microscopes, supercolliders. I just put a few things on here corresponding to the scales that you see. But I think all of you work with data from like countless other tools for understanding other scales. Whether it's a genome sequencing machine, buoys, phones, it goes on and on. So this data, it's right symbols, zeros, ones, A's, C's, T's, and G's most of it, it's not really even that is not something that's gonna be easily or readily perceived by us. And that's where, of course speaking to this crowd, I think you already mostly know this. But just to make sure we're all on the same page. This is from, I've seen the slide used in introductory data visualization courses and computer science. And in the middle there, set A and D. Those are just 11 X-Y pairs, right. So we're not talking about a really complex data set. But you can see, it's only in representing it graphically, creating a visualization of that data, that you can actually start to make comparisons, gain insights, or really start to grapple with what you're seeing. So there are many definitions for visualization. But I think one that I like as far as that perceiving beyond what is directly visible, it's artificial memory that best supports our natural means of perception. So I think we're all aware, as Rob just alluded to, we're not really just dealing with like 11 x-y coordinates anymore. We're in an era where it's not just nice to use visualizations to look at our data, it's absolutely essential, because we're talking about, these are actually a little bit dated. I think we're probably far beyond the petabyte era. And these are mainly scientific journals. But I think we all recognize that we're in an era where we have these massive data sets. And without visually representing them, we can't make any insights or observations. And I think as one of our advisors tomorrow, put it nicely. Visualization really puts the human in the loop. So without visualizing this data, the human, I guess that's us, can't actually start to make observations or do any of the things that we might be able to do. I think all of us see incredible visualizations almost every day. Now, many of them are made by you. But I think just so that we don't take it for granted, some of the things that we wouldn't have even been able to see a decade ago, we now can see. There's so many great visualizations from the National Oceanographic and Atmospheric Administration and NASA, of things like ocean currents, based on Boolean satellite data. We can do things, I know this makes sense to all of you. This is a comparison of dog and human chromosomes. So I think you're now fully enlightened as to your relationship with other mammals. I think it's, especially in a museum where we focus a lot more on natural phenomena, it's also important to be reminded that visualizations also play a really critical role, not just in exploring or seeing other realms, but helping us make really critical decisions. So this was, I think all of you saw last week, not only really nice satellite imagery, but lot of wind maps and other visualizations from NOAA. I'll just starts at . If you don't know the acronym, I think I just gave it but I'm gonna use it a lot. You now can make predictions about the path of a cyclone. It helps us not only with like these large scale emergency responses, but also in things like looking for genes that might be involved in cancer, or looking for a protein structure that might be a good drug target. Visualization isn't just about pretty pictures, or seeing different realms of the universe, it's actually critical for saving lives. So not surprisingly, given the importance of visualization in science, there has been a lot of intensive effort in science museums on experimenting with visualizations. So some the experiments that we've been trying, done by many of the people in this room are really trying to explore how we use visualizations as part of in narrated or filmed experience. So we have some scenes from like planetarium shows at Cal Academy, like NASA's Viz Wall, a lot of experimentation with different kinds of programming with NOAA Science On a Sphere. And that's as seen from the Adler Planetarium. So really finding ways that we can use visualizations in the storytelling in immersive context. There's been a lot of experimentation in how do we get visitors to engage with complex data? So on the top, we have an image from the Microscope Project run by Katy Borner at University of Indiana in Bloomington. Some of the work we've done here in the lower corner, Living Liquid, which you'll hear about at the conference. And also up in the corner, Tree of Life, which had been led by Chao Shen. And that she actually sends her regards. She's now a program officer at NSF and could not travel but wanted to wish everyone the best. So you know, really it experimenting with how we engage people with complex data. And there's been a lot of work on interfaces, not only those that you see here, but you know, with AR Sandbox or using Augmented Reality, virtual reality, topographic interfaces. As Rob pointed out, it's not just that we want to experiment with visualization, there's also a lot of active work in data literacy. How are we helping the public understand what data is, what a data representation is, and how to interpret them. But this slide also represents, not only a lot of exciting work, and this is just a snapshot of a few of the projects that you'll see and learn about in the two days here. I think it also represents one of the challenges, because I think anyone who's working in informal science, or maybe any of you from other fields, but especially for us, if you're starting on a project, you're like, "Okay, what do I need to know "about tangible interfaces and museums?' Because visualization is such a cross disciplinary field, we're all communicating and sharing in different locations. So even within informal science, a lot of people who are working in space sciences are going to, understandably, Space Science conferences or planetarium conferences. Well, then they're not overlapping with people doing things about biology, who might be at the American Association of Cell Biology, or the visualizing biological data conference, people who are working on environmental or ocean visualization might be at the American Geophysical Union meeting or the science on a sphere users group. The acronyms could go on, and on and on, and on. Conferences, you can go to conferences all year long, and you'd be trying to aggregate all the knowledge about different aspects of visualization. So this just reflects some of the different places that informal science has been sharing their work. And we're not even talking about other disciplines, like computer science and psychology. So that is why we're here. Hopefully, that's not too yellow. So we realized that there was a lot of knowledge being generated within our field. And there we're a lot of experts in adjacent fields like psychology, computer science, data journalism, where we really needed to come together to start sharing what we'd learned, what we actually know, what we don't know, so that we could move forward as a field. So that's why we're here. Sorry, I should go back when, if this goes back up. So this initially was a grant we put into the National Science Foundation, which was awarded. And we also got additional funding from the Gordon and Betty Moore Foundation so that we could put this event on. Some of the goals for the conference, are to share research and development on visualization, to identify common areas of success and failure. Yes, it's okay to talk about failure here. 'Cause I think this is hard work and we know there are challenges. To converge on areas of R&D to guide future work. So as we'll talk about, our hope is to coalesce this into an R&D agenda for our field and to promote dialogue across disciplines. So not only within the informal science field, but among those unrelated disciplines who can help us with our work. So I'm going give you a brief tour of the agenda, 'cause it's like, "Oh, great, you have these goals? "How are you gonna accomplish those goals?" Well, here's how. With this giant white sheet of paper that you can't read. So actually, you got one of these on the way in. I'm not expecting you to read this. I just wanted to really highlight, sort of some key things that will be happening. So there is a method to the madness. There are four, if it weren't apparent, there are sort of these four key blocks, or four sessions, and the themes for these four sessions our intention, or why, what are the purposes of some of the visualizations that we're creating, which will be our first session right after this. Research, a lot of us do research, but this is actually people who are doing research on visualizations that we invited that could inform the work we're doing here. Storytelling with data is something that I think everyone's very interested. So how to use a narrative, and what are different devices for finding or telling stories with data. And the last session is really all about museums. Even though the whole conferences were really highlighting some of the importance of place. What is it that we can do in physical places, like museums that we can't do anywhere else? So these themes, we had a survey that was conducted by someone you meet here, Kate Haley Goldman, where we talked to active practitioners in visualization and informal science. So these were things that they thought would be really important for us to talk about as a field. Now, so those are the four kinda main blocks. Some other... Oh, this is important, 'cause then you'll see me being like, I'm gonna be really an aggressive time keeper. So each of these four sessions has a similar format. I will give a very brief introduction to why we're even talking about it. There will be three to five short talks, depending on the session, there each 15 minutes. So hopefully, no one slides are gonna get cut off. But it might come to that. There will be the talks followed by Q ans A, we're gonna do the Q and A after all the talks. And then before or after a break, it kinda depends on where it is in the agenda, we'll have working sessions, where you will all be, that you have different formats, but it's a chance for us to hear from you, for you to talk to your colleagues, for you to reflect on your work, for you to contribute. So you're not just... I love sitting listening to talk all day, that's why I could have done like 20 PhDs and probably work in a museum, 'cause it's like, "I'll just sit all day." But I know not everyone likes to do that. And we want to learn from you. There's also this afternoon, late in the afternoon, you all will get a chance to introduce yourself. And in this lightning introduction, I save that for the end of the day, when we're less cognitively capable. I figured this morning, we could do the thinking and then we can introduce ourselves to each other later. And there's sort of a salon or Expo where people can share their new books, prototypes. It's not necessarily a poster session, but again, a chance for you to share your work with refreshments. And both nights tonight, there's a catered dinner in our life sciences gallery that you're all RSVP'd to, so hopefully you'll be there. And tomorrow night, there's a happy hour and an after dark that's open to the public. So if you have friends in the area that want to come, there's a public after dark featuring installations and talks by many of the participants. So other practicalities. There is an awesome team who put this together. Trust me, all I'm doing is talking. People from the Exploratorium couldn't stand up. They're gonna be introducing themselves later. But for now, while you're wondering, where's food? Yeah, you guys can stand up. Just stand up if you're from the Exploratorium and you're staying around. So these are people who can help you. They're gonna be introducing themselves later. But if you're wondering where things are, what to do, okay, you guys can sit down now. When you're up, you're up and when you're... So they can help you and probably the person who we're gonna have to be thinking profusely throughout and who knows genuinely everything is Kathy. Wave, Kathy, in the corner Kathy George, who everybody? Yes. There was just gonna be applauding Kathy all the time, because all of you probably have been getting many... Kathy knows everything and has done everything. And so try to ask us first. But then if we run into problems, Kathy already has the answer. So that's the team. The sexual harassment policy. So you should have received when you checked in this morning, a sexual harassment policy. We are an NSF funded conference or partially funded by NSF. And they require that all conference attendees adhere to the sexual harassment policy. So it's not just oh, read it, if you feel like it. Read it, you will be held accountable to it. And if anybody is violating it, please come to me or Kathy. And yeah, you won't be able to be here. So that's that. Code of conduct, we will put up during some of the breakout groups, but those are sort of come less extreme than the sexual harassment policy. Just common sense things like, be aware if you're the one that's always talking. Or make sure you're letting other people ask questions, or don't be the person in the front row doing email. I've noticed, especially at academic conferences, no offense to the academics, you're like, "Why are you sitting in the front row "if you're gonna be like, playing Game of Thrones? "I don't want to see that." So anyway, just be mindful of those things. But along those lines, ironically, here's our Wi-Fi, it will be up periodically. Last night when I was like going through the talk, I'm like, "Oh, I like the order of please be fully present. "Namaste. "Oh, and here's the Wi-Fi." So anyway, there's the network and password. And similarly about being present, we actually are going to be tweeting actively with #visualise2019. I know it has a strange spelling, but it's for informal science education. It's not just like some British. So visualize and Susan Schwarzenberg thought it is very clever. I was really impressed, 'cause you could see the names that I was coming up with. So anyway, we are gonna be tweeting, we have someone on our staff, Kevin Boyd, who's actually an incredible writer who's gonna be live tweeting, we're taking over the Exploratorium feed for the next two days. And this is not just so that we can share the observations or ideas, but there are, especially in science, there are a lot of people on science, Twitter, lot of people in data visualization, so we're hoping this extends the reach of the conference.