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- Good morning, thank you for the opportunity to talk to you today about the things I've been doing in terms of data visualization and making a case for broadening participation in visualization. So I want to take the opportunity to share with you some of things that I've done, and as this slide shows in the upper-right corner, I consider myself an agent for insight. And so I give a little drama with that, and my mission is to encourage and to empower others to consider data visualization as a path for telling these different types of stories that we've talked about today. So as I was preparing this presentation, one of the questions was, "Who is deciding "what stories or questions there are?" And so as I was thinking about that in the work that I've done, to me, we all are the creators and the storytellers because there's so much information out there, so much data, the demand for persons with these skill sets are outpacing the number of people who have these skills to actually create these visualizations. So what I want to do is to talk to you about the things that I've done, a few initiatives that really speak to engaging others, particularly students, but all persons who are interested in developing and being a part of the data visualization process. And so again, every person who generates and consumes data are actually telling stories. We come from diverse backgrounds, we have different cultures, and we bring all of those perspectives to the things and the works that we're doing. So I wanted to give you a short timeline in terms of what I've done to work towards broadening participation in visualization specifically. So it all started in 2014. And 2014, I was at Clemson University developing workshops for the Clemson community and faculty at Clemson who were interested in making sense of their research data. And so I wrote up a grant that was approved by NSF to fund a two-day workshop, which turned into a one-week workshop for some people, ask me about that later today. But this workshop actually engaged all persons with an interest in data visualization, and so we had undergraduates and graduate students, we had artistic people, we had administrators, everyone who had an interest in data visualization. Subsequently that year, I was invited to give a talk, a keynote talk, at the XSEDE conference. And this talk was featured in HPCwire. And at this point I started to think, you know, there may be something to this. We had high schoolers to come to the first workshop, which I could not fund due to NSF restrictions, they wrote a grant, funded themselves, drove from Louisiana to Clemson University in South Carolina. And so to have the much initiative and wanting to be a part of this spoke volumes to me. So I thought, well you know what, this was about broadening participation, including all persons who are interested in data vis, what if we had something specifically designed for students? Like I mentioned before, the demand for these students, or these persons with these skills, is outpacing the number of people who actually have these skills. What if we could do something to help the pipeline for this? So I wrote another proposal that was funded by NSF which was an REU Site, Research Experience for Undergraduates. I had funding to bring in students from all over the U.S. with an interest in data visualization to do research in data visualization. So other programs, other REU Sites, usually have a visualization component, which means that they do research, maybe the last week of the research experience, "Hey, I have some data, "I have to give a presentation, I need to create graph." In this case, the whole purpose, or the focus, of this REU site, what was so unique about it, is that the entire research experience was about data visualization. And so we had students, what I call your usual suspects, which were your engineers and your computer scientists, but being the PI of such a prestigious research experience, I had the opportunity to be strategic about who we reached out to, so I was strategic about reaching out to the non-STEM people as well. So we had liberal arts students, I was at Clemson so we had people from athletics who actually participated in it, from agriculture, and so it was a very broad interests and cohort, group of people, who actually participated. That year I also organized a conference at the IEEE Vis conference, which was in Chicago, and we started thinking about could visualization be a pathway to STEM? We've all heard about, there isn't enough people in STEM to actually move science and research forward, and so we had a very interesting conversation about that. What's interesting about this is that my keynote speaker at the very first BPViz workshop, which was Donna Cox, she was so impressed with the workshop itself, she went on to become a co-organizer of subsequent BPViz workshops. And you can see her picture in the lower-right corner as a panelist at IEEE Vis 2015. So 2016, that was an interesting year. Not only did I have the second BPViz workshop, this time I was at Purdue University. So Purdue was actually watching the things that I was doing, unbeknownst to me, at Clemson and recruited me to come to Purdue and to help build out a new undergraduate major in data visualization. So I'm excited to be a part of that, I think we're the only one in the U.S. with this type of program for undergraduates. So we have the second BPViz workshop, co-located at Purdue one day and then at the University of Illinois in Urbana-Champaign the second day, which really gave hands-on experience with visualization tools. And it kinda gave the participants a behind-the-scene perspective of what Donna Cox and her group does. They do phenomenal work in terms of data visualization. I also gave another panel, or organized another panel, on visualization capacity building, so what is that? So as I'm thinking about all of these people who are showing interest in data visualization, how do we build the skills of these students and help them to have the capacity that they need in order the transform data from its raw state into a visual representation of what that data means? And so I continued to develop the curriculum at Purdue University for the new major for undergraduates, submitted a paper, and continued to talk about visualization capacity building. And then there was Vis 2016. So if anyone's here who was there, and I know at least one person was, something happened at Vis 2016. So for special effect, dun dun dun. There was another panel, but on this panel, I was not a participant of, the panel was about "On the Death of Scientific Visualization." So when I looked at that, and I looked at the panel list, I didn't see anybody that looks like me. I didn't see any diversity in terms of gender and representation, so I will confess, I thought it was gonna be a bunch of white men pontificating about the death of scientific visualization. So I went to another panel, I didn't go. It turns out, that was the panel to go to because that's where things started happening. And so I will say, like I said I didn't go, anyone who's interested, they do have it online. The very end of this panel, so I'm told, remember I wasn't there, a young lady stood up and asked the panelist, the esteemed panelist, about diversity in visualization. And the panelist said, "We don't have a diversity problem "in visualization." So you can imagine, and this is secondary information that I'm sharing, I wasn't there, that opened a whole line of different types of questions and interests and so. It also led to another panel the next year on which I was one of the panelists, and so we talked about diversity in visualization. The panel won best panel, of course. And so it was very diverse in terms of the panelists, in terms of the backgrounds of people presenting. And so it was a very good thing to actually have that conversation and to move it forward. One of the panelists, Kelly Gaither, actually published a paper on how visualization could foster diversity and inclusion in the next generation of science. 2018 came along, and by now, I've been teaching data visualization as a part of the major at Purdue. I have undergraduates in my class who are actually doing research in data visualization. Purdue has an undergraduate journal, specifically for undergraduates, where they can publish their work. We had so many students from the data vis class to submit abstracts, they started a special issue on data visualization for this journal in which the students can actually publish their work. And so I'm happy to say that we are getting more students engaged and involved in this process. In 2018, I hosted the third BPViz workshop. And so in these workshops, it is important to me that participants walk away with some actual skills. It's OK to say things are not right in terms of what can we do to improve participation, but I also want them to walk away with some skill sets or with some interests in things that they may not have considered when they joined the workshop. So that brings me to today, 2019. As a result of the 2016 panel "On The Death of Scientific Vis" and in the subsequent panel on diversity in visualization, the panelist from that 2017 panel actually have written a book. And so this book was published this year. You will find chapter five is the chapter that I contributed to on community on-ramping. And also for those of you who are interested, I along with my colleagues, two of which are here today, Leigh Peake and Ryan Wyatt and Kim Kastens, we are co-chairs of the GRC conference on visualization in science and education. And so this year, the focus, or the theme, will be educating skillful visualizers. And for the first time that I'm aware of in this history of this particular conference, we will be looking at broadening participation in visualization and what that might mean and how you might broaden participation where you are in your organizations, in your classrooms for those of you who teach. And then also, we're going to have a pre-conference workshop, and so this is where we're actually going to look at what does diversity mean and what are the different ways that we can actually incorporate diversity in our daily dealings. And so for me, I am continuing with my research in visualization on capacity building. I think having a major in data visualization is a great opportunity to look at pedagogy and to look at different ways of implementing different things in the classroom and also developing modules for those persons who are interested in incorporating data visualization into their classrooms. But you may not have enough time to fully develop an entire course, but you want to incorporate maybe pieces of this that might help your students to better understand the data that they're working with. So we must empower all persons to be effective storytellers and not just data generators and consumers. So I thank you for your time.