 Okay. I think we can probably go ahead and get going. So welcome, everyone. Thanks so much for being here. I'm Rebecca Cummings, the Digital Matters Librarian, and I'm going to be introducing our speaker for today. John Flynn is a Digital Matters Fellow and a PhD student in history. His research focuses on environmental history and the American West. Before coming to Utah, John worked as a journalist in Austin writing about science and the environment. John graduated with the Masters in History from Brown University, where he worked on digital humanities projects as the John Nicholas Brown Center for Public Humanities and Cultural Heritage. As a graduate fellow at the American West Center, he worked with Professor Gregory Smoke on Native Places Atlas, an indigenous map project in conjunction with Digital Matters. That's on the topic of storytelling with maps. We are going to ask that you reserve your questions for the end, but do feel free to put them in the chat box as they come to you, and we can address all those at the end of John's talk. So with that, I'm going to pass it off to John. Do you need me to make you a co-host so you can share your screen? Yeah, that'd be great. You should have that capability now. Great. Thanks for that, Rebecca. Let me just try and share my screen here. Are you able to see this PowerPoint here? Yes. Okay. Again, thanks for that, Rebecca. Thanks everyone for coming. So the topic is going to be storytelling through maps, and today I'm going to walk you through kind of a simple way to take your dataset and visualize it using RGS online, which is a really powerful mapping tool. Completely free to use, and the great benefit of this is it's a really good way to not only present your data and a really visually appealing way to your audience, but also opens up some new avenues of exploration and raises new questions. So when we're talking about storytelling through maps, I want to first talk about a really famous example. Some of you may have already known about this, but what the power of storytelling through maps can be, and this comes from John Snow. So unfortunately, it's not the Game of Thrones John Snow. It's not that exciting, but it's the story of 19th century physician working during the cholera outbreaks in London. So he was able to use the power of data visualization on a map to pinpoint the source of a cholera outbreak from a contaminated water pump pictured here on Broad Street. And the way he did this is essentially following the steps that we're going to do today. He took this on the left, which amounts to a 19th century Excel sheet. It's just a list of the deaths from cholera in this area. And he went by several houses and found out where people were living and where people were getting sick. And then he mapped this out on a map of this area of London here. So he had a cartographer draw this out. And then if we zoom in here on these buildings, these little bars represent deaths. And so when we zoom out, we can see that a pattern starts to emerge. And then a little bit clearer way to see this. This is a map that was made on his data a little bit later. But each one of these dots represents a death. And by looking at this, a story appears that is not exactly clear when you just look at this Excel sheet, this list view, but we see that it clusters around this pump on Broad Street. So now we're able to get a new insight that's not as readily available just looking at these lists. So this is the initial, what a lot of like geographers point to is the first public health epidemiology like power of data visualization. And this is the same thing we'll be doing today, just with a little bit different tools. Now we'll be using Excel and ArcGIS. So mapping in the humanities, these tools can connect our scholarly research with the digital tools of ArcGIS to raise new questions. And as I said, it can serve as a really great research tool and a way to present information to your audience. So the data set that we'll be using today actually comes from the Southern Poverty Law Center. And it's a list of Confederate commemorative sites in the US. This is partly inspired by this really great article by John Winbury that talks about the memory of the Civil War and how it's remembered and how it plays out in across the US with the creation of Confederate statues and things like this. And this is a big topic that's entered into the public debate today. So by mapping it out, we're able to really explore the history in an engaging way and find some new insights. So this data set is really, really great because it has about 3000 entries, all that research has already been done. But when we work in the humanities, often we find that our research is usually contained in data sheets when we are doing our secondary research or sometimes primary documents themselves, take the form of like account ledgers or government documents that are already in these kind of excel spreadsheets, the same as John Snow's. So we have this data already here. But I want to talk about what makes the data set really work really well for mapping. So the first thing is it has a geographic component. This can be city, state or county. But ideally, we're looking for things that have GPS coordinates because this gives us a level of specificity and RGS can automatically read latitude and longitude to populate our maps. So anything that has a geographic component, even if you only have a county or city, you can still work manually with that as well. The second component that makes a really good data set for mapping is it will have several features or attributes that can be toggled on and off and explored. And when I show you the excel sheet in the next slide, I'll explain a little bit more what I mean by that. But just a quick note and this always serves as a reminder to me, it's a really good idea to create a project folder to hold all your data sheets and organize it because we're going to be importing them between two programs. You just want to have all this stuff contained in one site. So here is a look at the data sheet as you can download it from the Southern Parbury Law Center. And I have a link at the end of the PowerPoint where you can find this data set. If you want to explore yourself, it's really, really awesome to just mess around with but also can be used as a research tool. But here in the first row, row one, these are what our features are attributes. So we have the unique ID, feature name, honorees, so who is honoring city, county, state. Importantly, in column G, we have our coordinates, the symbol type. So if it's a building, if it's a school named after a Confederate general, or if it's a monument, symbol category, sponsor. So sponsor is who created it or who funded it. And then the year it was dedicated. So these are the things that I want to explore mapping it out here. But we want to clean this up because there are a couple of things we want to do before we can actually import this into ArcGIS. So as you can see, there are some empty cells here in the date. That's okay. ArcGIS will work around that. The one spot where this would be an issue is if you have a blank cell in the coordinates, then it won't be able to populate that pinpoint on the map. The other thing to note is that our coordinates are in the same column here. If you try to import this in ArcGIS, you'll get an error message. So what we need to do is just separate these into two separate columns. This is really easy to do. We'll just split the data and we use text to columns in Excel. And so you'll find whatever delineates these two latitude and longitude. In this case, if we look, there's a comma separating them. So I just put other comma here, and it'll give us a preview how it has neatly separated our latitude and longitude, and it'll just move it over to the next column. So now we can see we have latitude and longitude in two separate columns. ArcGIS will be automatically reading that and putting it into our map. So the last step you want to do is, even if you're working in Excel or Google Sheets, it's best to save this as a CSV of comma separated value because that's what ArcGIS is going to read. If you try to import an Excel sheet just as is, you'll get another error message. So just go to save as right here, CSV, put it in our project folder. And now here is our final data set. You'll see I have gotten rid of the unique ID and the simple category because I wanted to simplify things. And the main things I want to look at are the symbol type, the sponsor, and the date. So here's our clean data set with our separate columns of GPS locations. So our next step is importing this into the map. And as I said, we're using ArcGIS online. It's a really great free program. And it can all be done in a web browser. So you don't need to download anything. There are some other tiers that come later that are paid for, but everything we're doing today can be done totally free. You just create a free account. And the stipulation is that any map you make is going to be publicly viewable. I would want to briefly point out a couple other options we have here. Mapbox is pretty similar to ArcGIS where there's an initial free version and then you can pay for some more powerful versions later on. But they're both pretty user friendly. It's kind of like if you've ever used Squarespace, there's a bit of drag and drop. If you're looking for something that's a little bit more customizable and open source, leaflet here at the bottom is an open source map. The downside of that or maybe not downside is that it requires a pretty intensive knowledge of coding and JavaScript. So if you know the coding language and want something open source, leaflet is your best bet. If you don't want or don't have the time to do that, ArcGIS online is a really great powerful tool. So we'll just create an account and then sign in and then we'll click map and then it will automatically give us our landing page for the map. So a couple of things to point out here before we import our data. Over here on the left, you'll see this eye is highlighted. It has this kind of built-in instruction to help you walk you through. This is why ArcGIS is really good. It's very user friendly. This next box right here will be content. So that's where our layer is going to live. Our layer is going to be that file, our data sheet that we import. And then this one on the right is going to be the legend. So the key for when we actually map out our data. This map is kind of works like Google Maps where you can drag and move around with the mouse. Or if you come up here to this address bar, you can type in any specific location and it will center your map onto that location. So the first thing I like to do is just select a base map tile. So what our map actually looks like. So we'll come up here to base map. And there's a bunch of pre-created maps or base maps that we can use from ArcGIS. Anything from satellite imagery to streets, topographic maps. And beyond just the mere aesthetics of this, there are pros and cons to using whatever your project is looking for. Say you're trying to do something that's geared towards this environmental factors or something like that. You want to use mountains and streams. So topographic or terrain with labels would be a good one to use. For this, I'm going to use human geography because it has these state boundaries and it's really simple and clean. So just click on that. And then here is our human geography map. You'll see it has the state lines and a couple of cities. And as we zoom in, more and more detail will appear. So now we have our map set up and we're ready to import our data. So first we're going to create a single point map. So this will just put a point on our map for each one of those rows from our data sheet. And to do this, we're going to go up to this add tab, scroll down to add layer from file. We'll have our pop-up and ArcGIS will remind you what files you can put in here. So CSV is what we have. Perfect. Choose our file and then just click import layer. And once we do that, we see that ArcGIS has already started to map out our data. And what we're looking at here is this name attribute. And so these attributes up here come from this first row in Excel, right? So just because name is first, that's the first one that ArcGIS automatically went with. But that's not particularly helpful. I would actually like to see this broken down by symbol type. So I can see where monuments are, where schools that are named after Confederate generals are, and where parks are. So we'll just click on that delta and it'll drop down to symbol type here. And then we can see that our legend has updated. And now we can already start to glean a lot of information here. So red dots are monuments, blue dots are schools, green is parks and so forth. So by looking at this, we can see rather unsurprising, there is a lot of this happening in the South where there were former Confederate states. And most of these commemorative sites take the form of a monument or a statue. So there's a lot of red. But then we can also see there are other things we could explore. If we look over on the West Coast, there's a school in Washington. There's a couple monuments. There's a college up in Maine. So just by clicking on these, we could raise some new research questions to look at what was happening or what group formed these sites. So this map is still interactive. Each one of these dots can be clicked on and contains all that information from our data sheet. So if we zoom in on outside Atlanta and click on one of these dots, we'll see we have this pop-up menu emerge. And we have the name, the honoree, the city. And if this stuff looks familiar, it comes directly from this row in our Excel sheet here. This is a really great way to explore your data. So we know that all these red dots here are monuments. These green ones are parks. If we want to know specifically what something is, we can just click on it and get that information. This pop-up can also be edited. We can add more text in. It's describing it. We can also add files such as photos or audio as well. So if we wanted to go take photos of some of these sites, we could put that in here. So this is a really good way for you to explore for your own research or present to an audience that wants to understand the prevalence or proliferation of these monuments a lot more. A quick note. When you're done selecting your style, you just click OK down here and then remember to click Done. And that will save the features that you've chosen for that map. And so that'll bring us back to this main landing page. And we're on the content and we can see that this Civil War monuments, this is the name of my data sheet that I've imported, and it's appearing here. When I want to change that style again, I'll go back over here, hover over this layer file, and it'll highlight as blue. And then just click this triangle, square, and circle. That's our change style. And that'll bring us back to this menu. And then we can select a different drawing style. So for this case, I'm going to use location. So it's only going to appear as a single dot for that data entry. And this creates a much cleaner map. It's not as good for exploration, but if we wanted to add this into a research poster or an article that can be accompanied by a paragraph explaining it, it is a really good way to simply convey information. Okay, we know that a lot of these sites are along the south here. But single point maps are not the only way that we can explore this data. Another option we have are heat maps. So heat maps are really great. You can see an example of it here on the right. They draw our attention to these hotspots. And the way they work is they work numerical values. So their best use for intensity or frequency, anything that has a numerical value in your data set here. So if you have profits or sales, say you have the number of books published in a city or different cities, immigration numbers, there's a really great historical monograph I love called The Mortal Sea. It's about overfishing in North Atlantic. And the primary documents he uses are these fish catches of the day to have the numbers. So anything like that can be used to create a heat map that'll show the intensity of these numbers. So for our data set here, the only numerical data we have is the date, but we can still use that to visualize this. So if we go back to our change style and click on date here and scroll down and select our heat map, we'll see that we have a legend here. And then when we look at, excuse me, when we look at our heat map here, we get a really broad sense of trends. And there's no specific specificity here, but we can see, okay, these hot spots here occur around cities. So the highest concentration of these commemorative sites, schools, and monuments are occurring in southern cities. And then we have this really hot spot up here in Richmond. But if we wanted to have a more specific look at what was happening based on date, we have another option of how we can visualize this data. And this is called counts and amounts. So we're still in our change style menu here. And instead of a heat map, we'll go beneath it and click on counts and amounts. And then we'll see that our legend has changed into this gradient. And you'll see these commas here. That's because our gist is just reading these as straight numerical values, but these are our dates. So the further in the past it is, it's this yellowish color. And as we get further and closer to contemporary times, it's this dark blue. So anything that's this dark blue will be something that was created after 1955. So if we switch over looking at our map here, all these dark dots are something that was created in the latter half of the 20th century. So now we can see a different trend emerging where it wasn't immediately after the Civil War that these things were created. A lot of them have been created during different eras in the 20th century. And by looking at this, we can compare it with other historical research that was going on. Around 1955 into the 60s, we know the Civil Rights Movement is going on, so we can explore if these were a reaction to that. Or we can look over here somewhere like New Mexico that only has four dots and they were all created in the 20th century. So this opens up something that wouldn't be as easily readable just from our Excel sheet. If we were going through, we could see maybe New Mexico on there, but by looking at it this way, we say, oh, they're all concentrated in southern New Mexico and they were all created in the second half of the 20th century. So that is something for a historian that might be worth exploring what was going on at this time that there was a group creating these. So further, another way to explore this is by combining two elements. So something I'm really interested in is this idea of the sponsors. So who created these? We'll see that there's this group, the United Daughters, the Confederacy, and they created a lot of monuments. I want to know which ones they created and when and where. So to do this, we're going to combine sponsors with date and visualize that on our map here. And the way to do that is we'll go to our change style. We're going to select sponsors here, but then we're going to go to our options and type. And if we go down here to the bottom, we're able to set the transparency based on an attribute value and we're going to use date for this. So once we click on that, we're going to select date. And then we'll see we have this pop up here where there'll be a transparency for these dots based on the date. So the more solid it is, similar to our council amounts, the more recent it is, the more transparent, the further in the past. We can also see a little break down here along the side of when most of these were created. We can see there's a big surge at the turn of the century here. So when we put these two together, a quick thing we want to see, if you have something like an unknown category, this can be kind of a distraction here. I only want to know what groups like the Suns of the Confederacy or the United Confederate Veterans were making monuments. I don't want this unknown category. It's going to be a little distracting. So I'm just going to make that invisible by selecting this blue dot here. You'll have this pop up where you can change the color. You can do this for any of your icons here to customize the color scheme you want. But for this case, we're just going to click this red line through a white square that'll make that a null color. Click okay. And so now if we look on our legend, unknown is invisible. And so it looks like there's a lot going on in this map. But if we know how to read it, we can glean a lot of information from it. So one, as we already knew from that count, this group, the United Daughters of the Confederacy were creating a lot of monuments, but they were also creating them all along the south. And then compare that to the transparency, we see that they have some really pale colors and some really dark ones, which tells us they were not only creating these monuments throughout the entire south, but through like many decades after the Civil War, they've been working ever since the late 1800s up into the 21st century. And we can compare that to another group, say the screen dots, the Suns of Confederate Veterans. We see that these are all mainly solid, which tells us that they were mainly a more recent group working in the late 90s and early 2000s. So a couple of these up here are Confederate monuments that were made in 2004 and 2007. So by visualizing the date and sponsor, we can look at different ways to explore this data. So if we wanted to say what was happening in the 90s and 2000s that this group emerged and was making some Confederate commemorative sites mainly in this area of the U.S. Or if we wanted to just work on some historical research on the United Daughters and add a little bit of emphasis of how prevalent they were through time and geographic space, this map really exemplifies that. And if you want to emphasize a certain group, you can always make these other ones invisible the same way we did with Unknown. So if we wanted only United Daughters and the Suns of Confederate Veterans, just those green and red dots, it might make the map a little bit more clean. The last thing I want to go over is filtering by different features. So by doing this, say we want each symbol type to have a different icon to make it a little bit more visually appealing and easier to navigate and explore. ArcGIS does have a filter feature, but it only works with their built-in data sets. It doesn't apply to these imported CSV files. And there's a really easy workaround to do this. We'll just separate our data sheet into different tabs based on a feature class. And so I'll show you what I mean right here on our Excel sheet. So if we look here at the bottom, I've created different sheets, and they're all based on what kind of monument type it is. So if it's a military base, a park, monument, college, or school, and just copy and paste those into these different tabs. So when I'm on the Monument tab, it still has all of our information, but it's only one symbol type. You'll save each one of these as a CSV file. Again, this is where that project folder is really helpful if you have a lot of different tabs you want to keep it all in one spot. And then you'll import it the same way we did at the very beginning. And when we do that, we'll see our content page has changed. Now we have all these different layers here, and we can toggle these on and off just by clicking on those blue squares. So anything that has a blue check on it is going to be visible on our map, and we can still explore all these without deleting or erasing any of this data. So when we want to change these icons, again, we're going to go click on this change style. And we'll go to location single symbol here. And this will open up a new panel for us. And we can see here we can change the symbol. So I'm on the park layer. I'm going to choose something that represents parks. So ArcJS has this built-in icon list that has tons and tons of icons you can choose from anything from standard highway signs to National Park or these kind of simple geographic location dots that you would see on something like Google Maps. Points of interest is a really good one. I'm going to choose this tint here because it kind of represents a park to me. And you can change the symbol size here and click OK. And so when we do that, we get this variety of different icons here on our legend. Zoom in on this. You can see colleges, something that represents that, parks, monuments, and schools. The great thing about these icons is you can create your own and import it into ArcJS if there's something specific that you want it to use. So if you're doing something with topographic physical features, you can make a mountain or canyon and use that to designate this. So again, our map is busy just because we have so many data entries, but it should open up a little bit more, make it a little bit clearer what kind of trends we're looking at. Because if we look here in Arkansas, we see that most of what's going on here are colleges. There's not really anything but these blue dots here. But if we look at somewhere like Georgia, it's got a good mix of everything and a lot of these monuments going on here. And here's a zoomed in version of Richmond. Remember that was a hot spot we were looking at earlier. We can see what the breakdown looks like on the scale of just the city. So this is the medical center here. These blue dots are these schools. Most likely, most of the time, what that registers is like a college hall named after a Confederate leader. And then there's a couple of monuments. And then there's a street here lined with Confederate monuments. So this again is still interactive. Each one of these contains all that data. We can explore it this way if we want to look at what's happening here. By doing this with what we've done in the past by filtering by the attribute of sponsor, we can really explore this data in different ways, rather than just having a single data Excel sheet that we have to read through. Now we can start to see these different trends emerging, where if we were looking at it for Arkansas, it wouldn't be exactly apparent that most of the commemorative sites here are colleges. But now by visualizing it on a map, we can see these new trends and stores emerge. And this is why it's a really useful tool because now there's a lot of questions I have after this that I can do some independent research on. Say, looking at the Confederate sons of veterans, what was happening with them, why is it that they're only colleges in Arkansas? And so the final steps here of when we're finishing up our map to save it, because we're using ArcGIS online, it will be public. So when we click save as, we'll have this menu pop up, and you'll just have to do a couple of specific things. Other than giving it a descriptive title, you'll have to give it some tags. These don't have to be anything in particular, usually two or three are good. Just something that kind of relates to your project. So for mine, I just did monuments, statues and parks, a brief summary, and then save this map. And then then this will be stored on your profile in ArcGIS. When you go to your content page, you'll have a list of all of the maps that you have here. Didn't have time to go into this, but I wanted to briefly give you an idea of what you can do with these maps now. And ArcGIS does have a lot of really good FAQs on walkthroughs. And I think Justin Sorblin is here too. He's another really great resource. If you want to know what you can do with these maps, but they can be embedded on web pages. You can make them into a slideshow presentation, adding slides as you walk through it. Story maps is another powerful tool that ArcGIS has where you can have this more narrative function where you walk people through. But they can also just simply be printed out and used in a research paper or on a project poster at a conference or something like that. And so when deciding which map to use, I like to think these busy maps are really best left online and used for exploration where you can zoom in because, as you saw when you're zoomed out, they kind of overlap. But when you get into the cities, things start to become more apparent and you can still click on these and find out, okay, what kind of college is this? What kind of park is that? And then cleaner maps are really good for presentations where a map like this conveys a certain point that is really emphasized by just an additional paragraph accompanying it. And so this last slide here, here's where you can get the data. Like you've seen, it has a lot of stuff going on. It's really, really fun to explore. You can do a lot with it. And if you're just wanting to test out and explore ArcGIS, it's a really great data set to use that with. Here's a link to ArcGIS. And then here is a ArcGIS map that was made on that John Snow color map outbreak that we talked about at the beginning of this. That's really fun. Can show you a way to bring a historical narrative and data set to life. And here's my email if you have any questions. And I want to thank you all for taking the time to watch this. I hope it was informative. And I think there's some time for questions. I'll stop sharing here. Okay. Thank you so much, John. That was fantastic. I don't have the emoji clap. So I just do this. But this, that was so great. What a wonderful look under the hood of how to make maps with data. We do already have a few questions that have come in, but I am going to pause briefly, give John a chance just to breathe. I have an announcement. I should have said it, but we have a really special event coming up on February 4th. So before I lose anyone, you know, by the end of Q&A, I wanted to announce that Julia Flanders from North Western or Eastern, David, was it North Eastern? I feel like you would know that. Hold on. Okay, Julia Flanders. She is a professor of English Eastern. Thank you. Director of the Digital Scholarship Group at North Eastern University Library is going to be giving a talk called Digital Archival Literary, Evolving Models for Digital Scholarship. Julia is absolutely fantastic. She has run the Woman Writers Project for 30 years. One of the biggest text encoding initiatives in our industry that'll be co-sponsored with BYU. And I'm sure you'll see announcements on it, but mark your calendars for February 4th. So back to John. We already have some great questions coming in. I'm going to start with one that came through a private message, but it was a multi-part question. Let's see. So John, if you are collecting data, how do you find coordinate data? And I'm also curious if other data would work like street addresses. Yeah. So street addresses, anything like that you can work to kind of manually do finding the GPS locations for that. ArcGIS can also do that for counties and cities as well. There also are a lot of online databases that already have these things pre-loaded in. So the US Geological Survey has this like 40-page Excel sheet. We're actually using it on one of our projects that has pretty much every physical feature in the US listed on it with the GPS coordinates on it. So there are data sets that are available. This was a really great one because a lot of the research was already done where they had the GPS locations loaded in. But sometimes if it's in your own independent research, it would mainly be just manual plug-and-shot finding these sites. And then the second part of that question was, can the public interact with your data or is it administrator manipulation only? And I assume that she means for your data on your maps. So sorry, could you repeat the question? Sure. Can a public interact with your data or is it just administrator and manipulation only? So for example, if someone, if you had your map on a website, would a user be able to download the data and do something different with it or is it just you that can manipulate the data? You can make it public. So you can make your maps interactive where I was showing how you can click and pinpoint on certain things. There is also a way to make it where people can do that as well. But you have the choice to make that data public or not. Your Excel sheet, your data set's not, it's loaded in, but it's not able to be downloaded from ArcGIS for just anyone looking at it. Another question for you is, do the visuals export as JPEG or PMG? So when it shares, what can it be shared as? So it can be shared as a couple of different things. One way is it will live on this ArcGIS account and that's where it gets made public. You can also embed it as a box onto a webpage or you can export it as an image. I believe you can do a JPEG and a PNG, but I haven't done it on ArcGIS online. I've done it in the pro version. Okay. And it can be shared as a link as well? Yes, and it can be shared as a link as well. And it can be used, the great thing is they can all be used mobile as well on a web browser. Nice. That sounds really flexible. The next, oh, well, this was a question also directly sent to me, but can we have a link to the slide to the slideshow and links? And actually, yes, we've actually decided that we're going to start emailing out to the digital matters list of the day after or maybe two days after the materials because we've been getting some requests for those. So you will have a link to the slideshow and the recording of this as well. So a question from Max Schleicher. He says dumb question, but I doubt that's true. Dumb question, WRT to GPS, sorry, Max, do you want to read this? Let's see. Yeah, sorry, with regards to WRT. I didn't realize that sounded so like internety and slangy. Apologies. Yeah, so with regards to like how when you made those heatmaps, you're basically taking these like pinpoints and then expanding them into larger areas. And so I was curious about like how you take a group of pinpoints and expand them into a larger area. And so my question was like, does ArcGIS automatically do that? It seems like it does, but then numerically kind of like what's happening on the back end? Like how does it like on the longitude and latitude number values? How does it know like, you know, and how would you do it manually or something like that? So there's a couple of different ways. Like because I was using dates, it was a little bit different. If you're using say profit sales of different cities. So say you're looking at just alcohol sales in different cities. So we want to do like Austin, Atlanta, New York, Philadelphia, and they have different numbers. The intensity will be represented in each one of those based on how high it is. So say Austin has a really low one, it'll be a cooler color, New York has a higher one, it'll be hotter. And this particular map, it looks, let's see if I could maybe screen share one more time. Looks like it can't, it's, as you zoom out, you'll see you're seeing the concentration. So that's why Richmond looked really hot because there's a lot concentrated there. But if you zoom in on the map, you'll see that there are these separate locations. So those are the two ways to do it. If you have a single point, like I said, it'll go by the numerical value or it can just read it like this for the dates of just concentration of like where are these hotspots? Where are there a lot of them centrally located? I hope that answered your question. Okay, thanks, John. And I learned something new about Internet acronyms. That's good too. Here's a question from Matt Basso. He said that was great. Is there a central repository slash site for ArcGIS history datasets? For example, I'm interested in World War Two homefront datasets. Not that I know of in terms of ArcGIS, there are ways you can explore it because a lot of them are public made. So this John Snow one, for example. So that would be something you could look at. I haven't looked myself for that particular one, but to my knowledge, no, but Justin might be able to answer that question better than I could. I'm just not sure if there's an actual repository for these history datasets. I feel like I saw Justin at one point. Oh yeah, he's still here. Justin, are you familiar with any kind of historical, you know, latitude, longitude dataset repositories? I'm aware of, but generally you can do just kind of like a basic Google search and see what's available. Usually if it's like a state fund or a state repository or something like that, they'll have a link to it. Like Utah, the best place is like AGRC's website, something like that. Well, and Matt, also, if you ever wanted to reach out sometimes, especially when I was a data like, not so much. Is everyone else at the bias on the set? Rebecca? So Rebecca, you broke up there, but I think you said just to reach out to you if we want to work with you to try to find some datasets on our particular research areas. Thank you for that. Mine froze up and I didn't realize it. So thanks for what you said. I don't think you all heard Yamna's question though, which is in the chat box and I had said, and then it dropped me. But Yamna had a great question. Can you combine several files to show on the same map as a way to offset the bias in data collections? So for example, if one file focused on the south, maybe another organization focuses on another area. Yeah, didn't really have time to go into it, but that's another great way you can cross compare different datasets. So the way that we imported that layer file, and then the second thing where I separated them to different sheets, each one of those is essentially its own Excel sheets CSV file. So you could import two different datasets and toggle them on and off of those blue squares and have them lay on top of each other to compare in that way. And they would be registering as the source of that. So you could have two different, you know, research based datasets and then overlay them. So yeah, you totally can. I think that's all the questions we have in the chat box, but I had a question for you too, John. I was really interested to see like the mechanics of how you made the map and how you showed, you know, different filters. That's okay. My internet connection is unstable. I'll shorten the question. I was so interested to see you talk about the mechanics of building the map, but I am curious if you had any analysis or discoveries that came out of that data with Civil War monuments? Yeah, definitely. Some of the big insights were just how many were created in the 20th century and the certain groups that were doing them at certain times will kind of see these spikes and they correspond with certain historical events. This is why I think it's great to combine with other historical research. So there is a rise in the creation of specifically statues and certain dates that correspond with KKK movements and then also in reaction to civil rights movements. So we see a big push immediately after the Civil War, again at the turn of the century in the 1920s. And then we saw that there was a lot of those blue dots after the 1950s. So I like looking at it that way because you can see where it's specifically in geographic locations or across the south that there are these spikes and what they correspond to what's going on in other historical events. Other than that, it did open a lot of new doors to look at outside of the south. As I was saying, you see that there are some up in Maine along the West Coast and those are just interesting things to look at the history of why, especially in a place like Washington that was so far from the Civil War, what's going on there that there's a site created there or what happened in New Mexico that a couple of sites were created all in the second half of the 20th century. So that's why I really like this because I think it can present a nice picture to your audience. But for as a research tool, I would never have gleaned any of that information just by looking at this excel sheet because it's just a really long list. But now when we visualize it like that, there's new patterns that emerge. I think that's what's interesting to me about it as well. But we might have time for one more quick question. Any other burning questions for any of our attendees? Quick question. John, if you are looking for GPS coordinates that aren't really available and you want to find them manually, how can you do that easily? There's, and again, Justin might know a quicker cleaner way than I do, but say you have a general location such as a city or a street address, you can do it that way with street addresses or the way that I would have done it in some of my data sets is just manually on Google Maps or something like that finding these. But like I said, there might be a cleaner way that I just don't know about. And I've been doing this old fashioned way that Justin could tell you. But Google Maps is a really powerful tool. Any address you have, anything that is something relating to geographical location, you can do that way. Or comparing to these data sets, like I said, the US Geological Survey say I know that there's a site on this mountain. What's the GPS location for that mountain? I can compare it to that data set that's already done by the USGS. So at Google Maps, I could just pinpoint some random location and give me a GPS coordinate. There's a way on Google Maps to put in a pen in there and it'll give you a latitude and longitude. And Max just shared a link as well. Max said he was curious about that too, David. It looks like you might be able to hit an API to get that. And then he has a link in there if you wanted to save that. Max is coming through. So I think we've hit our time. So I just wanted to thank our presenter one more time. Thank you, John, for a wonderful workshop. Again, our next, yay, our next workshop or our next speaker session is going to be on February 4th with Julia Flanders from Northeastern University. I know that that's going to be a really exciting and in-depth one and I hope that many of you can make it. And thank you so much for coming, everyone. Stay safe.