 And I want to welcome everyone to this edition of the Public Good App House. We'll be showcasing tech for your nonprofit to unlock the power of location-based data. So the Public Good App House events, like these, are initiative of the TechSoups Caribbean Studios. At TechSoup, we believe technology like smartphones, internet connectivity, training and more have the power to serve our communities better. So today's presentation we have Nick Rabinowitz, senior staff software engineer at Foursquare. Nick has over 20 years experience in software engineering data visualization and information management. He's currently at Foursquare as a senior staff software engineer where he works on web-based geospatial applications. So thank you Nick, excited to hear from you. Thanks for having me. I'm here to talk about geospatial analysis with Foursquare Studio. And before I sort of get into our products, I really wanted to take a step back and talk about why we do geospatial analysis at all. Before I was a software engineer, I worked in a lot of nonprofits and I found that, we often wanted to use technology, but it was frequently not used for actually doing our core work, answering our core questions and supporting our programs. I really like maps because they take this messy, messy world that we have to work with, this hugely complicated geographic space we work in and they abstract it into these simple forms. They abstract it into points and lines and polygons. I especially like the abstraction of the grid where you divide everything up into these equal area cells. I think we understand in the nonprofit space that abstraction can also be dangerous. You can abstract over complexities that have real-world impact. But that said, abstraction can also be really, really helpful in giving us insight into our data and insight into things that would be invisible if they were masked by the mess of the real world. That sort of brings me into geospatial analysis and that's what I'm really here to talk about. We use geospatial analysis and geospatial tools to answer questions and to make decisions. I love storytelling maps and I'm never going to say that telling a story with a map or using a map for presentation is a bad idea, but I also really love using maps to actually answer some key question, to support some program decision that you can't otherwise easily access. This is most useful when geography matters, when close things are more related than distant things. This is a play on a famous quote from Waldo Tobler. You will have some times when the geospatial relationships between elements of your data really matter and sometimes when they don't. Sometimes a small city is more like another small city and not like the big city right next to it. So recognizing when you have a geospatial component can really lead you toward geospatial analysis. And as you've seen throughout this presentation, I think maps and visualizations are often a key component of this. So Foursquare, you may know us from our early days as a consumer app and we still do offer consumer mobile apps. But right now really our focus is on curating and offering these rich data sets of geographic information, our movement data set and our places data set. I'm going to talk mostly about the places data set, which has over 100 million different highly curated records of venues, points of interest, stores, landmarks, everything you might want to know about in the world and using both machine approaches to make sure the data quality is high and human verification to make sure that the data quality is high. We can tell you whether the store is open or closed. We can tell you what the hours are and you can trust that information. So that's incredibly useful. We sell that to a lot of enterprises, but we can also I think leverage that in nonprofit contexts. And then we have a variety of applications that build on top of this. And the one I'm going to talk about today is Foursquare Studio. So Foursquare Studio is a web-based application that allows you to do geospatial analysis to share it with your team and to integrate it with other systems you might have. You can integrate it with your own database. You can integrate it with your own geospatial application. Or you can just use it by itself and upload your data as easily as dropping a file into the browser. It's a place where you can make a wide variety of maps, share them with the people you work with, and collaborate on them. You can use either big or small data, whatever you have, drag it into the browser and start working with it almost immediately. So what I wanted to do was actually a quick demo of how we might use Foursquare Studio to do a small example of geospatial analysis that would be appropriate for a nonprofit context. So I'm going to start with this sort of blank map that I put together. And the context we're working with here is maybe you're a food bank working in Atlanta and you want to find a new distribution point. And this is a place where you're really concerned about where there is a need, where there's limited access to food. This I think used to be called food deserts. Now it's more called low income limited access. But we can start by just looking at where are the food retail locations? Where can people go to access food? So this is an extract of our Places dataset. It has thousands of different food retail locations in Atlanta. And it can easily tell you so quickly where you can go to buy food in the Atlanta area. We're really interested about access. So it's not just where the food retail locations are, but we want to really look at how difficult is it to get there. As a quick proxy here, we're going to take a one mile radius around every single place that you can buy food, healthy food in Atlanta. And we're going to be able to see quickly that there are some gaps in between where no one is serving those areas. Now this alone isn't really enough to allow you to draw a conclusion. You really need to know what's the population like? Are there underserved populations here? So in this case what I'm going to do, I'll hide this for a second, bring in our census dataset. We have a census dataset that's free and accessible in the app where you can look at all the census data on a grid basis. So this is the geospatial grid I was talking about before. For any place in Atlanta we can see what the total households are. It was drawn from the American Community Survey. And so this has income level as well. Right now this is showing total households, but we can quickly change the layer and show something else instead like income less than $20,000 a year. And we'll use, in the rest of this demo, we'll use that income level as a proxy for low income and people who might need food access. I'm going to close this and I'll say I took an extract of that data because it's a little easier to work with in geospatial analysis. So I basically just drew this circle around Atlanta. I took out all the census data that I wanted to work with. And now I have this extract that's a little bit quicker to work with than some of my other analytical needs. I can turn this back on. Oops, excuse me. I can turn back on the one mile radius. And we quickly sort of see, okay, here's some areas with many households that are not being served. And you can just sort of visually quickly see where there might be gaps. But usually the real advantage of using geospatial data is that you can apply not only the visualization element, but math. You can actually do some calculations. You can figure out ways to look at the data that might not be immediately visible to the eye. So what I did, and this is sort of taking the cake, the pre-baked cake out of the oven because I don't have time to go through the entire process, but it's pretty quick. And what I did was I joined all these circles from my food retail locations with my census data set. I get this spatial join data set. This is showing the total households. I can obviously, you know, I can still show this income less than $20,000 a year. But I can also show, you know, how many places you can access. So how many retail, food retail locations can you access in these areas? So I basically counted the number of food retail places you can access in each of these little cells. And now I have this map of food access. Having both of those together in one data set means that I can quickly set the kind of filters that I would want to set if I've been looking for key places where I might want to do some new intervention or new food distribution point. So I want to look for places where we have no food retail, sorry, no food retail. So zero, and I've got one more layer that I'm going to turn off just to make this a little clearer. So all those gaps, these are places where there's no food retail. Now it's showing us places. It's cutting out all the places where there is access. And I'm going to add one more filter to filter on low income households. So now if I want to, you know, I want to drag this up and I want to drag this over a little bit. And now I'm able to filter down on these areas that have low income households and are not served, whoops, dropped my, and are not served by retail areas. And that quickly, I've done a little bit, I can filter more aggressively or less aggressively, but you can see it's quickly bringing up these areas where we have, you know, a large number of low income households and where there's no food access within a mile. So again, this is an abstraction. This is not going to solve the question of, you know, where you should put your food distribution point. But I just wanted to give an example of how you can use this kind of geospatial analysis to quickly get an entry point for where you might go. Now you might want to go and talk to people. Now you might want to go and do more investigation in those areas, but this gives you a quick way of understanding where you might look for further information. I hope that was helpful. Thank you so much again for having me. Foursquare, I will say, we don't have a fully fledged sort of nonprofit support program, but we are really excited to offer free and discounted options for our data and our applications to nonprofits. So please get in touch with us at foregood at Foursquare.com. And Foursquare Studio, you can try it for free. And there's really a lot there that's available for free. So I would encourage you to go to studio.foursquare.com. Try it out and make some maps. Thank you so much.