Hi, everyone. Welcome to our ICSD side event on timely georeference data for the Sustainable Development Goals. I'm Mary Emerby and I manage SDGs today, one of the Sustainable Development Solutions Networks data programs, and I'll be moderating today's session. Before we get started, we're going to share a poll with you so that you can tell us a little bit about how much you know about our program. We're interested to learn if you're familiar with what we do as we'll be introducing you to SDGs today and the various projects we're involved in. We have a great lineup of speakers who have played a very important role in the development of the program. So let's give it another 30 seconds maybe for you to respond. And while you're doing that, I'd like to invite you to tweet during the event. Please follow us on Twitter at SDGs today and use the event hashtag ICSD 2021. Perhaps one of my colleagues could share our Twitter handle and event hashtag in the chat. Okay. So, great, it looks like some of you are familiar with SDGs today and for those who are not, please stick around as we will be walking you through our various activities and projects. Okay. Let's get started. It's a pleasure to introduce our keynote speaker, Gordon McCord, Professor of Economics at the School of Global Policy and Strategy at UC San Diego, the director of SDGs Policy Initiative, and senior advisor to SDSN. Gordon, thank you for being with us today. The floor is yours. Thanks very much, Mary. And thank you everybody for the invitation. Happy to join you for this event. Just to lay out, I think the challenge a little bit and the motivation behind SDGs today. When you think about many of the challenges of sustainable development, you realize that they're inherently spatial challenges. Things like understanding the spread of infectious disease, something that's been very relevant in our lives over the last 18 months. Understanding who's at risk and where to deploy different public health measures are inherently a spatial question and a spatial challenge. Understanding the spatial distribution of violent conflict around the world and what measures can be taken to reduce the likelihood of conflict in the future. Understanding how to use land sustainably in ways that meet our agricultural livestock timber and urban needs, while also meeting our collective goals and biodiversity conservation and reducing greenhouse gas emissions from land use and land use change. Questions like the land use implications of massive solar and wind energy infrastructure that we'll be building in over the coming decades and countries all over the world. What happens to the agriculture that was there, what happens to where the transmission lines go. These are spatial questions. Where should the next school be built. Where should the next obstetric surgeon most urgently be deployed to reduce maternal mortality in the country. All of these kinds of questions require a spatial lens through which to look at the world and timely data to understand in real time or as close to it as possible, what's going on across all of these different challenges and sustainable development. So solving these challenges requires understanding problems spatially and designing solutions spatially. We have many new tools over the last 15 years from geographic information systems to remote sensing with satellite data to drones to spatial data analytics and all of these will need to be mobilized and deployed. And yet, often we're depending on 20th century data collection methods. We're having to wait five years or 10 years for the next census or the next household survey to understand how poverty or education or migration is evolving in our societies. And we know now that working with national averages for indicators is just not enough. The countries are large, they're diverse in the challenges that they face. And so we need to be able to go down with data district district by district to actually diagnose challenges and progress towards the SDGs and tailor solutions to those different challenges. In the 21st century with all the technology we have available, we urgently need more timely data that's geospatially explicit. And that's what SDGs today is all about. The work of SDGs today is vital to inform data driven and evidence based policies to meet the SDGs. My own work at the SDG policy initiative at the University of California San Diego is all about this. Together with the sustainable development solutions network, we work at national and subnational scales, deploying systems to monitor as many SDG indicators as possible, and at the highest spatial resolution possible to help government and other stakeholders map out what areas are on track and what areas are off track to meet different SDGs. We can then work with policymakers to identify priority areas and communities, and work with those communities and stakeholders to plan public and public private investments that can begin closing those gaps. We do this work with national governments, but also with local governments. As an example here in the San Diego region, two kinds of projects that we have are helping to further progress towards the SDGs. We work with our local planning agency that's called Sandag, we're building an SDG dashboard at the highest geographic resolution possible, measuring things for example at census track level and then projecting out to 2030 to figure out how are different communities by race by ethnicity by socioeconomic status across different neighborhoods in our region. How are they progressing and where does the government need to focus efforts. A different project here is is a decarbonization trajectory or decarbonization pathway to mid century. So how is this area of Southern California going to reach zero. That's a spatial problem that needs timely data and understanding where is energy demanded and at what time, where do we need to put the solar power where do we need to put the wind power where will the new transmission lines go. How do we do that in a way that we don't offset agriculture or push out biodiversity or ecosystem services these are hard spatial planning challenges that we need. All of us in all of our societies to deal with over the coming decades and spatial data is critical for monitoring planning policy making and holding the system accountable. It's in everyone's interests, researchers analysts policymakers civil society to have timely measurement of SDG indicators, we should all work together to do that. Later today you'll hear an example the my school today program in which anyone around the world can help crowdsource SDG proxy indicators, sitting up systems where we can crowdsource the location of public infrastructure like schools and combining that data with high resolution population data sets, let's us have timely estimates of how many people live prohibitively far from public services. Working with universities and others around the world, we can enrich open source data repositories so such as open street map to reflect up to date state of public infrastructure in every country around the world. And that's just an example. Researchers across fields like environmental science epidemiology and economics now routinely work extensively with satellite data drone data mobile phone data to measure what's happening in human society and in the natural systems that humanity depends on. As a platform showcasing timely data for the SDGs. SDGs today brings to researchers policymakers and civil society from around the globe, the very cutting edge in measurement for sustainable development. I have no doubt that this initiative will catalyze improvement in how governments around the world and other stakeholders design data driven policy, and how researchers can help diagnose problems and evaluate solutions. Thanks very much for inviting me to join you today. Thanks so much Gordon and thank you for highlighting some of the questions and challenges we're trying to address that SDGs today through our various partnerships. Okay, now we will move on to a series of presentations by the SDGs today team. I'll start with an introduction to the program and hand the mic over to my amazing colleagues to share their work with you. So, I will go ahead and share my slides. And I hope that you can see my screen. Great. So, STSN, a president professor Jeffrey Sachs had using new data sources to measure and monitor progress towards the sustainable development goals. And in July 2020 SDGs today was launched by STSN in partnership with Esri and the National Geographic Society, with the aim to advance the production and use of real time and timely georeference data for the SDGs. As Gordon mentioned, when it comes to official data sources, what's available is often out of date. And data production processes advance at a slower pace than needed. But recently many researchers have developed a range of new data sets that could contribute to monitoring and measuring the SDGs and SDG related targets and indicators. One of the challenges we face is that oftentimes researchers develop innovative methods and data sets that could contribute to decision making processes, or provide a better understanding of the state of our progress towards the global goals, but they're not always made available to others in an accessible format. So we focus on identifying and producing data sets that meet our selection criteria, which my colleague in a while we'll talk about in more detail. And we focus on them in a way that is easy to understand and access by anyone concerned with the SDGs. Our goal at SDGs today is to provide a timely snapshot of the state of sustainable development, enable SDG stakeholders to produce access and engage with timely data and promote geospatial literacy and the integration of geospatial information systems or GIS in SDG applications. We've created and exploring new sources of data and methods that complement official data for the SDGs. To support our objectives and to stay informed about the latest data developments for the SDGs, we convened a group of experts from various sectors and expertise to guide our work and help us expand our data collaborations. This slide highlights some of the organizations are coalition of experts members are affiliated with. Currently, our program focuses on three core activities. We work with various data groups from academia international organizations and other sectors to curate produce and visualize timely and real time data on the SDGs. We use the ArcGIS story maps tool to create a data and GIS driven stories that contextualize the data for a wider audience and help our users understand how the data contributes to the assessment of our progress towards the SDGs. And lastly, we support education and training programs to help integrate GIS into SDG related activities. So we'll go into more detail about each of the three core activities and I'll hand the mic to a Nella who will present on the great work she's doing on the data hub. Hi everybody, I'm just as a brief introduction my name is Nella. I'm a GIS analyst on this team so most of my work is on adding the data sets to our website visualizing them, making sure that they are updated and maintained. So I will start to share my screen. I'll go through a little bit on how the data hub is organized, the types of data sets that we feature on our website. Our process for adding data to the website, the data criteria that we are looking for and I'll give you a little bit of a demo on some of the dashboards that we have featured on our website so on our data hub, all of the layers maps and dashboards are hosted on ArcGIS online. They are also on the data hub on our website they are categorized by SDG so as you can see on the right you can see how many data sets we have for each SDG and you can click on whatever SDG you're interested in and see what data sets are available for that. We also have three categories of featured data sets. The first one is data relevant to current events so right now what we have featured are a map on wildfires, there's also a map on armed conflict locations and also a dashboard on the COVID vaccine procurement process. The third category that we feature is our most real time data so we have a data set on poverty, which is updated in real time. A data set on coral bleaching events, which is updated daily and air quality, which is also updated daily. The third category that we have is the most recently added data sets. So the ones that we have added most recently in the past month or so. The first one is foreign direct investment. We also have a data set on mapping school locations which Mike will talk about in his presentation, and we have also recently added a data set on global phishing activity. So there are a few types of data featured I just want to give an overview of the types of data sets that you'll see on our website. So the first are surveys and statistics. Usually, these data sets are found commonly in reports and on tables and so we get that data set and visualize them on a map. These are data sets that we have our earth observations that includes satellite imagery data from monitoring stations and other types of remote sensors. And finally, another type of data that we have featured our models. And I'll go through the process of adding a data set so typically we'll ask a data provider to submit their data set to our website. We'll review all of the information that they have given us on the form and we'll consider the eight criteria that I will go through in a little bit to make sure that the data set is applicable to our website and our criteria. Once we figure out if your data set is something that we would like to feature will send a metadata template to fill out so that we have all of the information that we need to feature the data set and make sure that our users know everything that they need to know about your data set. And then we'll go through the process of receiving your data and then we'll also visualize it on maps and dashboards. And finally, once that process is over, we will feature the data set on our website on its own data set page, and also promote it on all of our social media. So to go through some of the criteria that we have. Again, you'll submit the data set on our website on the top right corner on our front page. There's a button that says submit your data set and you will go through a little bit more of how to navigate the website. So the first thing that we look for is the level of frequency of your data set. So, as Maria mentioned, we are mostly interested in timely and real time data sets. And this frequency is higher than official data sources. And we also want to look at the spatial coverage and disaggregation of that data set. So the data set that you are submitting must be geo referenced it must have some sort of spatial element so that we can visualize that data set on in that will also look at the methodology of how that data set was created. And we're looking for defined and robust methodologies that have either been here reviewed or validated in some other way to make sure that the data set that we are featuring as robust. Along with that, we'll look through the data sources of that data set and make sure that those data sources are also reliable. Next, we'll also look at public accessibility. So we prefer data that are licensed for reuse and are also open. And this allows our users to sort of hold the data providers accountable for their methodological integrity and also, we also just want to support the accessibility and transparency of data overall. Next, we'll look at thematic relevance. So we want to make sure that the data sets that we feature are relevant to one or more of the SDGs. We'll also look at the ease of understanding. So we want to make sure that we don't assume that all of the users that come to our website are GIS experts, or even experts on your particular data sets, we want to make sure that these data sets are clear and communicable to all users that come across it on our platform. Finally, we want to look at the sustainability of production because this project supports the SDGs, we want to make sure that the data sets that we feature will be available and updated through 2030. So finally, I will give a little bit of a demo on some of the dashboards that we have on our website. I'll start with the COVID-19 vaccine procurement dashboard that I mentioned earlier. So what I like about this dashboard is that it shows a lot of data sets in one dashboard so as you can see there are these tabs that you can click on that show three different data. The first is the population that's able to be vaccinated with the vaccine procurement that each country has acquired. So for example, the USA has this many doses and it can vaccinate 200% of the population. The next map that we have here is the actual procurement so this is just the total number of doses that each country has acquired. And then finally the COVAX status of every country so whether or not they are committed to COVAX or not. And as you can see there's also a breakdown of the vaccines by company. And if you click here, you select a country, Australia for example, you can see the breakdown of the vaccines that they have procured. And another dashboard that I would like to show is the digital gender gaps dashboard. I like this dashboard because not only can you select by country, but you can also select a time frame that you want the data to show so for example, the world in July of 2021, or June of 2021, everything changes dynamically. And you can select a country based on that month as well. This dashboard also has two different maps. So it shows information by internet, the female to male usage ratio of the internet and also mobile LTE data. That's about it for me. I just wanted to give a brief overview of our data hub, some of the data that we feature and give an overview of how we can interact with some of our dashboard and visualizations on the website. And I'll hand it over to Mike who will be talking about our first data creation in house. So just a quick introduction myself. My name is Mike Andrews I'm a GIS research assistant with STG today. Part of my work is supporting the data development on an Ellis and and programmatic work on marines and, but I also assist in the development of new methods and research opportunities at STG today. So I'm very excited today to be sharing our first in house data set looking at school location so So in July of this year, I see you today launched the my school today called action is called action and supportive SDG for utilizes a bottom up crowdsourcing approach to geo referencing schools across Africa. And in addition to the call to action itself, which aims to improve the data. We've also launched the first in house data set mapping school locations to utilize this data to explore population demographics as it relates to travel time to various to various school locations. So we have several goals with the my school today called action. Primarily, we want to support policymakers and other STG stakeholders with timely data on school locations and timely is really the key there. And we want that that data to be locally informed so that's where we decided to take a bottom up approach and utilize crowdsourcing in order to gather and solidify the data. So that's where we are our goal is to engage local communities and organizations efforts to geo reference their schools. So the idea is this data is coming from the people who know it best. And we also want to provide students with educational resources and us training lessons. So, the majority of the call to action is actually targeted at student matters. They can gain experience and geo referencing a core skill to GIS, as well as in educational resources and how to utilize the data once it's available. So we also develop shared learn lessons step by step mapping guides and several other products to help support students and learning of GIS skills to this point of action. And so in club or in in concert with the my school today call to action is also mapping school locations. And so, as a data set mapping school locations aims to utilize my school today location data in order to estimate walking only travel time for students to currently osm recorded schools. So this is in a data set that is constantly improving as my school today, school location data improves so it's one there to exist as a use case of the data itself, but it's also there to highlight a really important aspect of achieving school access here, which is school access and in this case we wanted to use the spatial lens in order to get a better understanding of physical physical access to schools. And I'll go ahead and actually run through how we move from school location data provided by my school today to the mapping school locations data set. So let's begin with the school locations and and within for those of you who are familiar with OpenStreetMap. OpenStreetMap has can can report schools in two different ways. One is as amenities which typically outline the school grounds or is just a point feature to show the school itself and then there's also school buildings. And they can work in concert with each other in our case we're only utilizing school buildings, because we thought that that was a better approach to providing the geo referencing skills. And it also can work in concert with future potential collaboration with machine learning method methodologies, but we first extract school locations using those school building features convert them to points. And those are used as what we as source locations when we calculate our travel time isochrone which I'll explain here in a second. So travel time isochrone is essentially a single isochrone be a polygon that represents a certain a certain amount of time it's it's a measure of time within a spatial spatial context. And so constructing an isochrone data set allows us to create a depiction of travel time from any given source point to any given other point on a map. So in the case on this map to the right. The red dots themselves are back to school locations and then each of those different colors are different travel times. In this case, that would be 30 minutes 30 to 60 minutes and 60 plus where 30 minutes is the yellow and 60 plus is the red. So isochrone construction also requires a cost raster and a cost raster basically provides the information of how difficult it is to move across any given space on a map and so we utilize a walking only surface friction raster that was developed by West at all in 2018. And this friction raster is fantastic because in addition to accounting to physical features, such as the difficulty of the terrain physical barrier such as as waterways it also counts for geopolitical elements as well including including political boundaries. So this is a cost raster is in utilized to provide the idea of how long does each, in this case, sell of movement cost for a student to walk across from to a given school location.  And what this does is that this provides us different bands of images of raster images that each provide different population counts for people for males and females aged one to five, five to 10, 10 to 15 so on and so forth. And so we extract each of those for male and female between the ages of five and 20, and then aggregate those into age bin groups, so that we end up with two, two images. So one of females age five to 20 and one of males age back to 20. And this is on the right here is a depiction of what that population data actually ends up looking like. It's one of my favorite data, data sets to work with this. It looks so fantastic. So we have the school age population raster images, we can then overlay that with our isochromes travel time travel time layers in order to get isochronal population counts. So the population raster images are masked by the travel time isochrome to create six gender specific image outputs, males within a 30 minute long time between 30 and 60 minutes over 60 minutes and the same group emails as well. So that masking is essentially, we are removing all for any given image, any given population image we're removing all data that does not exist within a specific isochrome time time grouping so within 30 minute walk time. So the total population, greater than 30 minutes away is essentially removed from that first image and then we utilize zonal statistics in order to count all of the cells that each provide population counts for the specific demographics that we're looking at. So that we end up with counts by travel time for males and females within first level country administration. And this ultimately ends up resulting in our final data set. So we'll go ahead and give you an example here. So like I know I highlighted before, once we have our in house data set assembled, we can go about sharing sharing relevant information and statistics using dashboards are very powerful visualization tools and now demonstrate it earlier. So here we have our isochronal population counts that are counted by first, first level administration within all the countries in Africa. And here you can get an idea of counts within each of those first level administration so the female population within 30 minutes of recording school we have 8504 and so on and so forth. There are certain limitations to the data as it exists now due to the underlying data still being in development. So typically we're assuming that most of these numbers that are greater than 30 minutes away are going to be higher than they are in reality but this is to demonstrate that use case and this will improve over time. And then, you know, the goal of my school today, this should reach a point where we can get a very accurate population counts for each of these, each of these areas. And then we can also aggregate those into statistics and focus down into specific countries. So we wanted to look at the name. We can see that, based off of our data, 59% of students live within over 60 minutes from recorded school, and you can get time specific and demographic specific population breakdowns and counts for each of those. And we can also share kind of like the ongoing work at my school today and explore how many schools are getting mapped and where there's where they're getting mapped and you can focus down in specific countries. And we can get very fine geographic resolutions and the school location data. And we can even track the ongoing development of the data set, both for Africa as a whole and for specific countries. So for example, down here on the bottom we have a graph that shows essentially the number of schools Africa wide that have been added since the launch of my school today. And so, there have been a good number of schools added. The good news is that this is really showing that this is like a constantly improving data set because there's a very active open street map community and online mapping community. And very, very strong local, very amazing and strong local OSM communities and organizations and colleges and universities as well as just volunteer mappers that continually improve this data set so we can see that the data is improving. And we hope to continue to contribute that with my school today. And so that's that's mapping school locations data set. And then just some tools that we have at our disposal for improving school location both that we've already implemented that we will be implementing soon and that we have plans for in the longer one open street map on street map forms the basis of the of my school today. Call the action as well as the mapping so locations data set. And it's a very powerful open source open source and crowdsource data set that allows anyone to geo reference schools. Anyone, students, teachers, academics, policymakers, any SDG stakeholder can go in and they can map schools in that area as well as any other public facilities that they they wish to include. And they can add additional details as they fit or they can have it as simple as just starting down a point. And in addition to it being openly available for anyone to contribute there's also an extremely large and extremely active mapping community within open street map that continue continually runs through all of the data and improves it runs various challenges to work for errors, can support the efforts with machine learning. So it's a really amazing crowdsourcing tool that we're that can be used to continue to continue to improve education data for us to do for. And so we have developed our own step by step mapping guides that are available on our website that are multilingual currently available in English French Portuguese and Arabic. In order to provide a step by step run through of how a student could hop in and add their school within within the data set. And it's realistically something that shouldn't take much more than 10 minutes but there's also some great GIS lessons that are just a part of that. And then for groups and organizations that want to go much more in depth and to improve anger school occasion data than just adding one or two schools. The humanitarian open street map team that we've been working with also has a fantastic resource in the hot toolbox online that provides skills for skills and guidelines for doing really deep dive mapping challenges and map programs and engaging local communities and local mappers in order to improve the data set wherever wherever the user is. And then outside of open street map. There's also as raise RTS survey 123 and for individuals that may not have access to open street map or desktop open street map. We developed a survey within RTS survey 123 that any individual can do literally just on their phone. And we basically run them through a guided data submission process in which they can geo references and satellite imagery available and as we space maps to draw a border around their school geo references school and then submit it to us at which point we can then upload that data into open street map. As well as gaining potentially supplementary data such as average student class size number of females female teachers etc. So we'll be continuing to develop that survey it is currently live. We will be adding more questions and creating more comprehensive survey out of there. And then finally there are mapping challenges which is a very exciting component of being a part of the online mapping community. And so this this is focused on the online community engagement and the real advantage of mapping challenges data quality improvements. So websites like map roulette can be used to feed users a series of tasks one task at a time so they can complete as many tasks as they like they can hop on complete one hop off and essentially feed them. This is a school location when you know that it's it is because it's labeled as an amenity but we want to get an idea of the school buildings. If you see if you don't see a school building here and go ahead and draw a boundary around it. And so we can use this for data quality improvement and to kind of like bring together the fact that the school location data can exist in like multiple formats. And in the future, we can use it to one actually add new schools that are not mapped as amenities or school buildings. And there's also some, some great potential there to be utilized with a machine learning in order to take schools that are that are mapped based off of certain machine learning criteria, and then bring in these mapping challenges to providing human element to track each of those, those outputs and ensure. Yes, that does appear to be a school or to fix like any, any boundaries or all corners that might not be lined up correctly. So these are just some, some opportunities that come with our bottom up crowdsourcing approach and really exciting opportunities to improve education data. So, I believe that's it for me and I'll be passing it back to Mary and so she can discuss storytelling tools and resources. Thank you, Mike, and another for your presentations. Let me share my screen again. Okay, great. Yeah, as Mike mentioned, I'll be talking a little bit about our storytelling and education activities. So to complement the data work that we do at SDGs today, we've integrated the ArcGIS story maps tool into our workflow to create interactive presentations of SDG related challenges and communicate use cases that highlight the data or innovative methods that have contributed to the SDGs. We've been working with our partners on creating a story maps the interesting SDG related projects, and we have a number of collections available on the website. So you can explore story maps by SDG, or through one of the featured collections. So for example, we do have a collection, a collection for story maps created by SDSN programs and members. But the theme of this conference is research for impact. I want to highlight that there are a number of story maps created by academics and researchers highlighting their work and kind of walking you through their projects and the outcomes I do encourage you to to check them out. We also had the pleasure of co organizing the 2020 ArcGIS story maps competition for sustainable development with our partner Esri, which we concluded earlier this year. We received submissions from about 50 countries and selected six winners. You can find the winning story maps on our website. And we recently added a link to guided geospatial information systems lessons of featuring the winning story maps. Moving on to our work on GIS education and training. We've gotten involved in a number of activities to support SDSN's global network of members and our secretariat by organizing workshops and training sessions. Recently, we partnered with the Center for Sustainable Development at Columbia University to integrate GIS knowledge and tools in their Eco Ambassadors summer program. The Eco Ambassadors program equips youth with the knowledge and skills for scientific research and advocating solutions for sustainable development and climate challenges. We worked with our team to introduce GIS and ArcGIS tools to the students. We created LearnPaths, which are a collection of guided ArcGIS lessons and story map collections to help them learn how to create story maps about their research projects at the end of the summer. The program recently ended and there will be another ICSD side event featuring the students work at 4pm Eastern time. So I invite all of you to attend if you're interested to learn more about that program and the students research projects. Now that we've presented an overview of our work in various activities, I'm going to invite my colleague Amiola to walk you through our website and show you how you can access all of our resources. Amiola over to you. Hey everyone. I'm Amiola. I have the pleasure of working with my fine colleagues. My contributions to the team are working on web design and development. So without further ado, as Ram said, I'm going to walk us through the website. Give me one second. Should be able to see my screen. Yeah, so just going to take us through the site. SEG today is a position to be the global hub for real time SEG data. And as my colleagues have walked us through how we're doing that as a combination of, you know, being a platform that hosts data sets across global providers offering and showing us how to use those data sets in the form of story maps with resources to learn how to do that yourself, as well as other educational resources about the SEG general as well as CIS specifically. Yeah, so I'm going to cover each of those in a second, but just going to walk through our homepage here. What you can see here is actually two different ways to navigate to data sets. We've organized them by the familiar SDG cards you can see here. And for each of them, you can see how many data sets we've been able to master in such a very short period of time. And then below here, you are able to see some of the data sets that we've actually featured here on the front page. So we'll take a step into that in a second. Last thing here on the front page that's your features are my school today site that Mike did a great job of walking us through, and we'll get to that in a second. But one of the ticketed look at the data hub. So we've had quite a few data sets on the site and we've got a number of different tools here for for not being towards to get to the right data set for source search. So for example, we were able to just type in a search and get a list of results that match that query. Any keyword here will work. It's pretty, pretty solid. And again, you can see the same grid, the SDG SD cards grid. I'll come back to that in a second, but below here as a never alluded to her. We do feature, you know, the data sets that are relevant to current events. Those are hand chosen by by by the team to to cover what we did this, what we see as the data sets that are most relevant to the current events going on, our most real time data sets, those generally around like daily updates. And then recently added data sets, which also includes mapping schools, the mapping school locations project which I'll come back to. So going to any of these SDG, click on any, any of these SDG cards here actually take you to the page where you can see a brief overview of what that SDG is, and you can get access to official SDG data, UN data. Here you can see a list of the data sets that we have for each of these support for this particular SDG SDG. And then you can also see more information here your way to like, you know, story maps like learning how to map specifically for that this this this SDG, as well as again those official the official data sets for the SDG going back to the data hub. You can't just scroll down here and click on any one of these, and then be able to, and then view that that data sets data set page. This is actually one of the data sets that another show us earlier, but in addition to being able to see this this dashboard here, we're also able to learn about that particular data set, including who that who the data provider was. And then a sort of metadata to get more granular information about those, you know, the criteria that an element mentioned earlier but like how we know what's unique about this data set how was it produced. And like methodology or methodology credits so on so forth. And then also we're able to get the underlying data as well as the artist layers here by clicking on these, these links. Yeah, so this is what this is, you know, the the meat of the working with the data hub that he's at all these data sets. Some of them are really got a good amount of dashboards here for these data sets some of them are actually just just maps. But they're all like very, very helpful and we're very, very much thankful for the tour data providers for for a lot for working with us to present those here. So I'm going to move on to storytelling. Actually, let me take a step back to, to the data hub. So these data, these, as now mentioned, we're working with different providers across the world to to get to aggregate all these data sets and so up here on the top right of the page to click that open submit, submit your data. There's a form here that you're able to fill out basic information about the data set. The SDG that and all the rest of the criteria that was about earlier, and what you're doing here is actually just sending us some information about the data set. And that starts a conversation with us to see how we can go about working with you to to to process and then to curate that data set to bring it into the site so please please feel free to to to click on that and start working with us. Moving on to storytelling that a bunch of resources here on like on the existing story maps that leverage some of the data sets that we have on the site on this site, as well as other story other data sets. All built on like to us. And in addition to that, we also have like resources at the bottom here that allow us to the to teach you how to actually make your own story maps are really really helpful for being able to take these data sets that can be quite, you know, data, data intensive information dense, take these, take these data sets and to build a narrative around them so as an example of one of those. Just click on one of these here. These are really, really great at communicating the context around these data sets, and not just showing me that we're all data. It takes you time to go through. There's a ton of them. We've got a bunch of different collections here for each of the SDGs. You can see the account here for each of these for each of the SDGs how many, how many story maps we have for each of them. So just click into one of them here and you can see we've got a good handful of story maps for SDG five. Moving on to education. We've got got down to the work with some great organizations to both develop curriculum for learning about the SDGs and GIS, as well as like working with organizations like the master's program. We've got a lot of students engaging youth in GIS and digital storytelling. And then this is about you can also navigate with navigate to the art as learn lessons for each of the SDGs. I've got a ton of resources into those to learn about to learn about both the SDGs and the GIS. And specifically, and also we got some helpful links here below. Wrapping up here. This is going to show you if you want to learn more about the about these today and the motivations behind this you say you please feel free to check out the about page. I think we'll get a great job of summarizing the purpose the motivations behind behind SDGs opportunity that we see. So if you have a chance to, you know, check out our freaking ask questions if you're having those and our data evaluation that they're going to school on the page you can see our awesome rockstar team here. There's a four of us featured here but they are they have been other people on the team that they're coming now. And so we're very grateful to both them as well as our team of the standard visors including Gordon. Yeah, that's the that is the website please take some time to look through it. If you this was very much a team effort. Different people pulling in resources and feedback and there's so many different iterations that have gone through so if you see anything that you'd love to improve on the site, please feel free to reach out and give us that feedback to wrap up. We went to you also. Again, hit on the hit the nail on the head like we would love to collaborate with you. So feel free to to reach out to us please hit that hit that link at the top of the page to submit your own data. And also, you can also work with us to publish your GIS story maps with SDGs today. We also invite you to connect with us across the web, obviously on our website but also across social media on Twitter and on LinkedIn, and feel free to send us an email as well. So, thank you so much for your time. I'm going to pass it back to Mary. Thank you, Amiola, and a big thanks to all of our presenters. This concludes our presentation and we'd be happy to answer any questions you have about SDGs today. We're eager, eager to hear from you and how you can make how we can make our work more accessible to you and work with you to identify new data sets and content we could add to our website. And that's like we already have some questions so I'll get started with what we have in the chat here. Mike, there's a question for you. You mentioned machine learning analysis, a couple of times. So, what are the specific approaches applications or assessments that my school today project is using. My school today call to action isn't actually using any machine learning methodologies. It's more that's an avenue we'd like to explore and it's really something we'd like to explore partners because there's, we know there's some amazing organizations out there that are doing work for machine learning based geo referencing buildings, school locations, and, you know, other other public utilities such as streets, and a lot of areas that otherwise don't have fantastic existing data. So, several of those methodologies are still in development. And there's some ongoing analysis of various biases that can be introduced in that, especially when we're talking about geo referencing a very large scale. And my understanding of it is one of the, one of the problems that comes out of the machine learning approach is through through the bias that is introduced I wish which school buildings are you using as as the basis for the machine learning to identify a school offer can introduce a bias of what schools look like and schools make with different in different areas, especially when we're talking about urban versus rural imagery data sets. And so, one thing that can that that my school today kind of has the unique advantages we can help introduce that that human element, whether it's through a map of time, or engaging our network and our local open street map communities to basically just like run through all the schools that have been mapped using that machine learning technology. And identify, does this look right. Are there any problems with this or are the borders correct, etc, etc. So this really an avenue that we hope to explore here in the future. And we think it would be a fantastic addition to supporting. I think it would be a great way to address the board through through better understanding of education, timely education data. Thank you Mike. While we're waiting for more questions to come through, I do have a couple of questions for the team. And Ella, how are data updates managed on the data hub. So it's sort of depends on how the data set is handed over some data sets we received by email some we have to download from the data providers website. But there are a few data sets that are updated via API so we have API access to them. And we're also starting to migrate our data update process into our GS online notebook, so that we can run tasks daily monthly weekly whatever. So that those data sets are updated automatically and you don't have to manually touch any of the data sets. Thanks and Ella. There's a question can anyone join your group if interested. I would suggest that you reach out to us via email. If you have any suggestions on how you would like to get involved were excited and open to collaborating with all of you. So whether it's through the creation of a story map or if you have any suggestions on data sets that we can feature we'd be happy to collaborate with you. And so we'll share our email in the chat. So please reach out to us with any suggestions or ideas you have. I do have a question for you. The development of the website has been a very long but exciting process. What are some of the challenges of making data more accessible to a wider audience especially those who don't come from maybe a technical background or not familiar with with GIS. That's a good question there's been a I mean it's been a tough challenge, building a platform like this specifically for aggregating GIS data sets from different providers that bring their data sets in different formats. The core challenge in trying to make it accessible to to as many people as possible involves you know things like building the site such that it responds well to you know different different sizes of devices, as well as different internet bandwidths there's certain things that we have to design around to make sure that it loads properly for you know someone who might be using a tiny phone and Niger for example with a low internet speeds. So things like that. So you know, being able to build a site such that it is easy to discover the right data sets right because there is a ton of ton of them that we have so far and like we are looking to have even a far more in the future. By working with our data providers so making it easy for people to discover the right data sets. There's another key challenge there. But yeah, I think I'll say it again like it's been a team effort, like, both to both understand the challenges and opportunities and how to to make it all this, these data sets accessible. But then also it's been a team effort and not to, you know, executing on that and not to making it and making the site as as great as it is today to to make it possible for people to to interact from really cities, countries all over the world. Yeah. Great question. Thank you. Gordon, I don't know if you're still on the line. Great. There's a question for you. You mentioned that you, you have some national data. How can our participants access that. I don't know if the question was for the United States or other countries. The answer is yes to both. And in different in different countries that challenges different but this is part of the problem is that there's not a standardized and easy way to access some national data for lots of countries at once or for the world at once. And so it completely depends on whether you're interested in kind of the distribution of the global population. There are products that exist for that Michael mentioned a few of those like world pop or Facebook AI, others, which which are modeled to try to understand where people live, then you can couple that with satellite data to understand what percentage of that population has access to electricity. And what's very hard is, for example, to access clinic level data from countries all over the world to understand what's the spatial distribution of malaria or dengue or Zika, or COVID at a high geographic resolution and that's often where you have to go country by country working with an individual ministry and seeing who can unlock that data for you. And that's what I mean by still being stuck in the 20th century because the data are there. And so living in these ministries and part of what SDGs today's philosophy is is to try to push the envelope a little bit and see how far we can go in getting these data up and publicly available and have analysts researchers and policymakers thinking at some national scale, without having to have a special connection to somebody inside the ministry who has the data. And now there's a question for you. In addition to data sets, do you have plans to add computational notebooks that allow users to work with quality with data directly in an online environment. That's a great question idea. I think currently in this phase of our project. We are starting to focus more on the visualizations of the data sets, turning some of the maps into more interactive dashboards but we will keep this in mind for the next phase of our project, because I think that's a really great idea. Thanks, Annela. Mike I have a question for you. Can anyone join the my school today called to action. Let's say even if they don't want to, or don't have access to data on schools to geo reference either through OSM or our survey 123. Yeah, I mean, so there are there are many ways that you can join and support my school today called action where by far and away not an exclusive club. In fact, we would love to get as many people involved as we can. So, obviously, the core role of my school today project is to geo reference schools. So, students can do that teachers can do that. Anyone can go in and do that. If you go on to go to our website for my school today under a CGS today.org. You can see a number of resources that we have for how can you get involved from simply just mapping a school to actually like running a large mapathon in your area. And now outside of that there are many other ways that you can help spreading the word is a huge, huge help us. So, we have, we have hashtags and guidelines for spreading the word of my school today on Twitter when Dan Facebook, really anywhere would like to we've had we've had partners sharing to Reddit for example, you know, it's just, you can get some fantastic engagement really anywhere that that you want to share so that's one fantastically can help us. If you are, even if you're not necessarily part of organizations but you have contacts or connections so local organizations, we really want to bring in local insights into this. So, having, having schools we would like to have that the influence and involvement of the mapping community that is there who's going to understand it better than someone who's mapping it thousands of miles away. And so, bringing us in contact with them or something or letting them know about us is a huge help as well. And really spreading the word and whatever format is just be a fantastic aid, even if you can't directly geo reference schools or don't have anything that matter. Thank you, Mike. Gordon, I'm going to direct this question to you. How are you dealing with quality data and the lack of data for some regions. This is a huge concern and we know that there's a large variation in data quality across countries and within countries. And part of the idea of putting everything on the table so that it's transparent is that people can see well, you know this, and the idea with my schools today even came from the idea that we don't have great data sub nationally for many developing countries on levels of education or access to education. And so we're trying to do the best we can in terms of building something better. But the idea is, if we can shine the light on places where data quality is lacking then hopefully that directs attention from communities like this one to try to improve. At the same time, public policy needs to be made today so public policy makers can't wait five years for better data to exist before they can make decisions. So I think our role as a community of researchers and people who are helping the monitoring community is to constantly push push push put out there, put available the best data that is available, let decision makers use that best data. But then our role is to constantly try to improve that data quality so that future decision makers have access to even better data. And where data is completely missing. We should point that out, and, and really put shine the collective spotlight on that and said, our global commitment to the STG includes measuring things that are right now not being measured. And great success on that if you go back to the, the millennium ecosystem assessment in the year 2000 it was an amazing report to read because half of the pages were black. And that was very purposeful by the international community to point out to the world look. Half of the things that we need to be measuring to save ecosystems across the planet we're actually not measuring and that was transformative and getting a lot of the ecological community and others. We need international finance to start measuring things more and better. So that's part of the call to action here is exactly that concern that data quality is not great everywhere and where it isn't, we need to push to make it better. Thank you, Gordon. There's a question perhaps for all of us, any plans to add geo query as a data provider. That's a great question, and to be completely transparent I don't think that's something that we've internally discussed, but it's something we'll definitely add on our list on our to do list in the next phase of our project. There's another question, is this data in addition to the UN data that has existed for years. So the data featured on SDGs today are not official data sets that you'll find on the UN data hub or other SDG data hubs that are supported by the UN. However, we do work very closely with different UN agencies and data groups to curate and visualize data on SDGs today that will hopefully complement official data sources. So data that we do have from the UN on our platform is updated more frequently than a lot of the official data sets available on, let's say the UN data portal, or other websites. I'm just going to emphasize they're not official data sets, but they do aim to complement what exists in. I can say one thing. I can say one thing about the geo query. A lot of what they have done is to is to cross link survey style data like the demographic and health surveys or biophysical data on physical geography to to make those things easily available to link across data sets. But the spirit of SDGs today is to go beyond that because we want timely data. So it's not enough to map out the demographic and health surveys because those are done every five years or seven years and in most countries that have these surveys sub nationally and yes they're geo referenced, and yes there's sub national data available. But the idea is to do better than that do better than survey data do better than waiting every five years and actually ask how do we deploy remote sense data, mobile phone data, other 21st century data collection systems that that can be updated at least annually. And that goes quite beyond a lot of what has been done on sub national data platforms. Not only at eight data but but elsewhere. Thank you, Gordon. There's another question. So, how would you choose which data to feature on the website. For instance, if there's an environmentalist or NGO on the ground that would say there are X number of trees that were cut, whereas the government provided a different statistics or or number. Would you take the official data or not. So let others chime in as well. But as I mentioned, we are not limited or committed to only featuring official data sets by governments or UN agencies we have our own evaluation and review process where we do work with a wide range of data providers from various directors to review evaluate and decide whether or not we feature the data on our platform so there's a rigorous progress that we go through and invite our senior advisors such as Gordon to help with that process. I don't know if anyone else on the team would like to add to that. But if there are any particular examples, or if you're interested in exploring or investigating a particular data set you're happy to, I'm happy for it to to work with you maybe connect via email and see if there is a particular example. He'd like us to look into and explore. Another question, do you integrate any data set that align with the ISO SDG. Does anyone. For instance, let's see. How would my community subscribe to provide data. So anyone who is aware of any data set that we could feature on the platform you can either use our submission form, which is available on the website so you can answer a series of questions. Submit the data will review it it'll go through the evaluation process and we'll get back to you about whether or not it will be featured on the platform. Thank you Cheyenne for submitting for sharing the link, or you can also reach out to us via email if you have any questions or suggestions that you'd like to share with us. Hey, are there any final comments from the presenters. Mike you're muted. Yeah, yeah just like to say, you know, thank you to everyone who has helped with the my school today project. And thank you everyone for joining and having interest in what we do. So please share my school today. You know, join us in any way that you can and we'd love to have anybody's anybody and everybody's participation. If you're not sure how you get involved. Please feel free to email us at sdg today. And we'd love to hear from you on any ideas or any interest or any role you'd like to play my school today. Thank you Mike and thanks again to all our presenters. And thanks to all of our participants for joining us today. As Mike mentioned, please do connect with us on through our social media platforms or via email. We look forward to working and collaborating with all of you. Thank you so much. Bye everyone.


The Chippewa National Forest shares boundaries with the Leech Lake Band of Ojibwe and they'll continue to do so. Nearly 18 acres of land in Flower Pot Bay on Tin Mile Lake has been acquired by the U.S. Forest Service. The property includes more than 1,500 feet of undeveloped shoreline along Tin Mile Lake and is now part of the Chippewa National Forest. The acquisition ends a 10-year campaign to preserve the land. Tin Mile Lake is considered to be one of 24 Sentinel lakes because of its high water quality. The Minnesota DNR also listed the lake as a Cisco Refuge Lake. This means the lake and its watershed is a high-long-term conservation priority. Chippewa National Forest is the first national forest established east of the Mississippi River in north-central Minnesota. If you've enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland Public Television.


Hi, I'm Dr. Gene Parois. In this lecture, we're going to focus on the experience Mexican Americans had during the World War I era. We want to address how the World War affected the Mexican American community, the rise of the Mexican American generation, and how experiences during World War II contributed to the Mexican American civil rights movement. As part of the background to war, we need to understand that the United States did not want to get involved in another European war following World War I. And so laws in the 1930s as legislators started seeing problems in Europe start to maybe foretell them that war was on the way, that they began to pass neutrality acts to keep us out of being involved in European conflicts. But in 1939 after the invasion of Poland, the United States President Franklin Roosevelt was able to get Congress to agree to a cash and carry policy, which would allow us to provide military munitions for our allies if they promised to pay for it up front. During the fall of France in June of 1940s, destroyers for bases was a new way of allowing us to provide military destroyers to the British Navy in exchange for the use of their territory to install American bases. Then there was a lend lease, which allowed us to lend material and then be paid at some point in the future. We later extended this to Russia. And finally on December 7, 1941, any attempt at remaining neutral was obviously over with the attack on Pearl Harbor. For Mexican Americans, the population during the Great Depression of the 1930s and repatriation efforts had led to a decline in overall Mexican American numbers in the United States Mexican and Mexican American numbers. But still when the draft occurred, young men were recruited and some drafted and we believe that between 300,000 to 750,000 of those draftees of those 34 million who registered were Hispanic, perhaps the majority of them Mexicans or Mexican Americans. And we have to realize too that Puerto Rican served the Tuskegee Airmen, others also served the Coast Guard in those numbers. And don't forget that women participated as well in military service. Mexican American women joined the Army Air Corps, the Army Reserves, the Waves, and they also served in Army and Navy Nurse Corps. Now why don't we have accurate numbers? Why are these guesses? Well, because we didn't really differentiate in military records on who was Mexican American and what country they were from and all this. So we don't have the real numbers we're guessing based upon last name. We do think that Mexican Americans were overrepresented and as your textbook points out, this may have been for one of three reasons to improve status, simple patriotism, right? It was our country, we wanted to fight it or was it machismo? For examples of distinguished service in the military, in Illinois, just west of Chicago is a town named Sylvus, there in a residential neighborhood about a block and a half long is a street called Hero Street, USA and this is an honor of the 84 men who volunteered or were drafted during World War II, Korea and Vietnam and served. We know that eight died from that little neighborhood property of about a block and a half long in World War II. So that was renamed Hero Street, USA. Mexican Americans also served in the Philippines, the New Mexico National Guard. For example, they were in at the Batan Death March in April of 1942. Guy Abaldon was a Mexican American from California who served on the Navy Cross and the Silver Star. In a Hollywood movie was not portrayed as Mexican American, was portrayed as Italian by a white actor and so this caused some disconcernment among Mexican Americans who felt they were being ignored. There were Medal of Honor winners as well in the military. Jose Martinez was the first Mexican American Medal of Honor winner in World War II and there were also Mexican nationals who were serving. Jose Lopez, for example, was from Mexico, was Mexican, but he did serve in the U.S. military, lived here in Texas as well. We talk about the Mexican American generation. This is just that World War II generation and they served in more areas than just the military, even at home. So they were building victory gardens, growing victory gardens along with other people in the United States. They worked, their women worked in the defense industry. So here is a photograph on the right hand side of a Mexican American woman in a Fort Worth airplane plant working as a machinist. Mexican Americans bought war bonds and contributed. They participated in USO. Now, Desi Arnaz, for an example, was a Cuban band leader and although he was Cuban American, he does represent the Hispanic participation in that. In 1947, Harry Truman's President's Commission on Civil Rights issued a report, however, called to secure these rights and in there they provided examples of discrimination that the Mexican American generation and other minorities faced. And what they did was they urged equality of opportunity in education, in housing or in jobs and they suggested that the government passed laws against lynching, passed laws against poll taxes. Established a permanent Fair Employment Practices Commission and established a justice division, a civil rights division in the Department of Justice. Now, the discrimination that they found didn't just happen after the war, it was actually before the war, of course. And so, for example, on the home front in 1942 while the war was raging, the sleepy lagoon case outside of Los Angeles, California was started because of the murder of a young man named Jose Diaz in Los Angeles, 600 Mexican Americans were arrested, charged to be in a gang or just assumed to be in a gang and 20 of them were tried for murder on very flimsy, circumstantial evidence, in fact, there was very little evidence that police had. But because they were, except that they were Mexican American and so it was assumed that they were Mexican American, therefore they belonged in gangs or they were members of gangs and Mexican American gangs like to stab people and murder. That was really what the prosecution was going on. There was a sleepy lagoon defense committee which hired lawyers to help represent these young men to help them get off on these rather flimsy, racist, prejudicial statements made during the trial. There was also more famously, probably a year later, the zootsuit riots which happened in downtown Los Angeles and this is where naval men were competing for part-time jobs with African American and Mexican American young men and this became known as the zootsuit riots and the federal government had to send in the military police to help quell the violence and to return the servicemen to the bases. There were other federal efforts against discrimination, first of all a continuation of the good neighbor policy. This was Franklin Roosevelt's policy developed in the 30s to build better relationships with South American countries who many of whom felt the United States intervened in their politics too often. There was the Fair Employment Practices Commission, Executive Order 8802 of 1941. Carlos Castaneda, a Texas Mexican American working at University of Texas was appointed to oversee Latin American issues. And finally there was the Office of Inter-American Affairs, the Spanish-speaking People's Division, Kerry McWilliams, a California journalist who had written about Mexican and Mexican American immigration was placed in charge of helping to reduce discrimination Mexican Americans faced in the Southwest. And here are two examples of signs that were not uncommon in Texas. One was a weasel of whites only, this was in Demet in West Texas and then in East Texas newspaper ran this ad which was very common that they advertising the patrons that they were only white people that they hired to work there. Agriculture also faced serious setbacks during the war because many young men were in the military and away from the farms and so who was going to help when harvest time came around but the federal government instituted the Bracero program in an agreement with Mexico to allow Mexican farm laborers to come in temporarily to help with growing season and harvest season. Now Texas was excluded from that because of numerous cases of discrimination and so the governor of Texas, Coke Stevens established the Texas Good Neighbor Commission to help eliminate discrimination, identify places where it was happening and work with the businesses or the towns and the areas to help reduce that discrimination. The state legislature also passed the Caucasian race resolution in 1943. This was basically to say that in accordance with the laws of the Treaty of Guadalupe de Algo, Mexican Americans were considered Caucasian and therefore should not be discriminated against. But in 1944, this was challenged with the Terrell Wells case. This was a private swimming pool in San Antonio that refused service to Mexican Americans and the judge said in the case that the Caucasian race resolution was just a resolution and it did not carry the full weight of the law. So segregation was allowed to continue. There was also efforts at promoting union benefits during the agricultural workers in World War II, during World War II and this was the National Farm Labor Union in California, formerly the Southern Tenant Farmers Union. Ernesto Galarza was one of the Californian union organizers working with him and he helped organize over 20 strikes in the years. Now this was mostly after the war. The United States government had passed the Servicemen's Readjustment Act or the GI Bill of Rights in 1944 to provide returning service personnel with opportunities, education with financial loans to help start businesses, buy homes or complete school. And Hector Garcia, a doctor, you see his photo on the top left-hand side there from Corpus Christi, established an organization called American GI Forum and what he wanted to do was to make sure that Mexican Americans were able to receive the benefits that the Servicemen's Bill of Rights provided. They received a lot of attention in 1948 when the young man pictured on the right-hand side, soldier Private Felix Longoria, was killed in the Philippines in 1945. In 1948, they removed his remains back to his hometown near Corpus Christi of Three Rivers, Texas. The funeral home, white-owned funeral home in Three Rivers, agreed to prepare the remains for burial, but they did not want to hold awake for the family because they feared that it would drive off other white customers from the funeral home. The whites wouldn't like it. So Hector Garcia, an American GI Forum, enlisted the services of Senator Lyndon Johnson to help. Johnson sent members of his staff to investigate, found out that, yes, there was what they considered discriminatory practices, and so in the end of the story, the Longoria Fair, Longoria's remains were buried in Arlington National Cemetery with full military honors. Johnson continued, however. You had restaurants who refused to serve servicemen, like Jose Lopez, a Medal of Honors. Winner in Brownsville, a restaurant refused him service. Macario Garcia, a Medal of Honor recipient in Sugarland, was denied service, and so you did have discrimination that continued long after the war. Finally in 1950, Operation Wetback, almost a half-million Mexicans and Mexican-Americans, too, were deported because of Cold War fears and isolationism that they were creating a nuisance within the country. Additionally, there were educational challenges. Now, while Texas did try to educate teachers that Mexican-American and other minority students were capable of learning, there was a widespread belief that minority students, Mexican-Americans, African-Americans simply could not learn like white children could. And so the Texas Supervisory Committee on Inter-American Education was aimed at helping teachers learn that Mexican and Mexican-American students did not have impediments to education that they could learn just like everybody else. In 1946, a case before California's Federal District Court, Mendez versus Westminster, challenged educational practices of segregating Mexican-American and other students from white students. So what the federal judge in Mendez issued their order that they could not be because the Treaty of Guadalajara in 1948 said that Mexican and Mexican-Americans were considered Caucasian and therefore could not be segregated. In 1948, a couple of years later, lawyers out of Austin and San Antonio and Houston got together to enact a similar decision here in Texas called Delgado versus Bastrop. This overturns another Texas court ruling, the Del Rio decision of 1930, which had said that you could segregate Mexican-American kids. So Delgado versus Bastrop, the federal district judge Ben Wright said you could not. So this was a victory by Lulac, who had hired many of the attorneys working on the case. So in this lecture, we've looked at how World War II affected the Mexican-American community. It brought increased opportunity for advancement socially and economically. It provided an opportunity for military service and recognition and therefore pride to the Mexican-American community. The Mexican-American generation is this group that was of age during World War II. Those who benefited from the war took advantage of the educational opportunities and struggled for increased civil rights and political participation. And finally, the war contributed to the Mexican-American civil rights movement because with the increased recognition of Mexican-American contributions, this gave more opportunities for Mexican-Americans to challenge prevailing segregation practices. It provided them additional economic and educational opportunities and therefore more political influence. So thank you very much for watching this video.