 Hello, everyone. Today, we will be presenting our project, our spatial data, which is a collection of data sources and tutorials on visualizing spatial data using art. Myself, Varsha Ajani Vijaykumar, and my colleague, Delini Seeman, we have completed this project in collaboration with Paula Muraga and Andrea Moral. Importance of spatial data. There are a large amount of open and reliable data being collected and made accessible in the recent years and different kinds of analytical tools and geographical information systems to visualize them. And these are being used by researchers in various fields like physical, social, environmental, and also in public health sectors to help improve the conditions within a country or across countries. For example, to map the HIV prevalence, child under nutrition, electoral planning and statistical studies, it could also be used in monitoring rice crops or the spread of different vector bond diseases like malaria are for data analysis and visualization. There are many R packages that have been recently released as clients for different spatial data repositories. And although there are documentation for each of them, there is an increasing need to have a one stop repository on how to visualize these spatial properties and tutorials on how to use them in their own projects. So this brings us to our project, our spatial data, which is a website which holds tutorials on different R packages used for visualizing spatial data for some of the spatial properties and you can find them on www.rspatialdata.jithub.io. Tutorials and data sources. So here I'll speak about the 12 spatial properties that they've created tutorials for administrative boundaries, open street map data, population, elevation, temperature, rainfall, humidity, vegetation, land cover, demographic and health surveys also known as DHS in short, malaria and air pollution. So here we use different R packages to download data related to these properties, out of which a few examples are the RGO boundaries R package, which is a client for the zero boundaries API, the raster package, which retrieves temperature data from the world claim database, and the modus CSR package, which gives us access to data collected by the NASA modus satellite. Our tutorials. So here I'll give a very general overview of the structure of each of our tutorials. Each tutorial will first talk about the data source that we are getting, retrieving data from for the tutorial to ensure the reliability of the data. And then we'll also include information about the R package used to download this data and installation instructions for the R package as well. So here we talk about the main functions available in the R package and how to download data using these functions as well. Then we'll include a small section on how to understand and interpret downloaded data and spatial objects as well. And then we'll include a main section which is different approaches, which we can use to visualize this downloaded data. For example, using different R packages and creating maps like non interactive and interactive maps as well. Then at the end we include a list of complete examples on how to download and visualize this special properties using different approaches and end of the tutorials with a list of references. Our vision. So vision for our special data is not to be a comprehensive list of our packages or tutorials, but to be a starting point for someone who is interested in visualizing spatial data using R and to know what packages are available and what functions are available as well. So we want our users to actually understand the process of visualizing different spatial objects using different R packages and apply to their need rather than just simply replicating our tutorials. Thank you. And I hope you find our special data as a useful resource.