Welcome to our online course of foundations of CyberGIS and geospatial data science. I'm Shaowen Wang, I'm a professor and the head of the Department of Geography and the Geographic Information Science. I'm also directing UIUC CyberGIS Center for Advanced Digital and Special Studies. This course is a call talk with my colleague Dr Anand Padmanabhan who is a senior research scientist at the CyberGIS Center. Thank you all for joining us. I'm going to start with the introduction to this course, we're going to cover for components in this introduction. The first one is geographic information science and the systems. We'll start with some definition GIS, as most of you perhaps have heard is standing for geographic information system. That is a computer based information system to enable, capture, modeling, storage, retrieval, sharing, manipulation, analysis, and presentation of geospatial data. Geospatial data essentially is a very popular data with geo location and spatiall references. GIS also stands for geographic information science, that is a branch of science, studies data driven and competition. All approaches to capturing, representing, processing, analyzing and visualizing geospatial data. In addition to systems and science, GIS also stand for a number of other different things such as services. Geographic information services now is a very popular in our life. For instance, I'm getting to my classroom using navigation services such as the Google map. And also GIS today is a major fabric of our information society. And also GIS is a very important way of synthesizing so many different kinds of data and information for a variety of applications. Such as for managing natural resources, for organizing our transportation infrastructure. To understand our societal sustainability, both the environment and energy for example. Important note here is geo and spatial are important characteristics for managing, organizing geographic information, and this requires special treatment. And the world hit this point, and many times in our course, especially in the data science subject. I would like to share with you a popular quote, this is relatively easy to understand. GIS are simultaneously the telescope, the microscope, the computer, the Xerox machine of regional analysis and synthesis of geospatial data. That says GIS is just so powerful for not only as a discipline of science. But also as a powerful tool that gets synthesis of geospatial data as well as a regional analysis put into perspectives. Just to mention a few related terminology, special information system is another term you might be aware of. For example, you go to a hospital, you look at medical images. The medical images are often times organized and managed in special database. And that kind of data is similar to the data GIS manages and organises, because they all have special references. And the way the special structure, the special interactions are handled in medical images are similar. For instance, to the images we capture for earth on our planet. And even, for instance, on the moon, part of the moon that we need to understand. So these are are inherently special, and another term is Geoinformatics, that is a branch of informatics. Informatics essentially studies information as a branch of information studies. And geo is focused on geosciences, and Geography is of course part of that. So Geoinformatics is a subject and the branch of informatics study. As we could easily relate, GIS is very much contextualized in computer based systems. In fact, one of the definitions of GIS, geographic information system, essentially the computer system. And for today are mainstream computer architecture is what is called one human architecture, that includes four major parts. Control essentially, coordinates, computing processing parts, and the logic inside of the computer chips. For instance, mobile devices have, and input and output. For instance, your mouse and keyboard gives signals to your computers to take actions and processing. Of course, the heavy lifting part of your computer to work and the storage the data where it lives, including the major pieces of data. Oftentimes you need to access before you could do the processing part. You need to load it up from storage to your memory that has faster performance, for your computer major tasks. So this architecture has been around for multiple decades, and in parallel to this architecture is the notion of high performance computing. Which essentially is always pushing to make the computers fastest. And essentially is the frontiers of computing to address what's coming in future as the best and the fastest computers. And today, as you perhaps noticed from your personal computers. Were not essentially advancing individual computers speed, we're essentially taking advantage of what is called parallelism. Parallelism is using a large number of computing resources simultaneously to achieve this high performance computing, that is the major foundation of cyber infrastructure. Before we are going to talk about a cyber instructor, I think this is a good point to pause. What we have learned is the major definitions of GIS, and the related terminology. As well as the computer architecture associate to GIS, essentially including high performance computing, which is a major foundation of cyber GIS. We're going to learn, and in that foundation, cyber infrastructure is a key concept we're going to cover in the next part.
