What's this? It's directions to buried treasure. This is amazing. If we draw a picture that we can see where it leads. First, it says take 1,000 paces North until you see a rock in the shape of a turtle, turn right at the turtle and continue 500 paces to the lagoon, then 700 paces South of the lagoon is a tree with an eagle's nest in it, turn right at the eagle's nest, and walk 300 paces West, and then 300 paces South, 200 paces West, you will find the treasure. But that leads right back here. Does that mean the treasure was inside me all along? Oh no, here it is, a crisp $100 bill. Drawing out that pirates map sure saves me a lot of time and pacing around. It was much clearer to me where I would find the treasure when I had a picture as my guide. Ever since the Pleistocene era, humans have been turning information into pictures. Why is that? Well, it's biological. Our brains are wired to understand imagery. The primary body part we use to observe the world is our eyes. Often we encounter information that's encoded into spoken words or written in numbers. In the caveman days, that information might have been instructions and how to hunt a mammoth. In my pirate's map, it was the number of steps I needed to take to get from place to place. For early World Explorers, the information might have been how the locations of stars and constellations corresponded to coastlines of new continents. These days, we live in a world filled with information. We have advanced telescopes that have cataloged more than 1.6 billion stars. There are at least five billion web pages on the Internet, and we have supercomputers that can do hundreds of quadrillions of calculations per second. Then we have access to all of this information, there's really no easy way to understand it. One of the best tools we have at our disposal for making sense of this information deluge is visualization. Visualization is the process of taking information and converting it into a picture that better conveys the meaning of that information. The term visualization means different things to different people though. If you talk to a psychologist, they may ask you to create an image in your mind, business executives might try to visualize the future of their company, filmmakers try to visualize their new movie on paper, but perhaps the most modern interpretation of the word visualization is data visualization. Data visualization is concerned with information stored as numbers, often generated by a computer, and turning it into imagery also generated by a computer. In this course, we will be talking about a specific subset of data visualization called scientific visualization. Scientific visualization is the process of turning three-dimensional numerical data that describes scientific phenomena like molecules, tornadoes, and galaxies into descriptive pictures. This type of data is called spatial data, meaning it has information about where in space it's located. Scientific visualization can be done in many different ways for many different purposes. Analytical scientific visualization is a type of visualization you can do to help a computational scientist understand their research data. Analytical visualization can help scientists make new discoveries by visually studying the output of their computational models. It can help them find errors in their code and understand what these immensely complex digital experiments might be revealing about the universe. Visualization is a valuable tool in the scientific process. On the flip side, cinematic scientific visualization is a type of visualization that we use to share science with people who are not experts in the field that the data came from. These visualizations that are made in the style of Hollywood movies, may not be as didactic, but they make computational models feel approachable to a wide variety of audiences. Experts from other fields, business-minded decision-makers, children, and parents, all respond well to visualizations made in the style of Hollywood movies. You may see these visualizations in movie theaters, at museums, or at scientific conferences. There are quite a lot of data sets being generated by researchers that do not have spatial data though. Non-spatial data are often referred to as relational data, meaning that the information they store is simply relative to itself. Examples of relational data include financial information, genomic relationships, or databases of people and events. Visualization of relational data is called information visualization. It's usually realized as a chart, or a network, or an infographic. These visualizations are often two-dimensional and interactive. Information visualization is a huge field within the data Visualization community. In this course, we mostly focus on three-dimensional time-evolving scientific visualization. It's worth mentioning that some of the most stunning and educational scientific imagery you will see does not actually fall under the category of visualization, because it's not imagery derived from numerical data. The field of scientific illustration involves artists collaborating with scientists to build as realistic a picture as possible based only on their understanding of the scientific field and their imaginations. Scientific illustrations are typically more prevalent in fields where computational research is limited or impossible. They're not intended to be as accurate as data-driven visualizations, but merely to help coalesce a new idea around that thing that humans understand best, imagery. Cinematic scientific visualization sits at the intersection of many different disciplines. It relies heavily on physical sciences like astronomy, biology, and geology to get any data to work with it all. It leverages the analytical software being developed by data scientists, and computer scientists, and the design software being developed by the computer graphics and film making industries. It relies on advanced computer hardware to process large amounts of data. It relies on the fields of education, psychology, and communication to effectively engage audiences. It relies on artistry, visual design, and information design to present something aesthetic and appealing. Professionals in cinematic scientific visualization understand that it's important to be able to interface with experts of different professions. It's not bad to have multiple disciplines of interest even for yourself. Since you are taking this course, you probably find yourself fitting into one of these fields, and if not that's great too. This course is designed with many audiences in mind. See we'll almost certainly hear some things that are very familiar and other things which are totally new to you. When we discuss something you are familiar with, it might help to think about how the information we're sharing is seen by students with other skill sets. Thinking about familiar topics from new perspectives can help when building a collaborative team, which is essential to successful visualization. There are many sub-fields of data visualization and it's helpful to understand how they are commonly used to see how you fit into them. With an understanding of how your experience is relevant to scientific visualization, soon you can be creating imagery from data for yourself. Fun facts, there's actually no evidence that pirates ever made maps to buried treasure. The treasure map is a common literary device originally created by Robert Louis Stevenson for his book Treasure Island.