Welcome to a new module of our information visualization course. So, in this lesson, we're going to focus on graphical components and mapping strategies. So, what are these elements? In the previous modules, we introduced the idea of visual encoding, which is how to go from the data to a visual representation. We also described how the method of performing data abstraction is useful as a way to map data to a given graphical form or format. So, today we dig much deeper into the issue of visual encoding. How to go from data to visual representation. The main difference between what you learned in the previous module and what you're going to learn in this module is the following. So, in the previous module, I described how to go from data abstraction to choosing a graph that is appropriate for that type of data. Today we go much more granular. We talk about in general, what kind of individual graphical elements are appropriate for different types of information. So, it's much much more granular. Is not just choosing what type of chart or graph to use, but what kind of individual components can be used to create a visualization that is appropriate for the type of data that you have and the goal that you have. In a way you can see that as a preliminary work or knowledge that is needed to create also new types of visualizations beyond the standard charts and graphs that exist out there. So, it's a very very powerful tool. Why do we do that? Well, we introduce these concepts of graphical components and mapping between data and graphical components mainly for two reasons. The first one is because it's useful as an evaluation tool. If you want to evaluate or even criticize an existing visual representation by understanding or knowing how to visually encode and as we will see in a moment decode this representation, you can actually better understand what elements form them, and also criticize much more in details the design choices that have been made. The second point that is highly related to the first one is that it's helpful for you to design and redesign visualizations. Think about it. If you are able to evaluate a given visualization, that's very useful for you as a designer because if you are able to create a number of alternative designs for a given problem, and then you are able to evaluate it, you have a very powerful tool in your hands as a designer. So, more precisely, when we talk about visual encoding, we're going to talk about a set of mappings between data items, what we call data items in the lecture about data abstraction and the graphical elements that represent these items which we call visual marks. The second step is going from data attributes to visual channels. So, the properties of these marks that encode information coming from the attributes. Let me give you a little example. So, here we have a scatter plot similar to some of the other scatter plots that I've shown you before earlier in the course. So, let us try to analyze this scatter plot in terms of its components and mappings. Okay. So, what do we see in a scatter plot? We see a lot of dots. So, every single dot is a mark, and each mark represents one item in this dataset, one row. In this specific case, this is data coming from representing a collection of food products. So, every row represents one food product. So, we have a mapping between food product which is the data item and the points. Every single dot represents one food product. Now, what else do we have in the chart, where we have three main visual characteristics. We have the x-position, the y-position, and color. So, these three channels represent three attributes that come from the table. So, we have amount of carbohydrates in these foods that is encoded as exposition. We have the amount of calories that is encoded as y-position, and we have color that represents the food category or food group. So, that's an example that shows you what we mean when we talk about visual encoding and what we mean when we say graphical components and mapping between data or data attributes and visual channels.
