31:T7b2,md` ### Level 1: Characterize the tasks and data in the vocabulary of the problem domain. The first level essentially tells the designer of the visual to figure out what area of knowledge their data and subsequent visualization falls under. The designer should know the problem they are attempting to address inside and out while showing users the most compelling and effective data that solves or displays the problem. Users should not walk away confused because the designer themselves was confused as to what domain the problem falls under. ### Level 2: Abstract into operations and data types. From my understanding this is the point where designers think about and build the objects and relationships that are the foundation of the visual. This includes transforming raw data into data types. In the paper referenced there is talk of developing a taxonomy, and therein lies the heart of what the second level is; a categorization of data into data types, objects, and operations that are used to construct the code base. ### Level 3: Design visual encoding and interaction techniques. This is where the magic happens. After the hours of prep going into cleaning and transforming data it is neccessary to think about how the visuals will appear and what their level of interactability should be. Will it be a bar chart race or a static word cloud? These considerations are made here and planned out to the smallest detail. ### Level 4: Create algorithms to execute these techniques efficiently. This is the nitty gritty of what makes your visual run and display visuals in a timely and clean manner. With a slow running algorithm an animated visual of a map situated in the US that displays where people are infected with COVID-19 might not even show the fill of colored dots of infected areas. Whether it be the complexity of the algorithm or the running processes of a desktop computer a designer needs to take all the barriers-to-entry into account. `32:T46f,md` Level 1 Threat: Designers tend to make assumptions about what they see in the data and that bias cascades down to implementing the algorithms that end up displaying the data. Opinion and bias are threats to the first level. Level 2 Threat: A designer will typically skip the first level of domain characterization and head straight here. This is a threat to this level because without proper consideration of all aspects of the domain a designer will often select the most interesting object to focus on and forego other important data types and operations that could be found in the raw data. Level 3 Threat: There is a myriad of ways to develop the visual encoding and level of interactivity. The biggest threat at this level is when a designer picks an ineffective technique to use without considering the limiting aspects of an inferior technique. Level 4 Threat: In my own words, I would say the biggest threat at this level is that designers get lazy and create alogirthms that run slow and don't capture the entire set of operations needed to effectively display their objects and data types built in previous levels. `33:T787,md`## Visualization Analysis For **two visualizations**, you are going to use the Nested Model of visualization design to describe what _you believe_ to be the intention of the work. For each one, you should first _display the visualization_ (either by importing it from a Notebook, or putting an \`\` or \`