UW iSchool Course INFO 474: focused on designing and building visualizations to better understand and communicate about pressing issues.
md`There are 4 levels in visualization design as shown in the paper.
> * __First Level:__ Characterizing the task and data according to a specific target domain. This would mean understanding each domain's vocabulary to describe its data, problem and workflow that solve their problems.
> * __Second Level:__ Transform the data and problem in the vocabulary into data types and operations that can be transformed into a visualization design. For example, the raw data is needed to be changed into a different form to find the right data type where a visualization representation can address the problem.
> * __Third Level:__ The transformed data is now designed into a data visualization and also plan out how users will interact with it.
> * __Fourth Level:__ The creation of the algorithm to carry out the visual encoding and interaction designs that were made in the previous level. `
md`> * Each level of visualization design will produce a certain desired output which will be needed to continue towards the next level as it will be used as the next level's input.
> * __First Level:__ Main vocabulary of the domain is characterized, where the output are detailed questions and instructions that are required to solve the problem.
> * __Second Level:__ The previous output is further cateogorized and transformed into relevant data to create the visualization, which is the output. Another output is also the description of tasks needed to be done.
> * __Third Level:__ The instructions and data required are inputted. The output is the design prototype on how the visualization will look like and how the users will interact with it.
> * __Fourth Level:__ Since the design is inputted, the output will be the completed algorithm that creates the intended design successfully as well as responds correctly towards user interations.
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md`> * __First Level:__ Mischaracterized problem - This means that the target users do not have those problems at all as it just may be based on assumptions.
> * __Second Level:__ Transforming raw data into data types and operations that create visualization designs that do not solve the characterized problems.
> * __Third Level:__ The design of the visualization does not effectively communicate what it is intended to. The person who's using the system do not understand the abstraction that is presented in the visualization.
> * __Fourth Level:__ The created algorithm has an inefficient runtime and memory usage. This means that the algorithm is not using the most optimal way to create the visualization or at least in comparison with the previously proposed algorithm.`
md`I didn't really have much problem completing this tasks but I am still confused on how to alter or use commands from visualizations of other notebooks. For example, in my second visualization analysis, I wanted to put a replay button from the other notebook but is unable to.
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import {
assignment_instructions,
observable_challenges
} from "@uw-info474/utilities"
import { chart as osChart } from "@mbostock/most-popular-operating-systems-2003-2020"
import { chart as raceChart } from "@d3/bar-chart-race-explained"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
