Data Visualization Process

Data Visualization Workflow

Definitions

  • Factual knowledge are the basic ideas students must know to be acquainted
    with data visualization in order to solve data visualization challenges.

  • Conceptual knowledge is the understanding of interrelationships that exist between
    the stages within the larger structure of the process that enable the stages to function together.

  • Procedural knowledge is the knowledge of techniques and methods and the ability to apply
    them in each stage of the process.


Factual & Conceptual Knowledge Outcomes
    Students will be able to demonstrate their factual and conceptual knowledge about the data visualization process:
  1. The basic stages for visualizing data.
  2. What happens in each stage of the visualization process.
  3. What stages are likely to initiate the iterative nature of the process.
  4. Different techniques used to better understand data.


Procedural Knowledge Outcomes
    Students will be able to demonstrate their procedural knowledge about the data visualization process:
  • Demonstrate actions to acquire data.
  • Demonstrate the ability to change raw data into a useful format for further processing.
  • Implement procedure(s) to extract data of interest from a larger dataset.
  • Choose the appropriate visualization chart for the task/data.
  • Implement methods and techniques to improve the visualization.
  • Apply best practices for data visualization.

    • Byrd, V. L. (2021, July). Innovative Pedagogy for Teaching and Learning Data Visualization. In 2021 ASEE Virtual Annual Conference Content Access.

Learning Objectives

  • LO1: Remember and define the stages of visualizing data.

  • LO2: Explain the interactions between the stages of the data visualization process.

  • LO3: Demonstrate what happens in each stage of the data visualization process.

  • LO4: Discuss the interactive nature of the data visualization process.

  • LO5: Generate/produce data visualization that provide insight.

  • LO6: Self and peer-critique the data visualization process.



Learning Objectives, Basic Ideas, Core Ideas

Self Assessment

Complete this assessment to demonstrate your current knowledge of the Data Visualization Process:

Prerequisites: Make sure to finish the following tasks before working on this assessment.

Evaluation Matrix

Review

Holistic Data Visualization Capacity Rubric

Score Description (Consistently does all or most of the following)
4
  1. Clearly articulate what happens in each stage of the data visualization process.
  2. Accurate, complete interaction between each stage of the data visualization process.
  3. Demonstrate the ability to apply each stage of the data visualization process.
  4. Discuss how output from each stage impacts other stages in the data visualization process.
  5. Clearly evaluate and appraise data visualizations for impact, effectiveness, and insight.
  6. Create visualizations that clearly show significant relationships that exist within the data, articulates assumptions and presentation of all relevant assumptions and point of view.
  7. Demonstrates data visualization best practices.
3
  1. Clearly articulates what happens in some stages of the data visualization process.
  2. Accurate, mostly complete interaction between some stages of the data visualization process.
  3. Demonstrate the ability to apply some of the stages of the visualization process.
  4. Discuss how outcome from some stages impact other stages in the data visualization process.
  5. Evaluate and appraise some data visualizations for impact, effectiveness, and insight.
  6. Create visualizations that show some relationships that exist within the data, present some relevant assumptions and point of view.
  7. Demonstrates some data visualization best practices.
2
  1. Identifies each stage of the data visualization process.
  2. Accurate but incomplete interaction between stages of the data visualization process.
  3. Simplistic demonstration of what happens between stages that ignores the iterative, non-linear nature of the process.
  4. Discuss how output from one or two stages impact the data visualization process.
  5. Articulates insignificant or illogical implications and consequences that are not supported by evidence (data), lacking insight.
  6. Creates visualizations that are simplistic and ignores feedback and point of view.
  7. Demonstrates a few data visualization best practices.
1
  1. Unclear articulation of stages of the process.
  2. Inaccurate, incomplete demonstration of interactions between stages of the data visualization process.
  3. Incomplete demonstration of what happens between stages that ignores the iterative, non-linear nature of the process.
  4. Fails to discuss the impact of each stage on other stages in the process.
  5. Generates invalid implications and consequences based on irrelevant evidence (data)
  6. Incomplete presentation that ignores relevant assumptions and point of view.
  7. Fails to implement data visualization best practices.


What you should know:
  • → The stages of visualizing data
  • → The interactions between stages
  • → The application of each stage
  • → How output from one stage impacts other stages in the process
  • → The value and purpose of the visualization process
  • → The iterative nature of the data visualization process


Data Visualization Process


What you should be able to do:

Focus You should be able to do
Identify The stages of visualizing data
Explain The interaction between stages of the data visualization process
Demonstrate The ability to apply each stage of the data visualization process.
Discuss How output from each stage impacts other stages in the data visualization process
Critique The outcome and process implemented to visualize data.
Determine The value of the visual product and data visualization process.


Data Visualization Process Horizontal Assessment