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Homework answers / question archive / ESR 173 Lab 4: Data Visualization Storytelling with Science Purpose: The purpose of this exercise is to give you the opportunity to explore data visualization tools and their applications

ESR 173 Lab 4: Data Visualization Storytelling with Science Purpose: The purpose of this exercise is to give you the opportunity to explore data visualization tools and their applications

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ESR 173 Lab 4: Data Visualization

Storytelling with Science

Purpose:

The purpose of this exercise is to give you the opportunity to explore data visualization tools and their applications. You’ll be able to practice deciding what type of tool to use for data you find, and data you have collected. You’ll also learn more about strategies to interpret visual data such as charts and graphs.

Background:

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data (Tableau, 2019). Data visualization is a tool for visual storytelling which can be especially important in the realm of science, to ensure that the message or narrative being told is clear to not only the scientific community but the public. Not all graphs or charts help in telling a story - too simple or too elaborate and the message can be lost.

The creation and use of data visualization are skills to be practiced, and worth learning.

 

What is data?

 

There are two main types of data that scientists collect when exploring different scientific concepts - qualitative and quantitative. Data is commonly the product of measurements or observations.

 

Qualitative - quality - information not numerical in nature; descriptive, and regards phenomenon which can be observed but not measured.

Ex. Public opinions about climate action

 

Quantitative - quantity - information that is numerical in nature; measurable

Ex. Temperature, the amount of CO2 in the atmosphere, ocean pH

 

NOTE: In some cases and particularly in Chemistry, quantitative data can be collected through modeling or calculations, rather than direct measurements, depending on the scale (i.e. length of a bond, quantity of a byproduct in a chemical reaction)

 

 

 

 

 

 

 

What are the major types of data visualization tools, and how are they used?

 

Review some great overviews by Storytellingwithdata.com to explore the following:

 

 

 

Line graphs

 

 

 

 

 

Bar charts

 

 

 

 

Pie charts

 

 

 

 

Instructions:

 

  • Follow the instructions in this packet to explore different visual tools for representing data.
  • Reflect on applications of data visualization tools as a means of storytelling in Chemistry.
  • Reflect on applications of data visualization tools for your Perspectives Project topic.

 

 

  1. Explore one or more the following websites for examples of data visualization:

 

 

    1. What types of elements (images, formats, features, animations, etc.) are used to visually represent quantitative data? Include a description of at least one (1) example, including the site from which you observed the visualization (1 point)

 

 

 

 

 

 

 

 

    1. What types of elements (images, formats, features, animations, etc.) are used to visually represent qualitative data? Include a description of at least one (1) example, including the site from which you observed the visualization. (1 point)

 

 

 

 

 

 

 

 

 

 

    1. What about these examples surprised you if anything? OR what questions were raised when viewing them? (1 point)

 

 

 

 

 

 

 

 

 

 

2. As mentioned previously, not all visual tools tell a story that is accessible for everyone. Explore Kaiser Fung's website JunkCharts.typepad.com and describe, briefly, an example of a poor data representation based on your own interpretations.

 

    1. Include the following information (where applicable) (1 point): 
  • Topic of the data visualization
  • Form (graph, bar chart, infographic, line graph, or other imagery)
  • Representing quantitative data, qualitative data or both
    • What data in particular did you observe

 

 

 

    1. What about the example selected made sense or clearly connected with the message it was trying to portray? (1 point)

 

 

 

    1. Why was the example unsuccessful in your opinion? (1 point)

 

 

3. Explore three (3) of the following websites that host web-based access to data visualization and infographics:

  1. https://www.compoundchem.com/category/environmental-chemistry/
  2. https://fivethirtyeight.com/features/the-40-weirdest-and-best-charts-we-made-in-2020/
  3. https://infogram.com/examples/maps
  4. https://www.acs.org/content/acs/en/pressroom/reactions/infographics.html
  5. https://public.tableau.com/en-us/s/blog/2020/12/2020-vizinreview-year-viz-days
    1. How is this data relevant to our study of environmental science? (1 point each)

 

Include the following information (where applicable): 

  • Which site you explored
  • Topic of the data visualization related to environmental science or chemistry
  • Form (graph, bar chart, infographic, line graph, or other imagery)
  • Representing quantitative data, qualitative data or both
    • What data in particular did you observe

 

Site 1: ______________________________________________________________________

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Site 2: ______________________________________________________________________

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Site 3: ______________________________________________________________________

 

 

 

 

 

 

 

 

 

 

 

 

 

 

    1. Of the sites you observed, which one resonates with you most personally, and why? (1 point)

 

 

 

 

 

    1. Reflect on your engagement with these sites and in particular those that most resonated with your learning style. What parallels, if any, do you see between this type of data presentation or “storytelling” and what you have encountered in terms of Chemistry content? (1 point)

 

 

 

 

4. In upcoming labs, you’ll be developing your own data visualizations using selected datasets related to a variety of environmental science topics. Additional guidance for the use of Google Sheets will be provided.

 

Before we apply this learning directly in Google Sheets, consider what data visualization tools would be best to communicate the following stories, and why (datasets from DataNuggets) (3 points)

 

HINT: Revisit Background section to recall different uses for various types of data visualizations including line graphs, bar charts, and pie charts.

 

  1. Scenario/dataset 1:

 

 

Type of data visualization you could make and why

 

 

 

 

 
  1. Scenario/dataset 2:

Type of data visualization you could make and why

 

 

 

 

 

 
  1. Scenario/dataset 3:

Type of data visualization you could make and why

 

 

 

 

 

 

5. Reflect on data you may include in your Perspectives Project. In what ways might you use data visualization to strengthen your message? (1 point)

 

Some Additional tools to consider when planning for your project:

https://www.chartjs.org/

https://public.tableau.com/s/

https://www.springboard.com/blog/free-public-data-sets-data-science-project/

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