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Background: Using Data to Tell A Story With flourish
Background: Using Data to Tell A Story With flourish
What is a Visualization?
Data visualizations can be used to explore data, but it can also be used to communicate ideas based on those data.
Usually we are starting with a question or series of questions that need to be answered
What is Data Storytelling?
Reach the broadest audience possible and to communicate a clear narrative and clear takeaways.
Putting Storytelling and Data Together:
What is Data Storytelling? A brief introduction.
https://public.flourish.studio/story/184765/
The Storytelling process:
The Storytelling process:
Identify a data source
Upload and edit the data in Flourish & Begin to create visuals:
Change Over Time
Drill Down
Zoom Out
Contrast
Visuals can lead to further questions and lead to different types of visualizations
Bring together the visuals and your text into a Flourish Data Story
Generally in Flourish, the workflow is to work with your data to create a series of visualizations of a dataset. Once the visualizations are created, they are pulled together into a 'Data Story'. Here is another example of how this looks when it is completed: https://public.flourish.studio/story/129951/
Case Study Example: Creating visualizations to tell the story of water usage in South East Asia
Here the goal is to create 1-2 visuals that can be used to start the storytelling process.
Step1: Identify the Data Source
In this example, the World Bank Data Catalog is queried to produce the following dataset:
Data:
Managed_Drinking_Water_PercentPop.csv
Description:
The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.
Source:https://datacatalog.worldbank.org/dataset/world-development-indicators
Note: the raw data from the World Bank is often not in a form that can be easily worked with. This video walks through the basic formatting changes that should be peformed to World Bank Data before uploading the data to Flourish: https://ny6mediashare.ensemblevideo.com/Watch/WorldBankDataDownload_PartIV
Step 2: Upload the Data to Flourish & Make Visualizations
Typically, the first 1 - 3 visuals you will be making become an exercise in 'exploratory data analysis'. In this phase, a basic understanding of the data is developed. Basic visualizations are created which may lead to new questions, and insights into the data. This will often lead to new visualizations.
A good place to get started, is to create a basic bar chart. The Bar Chart is a good way to make comparisons within the dataset. How do the different data points contrast with each other? How do the trends change over time?
https://ny6mediashare.ensemblevideo.com/Watch/FlourishBarCharts
See the videos links posted below for further details on working with Flourish
Step3: Developing additional visualizations
With a basic exploratory phase completed; trends over time appear to be an important theme in this data. Looking at trends over time is probably worth exploring. The Flourish platform provides interactive and animated data visualization options. One example is the line race chart.
Creating a line race chart: https://ny6mediashare.ensemblevideo.com/Watch/FlourishLineRace
See the videos links posted below for further details on working with Flourish
Step 4: Pull it all together
Once there are more than one data visualization; a narrative can be developed. In this step, the visuals that are created; can be pulled together to in the story editor.
https://ny6mediashare.ensemblevideo.com/Watch/FlourishDataStory
Wrap-up:
In this case study, we have worked with country-level, time -series data extracted from the World Bank in order to generate visualizations to support a narrative about drinking water usage in South-east Asia. Following data extraction and basic editing (which can be done using Microsoft Excel, Libre Office Calc or Google Sheets); the data was uploaded to Flourish and explored and visuals created. Finally we pulled together the visuals to start telling the story of drinking water in South East Asia.
Flourish How - to Videos
The videos below were posted to the Knight Center for Journalism MOOC course: "Data Journalism and Visualization with Free Tools"
https://knightcenter.utexas.edu/JC/resource/DATA0819.htmlData tables and column settings: https://www.youtube.com/watch?v=3zalmGgEguo&feature=youtu.be
Line, Bar and Pie Charts: https://www.youtube.com/watch?v=p0RI2Q2XMLM&feature=youtu.be
Scatterplots: https://www.youtube.com/watch?v=VAHV3RyU9fE&feature=youtu.be
Formatted Tables: https://www.youtube.com/watch?v=2zdccJyoW34&feature=youtu.be
Working with Maps: https://www.youtube.com/watch?v=RhljbWW5hsA&feature=youtu.be
Survey response summaries: https://www.youtube.com/watch?v=erg12o9c43A&feature=youtu.be
Advanced Symbol Formatting: https://www.youtube.com/watch?v=MRKNDBe2FO8&feature=youtu.be
References and Resources:
Knight Center for Journalism in the Americas: Data Journalism and Visualization with Free Tools Course https://knightcenter.utexas.edu/JC/resource/DATA0819.html (a complete set of Flourish Videos can be found in Modules 5 and 6)
Alberto Cairo; Alberto Cairo s the Knight Chair in Visual Journalism at the University of Miami. He’s also the director of the visualization program at UM’s Center for Computational Science. http://www.thefunctionalart.com/
Jan Diehm; Journalist Engineer for The Pudding; https://www.youtube.com/watch?v=XTvX_wjQwRI&feature=youtu.be
Storybench; Northeaster University School of Journalism; Digital Storytelling Resource Site: https://www.storybench.org/
Flourish Data Studio - https://app.flourish.studio/login
Questions?
Rob Beutner @ HWS
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