Guide: How to emphasize a story through data visualizations - data.org (2024)

When created with a story in mind, a data visualization can make key insights stand out for your audience. This guide is designed to showcase these principles and practices.

Guide Objectives:

  • Identify the right data visualizations for your story
  • Simplify your data visualizations to the essentials
  • Use human perception to emphasize data insights

“Data visualizations” are graphical representations of data that communicate insights. They consist of visual elements, such as charts, graphs, infographics, and maps, that make complex datasets more understandable and accessible to audiences. In other words, they are used to help make sense of the data we are bombarded with on a daily basis.

When telling a story about your organization, a program, or even research, a well-done data visualization can emphasize that story. When created with a story in mind, data visualization can make key insights stand out for your audience.

To do this, just like writing a novel, there are principles and practices to best tell these “data stories” or insights. This guide is designed to showcase these principles and practices.

Guide Specific Disclaimer

It is important to note that, unless we are careful, visualizations may misrepresent data or mislead decision-makers, ultimately causing harm. It is our job as designers of visualizations to consider the types of stories our visualizations tell, in order to best mitigate the risk of misrepresentation.

Determine the right chart to showcase your insights

We recommend starting this process with an idea of the story you want to tell using data visualizations. With this story in mind, you will be able to select the most effective chart. There are several types of charts, each one having value in showcasing different types of data and insights.

Guide: How to emphasize a story through data visualizations - data.org (1)

This diagram, Chart Suggestions – A Thought Starter, is a good place to start.

Chart Suggestions: A Thought StarterDownload

For a more detailed breakdown of the use cases for each chart, you can refer to the definitions and images provided.

More ways to get started on data visualization:

Guide: How to emphasize a story through data visualizations - data.org (2)

If you need a hand deciding on the story you want to tell, you can refer to Freytag’s Pyramid. Freytag’s Pyramid is a dramatic story structure that is commonly used to analyze and map the plot of a story. While originally applied to literature, it can also serve as a useful framework for designing engaging and effective data visualizations.

Selecting the Best Chart

Bar & Column Charts – when comparing across categories; Example: comparing diabetes rates in a given year across states

Guide: How to emphasize a story through data visualizations - data.org (3)

Line Charts – when following the specific path of data points through time; Use case: showing the trajectory of diabetes rates from 2000 to the present year

Guide: How to emphasize a story through data visualizations - data.org (4)

Scatter Plots & Bubble Charts – when associating the relationships between two or three variables; Use Case: associating per capita income and diabetes rates through a scatter plot

Guide: How to emphasize a story through data visualizations - data.org (5)

Histograms – when reviewing the distribution of discrete or continuous data within a category (salary ranges, weight ranges, etc.); Use Case: comparing diabetes rates by populations of different income ranges

Guide: How to emphasize a story through data visualizations - data.org (6)

Stacked Column or Pie Charts – when breaking down the composition of a group; Use Case: looking at the percentage breakdown of ethnicities of people living with diabetes

Guide: How to emphasize a story through data visualizations - data.org (7)

Number Charts – when you just need to show large, critical numbers or metrics; Use Case: showing the number of people living with diabetes

Guide: How to emphasize a story through data visualizations - data.org (8)

Utilize Gestalt Principles of Perception

Now that you have identified the best chart type to tell your story, it is now time to design your data visualization. At this stage, it is important to familiarize yourself with the Gestalt Principles of Perception. The Gestalt Principles of Perception are a set of principles in psychology that describe how humans tend to organize visual elements into holistic patterns and perceive them as wholes, rather than individual parts. These principles include concepts such as:

  • Proximity – elements close together will be perceived as a unit;
  • Similarity – elements with similar features will be perceived as a unit;
  • Continuity – one continuous path is perceived, even when that path is interrupted;
  • Connectedness – connected elements will be perceived as part of the same group;
  • Closure – gaps will be filled to be perceived as part of the same group
  • Enclosure – visually enclosed elements will be perceived as part of the same group

These principles, among others, help explain how we make sense of visual information and perceive order and structure in the world around us. You should consider each of these principles to best emphasize your insights and key relationships when developing data visualizations.

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Guide: How to emphasize a story through data visualizations - data.org (10)
Guide: How to emphasize a story through data visualizations - data.org (11)

Minimizing distractions on your chart

Keeping the Gestalt Principles in mind, the next step is to minimize distractions in your data visualizations to develop clear and engaging stories. Essentially, you want to further emphasize your insights by reducing the clutter (or “chartjunk”). Chartjunk can come from distracting formatting, unnecessary text, highlighted colors, and more that take the audience’s eye away from the insights and stories you want to tell, and move them in the wrong direction. It is up to the visualization designer to determine what is chartjunk, and what is useful to emphasize the insights.

Minimizing Chartjunk can be done in many ways. In general, when distracting or unnecessary, we recommend:

  • Removing backgrounds
  • Removing redundant legends and labels on axes
  • Removing borders
  • Removing colors (unless highlighting points or groups)
  • Removing special effects (ex. Shadows or 3D graphics)
  • Removing bolding
  • Lightening text
  • Lightening or removing grid lines and axes
  • Directly labeling data points (if possible)

Example of Minimizing Distractions on Chart

In this example, we remove borders, bolding, grid lines, redundant legends, and special effects, among other things, all in an effort of emphasizing only the story we want to tell.

Remove background, legend, redundant axes labels…

Guide: How to emphasize a story through data visualizations - data.org (12)

Reduce coloring, remove special effects, lighten text and gridlines

Guide: How to emphasize a story through data visualizations - data.org (13)

Reduce coloring, remove special effects, lighten text and gridlines

Guide: How to emphasize a story through data visualizations - data.org (14)

‘So what’ and next steps

After completing the guide, you should now have the key principles and techniques to design data visualizations that emphasize the stories you want to tell. If possible, pilot your data visualizations with a sample audience to ensure your data story is coming across, and the data is not misleading.

Data stories are most effective when they are aligned with your organization’s mission. You can dive deeper into this with the guide: How to align data collection to your organization or project’s overall mission

We'd love your feedback.

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Guide: How to emphasize a story through data visualizations - data.org (2024)

FAQs

What are the 5 steps in data visualization? ›

  • Step 1 — Be clear on the question. ...
  • Step 2 — Know your data and start with basic visualizations. ...
  • Step 3 — Identify messages of the visualization, and generate the most informative.
  • Step 4 — Choose the right chart type. ...
  • Step 5 — Use color, size, scale, shapes and labels to direct attention to the key.

How to use HR data visualization to tell an impactful story? ›

Use HR Analytics to Tell the People Story & Engage Execs
  1. Know your Data Inside and Out: Explore the people data you have, making note of interesting peaks, valleys, trends and anomalies. ...
  2. Know your Audience & Identify Top Priorities: ...
  3. Transform the Data into Stories: ...
  4. Share your Stories: ...
  5. Continue Onwards and Upwards:

What are the data visualizations for storytelling? ›

What types of visualisations are used in data storytelling? Data visualisations include scatter plots, geographic maps, timelines, line graphs, pie charts, bar charts, heat maps, and tree charts.

What are the steps of making a storytelling data analysis? ›

How to tell a story with data
  • Find the story within the data. ...
  • Consider your audience. ...
  • Determine what data matters. ...
  • Analyze data and find insights. ...
  • Identify the most effective data visualizations. ...
  • Provide context. ...
  • Structure your story. ...
  • Edit until the story is clear and concise.
Mar 14, 2023

What are the 4 main parts of telling a story in data visualization? ›

Data Storytelling Techniques: The 4 Steps. Good stories contain four main elements: characters, setting, conflict, and resolution. In order to make a good data story, you can use these elements to frame the complex information into compelling visualizations.

What are the 3 C's of visualization? ›

The three Cs of data visualization are correlation, clustering, and color.

How do visualization help an audience in data storytelling? ›

It helps the audience connect with the data on an emotional level, sparking their curiosity, and encouraging further exploration. Moreover, data visualization allows for effective storytelling by simplifying complex information, enabling storytellers to convey their message in a concise and engaging manner.

What is the role of storytelling in information visualization? ›

Storytelling allows visualization to reveal information as effectively and intuitively as if the viewer were watching a movie.

What three key components are required in a data storytelling narrative? ›

The three key components of data storytelling are: data itself, which provides the factual backbone; a clear narrative, which pulls the whole thing together into a coherent data story; and appealing visuals, which bring the data story to life.

How do you visualize storytelling? ›

8 tips for powerful visual storytelling
  1. Keep your readers top of mind. ...
  2. Be strategic in your use of interactive visual elements. ...
  3. If you have data, use it. ...
  4. Show, don't tell. ...
  5. Be ambitious — and get better results. ...
  6. Build content for the web, not print or PDF. ...
  7. Optimise your video and images for the web.

What are the three steps of data storytelling? ›

Three Stages for Mastering the Art of Data Storytelling To A Live...
  • Planning: Reviewing Strategic Fundamentals and Designing the Presentation. Planning the presentation involves two pivotal aspects. ...
  • Developing: Wording, Numbers, Charts, and Images. ...
  • Delivering: Making Final Preparations and Giving the Presentation.
Jun 20, 2023

What is the difference between data storytelling and data visualization? ›

Data storytelling differs from data visualization because it requires that the narrators of your story deliver a more significant, encompassing view of your message in a way that your audience can easily understand. On the other hand, data visualization is a tactic used to enhance your storytelling.

What is the first rule of storytelling with data? ›

1) Use a convincing voice. Data always has a story to tell. They just depend on you to deliver that message in a clear and concise voice to the audience. Explain what is happening in the data and why it is of importance to them and their business.

What is the basic structure of data storytelling? ›

The three-part data story structure

In data storytelling, always remember that there are three elements to every story: context, complication, and resolution. When you've thoroughly analyzed your data to determine each element, you'll be able to tell the whole story.

What is the main process of data visualization? ›

Data visualization is the representation of data through use of common graphics, such as charts, plots, infographics and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

Which are the process of data Visualisation? ›

Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends and outliers in large data sets.

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