Designing GitHub’s Octoverse: A Data Visualization Case Study

Designer Gemma Busquets shares how she created a responsive website and 20+ engaging charts and graphs for the software development platform’s annual report.

Designing GitHub’s Octoverse: A Data Visualization Case Study

By Gemma Busquets

Gemma is a designer and creative director with over 15 years of experience in UX, data visualization, and branding. She has taught data visualization for 7+ years at the university level and has directed a master’s degree program on the subject. Gemma’s portfolio includes collaborations with GitHub, Coca-Cola, Nike, Visa, and Seat.

Previously At

Last year I collaborated with GitHub to design the 2021 State of the Octoverse report . GitHub’s Octoverse analyzes real-world data from millions of developers and repositories in order to present the year’s software development industry insights. The 2021 report covers three major trends: improving performance and well-being by developing code, creating documentation, and supporting communities in a smarter, more sustainable way.

As the project’s creative liaison, it was my job to assist the GitHub team in making the data-heavy report easy to understand. Using data visualization , I designed 20+ charts, maps, and graphs to help readers unravel the information that GitHub data scientists collected.

In this data visualization case study, I explain my design process, showcase the website I helped to create for GitHub’s Octoverse, and share key learnings from the project.

Designing Engaging Digital Experiences With Data Visualization

State of the Octoverse 2021 is a sprawling report, with data collected from over 73 million GitHub developers and more than 61 million new repositories . It’s also the first time a survey on respondent demographics has been included. Making sense of the data required an extensive design effort.

Our modest team, which included developer Jose Luis Garrido and project manager Miquel Lopez , was tasked with synthesizing this immense amount of information for readers. Despite a delayed start and other simultaneous projects, we delivered.

Kicking Off the Design Process

The first stage of my data visualization design process was discovery. GitHub’s data scientists collected and analyzed information from developers and repositories through Excel files, PowerPoint presentations , and other data sets.

With this information, along with GitHub’s initial data visualization sketches and a 60-page context document, I began to think about how best to illustrate each data set. Then, I set about designing each chart, map, and diagram for maximum user engagement and an intuitive user experience.

Choosing Your Chart

There are three key points to choosing an effective data visualization :

1. Identify the Chart’s Purpose

Data can be represented in numerous ways–bar charts, line graphs, heatmaps, waterfall charts, and more. Each chart serves a purpose, and it’s important to use the right one to ensure that a clear and accurate message is conveyed.

For example, if you want to present the difference between two quantities, use a bar chart. If you want to show a trend over time, use a line graph.

2. Consider the End User

You also need to be aware of your users’ ability to read and analyze data. Most of us are familiar with pie, bar, and line charts. We see them everywhere, and we know how to read them.

On the other hand, fewer people know how to read box plots , which are used in many research publications to summarize multiple data variables into one chart.

If you present users with unfamiliar visualizations, they’ll have a hard time interpreting the data.

3. Design With Clarity

Is the data visualization clear and concise, or is there too much noise? Bar charts can be a great way to display data, but not if there are 100 bars with individual labels. Likewise, streamgraphs are beautiful and functional, but only when there’s a clear data pattern. Sometimes less is more.

Designing Perfect Data Visualizations

Throughout the 2021 State of the Octoverse report, you’ll find a variety of data visualizations that have been carefully composed in accordance with the corresponding data insight.

The Butterfly Chart

On the Overview page, I needed to design an infographic for two sets of data—showing where respondents worked before the pandemic and after it. GitHub provided me with two pie charts that each mapped out four data points: collocated, hybrid, fully remote, and not applicable. However, pie charts are not particularly effective when comparing two sets of data.

Instead, I opted for a butterfly chart . Butterfly charts plot the data as two horizontal bars side by side, resembling butterfly wings. These charts clearly show the difference between two groups that share the same parameters, and make comparing two sets of data much easier.

A butterfly chart for GitHub's Octoverse report showing two sets of data side by side. The data compares where respondents worked before (left) and after (right) the pandemic. There are four data points: collocated, hybrid, fully remote, and not applicable for both data sets.

The Bump Chart

Another effective data visualization is the bump chart . We used this chart to present the information on the most popular computer programming languages used by developers over the past eight years. Bump charts are great for displaying changes in rank over a period of time, and they have become a staple in the Octoverse report.

A bump chart for GitHub's Octoverse report that shows the most popular computer programming languages used by developers over the past eight years. Each language is represented by a different colored line. There are 10 languages in total.

The Treemap

I needed to illustrate the different sectors to which respondents contribute code. The final decision came down to pie charts versus treemaps.

Pie charts are useful when you have three or four sectors and when the quantities are clearly different. However, our brains don’t process angles well , so when there’s a pie chart with lots of similarly sized wedges, people have a hard time deciphering which is bigger.

In contrast, treemaps allow users to easily compare segments to each other, as well as to the whole. The largest rectangles are placed in the top left, followed by progressively smaller rectangles. It’s easier to compare straight lines than it is to compare wedges or angles.

A treemap for GitHub's Octoverse report illustrates the different sectors to which respondents contributed code during 2021. Each sector is represented by a rectangle.  The largest rectangles are placed in the top left, followed by progressively smaller rectangles. Each rectangle is a different color.

The Cartogram

Finally, I needed to illustrate the geographical distribution of organizations using GitHub in 2021 by region or country. For this, I used a population cartogram. Cartograms are maps in which the geometry is distorted to accommodate a particular economic, social, political, or environmental feature.

In this data visualization, the size of the squares indicates the population size. Additionally, the saturation of the square’s color indicates how many organizations in that area are using GitHub.

A population cartogram for GitHub's Octoverse report represents the geographical distribution of organizations in 2021. This map alters the reality of physical location in order to better visualize a particular factor, in this case business. The saturation of the square's color indicates how many organizations are using GitHub, with lighter shades representing fewer and darker shades representing more.

Responsive Website Design For GitHub’s Octoverse 2021

In addition to designing data visualizations, I also helped the GitHub team produce a website for Octoverse 2021. This site was a hub for users to read, explore, and interact with the report’s data insights.

To encourage user engagement, we opted for a fully responsive website that would adapt the site’s rendering to different sized viewports. GitHub asked us to pay special attention to the desktop version after finding that larger devices drove the majority of Octoverse visits.

When designing the responsive site, I followed these best practices :

  • Composing text with desktop-friendly and mobile-friendly typefaces. This included choosing optimal font sizes, typefaces, and line length and height, and refining how the text looks at different breakpoints.
  • Laying out the visual elements on each page to encourage scrolling .
  • Designing a user-friendly top navigation bar that adapts its layout to the viewport size.

Because I designed the website with different devices in mind from the start, most charts rendered well on all screen sizes. I only needed to make minor adjustments for optimal viewability, such as to the circular dendrogram at the end of the “Sustainable communities” section.

A circular dendrogram for GitHub's Octoverse report. Each circle represents one of the 20 largest repositories by category and repository contributors. Each sector is represented by a different color.

Organizing the Information Architecture

I explored different options for the website’s information architecture . I didn’t want to overwhelm users with too much information, but I also didn’t want the site to be scattered or difficult to navigate.

With this in mind, I started by designing a long scrolling website, with all the content on the same page. When that became visually overwhelming, I tried placing each chart on a separate page. To help with navigation, I added a side navigation menu to each page with a table of contents, similar to what you might find in a book. The final design on the Octoverse website consists of separate webpages for the three main trends, plus a homepage that serves as a summary of the most important data.

After deciding on the information architecture, I moved on to designing the site’s content structure, navigation flow, images, and graphics. I created wireframes to map out the content and show paths between different pages.

Making the Website Interactive

The scroll progress indicator.

To satisfy GitHub’s request for an engaging, dynamic website, we added interactive elements. For instance, under the top navigation bar, I designed a scroll progress indicator so visitors could keep track of where they were on the site. As readers scroll down a page, the indicator bar scales incrementally, and each page has a different fill color for the bar: gray, purple, blue, or green.

A portion of the "Sustainable communities" webpage within the GitHub Octoverse 2021 website. The scroll progress indicator across the top is interactive. As the user scrolls down the page, the indicator bar changes from light gray to green.

Animated Headers, Images, and Data Visualization

To keep the website from looking flat, we decided to animate the section headers. I created the illustrations and our team’s developer animated them. We also animated the hero image for the homepage and each subsection, and their corresponding chapter cards at the bottom of each webpage.

We also made some of the static data visualization charts interactive. For example, as you scroll over a line in the bump chart, the line thickens to emphasize the corresponding data point. It’s a simple but effective animation that lets site visitors interact with the data and quickly compare languages.

Creating Successful Data Visualizations and Digital Designs for GitHub: Key Learnings

Data is only useful if you can make sense of it, and the process of designing data-heavy content that users can easily decipher is challenging. Nevertheless, this collaboration with GitHub broadened my knowledge in data visualization design . Here are the most important takeaways from this data visualization case study:

  • Know the brand: Being familiar with a brand’s core style guidelines—such as ​​its use of type, color, and images—speeds up the design process because it frees designers to move on to the creative process. I was lucky that I knew a lot about GitHub’s brand before the collaboration, and I was able to use this knowledge to inform my designs.
  • Choose the right types of data visualizations: Selecting the correct visualization to represent a data point is essential. An incorrect representation can cause confusion or convey the wrong message.
  • Use color wisely: The right color combination will guide the reader’s eye and draw attention to a particular data point.
  • Stay curious: When you’re trying to tell a compelling data story, you’re bound to encounter complex design problems, so it’s important to be open to uncommon solutions and continuous learning.

Understanding the basics

What is the github octoverse.

GitHub’s State of the Octoverse is a report that presents software development trends and insights. Data from millions of developers and repositories is collected and analyzed to make up the annual report. Trends include working habits, productivity, and career satisfaction.

What is data visualization, and why is it used?

Data visualization is the process of creating graphical representations of data sets, such as charts, graphs, and maps. This design technique is used to clearly communicate complex data to users.

What does GitHub do, and why is it so popular?

GitHub is an open-source code-hosting platform for version control and collaboration where developers and programmers can download, review, and evaluate each other’s work. It is the platform of choice for millions of developers.

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A Reader on Data Visualization

Chapter 3 case studies.

This chapter explores some interesting case studies of data visualizations. Critiquing these case studies is a valuable exercise that helps both expand our knowledge of possible visual representations of data as well as develop the type of critical thinking that improves our own visualizations. Furthermore, the examination and evaluation of case studies help show that new designs are just as usable as existing techniques, demonstrating that the field is suitable for future development.

3.1 Introduction

Visualization is like art; it speaks where words fail. The usefulness of data visualizations is not just limited to business and analytics; visualizations can explain almost anything in the world. Wars, rescue operations, social issues, etc. can be visualized to synthesize the details important details relevant to the issues. In particular, phenomena like the Syrian war, the number flights during Thanksgiving in the USA, the controversy of ‘#OscarsSoWhite,’ etc. present such complexity that we can write endless paragraphs and still fail to convince readers. Below are visualizations of some of these important and complex topics - visualizations that are much more persuasive than an essay, and with a tiny fraction of the text.

Many of the case studies mentioned below come from the following articles:

3.2 Geographic Visualizations

Geovisualization or geovisualisation (short for geographic visualization), refers to a set of tools and techniques supporting the analysis of geospatial data through the use of interactive visualization. Like the related fields of scientific visualization and information visualization geovisualization emphasizes knowledge construction over knowledge storage or information transmission.To do this, geovisualization communicates geospatial information in ways that, when combined with human understanding, allow for data exploration and decision-making processes. Source: (contributors 2019 a ) More specifically, Geovisualization is a process that alters geographic information so that we can consume it with our eyes. Its purpose is to capitalize on our affinity for visual things and convert the seemingly random collection of information available to us into a form that can be quickly understood. Many tools can be used for Geographic Visualization, such as Mapbox,Carto,ArcGIS Online and HERE Data Lens. Source: (Gloag, n.d. : Tools & Techniques)

Often, people use maps to visualize data that should not be mapped. Here are some examples of when a map visualization is a good choice.

3.2.1 Spies in the Skies

The map below is from a Buzzfeed article (Aldhous and Seife 2016 ) that shows how common it is for the government to observe people. It was filled with red and blue lines (representing FBI and DHS aircraft, respectively) which illustrate the flight paths of the planes. When planes circle an area more than once, the circles become darker. The circles change by day and time, and individual cities can be typed into a search bar to see the flight patterns over them. The visualization rather creatively looks almost like a hand-drawn map. While presenting an ordinarily uncomfortable topic, this allows individuals to check things for themselves, hopefully providing some peace of mind.

Source: (Kayla Darling 2017 )

New York Flight Patterns

New York Flight Patterns

3.2.2 Two Centuries of U.S. Immigration

This interactive map from (Galka 2016 ) shows the rate of immigration into the U.S. from other countries over the last 200 years in 10-year segments. Each colored dot represents 10,000 people coming from the specified country. Countries then light up when they have one of the highest rates of migration. A tracker on the left indicates what countries sent the most people to the U.S. at what times.

This is a good visualization because it is engaging and easy to read and interpret. The movement of the dots draws the reader’s attention while the brightly lit countries make it easy to pick out the highest total migrations. The bright colors and dark background help the information stand out. This map is a bit simple, but effective.

Source: (Kayla Darling 2017 ) .

US Immigration

US Immigration

3.2.3 Uber: Crafting Data-Driven Maps

Map visualization is essential for companies like Uber that need to track metrics using geo-space points. In this article, the designer from Uber talks about the challenges of designing such visualizations and the possible solutions (Klimczak 2016 ) .

To tackle these problems, Uber started by defining base map themes by optimizing detail, color, and typography. Based on that, data layers are added using scatter plots and hex bins, with careful color selection to help their team make decisions. To make it even better, Uber took a further step by adding trip lines (see images below), which became a signature visualization of Uber. Choropleths are also used to help visualize how metrics and values differ across geographic areas. Uber uses US postal codes as geographic boundaries and infuses various datasets to create the color variation.

The visualization in this article is a classic problem of visualizing geographic data. The detailed explanation of the problems and how they are solved can be beneficial for people or startups trying to conceptualize and make appropriate visualizations that support the decision-making process.

Uber Route Maps

Uber Route Maps

Source: (Klimczak 2016 )

3.3 Demographic Comparisons

One common use of visualization is to compare different groups against each other, such as political parties or generations.

3.3.1 Young Voters, Class and Turnout: How Britain Voted in 2017

This article’s goal is to convey the change in party votes in the 2017 UK general election compared to votes in 2015 (Holder, Barr, and Kommenda 2017 ) . The change in party votes was shown with regards to three demographic factors: age, class, and ethnicity. For each factor, there are four graphs (one per political party), each illustrated in the party’s standard color. The change in the percent of votes is shown as an arrow where the arrow’s shaft is the length of the difference from 2015 to 2017 while the x-axis is the demographic factor split into different bins.

This a good visualization because it is straightforward to read and interpret. The color-coding of the arrows and party names makes it easy to pick out the different parties. The index is smartly spread across the visualization to reduce cross-referencing, and color in the graph represents the actual party colors in the campaign. The arrow lengths highlight just how significant of a change happened. For example, in the Age section, it is easy to see the pattern between the Labour party gaining many voters aged 18 to 44 and the Conservative party gaining voters aged 45 and up.

UK Party Votes by Age

UK Party Votes by Age

Source: (Holder, Barr, and Kommenda 2017 )

3.3.2 U.S. Migration Patterns

The New York Times data team mapped out Americans’ moving patterns from 1900 to present, and the results are fascinating to interact with (Aisch, Gebeloff, and Quealy 2014 ) . We can see where people living in each state were born, and where people are moving to and from. The groupings of the destinations vary based on that state’s trends, preventing unnecessary clutter while still showing detail when vital, as can be seen by the difference between the charts for California and Pennsylvania. When generating interactive charts, one must always assume that the audience will not interact with it. The message of a chart has to be clear enough that anyone just viewing the generic chart can understand.

Overall, this type of chart can work well to visualize movement in data over time, such as with migration. However, it must be done carefully to maintain clarity. Too many categories with colors and crossing lines can make it difficult for a reader to keep track of what the data is saying and it can quickly go from a very graphic visualization to a chaotic mess of lines. The designer does a pretty good job with these visualizations by limiting the number of categories in grouping states by region (West, South, Midwest, etc.). But when introducing many dimenional variables such as Migration from Pennsylvania, the chart can quickly turn convoluted and hard to read which costs the audience. Finally, it is not completely clear why so many crossing lines are necessary for the Pennsylvania chart. The crossing lines, along with the use of the same color for different lines within the same regional categories, can introduce unnecessary complexity.

Migration from California

Migration from California

Migration from Pennsylvania

Migration from Pennsylvania

Source: (Aisch, Gebeloff, and Quealy 2014 )

3.3.3 The American Workday

NPR tapped into American Time Use Survey data to ascertain the share of workers in a wide range of industries who are at work at any given time (Quoctrung Bui 2014 ) . The original question of when Americans work, rather than the number of hours worked, is answered in the graph. The chart overlays the traditional 9 AM-5 PM standard workday as a reference point, helping the audience draw exciting conclusions. Below is a screenshot of the data product; the original graph is more interactive and allows the audience to explore when people are working for different occupations.

visualization case study

Some interesting findings include: 1. Construction workers both start and finish their workday earlier and generally do not work at lunch hours as there is a massive drop at noon.

visualization case study

  • Servers and cooks’ schedule are the opposite of all other occupations with the peak from lunch through the evening.

visualization case study

This data product is an excellent example because the analytic design has been applied to contrast specific occupations to the traditional 9-5 working hours. This is easy to understand and make particular occupations stand out more manageable. The use of color for highlighting the selected occupation in the graph helps to categorize different occupations as well.

3.3.4 How People Like You Spend Their Time

This visualization from (Yau 2016 ) lists several categories such as “personal care” and “work” along one side of a graph with a line illustrating the amount of time the average person in a particular demographic spends on each subject. Entering different parameters at the top, such as changing gender or age, causes the lines to shift to feature that demographic. The simplicity of this visualization helps the information get across and avoids bogging down the statistics. Sometimes, less is more.

visualization case study

3.3.5 Britain’s Diet In Data

This is an excellent example about how to present a significant amount of comprehensive data - distributed across different categories and measured in different metrics - in a simple yet effective manner, while still maintaining interest and aesthetics. The data product attempts to show how the average Briton’s diet has changed over the last four decades for the better (Institute 2016 ) . It does this by displaying simple trend lines that show that more harmful and fatty foods are being consumed less while consumed more healthier and leaner foods. It further breaks down every major food category into tens of its constituent products, and in both the overview and deep-dive versions, provides further levers to massage more meaning out of the data. It also shows how the contribution of different foods to the typical diet has changed over the years. Here, we can toggle the year to see exactly how much of each food was consumed, again with another deep-dive into the constituents of every primary food group.

visualization case study

Such a visualization is ideal for a layman who would want to walk away with an immediate and accurate understanding of the overall dietary changes. It also provides plenty detail on demand for the more discerning viewer who might have more time and inclination to dissect and parse through the graphs. It is difficult to use the same data product to cater to both types of viewers in such an adequate capacity, which is what makes this particular data product so impressive and useful. It satisfies the principles of graphical excellence as stated by Edward Tufte : >“Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.”

Source: (Tufte 1986 )

3.3.6 Selfie City

Selfie City, a detailed multi-component visual exploration of 3,200 selfies from five major cities around the world, offers a close look at the demographics and trends of selfies (Manovich et al. 2014 ) . This project is based on a unique dataset compiled by analyzing tens of thousands of images from each city, both through automatic image analysis and human judgment. The team behind the project collected and filtered the data using Instagram and Mechanical Turk. Rich media visualizations (imageplots) assemble thousands of photos to reveal interesting patterns. It provides a demographic and regional comparison of selfies.

Estimated Age and Gender Distribution

Estimated Age and Gender Distribution

Source: (Manovich et al. 2014 )

3.3.7 Evolving Demographics

Another frequent use is to look at how something changes over time. Time-series data can be shown many ways, and these are some examples.

3.3.7.1 Millennial Generation Diversity

CNNMoney created an interactive chart using U.S. Census Data to show the size and diversity of the millennial generation compared to baby boomers (Kurtz and Yellin 2018 ) . While the article’s main point is that the millennial generation is bigger and more diverse than the baby boomer generation, it also contains information about all of the other living generations. It turns hard numbers into an intriguing story, illustrating the racial makeup of different age groups from 1913 to present.

The author also summarized three key findings from the graph: 1| The most common age in the US is 22 years old. 2| The median age in the US is 37.6 years old. * 3| Among the youngest generation, only 50% of the population is white with the potential of dropping from the biggest race in the US.

Racial Diversity of US Generations

Racial Diversity of US Generations

Source: (Kurtz and Yellin 2018 )

This is an effective graph because while it contains many data points, it makes the overall trends very clear without sacrificing much detail. You can see the drop in some white people and the increasing growth of the other racial categories.

3.3.7.2 How the Recession Reshaped the Economy, in 255 Charts

The first large graph contains 255 lines to show how the number of jobs has changed for every industry in America, using color to highlight the lines and let viewers see the specifics for each industry (Ashkenas and Parlapiano 2014 ) . By hovering over a line, viewers can get the detailed information of that industry’s job trend. Keeping this extra data hidden until needd will make it easier for readers to absorb the bigger picture from this vast data visualization. Following charts are subsets categorized by job sector and sub-industries. Readers can choose the industry or sector they are interested in and, similar to the first graph, view the more detailed information by hovering over a line.

visualization case study

Source: (Ashkenas and Parlapiano 2014 )

3.3.7.3 An Aging Population: Projected Number of Children and Older Adults

An aging population is always a hot topic in social economics and politics (United States Census Bureau 2018 ) . Here we explore a collection of data visualizations showing the aging population in the U.S. and the world.

visualization case study

Source: (United States Census Bureau 2018 )

This example includes a bar chart and a line graph to demonstrate the aging population compared with the population of children. This visualization allows easy comparison, employs color to differentiate the categories, and highlights the intersection point.

3.3.7.4 From Pyramid to Pillar: A Century of Change, Population of the U.S.

visualization case study

This is a population pyramid . “A population pyramid is a pair of back-to-back histograms for each sex that displays the distribution of a population in all age groups and in gender” (Bureau 2018 b ) . It is good to visualize changes in population distributions (sex, age, year). The shape of a pyramid is also used to represent other characteristics of a population. To illustrate, A pyramid with a very wide base and a narrow top section suggests a population with both high fertility and death rates. It is a useful tool to make sense of census data. (“An Aging Population,” n.d. ) offers an animated pyramid.

Comparison of aging population in US and Japan

Comparison of aging population in US and Japan

Source: (“An Aging Population,” n.d. )

This is an animated and multiple-population pyramid. It used to compare different patterns across countries. One additional benefit for the interactive population pyramid is that it shows the shape changes by year, which is useful for time-series comparison. A similar project with R code is here .

3.3.7.5 Music Timeline

Google’s Music Timeline illustrates a variety of music genres waxing and waning in popularity from 2010 to the present day, based on how many Google Play Music users have an artist or album in their library, and other data such as album release dates (Google 2014 ) . One useful feature of this graph is the reader’s ability to explore one specific genre and its subgenres at a more detailed level, as well as view the general timeline of all music. The drill-down interaction allows for more details without cluttering the overview of the visualization. Embedding the graph with names (e.g., Rock/Pop) makes similar color lines easy to distinguish.

visualization case study

Source: (Google 2014 )

3.4 Visualizing Urban Data for Social Change

(Neira 2016 )

One field in which visualization can have a meaningful social impact is promoting understanding of and generating discussions around cities. With the development of a city, demographic changes, economic, environmental and social problems become important issues. Visualization plays an important role in promoting understanding of how the cities and the societies within them work, debating the problems that cities face, and engaging citizens to work toward their dream cities.

Recently, as part of Habitat III side event , LlactaLAB - Sustainable Cities Research Group, presented a project called Live Infographics. It was an interactive methodology that put citizens and experts opinions about the New Urban Agenda on one platform to help generate a ‘horizontal governance’. The different opinions were materialized with a dynamic map to visualize the generated data. The primary objective of the project is to generate citizen-led data collection and to enable governments to build a better understanding of public sentiment, and then engaging people in the process.

visualization case study

A great Urban Data Visualization ought to have the capacity to start “Sociological Imagination”. It should provoke individuals to consider how their individual choices, issues, struggles, and in general their daily lives, are a extension of society, and how their choices collectively influence public opinion. Another key aspect of these kinds of data visualizations is their ability to make the audience understand how their activities impacts the cities they live in and help them work towards the betterment of the cities.

The following is an example of a visualization that is trying to effect social change. It shows how different states are populated on our way to wealth at the cost of the Environment and the percentage of adults who support the cause by estimating public opinions. Source : (“We Have Poluted Our Way to the Wealth in the Expense of the Environment,” n.d. )

visualization case study

Urbanization and the spread of information technologies transform Cities into huge data pools, that data will play a major role in understanding how city areas have changed and are likely to change in the future. Urban Data Visualization gives us a quick view of the architectural contrast of Urban changes in Cities. (MORPHOCODE 2019 )

This Urban Data Visualization based on the NYC Department of City Planning Data set, the result is a snapshot of Brooklyn’s evolution, revealing how development has rippled across certain neighborhoods while leaving some pockets unchanged for decades, even centuries. The visualization is interactive, the reader can check every block’s name and built year. (MORPHOCODE 2019 )

visualization case study

As urban areas continue to develop, diverse and complex issues evolve along with them. Disparity, isolation, loss of biodiversity and environmental quality, etc. are all important but thorny issues, and finding successful solutions will require uniting strategy producers, academics, designers, and citizens. Visualization, if done right, can help jumpstart important discussions between these diverse groups of people and help solve the issues that emerge as the world becomes more urbanized.

3.5 Animated Data Visualization

Like evolving demographics, these visualizations are demographics that change over time. These, however, are self-animated instead of interactive.

3.5.1 A Day in the Life of Americans

This animated data visualization shows the time people spend on daily activities throughout the day (Nathan Yau 2015 b ) . The plot is simple and easy to interpret, but it also includes a good number of variables including time, activity type, number of people doing each activity, and the order in which activities are done.

One of the plot’s biggest strengths is that by using one dot to represent each person in the study and using animation, we can drill down to the level of an individual and follow him or her throughout the day. The accumulation of dots for each particular activity also gives us an aggregate-level view of the same data, so that we get both individual and aggregate insights.

A drawback of the plot is that it is hard for our eyes to keep track of 1000 simultaneously moving dots. The author of the post addresses this by creating subsequent plots with stationary lines at crucial times of the day. This represents people’s movements from one activity to another without overwhelming the reader.

Overall, this is an engaging, informative, relevant, and fun animated plot that tells a story.

visualization case study

Source: (Nathan Yau 2015 b )

3.5.2 Hans Rosling’s 200 Countries, 200 Years, 4 Minutes

Global health data expert Hans Rosling’s famous statistical documentary “The Joy of Stats” aired on BBC in 2010, but it is still turning heads. In the remarkable segment “200 Countries, 200 Years, 4 Minutes”, Rosling uses augmented reality to explore public health data in 200 countries over 200 years using 120,000 numbers, in just four minutes (Rosling, Hans 2010 ) .

Screenshot from “200 Countries, 200 Years, 4 Minutes”

Screenshot from “200 Countries, 200 Years, 4 Minutes”

Source: (Rosling, Hans 2010 )

What makes this visualization so well-known is its use of animation and narration to highlight different stories within the overall data. While the visualization could have been made as an interactive chart where the audience can select the year, instead it is a video. Rosling’s narration of how various regions have fluctuated over the last two hundred years is necessary for his argument since there is no other description or explanation.

3.6 Dust in the Wind: Visualization and Environmental Problems

Environmental issues can quickly become extremely complex. When dealing with assessments of site, environmental remediation design, monitoring, environmental litigation, the quantity of data involved can quickly become overwhelming. Maintaining and organizing that data and keep a balance is insufficient. Visualization is the only means for condensing and communicating vast quantities of data. Visualization provides an invaluable tool to communicate complex data in a form that makes it intelligible to all parties. There are many case studies on visualization of environment-related issues. Some of them are mentioned below:

3.6.1 Global Carbon Emissions

This data visualization, based on data from the World Resource Institute’s Climate Analysis Indicators Tool and the Intergovernmental Panel on Climate Change, shows how national CO₂ emissions have transformed over the last 150 years and what the future might hold. It also allows the audience to explore emissions by country for a range of different scenarios (World Resources Institute 2014 ) .

visualization case study

Source: (World Resources Institute 2014 )

3.6.2 What’s really warming the world?

This case study begins by clearly explaining necessary background information and the analytic questions it seeks to answer. Next, it analyzes each factor separately using both verbal explanations and dynamic graphics to compare the observed temperature movements, and then categorizes related factors into “natural factors” or “human factors.” After that, it combines all the dynamic graphics into one, which makes the results more accessible and more straightforward to compare. Lastly, the authors provide further detailed explanations of dataset sources to support their results. Overall, this case study is straightforward, easy to understand and informative (Roston and Migliozzi 2015 ) (Crooks 2017 ) .

visualization case study

Source: (Roston and Migliozzi 2015 )

3.6.3 Understanding Plastic pollution using visualization

Plastic pollution is the accumulation of plastic products in the environment that adversely affects wildlife, wildlife habitat, or humans. Human usage of plastic has increased manifolds in last few decades. Since plastic is inexpensive and durable, it has a wide variety of uses in our everyday life. Since the 1950’s, an estimated 6.3 billion tons of plastic has been produced, of which only about 9% is recycled (contributors 2019 b ) .

visualization case study

Plastic has become part of our daily life, and human dependence on plastic has increased over time. The visualization below shows some common plastic products undermining environmental health. (Grün 2016 )

visualization case study

With a share of 26 percent, China may be the largest plastic producer in the world; yet the largest plastic consumer is neighboring Japan. The people living in the island nation have consumption that exceeds that of Africa and the rest of Asia combined.

Donut chart is a modern version of pie-chart which looks cleaner, and embedded visual imagery makes the distribution easy to understand. (Grün 2016 )

Plastic Use: Industrial nations top the charts (Grün 2016 )

visualization case study

This visualization uses a simple line chart to show increasing trends. A positive aspect of this chart is the removal of the vertical grid which creates noise in the visualization when its objective is to show the trend, rather than the numbers.

visualization case study

“Plastic where it shouldn’t be” combines four large-scale plastic marine pollution datasets, each published in a different scientific journal over the last five years, totaling 9,490 surface net tows. It is a symbol map shows the amounts of plastic wastes distribute in oceans. Please note: just because there is no plastic displayed in a certain region does not mean that it isn’t there. The open ocean is vast and pollution research is both time- and cost-intensive. (Moret 2014 )

visualization case study

How long does plastic remain in the ocean? (Grün 2016 )

Overall, this visualization is useful in the following ways:

  • It provides content: those plots serve one of the primary purposes of data visualization - storytelling. It naturally leads the audience to understand the effects of plastic pollution.
  • Effective use of charts: the correct use of different types of plots makes the visualization both effective and exciting.
  • Efficient use of color: this visualization is a good example of color playing an essential role in a data visualization by guiding the reader to grasp the relationships in the data. There is no redundant color, and no primary color is missing.

3.7 Language

3.7.1 green honey.

Language shapes the way we view the world. Different languages may have vastly different ways of describing things—including color.

visualization case study

Source: (Lee 2016 )

3.7.2 Linguistic Concepts

This case study is about the use of linguistic concepts; it discusses how the data is being used and how visual graphics are used to deliver the central insights. It presents an educational tool that integrates computational linguistics resources for use in non-technical undergraduate language science courses. By using the tool in conjunction with case studies, it provides opportunities for students to gain an understanding of linguistic concepts and analysis through the lens of practical problems in feasible ways. (Alm, Meyers, and Prud’hommeaux 2017 ) .

HistoBankVis is a novel visualization system designed for the interactive analysis of complex, multidimensional data to facilitate historical linguistic work (Michael Hund 2015 ) . In this paper, the visualization’s efficacy and power are illustrated utilizing a concrete case study investigating the diachronic interaction of word order and subject case in Icelandic.

Much of what computational linguists(CL) fall back upon to improve natural language processing and model language “understanding” is the structure that has, at best, only an indirect attestation in observable data. The sheer complexity of these structures and the visible patterns on which they are based, however, usually limit their accessibility, often even to the researchers creating or studying them. Traditional statistical graphs and custom-designed data illustrations fill the pages of CL papers, providing insight into linguistic and algorithmic structures, but visual ‘externalizations’ such as these are almost exclusively used in CL for presentation and explanation. There are particular statistical methods, falling under the rubric of “exploratory data analysis,” and visualization techniques just for this purpose are available. However, these are not widely used. These novel data visualization techniques offer the potential for creating new methods that reveal structure and detail in data. Visualization can provide new ways for interacting with large corpora, complex linguistic structures, and can lead to a better understanding of the states of stochastic processes.

3.7.3 State of the Union 2014 Minute by Minute on Twitter

Twitter’s data team assembled an impressive interactive data hub that depicts how Twitter users across the globe reacted to each paragraph of President Obama’s 2014 State of the Union address (Belmonte 2014 ) . You can slice and dice the data by topic hashtag (for example, #budget, #defense, or #education) and state, resulting in a powerful detailed and cluttered visualization. Since the visualization is about the topic density in a specific time frame, maybe it’s a good idea for us to use this kind of format when we encounter the expression of a poisson distribution.

visualization case study

Source: (Belmonte 2014 )

3.8 Political Relationships

3.8.1 connecting the dots behind the election.

This article in the New York Times lists several different candidates and creates compelling visuals that link their campaigns to previous ones (Aisch and Yourish 2015 ) (Kayla Darling 2017 ) . Each visual contains several different sized dots that represent a specific campaign, administration, or other governmental organization related to the candidate’s current campaign, which is then connected by arrows. Hovering over a specific dot highlights the connections between the groups. This visual is a great way to summarize what would otherwise require a long slog through years of information into an easily accessible and viewable format so that voters can figure out where the candidates’ experiences lie.

Clinton 2016 Campaign Staff

Clinton 2016 Campaign Staff

3.8.2 A Guide to Who is Fighting Whom in Syria

One of the charts shown in the link (Crooks 2017 ) , the visualization of ‘A Guide to Who is Fighting Whom in Syria’ is an exciting graphic to study. The visualization and its report can be seen at (Keating and Kirk 2015 ) .

Who is Fighting Whom in Syria

Who is Fighting Whom in Syria

Source: (Keating and Kirk 2015 )

This visualization helps elucidate an extremely complicated topic like the Syrian War. It consists of 3 different emojis in three different colors, with each color and facial expression combination showing the ties and conflicts between the various groups involved in the Syrian War. When you click on each emoji, a small dialogue box pops up that explains the relationships between the various countries and rebel groups involved in the war. This is not only easy to understand but is also pleasing to the eyes.

On the other hand, the inherent complexity of relationships between different groups make it difficult to understand the complete picture. If the list of involved parties could be sorted by simplified “sides” (such as Syrian Government on one end with Syrian Rebels on the other) or ranked by how liked they are, then it may be easier for a trend to emerge at first glance. Also, the table format of the visualization means that the data is duplicated, making it appear even more complicated. Instead, one side of the diagonal divide could be greyed-out to simplify the audience’s experience with this visualization.

Green emoji shows ‘Friendly’ relationship

Green emoji shows ‘Friendly’ relationship

Red emoji shows the ‘Enemies’ relationship

Red emoji shows the ‘Enemies’ relationship

Yellow emoji shows ‘Complicated’ relationship

Yellow emoji shows ‘Complicated’ relationship

3.9 Uncategorized

3.9.1 simpson’s paradox.

The Visualizing Urban Data Idealab (VUDlab) out of the University of California-Berkeley put together this visual representation of data that disproves the claim in a 1973 suit that charged the school with sex discrimination. Though the graduate schools had accepted 44% of male applicants but only 35% of female applicants, researchers later uncovered that if the data were properly pooled, there was a small but statistically significant bias in favor of women. This is called a Simpson’s Paradox.

By “properly pooled,” the investigators meant broken down by the department. For instance, men were more inclined towards science and women towards humanities. When compared to each other, the science departments required more specialized skills while the humanities would accept applicants with a more standard undergrad curriculum, thus creating the Simpson’s Paradox.

Simpson’s Paradox originally from vudlab.com

Simpson’s Paradox originally from vudlab.com

Source: (Lewis Lehe 2013 )

3.9.2 Every Satellite Orbiting Earth

This interactive graph, built using a database from the Union of Concerned Scientists, displays the trajectories of the 1,300 active satellites currently orbiting the Earth. Each satellite is represented by a circular icon, color-coded by country and sized according to launch mass (Yanofsky and Fernholz 2015 ) .

Low Earth Orbit Satellites

Low Earth Orbit Satellites

Source: (Yanofsky and Fernholz 2015 )

Interactive graph have its own specific advantages. It helps bridge the gap between programmers and non-programmers. This plot is a good example why using interactive graph is a good idea: - It provides an intuitive way for anyone to understand the data regardless of their technical knowledge. - It helps to identifying causes and trends more quickly - It tells a consistent story through data - It improves efficiency of representing data

3.9.3 Malaria

The authors of Vizwiz redesigned “The Seasonality of Confirmed Malaria Cases in Zambia Southern Province” by pointing out what works well, what could be improved, and why their new visualization will be better (Andy 2009 ) .

Original visualization of malaria cases

This chart below shows number of malaria cases reported for health facilities and community health workers and a comparison between the two over the years. From this chart we can clearly see that as summer approaches, cases of malaria increase indicating a seasonality. The colors are also distinct from each other.

The original visualization effectively shows the seasonality of malaria cases but is unclear if the two reporting categories are stacked or one behind the other and is rather garish. The creator of the redesign made the seasonality more obvious by combining the reporting categories and explaining the spikes better.

Furthermore, by adding the yearly data split by districts, we can lead to a possible actionable solution to the study of malaria cases in Zambia which is an important objective of visualization. The author has combined the data to find out what the data looks like when combined with health facilities and health workers. And the usage of the color scheme is much more effective than the previous version which makes seasonality more evident.

Redesigned visualization of malaria cases

3.9.4 Is it Better to Rent or Buy?

There are many factors involved in deciding to rent or buy a house which has led to many calculators that are supposed to simplify this decision. This calculator includes several sloping charts, each including a factor that will affect how much you will have to pay, such as the individual cost of your home and your mortgage rates (Bostock, Carter, and Tse 2014 ) . A movable scale along the bottom of each chart allows you to enter different data, such as changing the “cost of rent per month” on the side. This can be useful for price comparison: if you can find a similar house to rent for that much per month or less, it is more cost effective just to rent the home. This visualization is incredibly thorough and a useful tool for homeowners of any age and status.

visualization case study

Source: (Bostock, Carter, and Tse 2014 )

3.9.5 An Interactive Visualization of NYC Street Trees

Using data from NYC Open Data, this interactive visualization shows the variety and quantity of street trees planted across the five New York City boroughs (Zapata 2014 ) . As the reader hovers over a tree or bar segment, the connected sections light up, making it easier for the reader to look at what otherwise could have been a very dense chart.

We can see what some of the familiar and uncommon trees planted in the five boroughs of New York City are. This visualization allows one to see the distribution quickly. One can make inferences based on the distribution, such as trees in the Bronx and Manhattan seem to be distributed more uniformly compared to the other three boroughs. It gives a direct comparison between the five boroughs which could be used to make a compelling decision by the audience.

NYC Street Trees

NYC Street Trees

Source: (Zapata 2014 )

The interactive visualization is an advantage that enables the display, and intuitive understanding of multidimensional data provides a variety of visualization chart types and enables the audience to accomplish traditional data exploration tasks by making charts interactive. Moreover, this visualization provides a good example: it enables the audience to explore on their own and finds exciting facts about NYC street trees.

3.9.6 Adding up the White Oscars Winners

A visualization of all previous winners of the Best Actor/Actress Oscar winners can be seen in an article by Bloomberg (“Adding up the White Oscar Winners” 2016 ) . From the attributes of past Oscars winners, the authors have developed a set of attributes that they believe will continue to be prevalent in future Oscar winners. It is fascinating to see how the article shows the features of the Best Actress, Actor, movies, etc. in a simple and captivating visual.

The visualization is interactive, and we can click on each attribute like ‘Hair Color,’ ‘Eye Color,’ etc. to see the features of the actors and actresses who are likely to win the Oscars. Based on different attributes selected, the visualization changes to give you the data specific to the attributes. For each attribute selected, it gives you a fact about the selected attribute related to the Oscar Winner. For instance, when you select the race, it states “In the entire history of the Oscars all but 8 of the Best Actors and Best Actresses have been white”. Similarly, the visualization also gives information about the different aspects of movies that are more likely to win, like ‘Length,’ ‘Month,’ ‘Budget,’ etc., and also predict about the future nominees who are likely to win Oscar.

Best Actor and Best Actress

Best Actor and Best Actress

Best Picture

Best Picture

Source: (“How to Build an Oscar Winner” 2015 )

3.9.7 Kissmetrics blog: visualization of metrics

Kissmetrics blog is a place where people talk about analytics, marketing, and testing through narratives and visualization of metrics. Metrics are essential in the real world, especially when developing/promoting products. Visualization of metrics is also essential so that stakeholders can monitor performance, identify problems and dive deep into potential issues.

This example from the Kissmetrics blog is about Facebook’s organic reach (Patel 2018 ) . One crucial point discussed in the blog is whether the Facebook’s organic reach is decreasing drastically.

The general trend shows that there is a considerable decline in Facebook’s page organic reach.

visualization case study

The following graphs show that the engagement is increasing; that is, while the quantity of content is decreasing, the quantity is increasing.

visualization case study

Source: (Patel 2018 )

This resonates with what we have learned at class regarding how different perspectives of interpreting data can lead to different conclusions.

3.9.8 Describe Artists with Emoji

Using the data from Spotify, the author listed the ten most distinctive emoji used in the playlists related to favorite artists (Insights 2017 ) . The table being used in this visual is very straightforward to link the artist to the emojis and is very easy to compare among artists. When you hover over the emoji, further information is presented.

visualization case study

Source: (Insights 2017 )

3.9.9 Goldilocks Exoplanets

Using data from the Planetary Habitability Laboratory at the University of Puerto Rico, the interactive graph on Astrobiology plots planetary mass, atmospheric pressure, and temperature to determine what exoplanets might be home, or have been home at one point, to living beings (Tomanio and Gonzalez Veira 2014 ) .

One highlight of the graph is how color has been used. The red dots represent planets that are too hot, the blue dots mean too cold, and the green ones mean just the right temperature. This is very intuitive for people to understand without the necessity to read through the notes. The dots are semi-transparent so the overlapping of planets does not detract from the audience’s ability to read the graph. (VERGANO 2014 )

Additionally, the size of each dot represents the radius of each planet. At first glance, one might assume that most planets are much larger than Eath, but the visualization includes a note explaining that larger planets are easier to find. This is a good example of how much explanation to include in a visualization, not so much that the audience is distracted from the graph but enough that they have the information needed to interpret it.

visualization case study

Source:[Astrobiology]

3.9.10 Washington Wizards’ Shooting Stars

This detailed data visualization demonstrates D.C.’s basketball team’s shooting success during the 2013 season (Lindeman and Gamio 2014 ) . Using statistics released by the NBA, the visualization allows viewers to examine data for each of 15 players. For example, viewers can see how successful each player was at a variety of types of shots from a range of spots on the court, compared to others in the league.

visualization case study

Source: (Lindeman and Gamio 2014 )

Generally this is a data visualization for following reasons because it demonstrates complex infomation in a simple and topic-related format. It highlights fact numbers to tell important information. The use of colr is retrained but efficient. However, it is undefined that what is targeted audience. It can also reduce cognitive overload for lines.

3.9.11 Visualization of big data security: a case study on the KDD99 cup data set

This paper utilized a visualization algorithm together with significant data analysis to gain better insights into the KDD99 dataset:

Abstract Cybersecurity has been thrust into the limelight in the modern technological era because of an array of attacks often bypassing new intrusion detection systems (IDSs). Therefore, deciphering better methods for identifying attack types to train IDSs more effectively has become a field of great interest. Critical cyber-attack insights exist in big data; however, an efficient approach is required to determine strong attack types to train IDSs to become more active in critical areas. Despite the rising growth in IDS research, there is a lack of studies involving big data visualization, which is crucial. The KDD99 dataset has served as a reliable benchmark since 1999; therefore, this dataset was utilized in the experiment. This study utilized a hash algorithm, a weight table, and sampling method to deal with the inherent problems caused by analyzing big data: volume, variety, and velocity. By utilizing a visualization algorithm, the researchers were able to gain insights into the KDD99 dataset with precise identification of “normal” clusters and described distinct clusters of possible attacks.

To read the full paper, please follow the reference link:

(Ruan et al. 2017 )

3.9.12 The Atlas of Sustainable Development Goals 2018 - Data Visualization of World Development

(TEAM 2018 )

This is an exciting source and an excellent visual guide to data and development. It discusses trends, comparisons, and measurement issues using accessible and shareable data visualizations. As the graphs cite below, they are informative and clean:

visualization case study

The data draws on the World Development Indicators- the World Bank’s compilation of internationally comparable statistics about global development and the quality of people’s lives. For each of the SDGs, relevant indicators have been chosen to illustrate important ideas. The Atlas features maps and data visualizations, primarily drawn from World Development Indicators (WDI) - the World Bank’s compilation of internationally comparable statistics about global development and the quality of people’s lives.

The editors have been selected to emphasize on essential issues by experts in the World Bank’s Global Practices. The Atlas aims to reflect the breadth of the Goals themselves and presents national and regional trends and snapshots of progress towards the UN’s seventeen Sustainable Development Goals related to: poverty, hunger, health, education, gender, water, energy, jobs, infrastructure, inequalities, cities, consumption, climate, oceans, the environment, peace, institutions, and partnerships.

Contents of this publication: (Group 2018 a ) . The data is available at (Group 2018 b ) . The code used to generate the majority of figures is available at (Whitby 2018 ) .

3.9.13 Is Beauty Important?

This case study is about this article: https://www.infoworld.com/article/3048315/the-inevitability-of-data-visualization-criticism.html

Andy Cotgreave is the current Senior Technical Evangelist at Tableau. In the above article he defends the use of elaborate visualizations and argues that beauty is a quality worth pursuing when making data visualizations. One visualization that he focuses on is a heat map that shows the effect of introducing vaccines on the number of polio cases in the US made by the Wall Street Journal. This particular visualization received a great deal of attention, and was sent around the internet to demonstrate the positive effects of vaccination. After spending some time on the internet, another author named Randy Olson responded with his own article where he remade the heat map as a simple line graph. Both versions are shown below.

visualization case study

In his article, Cotgreave argues that the heat map was visually striking, and its novelty made him more likely to interact with it. As someone involved in visualizations, he seen hundreds, if not thousands of line graphs, and would’ve likely skipped over the line graph version. Cotgreave doubts that the line version would have won awards, or been virally shared as the heat map was. While Cotgreave acknowledges the readability of the line graph, he ultimately feels that there is a place for visualizations to be beautiful.

The takeaway then, is that the visualization you choose to present should be tailored to your situation. In other words, think of your audience. If you were presenting your visualization to the internet at large, then being beautiful and novel is important. If your visualization becomes viral, then it will advance and promote your message to exponentially more people. On the other hand, if you have a more limited audience, like a team of managers, that wants visualizations that can be read quickly, then the line chart will be more suitable.

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Tomanio, John, and Xaquin Gonzalez Veira. 2014. “Goldilocks Worlds: Just Right for Life?” https://www.nationalgeographic.com/astrobiology/goldilocks-worlds/ .

Tufte, Edward R. 1986. The Visual Display of Quantitative Information . Cheshire, CT, USA: Graphics Press.

United States Census Bureau. 2018. “An Aging Nation: Projected Number of Children and Older Adults.” https://www.census.gov/library/visualizations/2018/comm/historic-first.html .

VERGANO, DAN. 2014. “Kepler Telescope Discovers Most Earth-Like Planet yet.” https://news.nationalgeographic.com/news/2014/04/140417-earth-planet-kepler-habitable-science-nasa/?_ga=2.208654481.2018531223.1556082373-1845695105.1556082373 .

“We Have Poluted Our Way to the Wealth in the Expense of the Environment.” n.d. https://public.tableau.com/shared/6F6TG3KJD?:display_count=yes&:showVizHome=no .

Whitby, Andrew. 2018. “Replication Code for the World Bank Atlas of Sustainable Development Goals 2018.” https://github.com/worldbank/sdgatlas2018 .

World Resources Institute. 2014. “Carbon Emissions: past, present and future - interactive.” https://www.theguardian.com/environment/ng-interactive/2014/dec/01/carbon-emissions-past-present-and-future-interactive .

Yanofsky, David, and Tim Fernholz. 2015. “This is every active satellite orbiting earth.” https://qz.com/296941/interactive-graphic-every-active-satellite-orbiting-earth .

Yau, Nathan. 2016. “How People Like You Spend Their Time.” http://flowingdata.com/2016/12/06/how-people-like-you-spend-their-time .

Zapata, Cristian. 2014. “An Interactive Visualization of NYC Street Trees.” https://www.cloudred.com/labprojects/nyctrees/ .

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Visualizations That Really Work

  • Scott Berinato

visualization case study

Not long ago, the ability to create smart data visualizations (or dataviz) was a nice-to-have skill for design- and data-minded managers. But now it’s a must-have skill for all managers, because it’s often the only way to make sense of the work they do. Decision making increasingly relies on data, which arrives with such overwhelming velocity, and in such volume, that some level of abstraction is crucial. Thanks to the internet and a growing number of affordable tools, visualization is accessible for everyone—but that convenience can lead to charts that are merely adequate or even ineffective.

By answering just two questions, Berinato writes, you can set yourself up to succeed: Is the information conceptual or data-driven? and Am I declaring something or exploring something? He leads readers through a simple process of identifying which of the four types of visualization they might use to achieve their goals most effectively: idea illustration, idea generation, visual discovery, or everyday dataviz.

This article is adapted from the author’s just-published book, Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations.

Know what message you’re trying to communicate before you get down in the weeds.

Idea in Brief

Knowledge workers need greater visual literacy than they used to, because so much data—and so many ideas—are now presented graphically. But few of us have been taught data-visualization skills.

Tools Are Fine…

Inexpensive tools allow anyone to perform simple tasks such as importing spreadsheet data into a bar chart. But that means it’s easy to create terrible charts. Visualization can be so much more: It’s an agile, powerful way to explore ideas and communicate information.

…But Strategy Is Key

Don’t jump straight to execution. Instead, first think about what you’re representing—ideas or data? Then consider your purpose: Do you want to inform, persuade, or explore? The answers will suggest what tools and resources you need.

Not long ago, the ability to create smart data visualizations, or dataviz, was a nice-to-have skill. For the most part, it benefited design- and data-minded managers who made a deliberate decision to invest in acquiring it. That’s changed. Now visual communication is a must-have skill for all managers, because more and more often, it’s the only way to make sense of the work they do.

  • Scott Berinato is a senior editor at Harvard Business Review and the author of Good Charts Workbook: Tips Tools, and Exercises for Making Better Data Visualizations and Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations .

visualization case study

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Data visualization case studies.

Mercedes-Benz logo as part of our dashboard design case study

Mercedes-Benz Case Study

The Datalabs Agency took a collaborative approach injecting a lot of the Mercedes-Benz (or Daimler) brand and updating it to fit data visualization best practices. The icons, fonts, and color palette all got extensive and worthwhile attention.

Department of Transportation prototype design of a traffic management tool design by the Datalabs Agency

Traffic Management, IoT, and XAI Software Design

The Department of Transportation asked the Datalabs Agency to design a traffic management platform for its data. The result: a suite of interface designs showing the complexity of the road system and a way forward to optimize it at a systems level. See the future of transportation design…

User interface design for an interactive data visualization tool for an energy company

Hydro Tasmania Energy Portal

The Datalabs Agency was commissioned by the energy company, Hydro Tasmania, to prototype an asset and resource management tool, utilizing the best practices in UI and data visualization design

The team at Walton Family Foundation reached out to Datalabs seeking assistance with a series of Tableau dashboards,  dashboards to present a series of metrics and KPIs on the environmental program for the foundation's leadership team.

Walton Family Foundation Case Study

The team at Walton Family Foundation reached out to Datalabs seeking assistance with a series of Tableau dashboards, dashboards to present a series of metrics and KPIs on the environmental program for the foundation’s leadership team.

Annual report design for HCF

HCF Annual Report Case Study

A health care fund, HCF, asked the Datalabs Agency to design its Year in Review report and animated data videos, a suite of designs that included a video summary of two important reports.

The fine folks at Michael and Susan Dell Foundation reached out to Datalabs with a unique Power BI design and development challenge. That was to re-design the education reporting system and migrate it from custom software to Power BI.

Dell Foundation Case Study

The fine folks at Michael and Susan Dell Foundation reached out to Datalabs with a unique Power BI design and development challenge. That was to re-design the education reporting system and migrate it from custom software to Power BI.

A long-term client of the Datalabs Agency, Mercedes-Benz in Germany and Singapore trusted us to design and develop their Power BI dashboards, style guides, and BI framework.

Mercedes-Benz Dashboards

A long-term client of the Datalabs Agency, Mercedes-Benz in Germany and Singapore trusted us to design and develop their Power BI dashboards, style guides, and BI framework.

Image of a UPS truck that was used in our data visualization training

UPS Online Workshop

UPS asked the Datalabs Agency to train its staff in the fundamentals of data visualization. Our agency facilitated a series of training workshops using their data and design guidelines to lift their thinking and skills to the next level.

Photo of Our Design Workshop Infographics & Data Visualization

Rabobank Data Visualization Workshop

The Dutch bank, Rabobank, hired us to train its staff in Hong Kong. We tailored our Introduction to Data Visualization & Storytelling Workshop to include agriculture data, Power BI design, and collaborative exercises.

Tableau style guide scatter plot from the Datalabs Agency

Tabcorp Tableau Style Guide Project

Tabcorp approached Datalabs to see if we could help them define a style for their business intelligence platform, Tableau. Here’s a peek inside…

Infographic report image showing a trifold print

ADF Infographics & Animations Case Study

A beautiful suite of infographic reports and animated data videos designed with data-driven graphics, icons, and illustration for our client the Australian Drug Foundation.

Infographic Workshop Team Exercise

Al Jazeera Infographics Workshop Case Study

Two days with Al Jazeera journalists, producers & designers in Doha, Qatar talking about infographics, data, and their process in creating data-driven motion designs for their broadcasts.

Instructions image for an employment data tool showing visualized data and practice UI designs

SEEK Employment Data Microsite Case Study

A case study of SEEK Australia’s Laws of Attraction Interactive Microsite, showcasing employment data from Australia, Hong Kong, Singapore…

Map of Australia for interactive project

Case Study: Rewilding Australia Project Map

With an interactive map now live on their website, Rewilding Australia has increased the amount of interactive media on its site tenfold. Check out the cartographic experience.

The Datalabs Agency was engaged to help Australia's Department of Education provide a clean and simple user interface in which parents and carers of children could estimate the amount of money they may be entitled to receive.

Department of Education and Training Child Care Subsidy Estimator

The Datalabs Agency was engaged to help Australia’s Department of Education provide a clean and simple user interface in which parents and carers of children could estimate the amount of money they may be entitled to receive.

Nestle-Dashboard-Design-Creative-Interface-Datalabs

Case-study: Intranet Dashboard Design for Nestlé

Nestlé’s aim was to develop an easy-to-use, visually engaging experience that would help to make Nestlé employees’ jobs easier, and therefore, more enjoyable. The Datalabs Agency designed and developed a fun Intranet portal in response.

Dashboard Prototype design

Interface Design Case Study

Our client engaged Datalabs to design a best-in-class dashboard and user interface for their frontline staff’s main workstation. Check out the infographic look in this data visualization case study.

The Datalabs Agency was commissioned to turn the list of the University of Melbourne’s partners and connections around the world into an interactive map that would sit on the home page of their site.

University of Melbourne Map Project – A Case Study

The Datalabs Agency was commissioned to turn the list of the University of Melbourne’s partners and connections around the world into an interactive map that would sit on the home page of their site.

Image of department of education calculator

Department of Education & Training Case Study: Interactive Calculator

The Department of Education and Training needed a clean and simple user interface to assist in the communications strategy for the Australian Government’s New Child Care Package. This interactive tool was a hit with parent’s in need of some numbers.

Vic-Uni-Case-study-Dashboard-Infographic-Tableau-Marketing-Education

Case-study: Victoria University Dashboards & Infographic Reports

A case study on a Tableau dashboard, infographic and data design project for the marketing team at Victoria University.

Interactive Data Map

Case Study: Interactive Data Map

We built this interactive map as a use-case for interactive/explorable maps. It’s UI and easy-of-use is a case study of how data visualization can make better sense of geographical data. Certainly better than a table in a spreadsheet!

Interactive Digital MAp

Case study: International Women’s Development Agency Map

Looking for what data visualization can do for your website? Check out this live example of an interactive map developed for International Women’s Development Agency.

User-Journey-Data-Visualisation

Case Study: Monash Health Interactive Timeline Tool

Monash Heath wanted a time-based interactive data visualization to show the pathway of a patient’s journey through the healthcare system. We used Adobe Illustrator, Excel, HTML, JavaScript, and CSS to come up with this digital experience.

Infographic_Case-Study_Medical_Research_Design_Datalabs

Case Study: Medical Research Infographic

Case Study: Medical Research Infographic Who: Association of Australian Medical Research Institutes What: Summary Report Infographic When: August 2016 Why: The team at the Association of Australian Medical Research Institutes

Short Infographic Design

Infographic Case Study

A large Australian and New Zealand food manufacturer engaged Datalabs to visualize a set of survey results undertaken by their human resources department and an external consultancy. The result was this visually engaging infographic.

IDWA Interactive Annual Report Microsite

Case Study: IWDA Annual Report Microsite

Considering going digital with your annual report? Do it! Here’s an example of what interactivity and a non-profit organization’s ‘year in numbers’ looked like after they ditched paper and went digital.

Tableau-Dashboard-Bar-Chart

Pillar Superannuation Tableau Dashboard Report

The aim for this project was to create an interactive dashboard, utilizing Tableau, to convey the data that had been collected over the financial year. Check out this financial firm’s reporting suite.

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Visualisation Case Studies

All the visualisation case studies below were developed by researchers at the DSI and shown on the DO. Visit how to book the DO to see some of the visualisations first hand!

Bioinformatic Analysis of Severe Asthma

visualization case study

Every transaction conducted in the Bitcoin network is recorded permanently and irrevocably in a public database known as the Blockchain.  By visualizing this network of highly associated data in a large scale environment we are able to accelerate algorithmic discovery of anomalous transactional patterns, with obvious applications into areas such as fraud detection.

Real time obseravtory on the different patterns of transactions that occur on the bitcoin network.

It also features some past blocks which contains relevant, unusual activity

If you want to read further about Bitcoin through a Master's student's visit, please click  here . 

Please read the publication  Visualizing Dynamic Bitcoin Transaction Patterns   written by our researchers,  here.

Bit Coin- Visualization Case Study

Chinese Migration

china

Working with collaborators at Zhejiang University, the DSI has had access to data from a sample population of one million people. By employing various data mining and modelling techniques, researchers have been able to visualise the Chinese floating population and urbanisation over the past five years on the Data Observatory.

Results have shown that migrants to Henan have been relatively young and well educated, often from wealthy provinces like Zhejiang. After mining deeper into the data, our results indicated that more than half of these people were involved in new business start-ups, and the income of these businesses grows much faster than other cities like Beijing.

From analysing news concerning Henan over the past five years, we found that prominent terms relating to the migration to Henan Province were ‘high speed railways’, ‘business start-up policy’, ‘urbanisation’ and ‘rising strategy of central China’. It appears that the principle reasons for the young and highly-educated migrating to Henan are accessibility, business start-up oriented policies and rapid urbanisation. In turn, this has led to the province benefiting from a young and educated workforce.

The visualisation allows the presentation of this research in a format which can be easily interrogated by researchers, and communicated to non-experts. 

MAPS: Interactive Maps

maps

Interactive satellite maps, with the possibility of adding geolcated information on top of it. 

We usually show London, frequent bike paths and Imperial campuses.

This brings maps to life in the DO, getting to see which routes are faster and getting to see the areas we know from a different perspective. 

People Flow

PF

Visualisation that shows how employees in a bank moved between different departments within the company through several years.  Data comprises biweekly HR record. 

Personalised Medicine

personalized

This demonstration presents the open-source data management and analysis system we have been developing for future personalised medicine. The system has been used widely by numerous institutions in the biomedical research and pharmaceutical industries.

The volume, complexity and heterogeneity of data generated from biomedical research require a knowledge management infrastructure which can provide effective data sharing, integration, standardisation and analysis of biomedical data.In the DSI we have been developing an open-source data management platform to support large-scale data management and complex analytical tasks for personalised medicine in clinical applications.

The data shown in this demonstration is from the Innovative Medicines Initiative (IMI) ‘Unbiased Biomarkers in the Prediction of Disease’ (U-BIOPRED) project, which contains samples and medical information from hundreds of adults and children with severe asthma. We have been working with U-BIOPRED to create a system in which the diverse data sets can be compared in an unbiased way – deploying cutting edge analytical techniques to identify different sub-types of severe asthma. The system can select a specific patient cohort based on the chosen clinical parameters, and analyse the genetic and genomic data of the patient cohort to identify the set of genes which are most likely to cause asthma. The sequences of these genes can be further analysed and the molecular interactions among these genes in the cell can be explored in the system. The findings are expected to provide novel insights into the underlying mechanisms of asthma for each patient.

Shanghai Metro

SM

Study that shows the pulse of the Shanghai Metro in China during a day, depicting the majority of its stations. Taking data from how many people were coming in and out from the stations, they were able to visualize the pulse or flow at stations throughout the day.  It also comprises a proof of concept of what is possible if a simulation model is created

Sharing Economy

se

Longitudinal study of how Sharing Economy (Uber, Airbnb, etc..) has risen in the last few years in the UK.n It includes a detailed study on the demographics of the participants, together with a timeline of events leading to it.

Telematics from Smartphone Data

wejo

GPS data in our mobile phones are a great source of information for insurance companies. The aim of the 'Telematics from Smartphone Data' project is to  enable car manufacturers, insurers and service providers to deliver an enriched driving experience that creates loyalty and unlocks the value in vehicle. With the help of the DSI, t he visualisation presented in the DO shows three user cases of how those data can be used for f raud detection, c rash forensic, r isk assesment and more. 

Trump vs Clinton: US Presidential Election Speeches

Were contents of the speeches of Trump and Clinton during their campaigns any different?

campaign

We analysed the content of Mr. Trump's and Mrs. Clinton's speeches in the lead up to the US election to see which topics the presidential candidates touched on the most.

This analysis allowed us to create a semantic fingerprint of both candidates and their topics, and to understand what are the topics each candidate talk more about.

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Case Study: Big Data And Visualization

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December 5, 2023 by Izhar Alam 2 Comments

This blog post gives a walkthrough of the Step-By-Step hands-on Case-Study on Big Data and Visualization that We cover in our Azure Data Engineer [DP-203] Training program. To understand more about the certification read our blog Data Engineering on Microsoft Azure.

In our Big Data and Visualization case study, we deploy a web app using Machine Learning (ML) to predict travel delays given flight delay data and weather conditions.

The hands-on steps that we include in our Big Data and Visualization case study are:

  • Step 1: Read the Case study
  • Step 2: Design the solution

Let’s understand the Case Study

Big Data And Visualization Case Study

  • A Travel Company (Eg. Expedia Group) provides concierge services for business travelers. They always looking for ways to differentiate themselves and provide added value to their corporate customers.
  • They want to use predictive analytics to separate themselves in an increasingly crowded market.
  • They proposed a solution to provide flight delay risk assessment to customers.
  • Most of the premium clients often book their travel within a week of departure, and often ask questions like, “ I don’t have to be there until Sunday, so is it better for me to fly out on Wednesday?”
  • So, Travel Company believes an innovative solution is to provide customers an assessment of the risk of encountering flight delays, based on historical trends in weather patterns.
  • They plan to use 30 years of flight delay and weather data . They plan to use this data to predict the likelihood of flight delays to help customers plan their trips.
  • REST API calls to a third-party service will be used to retrieve current weather forecasts.
  • Travel company plans to pilot this solution internally, whereby the small population of customer support who service the company’s premium tier of business travelers would begin using the solution and offering it as a supplementary data point for travel optimization.

customer-situation

Also Check:  Our blog post on Azure Delta Lake . Click here

Customer Requirements

  • Travel Company wants to modernize their analytics platform, without sacrificing their ability to query data using SQL.
  • They are looking for a way that allows them to store all of their data in Azure, including the raw source data and the cleansed data from which they query for production purposes.
  • They want to understand how they will load their large quantity of historical data into Azure. The data is currently stored on-premises.
  • They required the ability to query the present weather forecast and use it as input to their flight delay predictions.
  • They desire a proof-of-concept ML model that takes as input their historical data on flight delays and weather conditions in order to determine whether a flight is likely to be delayed or not.
  • Need web-based visualizations of the flight delay predictions.

common-scenario-blog-img

Image ref: Microsoft

Also Check Data Science VS Data Analytics , to know the major differences between them.

Design The Solution For Big Data And Visualization

  • Historical data being copied into Azure blob storage utilizing Azure Data Factory.
  • Historical data explored and prepared using Spark SQL on Azure Databricks.
  • Azure ML model created and implemented into a published Predictive Web Service for the web app to query
  • Batch ML scoring handled via Azure Data Factory. Data are written back to blob storage, for querying via Spark SQL. Data are also written to Azure SQL Database for access from Power BI
  • Map visualizations are provided via an embedded Power BI report.
  • Weather forecast data is provided through a third-party API, such as OpenWeather.
  • Batch-scored predictions are stored in Azure SQL Database , which operates as the serving layer for Power BI reports.
  • Azure Key Vault is used as a secret store to centrally manage and securely provide access to secrets, such as connection strings and application keys, to Azure Databricks notebooks and other services, such as Azure Data Factory and the Web App.
  • Azure Monitor provides centralized monitoring and logging of all Azure components of the solution.

high-level-overview-blog-img

Source- Microsoft

1) Data Loading

Loading historical flight and weather data from their on-premises data store into Azure should be performed using Azure Data Factory (ADF).

data-loading

Also Check:  Our blog post on DP-203 . Click here

2) Data Preparation

We will use Azure Databricks to prepare their data using SQL using Spark SQL to query files that live on any number of data sources such as Azure Blob Storage.

historical-data-preparation

3) Machine Learning Model

The model will first be built and trained within an Azure Databricks notebook. We can use the programming language of our choice (Python, Scala, R, etc.) as well as Spark SQL to featurize and fit the data into the chosen machine learning algorithm. ML libraries such as Spark MLlib or SciKit-Learn can be used within the notebook to simplify things. Once the model is trained and tested with a sufficient amount of historical data, then the model can be exported for deployment to a web service. The model can also continue to be used within Azure Databricks for batch scoring.

ml-model-creation

4) Operationalizing Machine Learning

We will use the Azure Machine Learning service and the Azure Machine Learning SDK to register the model in the Azure ML’smodel registry and automatically deploy the model to an Azure Kubernetes Service (AKS) cluster. This creates a web service that can be invoked by any REST client, and the cluster can scale to meet demand as needed. This deployed web service takes the flight information and weather conditions as input and returns feedback with the classification.

operationalizing-ml-blog-img

5) Visualization And Reporting

Minor changes, such as a change to the data types of a column in the model, can be accomplished using the Query Editor part of the Power BI Desktop application. We will then upload this file to the Power BI service. Access to these reports can be secured to only their internal customer service agents by utilizing the Power BI service. We will then create a Content Pack that contains only the desired dashboards, reports, and datasets and restrict access to those groups in Azure Active Directory to which the customer service agents belong.

visualizing-bulk-delay-predictions

We will be covering this Hands-on Case Study: Big Data and Visualization created by Microsoft Cloud Workshop in our Microsoft Azure Data Engineer Certification [DP-200 & DP-201] Training program.

Related/References

  • Microsoft Certified Azure Data Engineer Associate | DP 203 | Step By Step Activity Guides (Hands-On Labs)
  • Exam DP-203: Data Engineering on Microsoft Azure
  • Azure Data Lake For Beginners: All you Need To Know
  • Batch Processing Vs Stream Processing: All you Need To Know
  • Introduction to Big Data and Big Data Architectures

Next Task For You

In our  Azure Data Engineer  training program, we will cover 28 Hands-On Labs.  If you want to begin your journey towards becoming a  Microsoft Certified: Azure Data Engineer Associate by checking out our  FREE CLASS .

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Thanks and Regards Rahul Dangayach Team K21 Academy

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visualization case study

Data Visualization in Education: 14 Case Studies and Statistics

The human brain possesses an innate ability to establish meaningful connections between visual objects, facilitating swift and effortless comprehension. In light of this, data visualization emerges as a potent tool for expeditious and effective learning. Research shows that data visualization often provides superior learning outcomes when compared with traditional text-based or verbal approaches.

By transforming textual data into visually stimulating resources, data visualization streamlines the learning process, empowering learners with a deeper understanding of complex concepts.

With the potential to revolutionize the realms of comprehension, learning, and assessment in online learning, data visualization warrants attention. In this regard, we shall explore several compelling case studies and research findings that substantiate this claim with empirical evidence.

14 Case Studies, Examples and Statistics about Data Visualization in Education

1. student retained 65% of visual information, compared with 10-20% of written or spoken information.

A study found that a student was able to retain 80% of the visual information after 3 hours and 65% after 3 days but was only able to remember 25-72% of the verbal or written information after 3 hours and 10-20% after 3 days.

2. Illustrated text is 83% more effective than text alone

A complimentary study to the one above found that illustrated texts are 9% more effective when tested for immediate comprehension and 83% more effective when the tests were conducted after a delay.

3. Visuals improve learning by up to 400% against text-based elearning

A 2014 study on the impact of visualization found that visualization has a much greater impact on a learner’s understanding compared to pure text content. It helps to understand complex patterns, improve comprehension, and learning by up to 400% .

3D Data Visualization

4. Our brain transmits 90% of the information in visual form

According to MIT, our brain can view images lasting less than 13 milliseconds , our eyes register more than 36,000 visual messages per hour, and 90% of the information our brain transmits is in the form of visuals.

5. Our brain can process visual information 60,000x times faster

Findings of a study by the University of Minnesota state that the human brain is capable of processing visual information 60,000x times faster than text.

6. 70% of teachers use video during lessons multiple times per week

A 2018 Boclips survey of teachers across the globe revealed that 70% of the teachers were using video in classroom sessions multiple times during the week.

7. 93% of institutions indicate that video use increases student satisfaction levels

The Annual State of Video in Education Report 2016 conducted a survey on 1,500 respondents from across the globe.

The survey revealed that 93% of the institutions showed that video tools have a positive impact on student learning and satisfaction, and 88% felt it led to increased achievement levels for students.

8. Visual aids are 43% more effective at persuading audiences

A University of Minnesota study found that when presenters used visual aids, their presentation was 43% more effective to persuade audiences to take a desired course of action.

9. Visual language is more impactful for groups to reach consensus

A study found that when groups used visual language, they were able to reach a consensus 21% more often than groups that did not use visuals.

Other findings from this survey revealed that visual language produces 22% higher results in 13% less time.

Spatial 3D Data

10. 29% increase in believability quotient for scientific facts presented with graphs

A study conducted at Cornell University found that when a scientific claim was presented with numbers or in pure words 68% of the people believed it.

But when the claim was accompanied by a simple graph, the number rose to 97%.

11. Visuals aids assist in quick decision-making in e-learning

A Stanford study was conducted with 110 engineering students and they were asked to view design presentation slides.

64% of participants made an immediate decision following presentations that used an overview map as a data visualization tool. The essay and multiple choice responses were used to assess learning outcomes, and the visual presentation was found to be more effective in facilitating comprehension and learning. The study also found that the benefits of the assertion-evidence slides persisted over time.

12. Written plus visual information is 70% more memorable

The findings of a study revealed that written information, when combined with visual information and actions, was 70% more memorable than text-alone.

13. Visual language improves problem solving by 19%

By incorporating visual language tools such as maps, icons, and storyboards, managers can improve communication, resulting in faster responsiveness, shorter meetings, and increased ability to reach consensus. According to research , the use of visual language improves problem-solving effectiveness by 19%, produces 22% higher results in 13% less time, and increases the persuasiveness of presenters by 43%. In conclusion, the inclusion of visual language tools in change programs is essential in facilitating faster and more effective change implementation.

14. 16% increase of audience persuasion with visual tools

The Wharton School of Business conducted a study that found that when a verbal-only presentation was used to convince the audience only 50% were in favor. However, when the presentation was supplemented with visuals the numbers rose to 2/3rds .

What does data visualization hold for metaverse-based learning platforms?

Interactive educational tools and 3D metaverse learning platforms offer an opportunity for users to visually engage with data, which can lead to better decision-making.

The convergence of emerging technologies such as AI and XR has significantly increased the capability to generate visual tools like pictures and illustrations.

Platforms like Axon Park can harness these tools to facilitate learning, better comprehend and interact with data. Data visualization can also create equal learning opportunities for all students by improving their visual senses, ultimately enhancing the learning experience.

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Visualization Techniques in Healthcare Applications: A Narrative Review

Nehad a abudiyab.

1 Health Informatics, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, SAU

2 Researcher, King Abdullah International Medical Research Center, Riyadh, SAU

Abdullah T Alanazi

3 Researcher, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, SAU

4 Health Sciences, King Abdullah International Medical Research Center, Riyadh, SAU

Nowadays, healthcare management systems are adopting various techniques that facilitate the achievement of the goals of evidence-based medical practice. This review explores different visualization techniques and their importance in healthcare contexts. We performed a thorough search on databases such as the SLD portal, PubMed, and Google Scholar to obtain relevant studies. We selected recent articles published between 2018 and 2021 on visualization techniques in healthcare. The field of healthcare generates massive volumes of data that require visualization techniques to make them easily comprehensible and to guide their efficient presentation. Visualization in healthcare involves the effective presentation of information through graphics, images, and videos. Big data systems handle a massive amount of information and require visualization techniques to present it in a comprehensible manner. The significance of visualization techniques in healthcare is not confined to healthcare practitioners and healthcare management but encompasses all the stakeholders; patients can benefit from the visualization of his/her data for a better understanding of their condition. In short, visualization techniques have demonstrated their benefits in the healthcare sector and can be extended to the payer and the patient. They have also had a positive impact on the quality of the healthcare provided as well as patient safety.

Introduction and background

Data visualization in healthcare sectors relies on sophisticated modern technology that enables professionals from various fields to demonstrate their work and present information efficiently. Visualization techniques assist healthcare providers in understanding the trends that have occurred in the past as well as those in the present and in predicting and anticipating future trends and directions. Generally, data visualization involves representing data and information in various forms, such as graphs, charts, diagrams, and pictures [ 1 ]. These visualization techniques can provide healthcare providers with an easy way to identify and understand data trends, outliers, and patterns [ 2 ]. Visualization techniques have been essential in various healthcare sectors, especially in terms of supporting providers in making important clinical decisions regarding patient and community health. Through various visualization techniques, the healthcare organization can synthesize raw data into graphs and then present it in charts to enable the prompt interpretation of the trends and patterns [ 3 ].

This review aims to explore the different visualization techniques in healthcare, identify the benefits they bring to the field, and provide future directions for visualization-related studies.

This literature review provides a descriptive analysis of the application of visualization techniques in healthcare settings. The review criteria focus on incorporating the available studies in the review context and identifying recent research on visualization techniques in healthcare. The selected articles were obtained from various databases (SLD portal, PubMed, and Google Scholar).

The information about applications of visualization techniques in healthcare sectors is derived from data analysis and presentation. The most viable techniques are employed in the contemporary aspects of data visualization. Statistical analysis is complex to present via data visualization. Hence, it is accomplished through the use of interactive visualization. According to Gartner (2021), interactive visualization can be defined as manipulating graphical information via brightness, color, motion, and shape to elevate the meaning of the presented data [ 4 ]. Distinctly, the core objective of interactive and data visualization is to present and display the information in a way that the stakeholders will be able to interpret the data and increase their knowledge, thereby directly improving the service quality. In this context, many researchers have explored visualization techniques in healthcare sectors.

Historical Context of Data Visualization in Healthcare

One study discussed the application of data visualization in healthcare sectors in the context of what the author calls the Florence effect [ 5 ]. According to this study, the healthcare sector requires using the information in a potent way that propagates efficiency, promoting evidence-based practice [ 5 ]. The implication is that incorporating visualization techniques in healthcare sectors has enabled them to achieve various goals of evidence-based practice. Furthermore, the healthcare sector has established a platform that utilizes data visualization to interpret and assimilate complex healthcare data [ 5 ]. The researcher established the historical context of data visualization by referring to the efforts of Florence Nightingale in the 19th century [ 5 ]. Florence Nightingale was a military nurse who took care of injured British soldiers. Based on her daily treatment of injured soldiers, she accumulated sufficient patient information that could be used to help reduce the mortality of the other wounded soldiers. However, due to patient confidentiality and the strict rules regarding the disclosure of patient information, she designed a statistical representation through pie charts to present data that could help reduce mortality among military personnel. Later, it was discovered that statistical presentation made accessing and interpreting patient information and outcomes easier [ 5 ]. This study is crucial as it provides the historical context regarding the integration of data visualization in healthcare sectors and its importance in monitoring and evaluating healthcare indices.

Types of Data Visualization Techniques

According to the study by Narayan et al. in 2021, accumulating a large volume of healthcare data makes the big data concept very common in the healthcare sectors, considering the aspects of volume, velocity, variety, and veracity of the data [ 6 ]. Visualization techniques make big data less complex and easy to interpret, even for non-healthcare providers. The healthcare sectors need to have tools to develop visualization. Many tools use data visualization techniques, such as pivot tables and charts. Furthermore, different visualization tools are available for those with technical and non-technical backgrounds. For example, Microsoft Excel provides a great visualization tool for healthcare providers with little or no knowledge of technical aspects.

Another example is statistical software such as IBM SPSS and JASP. Statistical software provides interactive visualization systems that can be used by expert providers. These visualization tools can be used in public disease surveillance [ 6 ]. For efficient and prompt healthcare data visualization, it is essential to consider publicizing the information to the stakeholders via various platforms. In public community healthcare, sharing data and integrating visual information into one universal platform is beneficial and necessary. Several types of platforms are available for this purpose, including cloud-based platforms. Moreover, cloud-based platforms such as ParaView and Gephi enable the provider to generate and host the graphics. Furthermore, these platforms could facilitate scientific reproducibility by matching the scientific figures to their underlying data and promoting discussion among collaborators [ 6 ].

Process of Healthcare Data Visualization

Most of the time, data analysis in healthcare sectors incorporates control checks to maintain visualized data accuracy. Electronic health systems are rich in raw data that can be subject to analysis. Analytics data are fed into a learning machine, artificial intelligence tools, and other analysis tools [ 7 ]. These tools provide a visual presentation of healthcare data regarding different aspects, including disease prevalence, patient age that is associated with the most prevalence, and other factors related to the disease. After the analysis, the visual data can be contrasted with other data collected before, and the same analysis and visualization techniques can be applied to them. Also, this effort to contrast the data enables healthcare providers to easily identify the trends and the changes in different aspects that have occurred over a certain period [ 8 ].

Implementation of Data Visualization in Healthcare

The main objective of data visualization in healthcare sectors is to simplify complex data to make them user-friendly so that healthcare providers can easily interpret them.

Interactive Dashboard

According to Pestana et al., dashboards and data analysis tools are usually built into the healthcare systems' existing software [ 9 ]. Usually, the dashboards help with combining several interactive reports. The dashboard is usually classified into three main types: the active type, which usually shows real-time data in healthcare organizations; the strategic type, which displays trends over time; and the analytical type, which presents advanced analytics. An example of data visualization through a dashboard in the Ministry of Health in Saudi Arabia is illustrated in Figure ​ Figure1. 1 . The image shows the dashboard used for analyzing COVID-19 prevalence in Saudi Arabia

An external file that holds a picture, illustration, etc.
Object name is cureus-0014-00000031355-i01.jpg

COVID-19: coronavirus disease 2019

Advantages of Visualization Techniques in Healthcare Implementing and adopting different visualization techniques in healthcare sectors is vital in enhancing the overall healthcare provision by healthcare providers. Several healthcare facilities have implemented various data analysis tools in healthcare sectors, including machine learning and artificial intelligence. There are several benefits to implementing and adopting such techniques in healthcare facilities, and some of these are as follows: I. Improving overall patient care: utilizing health data visualization has positively affected the general provisioning of healthcare. Health data visualization has a significant role in supporting healthcare providers in their clinical decision-making and facilitating their ability to predict the threat and react immediately. Moreover, these threats were discovered by identifying various measures that permit the situation to be analyzed critically within a healthcare organization. Visualizing patient health data in real-time is crucial for improving the quality of care. It enables the healthcare provider to make the necessary clinical decisions based on the patient's situation [ 10 ]. For example, data visualization techniques help in monitoring various healthcare parameters, such as oxygen saturation [ 11 ]. Furthermore, patients' oxygen saturation levels and treatment can be analyzed in real-time to evaluate their responses to the treatment provided. For instance, during the coronavirus disease 2019 (COVID-19) pandemic, many patients developed lung disease due to severe pneumonia infection. Moreover, those patients were suffering from breathing difficulties and a decrease in their oxygen saturation level. Using data visualization techniques that involved displaying data on the monitoring machines was vital in assessing patients' responses to the oxygen level provided through the ventilator machine [ 12 ]. In various inpatient units, real-time data visualization has been used to monitor other patient parameters such as pulse, heart rate, and blood pressure [ 13 ]. Again, these real-time data visualizations significantly helped the providers to detect abnormal parameters and facilitate the intervention needed to improve patient outcomes and overall healthcare quality in the healthcare facility. II. Disease trend and pattern recognition: identifying trends and patterns is another significant advantage of utilizing visualization techniques in healthcare sectors. Determining the trends in healthcare is vital for making decisions regarding healthcare provision. Moreover, one of the critical trends in healthcare sectors is identifying and assessing disease patterns among specific populations. The trend of the disease patterns is an important attribute that should be monitored closely as it provides the necessary indications to investigate the factors causing an elevation in the trend. Data analysis and visual presentation on obesity is a good example of trend and pattern recognition; it acts as an indicator for public and community health. Identifying the factors behind the trends can help raise awareness about modifying the lifestyles of the patients as well as the general public [ 14 ]. III. Data presentation for various audiences: most of the time, healthcare data are more challenging to interpret among providers working in different disciplines compared to individuals with no medical background. Moreover, the primary purpose of data presentation is to simplify complex data so that it can be easily interpreted by any audience regardless of their background. An example of simplifying the data for disease prevalence is displaying it in graphics to the audience [ 1 ]. Also, utilizing the presentation to illustrate some of the factors affecting disease prevalence makes the medical data valuable and easily accessible to any intended audience. IV. Accelerated performance: Another advantage of real-time data visualization in a healthcare organization is accelerating the performance of the healthcare provided through several measures, such as ensuring prompt clinical decision-making in critical situations, which will positively impact patient prognosis and health status. Furthermore, accelerated performance can reduce the inadequacies of the provided care. Hence, accelerated performance can guarantee the overall better performance of healthcare organizations by building a good reputation for efficiency and better patient outcomes [ 2 ]. V. Errors and fraud detection: the most prominent benefit of implementing various data analytics and visualization techniques in healthcare sectors is that it enables the detection of frauds and errors that occur within healthcare organizations, such as errors and frauds in medical billing. According to the report published by Medicare and Medicaid, most of the fraud cases that occur within healthcare facilities are committed by the healthcare providers who work in the healthcare facility. Moreover, fraud cases usually cost healthcare facilities losses amounting to 58.5 to 89.3 billion dollars [ 14 ]. The most prevalent forms of billing fraud in healthcare facilities are duplicate billing, phantom billing, false prescription, and other types of insurance fraud by healthcare providers. Furthermore, clear and proper correlation among the stakeholders, including patients, healthcare payers, and providers regarding claims can enhance the integrity of the billing process and decrease fraudulent schemes [ 15 ]. Implementing data visualization techniques has significantly improved transparency in the healthcare sector.

Benefits of the review

Several advantages can be drawn from this literature review. It can be a source of information for researchers and students seeking knowledge on the same or similarly relevant topics. Moreover, the literature content has been designed in such a way that the audience can easily grasp and comprehend the information. In addition, the review can serve as a platform for identifying the loopholes in the application of visualization techniques in healthcare sectors based on recently published scientific research [ 16 ]. Also, it is essential to highlight that the review discussed several strategies that could help the medical professional improve the care delivered to the patient based on the best practices and applications of visualization techniques. It should be noted that some of the studies selected for this literature review are not directly about visualization techniques in the healthcare sector. We have made an effort to expand the scope of the review and explore the broader implications of the impact of visualization techniques.

Future directions

This review was based on recently published articles. It has certain drawbacks and loopholes that can be addressed by future research to enhance patient outcomes and quality management in healthcare sectors. There are some areas that need further investigation, including the use of interactive visualization techniques and their impact on healthcare sectors. In addition, only some of the studies included dealt with interactive visualization techniques, and studies have yet to analyze the importance of these techniques to healthcare facilities. Another area that needs further investigation is the role of patient-oriented visualization tools and their ability to support patients' health and outcomes [ 17 ]. Further studies need to be conducted by focusing on these topics, which would enhance and improve the knowledge base in terms of utilizing visualization techniques in healthcare sectors.

Limitations of the review

This review fully relied on published articles of the research that other scholars have conducted. Hence, our findings are wholly based on secondary knowledge obtained from peer-reviewed sources. These resources might include some errors that might impact the findings of this review as well.

Conclusions

This review article highlighted the importance of data visualization techniques in healthcare from the standpoint of the following main benefits: improving the healthcare provided, prompt diagnosis of the disease, recognizing the patterns, simplifying the presentation of the healthcare data, accelerating healthcare performance, and improving error detection. The concept of visualization has been one of the significant innovations implemented and adopted in various healthcare facilities. Data visualization has several advantages and hence most healthcare facilities have embraced and implemented it in their day-to-day functioning. Moreover, the benefits of visualization techniques are clearly reflected in their effectiveness in the decision-making process, resulting in improved patient safety and quality of care. In addition, identifying the pattern and disease recognition via the presented data can provide vital knowledge in terms of treatment, diagnosis, and even adopting new policies in healthcare facilities. Also, it enhances the transparency of medical billing by reducing errors and fraud cases in healthcare facilities. Therefore, visualization techniques in healthcare sectors encompass many stakeholders, such as patients, healthcare practitioners, payers, and healthcare management. Also, we discussed the main limitations and challenges faced while conducting this literature review. Lastly, this review provides insight into the potential directions that future efforts on this topic can adopt.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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Developing a real-time detection and visualization of landslide hazards using web-GIS: A case study in Pacet, Mojokerto, East Java, Indonesia

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Listyo Yudha Irawan , Widodo Eko Prasetyo , Melinda Meganagatha , Rosbella Devy , Damar Panoto , Irfan Helmi Pradana , Dicky Arinta; Developing a real-time detection and visualization of landslide hazards using web-GIS: A case study in Pacet, Mojokerto, East Java, Indonesia. AIP Conf. Proc. 21 February 2024; 3001 (1): 050001. https://doi.org/10.1063/5.0184132

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Landslides hazard is increasing in Pacet District, Mojokerto Regency. The increase of landslides hazard in this area occurs during the rainy season. The topography and physiographic conditions of the area are other factors that trigger the hazards. Detection of hazards can be done using a GIS tool. Currently, the development of GIS technology has made it possible to detect landslide hazards in real-time. Therefore, this research is designed to develop a Web-GIS application to detect the landslide hazards in Pacet District, Mojokerto Regency. The Web-GIS method in this study includes acquisition and gathering data, processing data, analyzing data, and visualizing data. Based on the results of data analysis and visualization in WebGIS, it was found that an area of 4,751.12 Ha (44%) of the Pacet area has a very high landslides hazard. From the Web-GIS analysis, several areas are prone to landslide hazards include DesaKemiri, DesaSajen, DesaPacet, DesaPadusan, DesaClaket, DesaCempokolimo, DesaNogosari, DesaCembor, and Forest Areas.

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