2021 Data Viz Competition

Watch the finalists present their winning entries! Watch the Award Ceremony here.

1st Place - Judit Bekker

Fire Walk with Me

2nd Place - Anjushree Shankar

LEPROSY, India's Hidden Plague!

3rd Place - Oana Tudorancea & Nicole Klassen

Women in Government Worldwide

Top 5 Finalists

Click on the tabs to interact with and learn more about each visualization.

About this Entry

Gender equality and female representation is important to both of us. We decided to use this platform to help inform why it’s important to have women leaders in national governments, some of the challenges toward the path to gender parity, and provide resources for those who want to support and learn more about these efforts. Our visualization illustrates the gender parity problem in national governments, the barriers and facilitators to increasing the number of women in government, and how the quality of life for all citizens, especially women, can improve as the number of women in national governments increases. We utilized research from the UN Women and Council on Foreign Relations to select the metrics to tell the story. We pulled data from the World Bank, Alteryx to clean and prep the data, and Tableau to visualize our story. We chose to use data from 2018-2019 because that was the most complete data year in the World Bank for the metrics selected. Because data from the World Bank are mainly percentages, our design focuses around trends in countries that have greater than or less that 30% women, rather than overall averages, to avoid the “average of averages” problem.

Author

Oana Tudorancea and Nicole Klassen

Medium

Tableau Dashboard

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About this Entry

This project has started with one visualization and turned into a full-scale visual storytelling that illustrates activism and political violence against women during the COVID-19 Pandemic Burst. Just think, for every news headline you read, there are hundreds of daily attacks on women that go unreported. What was really happening during COVID-19? Can it be visualized to raise empathy and awareness?Our research is based on the ACLED database {curated data about political activities and violence around the world} and our own tracked stories. It combines different visualizations, like comparison charts, a Sanaky diagram, a cluster dendrogram, and a’ flowers’ map. Each has been designed uniquely, but derived from one visual language of predefined structural elements (as line, shape, color scheme, form, proportion) and principles (as balance, unity, emphasis, white space) to communicate this sensitive data. For example, “Hair me out!” has started from a simple draft of a Sankey diagram, displaying events during the “COVID-19 Pandemic Burst”, but as I worked more with it, the bands of data transformed in my mind into strands of hair belonging to the women’s hidden stories behind that data.

The insights that are revealed demonstrate both uplifting and alarming trends in political protests and violence. The world kept turning and violence did not cease despite this pandemic.

Author

Inbal Rief

Medium

Tableau Dashboard

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About this Entry

My data visualisation is about the gun epidemic in the US with a specific focus on police brutality and how the African American community are disproportionately affected.

Author

Soha Elghany

Medium

Tableau Dashboard

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About this Entry

The visualization I present is about a long forgotten disease LEPROSY- a disease that WHO has declared the world to be free of. However, India still suffers remarkably from leprosy with continuous transmission & has been at the top position more than decades. My main focus is to get an awareness among people about the disease & to enable them to rethink the measures taken to declare the world to be leprosy free.

I focus on a longform dashboard to present my narrative in parts:

Firstly, I present the global overview to emphasize how concentrated the disease is in India and has been for over 20 years. I use the technique of combining map & bump chart to highlight both issues together. My technique can be referred in this blog. I depict the causes for the issue with a multiple layer Sankey funnel graph to visually represent the magnitude of each cause affecting the leprosy transmission. Have utilized scatter plots to highlight the positions India holds. Various reasons rule for different states to have the highest no of cases & I chose to highlight those sections & the reasons for them. You could choose to highlight the leprosy centers to see the distribution of centers along with the density of cases. Lastly, I provide a timeline of measures taken by the government to bring a change.

I want to emphasize that a world is leprosy free not with just ELIMINATION but it has to be with ERADICATION.

Author

Anjushree Shankar

Medium

Tableau Dashboard

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About this Entry

My superpower is never being bored. I have tons of hobbies: I’m a heavy reader, I like riding my bike, cooking, listening to podcasts, but I probably spend the most time watching series. Last year this added up to 645 hours of content, that is 27 whole days. By looking at this number, I was half proud – half ashamed, but let me tell you, it was a damn fine year!

Prepare to be disappointed: I haven’t scraped the data but logged everything I watched each day to a spreadsheet. At the end of the year, I double-checked the Rotten Tomato and IMDB scores if they changed. I was anxious all the time that I might have forgotten to make a note of something that would ruin my whole project, but I managed to follow through. This was one of my hardest ideas to execute, and I’m 100% sure I wouldn’t do it again. If I’d get paid for the hours I spent building the dataset, drinks would be on me. I still have PTSD when I’m watching something and realizing this should have been logged.

For the visualization I used Tableau and Adobe Illustrator with a 4 component layering technique.

Author

Judit Bekkar

Medium

Tableau Dashboard/ Adobe Illustrator

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2020 Data Viz Competition

In 2020, the top 5 finalists presented their entries in the Virtual Data Gallery. Watch the recording here.

1st Place - Kinsey Miller

Coffee Calculator

2nd Place - Kimly Scott

Coming to Australia

3rd Place - Meera Umasankar

Refugee Migration

Top 5 Finalists

Click on the tabs to interact with and learn more about each visualization.

About this Entry

As an avid coffee drinker who cares about her health, I have personally struggled to find an online resource that allows me to quickly and dynamically view the nutritional information associated with my favorite beverages. Using data from public sources that I manually aggregated, I decided to put together a nutritional calculator that would enable the end-user to learn about a variety of beverages (including the ability to modify size and milk options) to inform healthy, caffeinated choices.

The star of the show (and the component that required the most data gathering, scrubbing, formatting, and validating) is the nutritional facts calculator that is cleverly disguised as a nutritional label. This is a dynamic tool that enables customization and empowers the user to explore the data as he or she customizes and compares a large variety of orders.
My hypothesis is that end-users will be most surprised and enlightened by the following:
– ounce per ounce, brewed coffee is more caffeinated than standard espresso beverages (i.e., Americanos, Lattes, Cappuccinos)
– for comparable beverages, those made with blonde-roasted beans are more caffeinated than those made with dark-roasted beans
– while Nonfat Milk serves up the lowest fat content for a 16 ounce Latte, Almond Milk is most favorable when it comes to minimizing sugar and overall calorie content

I hope you find the dashboard informative and transparent. Cheers!

Author

Kinsey Miller

Medium

Tableau Dashboard

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About this Entry

“My visualisation titled ‘Coming to Australia’ looks at refugee resettlement in Australia and how it compares to the rest of the world.Here, I wanted to highlight the global refugee crisis. At the end of 2018, there were over 25 million refugees worldwide, but less than 0.4% of the total refugee population had been resettled in another country. The majority of refugees are fleeing from war, conflict, violence and persecution.

Drawing on my family’s own experience as refugees resettling in Australia, I wanted to show the challenges and struggles refugees face when they flee their home country. Challenges such as language barriers, physical and mental health and racism and discrimination. By sharing my own personal story, I wanted to remind people that behind the data and the numbers, there are real people with real lives who matter.

The visualisation is built in Tableau to allow for interaction and exploration. I wanted the design to be clean and minimalist as to not detract from the important and often sensitive topic.

Author

Kimly Scott

Medium

Tableau Dashboard

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About this Entry

This Data Studio Dashboard explains the impact of ITP (Intelligent Tracking Prevention) on data in Google Analytics. It’s made for online marketeers, who had troubles understanding the subject because of the technical and theoretical aspects to it. The goal of this dashboard was to make ITP clear and accessible for marketeers. To do so, I made three design choices:

1. The dashboard has the look-and-feel of an online article. That’s why the design is very clean and white, and why it combines data with informative paragraphs and infographics.

2. The dashboard is a story. Many dashboards show a lot of data at once without any hierarchy. This makes it hard for the viewer to see what is really important. This dashboard does the opposite: it takes viewers through the subject step-by-step. In the end, they know exactly what ITP might mean for their data.

3. The dashboard is personal. Many articles about ITP remained on a theoretical and general level. With this dashboard I wanted to show directly what ITP means for THEIR data. That’s why viewers can select their own Google Analytics data view on top.

Next to the dashboard, I also wrote an actual article that supports and promotes the dashboard. Even today, 2 months after the release of the dashboard, many people still view the dashboard on a daily basis.

Link to article

Author

Marieke Pots

Medium

Data Studio

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About this Entry

The global refugee population reached a record high of 25.9 million in 2018. In this visualisation, users can explore where refugees mostly come from over the past decade and also where they usually seek asylum seeking safety, as a result of war, genocide and persecution. The visualisation also allows the user to explore where refugees resettle to start their new life and how host countries allowed refugees into their countries over the past decade.

Author

Hesham Eissa

Medium

Tableau Dashboard

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About this Entry

The Tableau visualisation here shows the movement of refugees from various countries around the world to the US. The visuals here shows the trend, where the refugees were from, where did they settle in and which religion they belong to. The migration trend as of 2018 is on the decrease because of Trump’s presidency & his resettlement program. Burma ranks the top from where the people migrate. Texas ranks top on welcoming the refugees to their state. And of course, Muslims are not accepted like before due to Trump’s presidency & his rules. The call to action button below on the visualisation navigates to the UN refugees website so that the users can contribute or help the refugees with whatever they can.

Author

Meera Umasankar

Medium

Tableau Dashboard

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2019 Data Viz Competition

1st Place - Kuhu Gupta

The Impatient List

2nd Place - Kimly Scott

How Water Contributes to Gender Inequality

3rd Place - Amanda Phillip Lopes

Women as Leaders

Top 5 Finalists

Click on the tabs to interact with and learn more about each visualization.

The Impatient List

"The Impatient List" is a storytelling piece that calls the general public's attention to patients of the kidney transplant in the United States. Organ transplantation is a highly collaborative task, involving the patient, the donor, hospitals and organizations like OPTN and SRTR. With empathy to those patients, we want our designs to tell a story about those data to the general public. Therefore, to personalize the analysis for users, our design asks the user to imagine of being a kidney patient looking for registering onto the waiting list and enter his/her zip code. Then, each marker shown is the hospital with its transplantation rate and death rate. Then the audience will be presented with the waiting list information of the specific state his or her zip code locates in. During our analysis, we figured out that California and Alabama have long waiting list and more than 19000 people have to wait for a transplant for more than 3 years.

Moreover, the user can see an imbalance between donors and patients. supported by filtering in terms of BMI and blood type and years.  After that, an animated visualization will show how the waiting list length and the donor number has changed from 1995 to 2018. Encoding each pixel as one person, the animation will mimic the change of the waiting list in a year, and present the patients who left and added. We end our visualization with a call to register as a donor.

The tools used are Leaflet.js, WebGL, Bootstrap, D3.js and Scrollama.js

Author

Kuhu Gupta

Medium

Tableau Dashboard

How Water Contributes to Gender Inequality

An estimated 844 million people around the world do not have adequate access to clean water and in most countries, water collection is most often left to the women and girls of the family, impacting their jobs, livelihood and education. The aim of my visualisation was to bring to light the far-reaching impacts the absence of safe drinking water, ample water supply and inadequate sanitation has on women and girls. Something that is not immediately apparent when thinking about this subject at face value.

The visualisation highlights the fact that lack of clean water and adequate sanitation is a gender issue and puts girls and women far behind their male counterparts. In producing this visualisation, I wanted to show the connection between water's contributes to gender inequality and how there can never be equality until everyone, everywhere in the world has ample access to clean water.

The visualisation was built using Tableau. Even though I used a minimal colour palette, the colours were chosen as a story telling device to tie the different section of the viz together. The long form format of the viz was also chosen as a way to tell the whole story in a linear fashion.

Author

Kimly Scott

Medium

Tableau Dashboard

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Round the World with Nellie Bly

Nellie Bly was an American journalist in the late 1800s, who revolutionized journalism. In 1889 she set off on an adventure to travel the world in less than 80 days, documenting her travels along the way. Originally she was turned down the opportunity, because it was thought to be too dangerous of an adventure for a woman. Fortunately, she was able to go and show the world that it could be done! This visualization, created in Tableau, was designed to showcase her journey. It was designed to look like a newspaper article from the late 1800s, which is why it is in black and white. Bly's book Around the World in Seventy-two Days was compiled from the stories she wrote for the New York World. Fortunately, Bly collected data on her journey, so this visualization highlights those points that she collected. This included the places she went, the time she spent at each stop, and the amount of time she spent waiting on delays.

Author

Michelle Maraj

Medium

Tableau Dashboard

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Women as Leaders

My topic for this competition is inspired from the book 'Lean In' by Sheryl Sandberg. While reading her book I realized there are very few women in the leadership roles. I wondered why? So, I researched more into this topic and made this viz with hope to spread awareness and encourage women all over the world to be proactive and take part in leadership roles in all domain.

There are many well known reasons like sexism, discrimination, bias, etc. which hinders a woman's growth. The shocking reason I found out was many women under value themselves and think men are better suited for leadership roles. Women lack the confidence and drive like men do. Also, another major reason is parenting. There is a common believed notion that women cannot have balanced work and family life. Women’s main responsibility is to raise their children. A workaholic woman is often criticized for not spending time with her children/family while this is not true for men.

Purple is a color for symbolizing women. It combines the calm stability of blue and the fierce energy of red representing us women.

Author

Amanda Phillip Lopes

Medium

Tableau Dashboard

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Drunk Driving

This visualization is an infographic style visualization with several interactive features.  If focuses on the grave dangers of drunk driving.  The visualization is inspired by the death of a loved one, who was killed by a drunk driver on the Brent Spence bridge 14 years ago.

Author

Kevin Flerlage

Medium

Tableau Dashboard

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2018 Data Viz Competition

1st Place - Dinushki De Livera

Women of the City

2nd Place - Suneeth Nair

World Happiness

3rd Place - Alisa Noll

Ticketmaster

Top 5 Finalists

Click on the tabs to interact with and learn more about each visualization.

About this Entry

As an avid coffee drinker who cares about her health, I have personally struggled to find an online resource that allows me to quickly and dynamically view the nutritional information associated with my favorite beverages. Using data from public sources that I manually aggregated, I decided to put together a nutritional calculator that would enable the end-user to learn about a variety of beverages (including the ability to modify size and milk options) to inform healthy, caffeinated choices.

The star of the show (and the component that required the most data gathering, scrubbing, formatting, and validating) is the nutritional facts calculator that is cleverly disguised as a nutritional label. This is a dynamic tool that enables customization and empowers the user to explore the data as he or she customizes and compares a large variety of orders.
My hypothesis is that end-users will be most surprised and enlightened by the following:
– ounce per ounce, brewed coffee is more caffeinated than standard espresso beverages (i.e., Americanos, Lattes, Cappuccinos)
– for comparable beverages, those made with blonde-roasted beans are more caffeinated than those made with dark-roasted beans
– while Nonfat Milk serves up the lowest fat content for a 16 ounce Latte, Almond Milk is most favorable when it comes to minimizing sugar and overall calorie content

I hope you find the dashboard informative and transparent. Cheers!

Author

Dinushki De Livera

Medium

Tableau Dashboard

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About this Entry

These visualizations are based on encrypted Ticketmaster data. There were three different documents used each with about 6 MM records. My friend and I set a goal to find an insight around ticket prices.

The first graph was made with Spotfire. It displays how much more users are willing to pay for pre-ordered tickets. The Rock / Pop genre capitalized on this time period. However, although R&B was in higher demand, there was a shorter presale. I therefore recommend that this period begin earlier/ last longer in the future.

The second viz was made with two maps laid on each other from Tableau. This shows, based on the brightest blue color, where high paying customers are being charged low prices. Although not the best news for the consumer, I recommend increasing prices in these areas.

Author

Alisa Noll

Medium

Spotfire/ Tableau Dashboard

About this Entry

This is a group project that I did along with three colleagues for a Data Visualization class. We chose a dataset on world happiness to tell a story on how happy (or sad) the people around the world were. We wanted a compelling story that used multiple interactive visualizations to establish our perspective. With that in view, we designed the visualization's interactive elements to allow the user to explore and/or engage with the analysis.

Author

Suneeth Nair & Team

Medium

Tableau Dashboard

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About this Entry

I created my visualization before the 2017 NCAA Basketball Tournament because I was curious what mixture of seeds made the Final Four every year. I was also curious if the men’s and women’s tournaments followed the same patterns. To answer these questions, I created a Tableau dashboard. I placed the question I wanted the user to be able to answer at the top of the visualization, “how does the composition of the Final Four differ between men’s and women’s college basketball?” I then used callout numbers to allow for a quick way to answer the question. This shows that 55% of women’s Final Four teams are 1 seeds, while only 41% of men’s Final Four seeds are. In order to see if any one school dominated, I used a bar chart to show the number of Final Four appearances as a one seed by university. This chart shows the dominance Connecticut and Tennessee had over women’s basketball while no school was as dominated on the men’s side. Next, I wanted to detail the seed composition for every year of data, 1985-2016. I thought the best way to represent the data was through a modified lollipop chart, with a circle placed at each seed that was represented in a given year. I then sized and colored the circle by the number of teams at that seed. This approach allowed my visualization to show that low seeded women’s teams are much more likely than men’s teams to appear in the Final Four.

Author

Lindsey Poulter

Medium

Tableau Dashboard

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About this Entry

“Traveling with Michelle in 2017” is an interactive Tableau dashboard created to show where I traveled to in 2017. It took about 20 minutes for me to manually create the dataset in excel that showed when and where I traveled, using my work Outlook calendar that tracks all of my flights. As a consultant, I not only get the opportunity to travel for work, but I also have the opportunity to work from home when not traveling at a client. This past year, I spent a lot of time working from home in Columbus, but also working from my hometown in Dallas when I was planning my wedding in June.

You can see from my calendar that earlier in the year I did not travel too frequently – about once a week per month. In mid-September however, I started traveling every week until the end of the year. Based on the map you can see that most of my personal travel time was spent in Dallas planning my wedding, while most of my work travel time was spent in New York where I started one of my largest projects. My Tableau dashboard is interactive as well – on Tableau Public, hovering over the calendar will give a tooltip that describes where I went and why I was there, whether it is for a client or for fun. Clicking on the map will highlight when I went to that location on my calendar.

Author

Michelle Maraj

Medium

Tableau Dashboard

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