Previous Data Viz Winners & Finalists

EVERYTHING  YOU WANTED TO KNOW ABOUT SHERLOCK HOLMES IN CHARTS:  
Sherlock Holmes is one of the most recognizable fictional characters. He  has been a cultural fixture since he first appeared in print and no detective  has been quite as prevalent as Sir Arthur Conan Doyle’s Sherlock  Holmes. From the time I first read the books, my appetite for content based on him  has been undiminished. So, I decided to go back to the stories and search the  data to understand and explain his enduring appeal using charts.  

Here I have designed a dashboard in tableau, it is in the form of an eBook,  with the purpose of each chapter to tell a story, removing the noise from  data and highlighting the useful information. The visualization is a  collection of multiple dashboards connected and to be navigated through the  navigation button – the chapters. You will come across various chart types in this dashboard- ranging from a simple bar chart to a donut chart, from a  treemap to a real map, from a lollipop chart to a coxcomb chart. Hoping these  charts will let you analyze Sherlock Holmes the way Sherlock Holmes would have analyzed you.

"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

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.
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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!