These data visualizations were created in order to give the user a fresh perspective on data they may have seen in tables or simple charts many times before. The data is visualized in a way that is aesthetically appealing while also informative; in its interactive capabilities, the user has the ability to view the same data visualized in multiple ways.
The initial decision of visualizing this data was based on a proto-persona I developed, who is an ocean-liner enthusiast. Lefty has a particular penchant for the Titanic, owing to the fact that she was the subject of the only book he owned as a child, given to him by a pastry chef who worked on the Queen Mary. He read it so many times that he became the neighborhood Titanic expert. He has seen James Cameron’s 1997 adaptation of the story once or twice, but prefers the film A Night to Remember. He refers to his memory bank as a Rolo-dex, and while all of the data has resided there at one time or another, he’s getting old and wants a new way to look at data concerning his passion. While he can rattle off statistics about notable passengers, he’s more interested in the crew, primarily showing people how the crew made up almost half of the entire casualties in the disaster.
After developing this proto-persona, I realized that he appreciates the complexity that can be represented by graphs, and that he would like to be able to show comparisons and see the data organized in a way that is different from the book he cherished as a young man.
I was heavily inspired in the visualization process by Florence Nightingale’s chart of the causes of death in the Crimean War, and by Tableau’s bubble charts. I had also seen some radial bar charts, which to me seemed a more interesting way of showing data as opposed to a standard bar graph.
After analyzing a public domain data set of R.M.S. Titanic’s passenger list, I realized that a list of the crew was not included. It was important to me to include these statistics, as the crew made up a considerable portion of the people on board, and also significantly impacted the percentage of total lives lost in the maritime disaster. I researched and found crew statistics, and included them in the data set.
My initial leanings were to use more imagery and create an infographic (which I eventually did) that also had quantifiable data, but this did not exactly suit the needs of my proto-persona. I searched online for other data visualizations and found a wide variety of them, but they were either very confusing or not particularly interesting to look at.
In the beginning stages of visualizing the data, I found quite a few ways to compare the most basic statistics, so I primarily focused on sex, survival, passengers, crew, and class of passengers.
In attempts to visualize these data with a standard bubble chart, I wanted to be able to compare multiple factors at once, and eventually decided it would be interesting to compare them using the diameters of circles. By doing this, I could put multiple circles inside one larger circle without them overlapping, and show different ratios of a larger set of data. This type of chart was not available to me via any conventional methods, so I had to create each chart “by hand.” This makes for an interactive chart that represents the 2,217 souls on board while making it possible to see how many females in third class survived, or how many male crew members perished. I made an interactive prototype that highlights different aspects of the data while also showing zoomed in versions of certain bubbles with numbers. This way the viewer can compare the bubbles by their diameter and also see the numerical values they represent.
I also created a Rose Chart a la Florence Nightingale, which compared the data in a different way, also helping the viewer to compare the breadth of information while looking at one graphic. The largest “petal” once again represents the 2,217 people on board in a dark blue color. Each smaller overlaid petal denotes passengers, survivors, crew, men, women, ad nauseum as a percentage of the total. The following petals concern survivors, crew, passengers, etc, each with their own corresponding relative data. The final six petals show the passenger classes divided into survived and perished men and women; the first three show them in direct proportion to the previous petals, while the latter three are enlarged 2x in order to compare them more easily.
The radial bar charts are more straightforward. The first bar always takes up 100% of the chart, with each following bar representing a percentage of the first bar. I made 10 different radial bar charts, each comparing different aspects of the data.
I learned from this experience that the many different ways of visualizing data are important in order to accurately portray them. I also learned that sometimes there isn’t a way to portray data in the way one might like, and so creating them step by step is necessary. While the nesting bubble chart is a helpful way to look at comparative data, it can also be made very beautiful, and if beauty can be added to something seen so mundane as data analysis, that’s an added bonus.
Using the Lean UX method served the project well. In the process, I developed empathy for the Proto-Persona, making charts based on his goals and pain points. I researched and analyzed other methods of organizing data, which enabled me to develop the graphing methods I eventually iterated.
Developing a new way to visualize data in the nesting bubble chart, I am very excited at the prospect of continuing to find new data to express in that way. I have begun a new project called Grateful Data, in which I am visualizing various aspects of the Grateful Dead’s live show history.