UX & dATA VISUALISATION (2020)
Methods:
Researching, Exploratory Data Analysis, Analysing Graph Types, Data Wrangling, HTML/CSS/plotly.js, Web Design, User Persona, Prototyping, User Testing
Tools:
Microsoft Excel, Adobe Photoshop & Illustrator, Visual Studio Code, Google Slides, Google Spreadsheet, Figma
Team:
Thomas Brettell, Alannah Frankel, Dylan Hensby
Comparing Different Causes of Death Around the World
This was a group project. Using Visual Studio Code, our team collaboratively coded an interactive data visualisation to represent the estimated causes of death for every country between 1990 and 2017, as a percentage. Our information was sourced from Our World In Data, which calculated the data from sources provided by the Global Burden of Disease, World Health Organisation, Global Terrorism Database and Amnesty International.
In the radial graph, each data point represents the weighting of the corresponding cause of death out of the total deaths that occurred in the selected country and year. Ultimately, the visualisation was developed to allow a comparison of causes of death between multiple countries and how these causes of death have changed over time.
Data Wrangling
In the process of grouping 34 types of death into smaller categories, the classifications provided in Our World In Data were cross referenced with additional research to ensure they retained scientific accuracy. For example, in creating the Infectious Diseases, Chronic Diseases and Non-Infectious Diseases categories ‘Bringing Chronic Disease Epidemiology and Infectious Disease Epidemiology Back Together’ consulted that these three groups, although at times interdependent and overlapping, needed to be kept separate due to the nature and circumstances of the diseases .
The Target Audience
Our visualisation allows a curious exploration of the data, enabling students to come to their own findings and conclusions by comparing different countries, isolating data points of interest, or even using the timeline to observe change. The hope is for students to use the visualisation to assist in the exploration of a challenging dataset as Perdana, Rob, & Rohde found that allowing people to process and select multiple visualisations relevant to their current task can improve the results of their decisions (2018). By allowing students access to multiple visualisations of the data, our design can serve as a way to improve their decision making, and educate them about our topic. Using curiosity as their main drive, every user will discover a story in a unique way.
Research
Our design process report documents our process of using design principles, user testing, design methods, and exploratory data analysis to transform a chosen data set into an interactive webpage. We discuss the exploration into the chosen data set, the design methods and decisions involved, as well as the final rationale. Our aim was to create a visualisation that was both engaging and educational for not only our target users – high school and university students – but also a broader audience. This meant designing a dynamic and interactive visualisation that empowered users to ‘explore the data for themselves’ (Murray, 2017).
View the full report
User Testing
In order for our design to tell our story effectively, it needed to control the way the information was consumed (Knaflic, 2018). To ensure this, it was crucial we performed user testing. Once functioning and formatted, a small sample of 8 users were asked to assess and provide feedback on the interface. In a brief five to ten minute session, each user was asked to “explore the page” by thinking-aloud, and to “provide general feedback on how it looks and feels”. This was a crucial step in realising our final design as it revealed key details that needed to be improved and adjusted.
Design & Iterative Process
References
Choi, B. C., Morrison, H., Wong, T., Wu, J., & Yan, Y. P. (2007). Bringing chronic disease epidemiology and infectious disease epidemiology back together. Journal of epidemiology and community health, 61(9), 832. https://doi.org/10.1136/jech.2006.057752
Murray, S. (2017). Interactive data visualization for the web (2nd ed.). O’Reilly Media, Inc, USA.
Our World in Data. (2020). About. Retrieved 23 May 2020, from https://ourworldindata.org/about
Perdana, A., Robb, A., & Rohde, F. (2018). The Role of Interactive Data Visualization to Make Sense of Information. Retrieved 23 May 2020, from https://doi.org/10.3127/ajis.v22i0.1681
Knaflic, C. (2018). Storytelling with Data. [Place of publication not identified]: John Wiley & Sons.