Since I was young, I have loved using doodles and drawings to document the contents of life. Art and design have become an inseparable part of my life. In my undergraduate studies, I chose visual communication design as my focus. During my four years of undergraduate studies, I had the opportunity to engage in and complete my first data visualisation project. In this project, I recorded the occurrences of goosebumps I experienced over several weeks, along with the time and various factors. I enjoy the process of breaking down everyday life details and organising them through data visualisation, and the feeling of analysis. This is also why I chose to further develop my skills in data visualisation on my master's programme.
“Data represents real life. It is a snapshot of the world, in the same way that a picture catches a small moment in time” (Lupi, 2017).
When providing data visualisation services, I need to work with various types of datasets. Initially, I might have a preference for datasets that are more “interesting”, similar to the ones documented by Giorgia Lupi and Stefanie Posavec in the Dear Data project (Lupi & Posavec, 2015). As the course progressed, although my passion for my original interests remained, I began to realise the responsibility of being a practitioner of data visualization design. I discovered that "doing good with data" (Periscopic, no date) was also necessary. Behind the data lay human behavior. As Lupi mentioned, "we are ready to question the impersonality of a merely technical approach to data and to begin designing ways to connect numbers to what they really stand for: knowledge, behaviors, people" (Lupi, 2017). As a data visualisation designer, I should have brought forth the issues represented by the numbers and presented them to the audience, enabling them to understand the various inequalities and crises that existed in the world. Just as Design Justice emphasized, "we see the role of the designer as a facilitator rather than an expert" (Design Justice, 2018). Throughout this process, I should have also used the principles of data feminism to examine my data visualisation work, avoiding biased content such as so-called "objective" expressions or "categories we had taken for granted" (D'Ignazio & Klein, 2016).
*Seek sound project
In this unit of study, my teammates and I completed several projects where we collected data ourselves. This made me realise the importance of fully understanding the data context when participating in the data collection process. In the "Seek Sound" project, we took to the streets and tapped objects to capture their sounds. In the presentation of the project's outcome, we used a more accessible interactive approach to recreate the process of exploration. I believe that this form of presentation allows the audience to better understand our concept of spending more time experiencing the sounds around us and creating our own sound impressions. “How a dataset is collected and the information included-and omitted-directly determines the course of its life. Especially if combined, data can reveal much more than originally intended” (Lupi, 2017). I am often asked by relatives and friends what my course, data visualisation, is all about. When I'm feeling lazy, I would simply tell them, "I make charts." However, in reality, I believe that data visualisation is not just about transforming datasets into charts. It also communicates the stories behind the data through empathy, helping the audience to better understand and engage with the narrative, thus improving not only the efficiency of comprehension but also the emotional connection. In this process, context plays an important role. “Data, if properly contextualized, can be an incredibly powerful tool to write more meaningful and intimate narratives” (Lupi, 2017).
In my ongoing Final Major Project, tentatively titled "Perception of Time," I planed to invite participants to join in the data collection activities. I hope to collect details from their recorded experiences under ethical requirements, to help me create a visual language that can evoke empathy in the audience. In future projects where I am unable to personally participate in data collection, I should strive to fully understand the background knowledge. This will not only contribute to improving the project's communication methods and subject construction but also help me evaluate the project from the perspective of data feminism. Particularly, it aligns with the principle of Considering Context (D'Ignazio & Klein, 2016), emphasising the importance of recognising and understanding the social, cultural, and material contexts in which knowledge and visualisations are produced. This leads to more informed and meaningful design choices.
*BWS workshop project