Week 07 - 09 | MA Data Visualisation Term 1
Reading Data Feminism (D’Ignazio & Klein, 2020) deepened my understanding of decentralised knowledge and the need to recognise data’s inherent biases. I also drew on Crawford’s (2021) critique of algorithmic systems to reflect on how visual narratives can reinforce existing inequalities. Furthermore, Responsible Design for Digital Systems (Lukoff et al., 2021) introduced the idea of ethical checkpoints throughout the design process, which I found particularly useful for analysing visualization workflows from data collection to user interaction.
This learning phase strengthened my awareness of the social responsibilities embedded in design and offered a critical foundation for developing more inclusive, transparent, and reflexive data visualizations.
Peer Reviews?
Over the weekend, I had an in-depth discussion and learning session with a senior alumna from my programme, who is currently working as a data visualization designer at The Telegraph. She shared her professional experience in designing news graphics, particularly how to efficiently handle complex datasets under tight deadlines and present them in a clear, narrative-driven format for the public. Through this conversation, I gained a deeper understanding of the demands placed on visualization design within the media industry—especially the need to balance accuracy, visual clarity, and ethical responsibility. I also became more aware of the challenge of simplifying data without distorting its meaning, which is a critical skill in this field. This exchange has inspired me to consider news-based data visualization as a potential focus for future research and practice.