MSc thesis topic: Comparative Evaluation of Data Visualization Methods

Data visualization plays a crucial role in academia by facilitating effective communication, exploration, and interpretation of complex information. To do so effectively, we must understand how to enhanced understanding of complex data. By simplifying complex concepts, research findings can be more accessible to a wider audience, including fellow researchers, policymakers, and the general public. This can also enhance exploration and discovery. However, we must also remain cognizant of how presented data can also influence decision making and misrepresentation of the truth. Overall, data visualization is crucial for effectively communicating research findings, however, the importance of doing so effectively and honestly and the research supporting this is severely lacking.

Objectives and Research questions

• What are the key criteria for evaluating the effectiveness of data visualization methods in conveying information to users?
• Which data visualization methods are most effective in facilitating exploration and discovery of insights within complex datasets?
• What are the strengths and weaknesses of different data visualization methods in conveying uncertainty and variability in the underlying data?
• What are the optimal design principles and best practices for creating effective and accessible data visualizations for different target audiences?
• How can data visualization techniques be combined or integrated to create hybrid visualizations that leverage the strengths of multiple methods?

Literature and information

• Nguyen, V.T., Jung, K. & Gupta, V. Examining data visualization pitfalls in scientific publications. Vis. Comput. Ind. Biomed. Art 4, 27 (2021).

Theme(s): Modelling & visualisation; Empowering & engaging communities