One of the critical elements of impactful research is to convey meaningful implications through effective data visualization. Well-formulated and crafted visualizations should be able to deliver a story that is understandable to audiences across multiple disciplines. Understanding the value of this, Prof. Bruce D. Malamud from the Institute of Hazard, Risk and Resilience of Durham University, UK in collaboration with the University of the Philippines Resilience Institute (UPRI), conducted an interactive workshop on Quantitative and Qualitative Data Visualization on September 20, 2024, at the UPRI Training Room. UPRI staff from various divisions attended the workshop. This initiative is aimed to discuss the different attributes one can practice in visualizing information, show examples and methods of quantitative and qualitative approaches for both physical and social sciences, and provide examples and discuss some issues when visualizing uncertainty.
Setting up the stage, Prof. Malamud began the workshop by assessing the participants’ prior knowledge regarding visualization attributes and qualitative and quantitative data examples. These aspects are prerequisites for selecting appropriate tables and figures to present data effectively.
One of the highlights of the workshop is the qualitative data visualization. Many published articles rely mostly on tables and quotes to present findings, and less attention is given to the use of visual elements. Prof. Malamud introduced visualization techniques for qualitative data, such as bar graphs, word clouds, quotes with metrics or photos, icons with texts or descriptions, and infographics.
Prof. Malamud also stressed the importance of communicating uncertainty in visualization, which is often overlooked in research. He also shared best figure and table formatting practices, drawing from his experience as an executive editor of Natural Hazards and Earth System Sciences. The common issues in submitted articles that should be avoided include figures with unsuitable titles, formats, scales, captions, and units. For tables, this includes unnecessary lines, not high-lightened significant statistics, and incorrect italicization of scientific names.
As a culminating activity, Prof. Malamud reviewed the participants’ submitted samples of data visualization. He focused on the best practices observed and several points for improvement. The workshop concluded with closing remarks from Mr. Richard L. Ybañez, Chief Science Research Specialist of the Education Division of UPRI. In his remarks, he exemplified the potential advancements and integration of artificial intelligence (AI) in data visualization. He expressed the possibility of collaborating with Prof. Malamud regarding other workshops, such as publishing and natural hazard activities and demonstrations.
The workshop offers valuable insights into data visualization and serves as a refresher for the participants. This is very beneficial to UPRI as an institution involved in a wide range of programs, such as research, conferences, and workshops, where data visualization is essential.
