Problem-driven visualization design of health and pollution big data - Giannella, Julia; Illarramendi, Ximena; Mauro, Renato; Barcellos Oliveira, Lucas; Falconieri, Igor; Esperança, Claudio; Kosminsky, Doris (InfoDesign, 2024)
We present the design of a big data visualization application aimed at investigating the potential relationships between air pollution and perinatal health. We integrated data from singleton pregnancies in Brazil over a seven-year period and records of fine particulate matter (PM2.5) levels. Our methodology combines Design by Immersion and co-design, engaging specialists from various domains in problem-driven visualization design. The interactive visualization allows exploratory queries and comparative analyses based on medical birth certificate data restructured according to estimated conception dates. The collaboration of various domain experts was essential for leveraging complex data for an informed decision-making visualization.