Ziman, RoxanneBudich, BeatriceVaudel, MarcGarrison, LauraGarrison, LauraJönsson, Daniel2024-09-172024-09-172024978-3-03868-244-82070-5786https://doi.org/10.2312/vcbm.20241194https://diglib.eg.org/handle/10.2312/vcbm20241194Visual analytics dashboards enable exploration of complex medical and genetic data to uncover underlying patterns and possible relationships between conditions and outcomes. In this interdisciplinary design study, we present a characterization of the domain and expert tasks for the exploratory analysis for a rare maternal disease in the context of the longitudinal Norwegian Mother, Father, and Child (MoBa) Cohort Study. We furthermore present a novel prototype dashboard, developed through an iterative design process and using the Python-based Streamlit App [TTK18] and Vega-Altair [VGH*18] visualization library, to allow domain experts (e.g., bioinformaticians, clinicians, statisticians) to explore possible correlations between women's health during pregnancy and child development outcomes. In conclusion, we reflect on several challenges and research opportunities for not only furthering this approach, but in visualization more broadly for large, complex, and sensitive patient datasets to support clinical research.Attribution 4.0 International LicenseCCS Concepts: Applied computing → Life and medical sciences; Human-centered computing → Visualization design and evaluation methods; Interaction design process and methods; Interface design prototypingApplied computing → Life and medical sciencesHuman centered computing → Visualization design and evaluation methodsInteraction design process and methodsInterface design prototyping10.2312/vcbm.202411945 pages