Visualizing Causes and Effects of California Sea Lion Unusual Mortality Event (UME) Yoon Chung Han* California State University, Fullerton ABSTRACT This paper introduces our project Causes and Effects, which visualizes California sea lion unusual mortality events (UME) to create a new layer of understanding of the situation as an important environmental issue. It examines the causes of and impacts on sea lion UME by controlling multivariate factors that impact sea lions’ health and stranding. Previous visualizations for sea lion mortality only captured temporal data and the relationship between causes and effects using simple graphs. However, sea lion UME results from multiple causes and it requires multivariate visualization to establish clear solutions for future results. The resulting images of our visualization allow users to explore how environmental factors impact the lives and situations of sea lions. Keywords: Data art, multimodal data visualization, California sea lion mortality, interactive art Index Terms: K.6.1 J.5 [Arts and Humanity]: Architecture; I.3.m: [Computer Graphics]: Miscellaneous: H.5.m. [Information interfaces and presentation (e.g., HCI)]. 1 INTRODUCTION Various visualization techniques have depicted cause-effect relationships. The best example is the cause-effect diagram—also called the fishbone or Ishikawa diagram [1]—developed in Japan in the 1940s. The Ishikawa diagram provides a structure through which to understand the relationships between many possible causes of a problem. However, the diagram uses many numbers and lines of text, which prevents examiners from reading data easily, due to its complexity. Furthermore, it has been hard to find aesthetically or artistically meaningful visualizations/sonification indicating cause and effect. A more effective method of visualizing the cause-and-effect relationship is undoubtedly necessary for readers. Praful Surve** California State University, Fullerton Subin Kim*** California State University, Fullerton Josh Cuellar**** California State University, Fullerton * yohan@fullerton.edu ** survepraful@csu.fullerton.edu *** subinkim@csu.fullerton.edu **** joshuacuellar@csu.fullerton.edu Figure 1: Visualizations and a Prototype of the Data-driven artwork “Causes and Effects”