An Interactive Multi-Degree Analysis Approach

Over 500 million people make their livelihoods through fishing or fishing-related activities. However, illegal, unreported, and unregulated fishing are major issues that impact marine ecosystems and food security. In order to address these issues, in this paper, we present an interactive web application aimed at aiding NGO FishEye International in identifying illegal fishing patterns from provided graph data. Our web application provides various customized factors, such as link length, node image, and node radius, and also allows the user to filter node type and link type in the legend panel. Our analysis centers on revealing hidden IUU fishing trends by examining the intricate relationships among entities involved in the provided data. The web application employs graph network visualization techniques to illustrate these relationships, incorporating varying degrees of separation for each suspected node. Through this visualization, distinct patterns emerge, highlighting the absence of affiliations with political organizations among entities engaged in suspicious activities, many of whom own their own vessels or movement nodes.