Whales are an important part of the oceanic ecosystem. Although historic commercial whale hunting a.k.a. whaling has severely threatened whale populations, whale researchers are looking at historical whaling data to inform current whale status and future conservation efforts. To facilitate this, we worked with experts in aquatic and fishery sciences to create WhaleVis -- an interactive dashboard for the commercial whaling dataset maintained by the International Whaling Commission (IWC). We characterize key analysis tasks among whale researchers for this database, most important of which is inferring spatial distribution of whale populations over time. In addition to facilitating analysis of whale catches based on the spatio-temporal attributes, we use whaling expedition details to plot the search routes of expeditions. We propose a model of the catch data as a graph, where nodes represent catch locations, and edges represent whaling expedition routes. This model facilitates visual estimation of whale search effort and in turn the spatial distribution of whale populations normalized by the search effort -- a well known problem in fisheries research. It further opens up new avenues for graph analysis on the data, including more rigorous computation of spatial distribution of whales normalized by the search effort, and enabling new insight generation. We demonstrate the use of our dashboard through a real life use case.

翻译：鲸类是海洋生态系统的重要组成部分。尽管历史上的商业捕鲸严重威胁鲸群数量，但鲸类研究者正在借助历史捕鲸数据，以了解鲸类现状并指导未来的保护工作。为此，我们与水生及渔业科学专家合作，创建了WhaleVis——一个面向国际捕鲸委员会（IWC）维护的商业捕鲸数据集的交互式仪表盘。我们明确了鲸类研究者对此数据库的关键分析任务，其中最重要的是推断鲸群随时间的空间分布。除了基于时空属性分析捕鲸量，我们还利用捕鲸探险细节绘制了探险队的搜索路线。我们提出将捕鲸数据建模为图结构，其中节点代表捕鲸位置，边代表捕鲸探险路线。该模型有助于可视化估计捕鲸搜索努力量，进而计算经搜索努力量归一化的鲸群空间分布——这是渔业研究中一个著名的难题。此外，该模型为数据的图分析开辟了新途径，包括更严格地计算经搜索努力量归一化的鲸群空间分布，并促进新洞察的产生。我们通过一个真实案例展示了该仪表盘的应用。