Optimal ski route selection is a challenge based on a multitude of factors, such as the steepness, compass direction, or crowdedness. The personal preferences of every skier towards these factors require individual adaptations, which aggravate this task. Current approaches within this domain do not combine automated routing capabilities with user preferences, missing out on the possibility of integrating domain knowledge in the analysis process. We introduce SkiVis, a visual analytics application to interactively explore ski slopes and provide routing recommendations based on user preferences. In collaboration with ski guides and enthusiasts, we elicited requirements and guidelines for such an application and propose different workflows depending on the skiers' familiarity with the resort. In a case study on the resort of Ski Arlberg, we illustrate how to leverage volunteered geographic information to enable a numerical comparison between slopes. We evaluated our approach through a pair-analytics study and demonstrate how it supports skiers in discovering relevant and preference-based ski routes. Besides the tasks investigated in the study, we derive additional use cases from the interviews that showcase the further potential of SkiVis, and contribute directions for further research opportunities.

翻译：滑雪路线的最优选择是一项基于多重因素的挑战，例如坡度陡峭程度、朝向及拥挤程度。每位滑雪者对上述因素的个性化偏好需要单独调整，进一步加剧了该任务的复杂性。当前该领域的研究手段既未将自动路径规划能力与用户偏好相结合，也未能充分利用领域知识融入分析过程的可能。我们提出SkiVis——一种基于用户偏好进行交互式雪道探索并给予路线推荐的可视分析应用。通过与滑雪向导及爱好者协作，我们梳理了此类应用的需求准则，并针对滑雪者对雪场的热悉程度差异提出相应的工作流模型。在阿尔贝格滑雪场的案例研究中，我们展示了如何利用志愿者地理信息实现雪道间的数值化比较。通过配对分析实验评估，证实该方法能帮助滑雪者发现符合偏好的个性化路线。除实验探究的任务外，我们还从访谈中衍生出SkiVis潜在应用场景，并指出未来研究方向。