MultiSegVA：使用可视化分析在多个尺度上分割生物记录时间序列
MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales
摘要：
在多个时间尺度上分割动物的生物记录时间序列是一个重要步骤，需要复杂的技术，仔细的参数化和可能的跨领域的专业知识。然而，缺乏强烈支持这种多尺度分割的视觉交互工具。为了缩小这一差距，我们提出了我们的MultiSegVA平台，用于在多个时间尺度上交互式定义分割技术和参数。MultiSegVA主要为在多个尺度上分割未标记的时间序列提供量身定制的可视化交互方式和可视化分析范式。此外，为了灵活地组合多尺度分割，该平台提供了一种新的可视化查询语言，该语言连接了各种分割技术。为了说明我们的方法，我们提出了一套面向领域的分割技术与运动生态学家合作。我们展示了MultiSegVA在运动生态学的两个真实用例中的适用性和有用性，这些用例与环境感知分割后的行为分析和渐进聚类后的行为分析有关。运动生态学家的专家反馈显示了定制的视觉交互手段和视觉分析范式在分割多尺度数据方面的有效性，使他们能够进行语义上有意义的分析。第三个用例表明，MultiSegVA可推广到其他领域。
英文摘要：
Segmenting biologging time series of animals on multiple temporal scales is an essential step that requires complex techniques with careful parameterization and possibly cross-domain expertise. Yet, there is a lack of visual-interactive tools that strongly support such multi-scale segmentation. To close this gap, we present our MultiSegVA platform for interactively defining segmentation techniques and parameters on multiple temporal scales. MultiSegVA primarily contributes tailored, visual-interactive means and visual analytics paradigms for segmenting unlabeled time series on multiple scales. Further, to flexibly compose the multi-scale segmentation, the platform contributes a new visual query language that links a variety of segmentation techniques. To illustrate our approach, we present a domain-oriented set of segmentation techniques derived in collaboration with movement ecologists. We demonstrate the applicability and usefulness of MultiSegVA in two real-world use cases from movement ecology, related to behavior analysis after environment-aware segmentation, and after progressive clustering. Expert feedback from movement ecologists shows the effectiveness of tailored visual-interactive means and visual analytics paradigms at segmenting multi-scale data, enabling them to perform semantically meaningful analyses. A third use case demonstrates that MultiSegVA is generalizable to other domains.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
