论文标题
以数据为中心的方法和任务类型学的时间戳记事件序列
A Data-Centric Methodology and Task Typology for Time-Stamped Event Sequences
论文作者
论文摘要
任务的任务抽象和分类结构对于交互式数据分析方法的设计师很有用，该方法是设计目标和评估标准。对于单个数据类型，数据集特异性的分类结构捕获了独特的数据特征，同时可以在应用程序域中推广。很难创建以数据集为中心但域形不足的分类结构，尤其是如果仍然缺少专注数据类型的最佳实践，观察专家是不可行的，并且反思和概括的手段很少。我们在使用时间stamp的事件序列时发现了对方法学支持的需求，该数据类型尚未在可视化研究中进行全面研究。为了解决这一缺点，我们提出了一种方法，使研究人员能够在五个阶段（数据收集，编码，任务分类，任务合成和动作目标（标准）交叉）中抽象任务并构建以数据集为中心的分类结构。我们通过将其应用于时间stamp的事件序列来验证该方法，并提出一种任务类型，该任务类型将三倍作为任务的新颖语言：（1）操作，（2）数据目标和（3）数据标准。我们进一步评估了类型学的描述能力，并具有现实世界中的网络安全案例。
Task abstractions and taxonomic structures for tasks are useful for designers of interactive data analysis approaches, serving as design targets and evaluation criteria alike. For individual data types, dataset-specific taxonomic structures capture unique data characteristics, while being generalizable across application domains. The creation of dataset-centric but domain-agnostic taxonomic structures is difficult, especially if best practices for a focused data type are still missing, observing experts is not feasible, and means for reflection and generalization are scarce. We discovered this need for methodological support when working with time-stamped event sequences, a datatype that has not yet been fully systematically studied in visualization research. To address this shortcoming, we present a methodology that enables researchers to abstract tasks and build dataset-centric taxonomic structures in five phases (data collection, coding, task categorization, task synthesis, and action-target(criterion) crosscut). We validate the methodology by applying it to time-stamped event sequences and present a task typology that uses triples as a novel language of description for tasks: (1) action, (2) data target, and (3) data criterion. We further evaluate the descriptive power of the typology with a real-world case on cybersecurity.
