Survey on the Analysis of User Interactions and Visualization Provenance
Survey on the Analysis of User Interactions and Visualization Provenance
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DOI：
10.1111/cgf.14035
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发表时间：
2020-06-01
影响因子：
2.5
通讯作者：
Wenskovitch, John
中科院分区：
文献类型：
--
作者：
Xu, Kai;Ottley, Alvitta;Wenskovitch, John
关于出处相关研究的文献快速增长，涵盖了其理论框架，用例以及捕获，可视化和分析出处数据的技术等方面。因此，越来越需要对现有的奖学金进行识别和分类。这样一种研究格局的组织将提供调查现状的全貌，并确定知识差距或进一步调查的可能途径。在这篇星星中，我们的目标是对数据可视化和可视化分析领域的工作进行全面的调查，重点是分析用户交互和来源数据。我们的调查围绕三个主要问题进行：（1）为什么要分析来源数据，（2）编码什么来源数据以及如何编码，以及（3）如何分析来源数据。最后的讨论提供了基于证据的指导方针，并强调了这一新兴领域未来发展的具体机会。调查和讨论的论文可以在https://provenance-survey.caleydo.org上在线交互式探索。
There is fast-growing literature on provenance-related research, covering aspects such as its theoretical framework, use cases, and techniques for capturing, visualizing, and analyzing provenance data. As a result, there is an increasing need to identify and taxonomize the existing scholarship. Such an organization of the research landscape will provide a complete picture of the current state of inquiry and identify knowledge gaps or possible avenues for further investigation. In this STAR, we aim to produce a comprehensive survey of work in the data visualization and visual analytics field that focus on the analysis of user interaction and provenance data. We structure our survey around three primary questions: (1) WHY analyze provenance data, (2) WHAT provenance data to encode and how to encode it, and (3) HOW to analyze provenance data. A concluding discussion provides evidence-based guidelines and highlights concrete opportunities for future development in this emerging area. The survey and papers discussed can be explored online interactively at https://provenance-survey.caleydo.org.