Probe-It! Visualization Support for Provenance

Probe-It! Visualization Support for Provenance
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探测它!

DOI:
10.1007/978-3-540-76856-2_72
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发表时间:
2007
影响因子:
4
通讯作者:
Paulo Pinheiro da Silva
Paulo Pinheiro da Silva
中科院分区:
医学3区
文献类型:
--
作者:
N. D. Rio;Paulo Pinheiro da Silva

文献摘要

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可视化是一种用于促进科学结果(例如大数据集和地图)的理解的技术。出处技术还可以通过提供有关用于得出它们的来源和方法的信息来帮助提高对科学结果的理解和接受。可视化和出处技术虽然很少用于组合,但可能会进一步提高科学家对结果的理解,因为科学家可能能够使用单个工具来查看和评估结果推导过程,包括任何最终或部分结果。在本文中,我们介绍了探测器!:一种可视化工具,用于科学出处信息,使科学家能够将可视化焦点从中间和最终结果转移到来回来回。为了在地图的背景下评估探测器的好处,本文介绍了科学家如何使用该工具来区分质量结果和具有已知缺陷的结果的定量用户研究。该研究表明,只有很小比例的科学家可以在没有知识出处的帮助下使用地图识别缺陷,并且大多数科学家(是否GIS专家,主题专家(即重力数据图专家))都可以识别并解释使用地图以及知识出处可视化的几种地图瑕疵。
Visualization is a technique used to facilitate the understanding of scientific results such as large data sets and maps. Provenance techniques can also aid in increasing the understanding and acceptance of scientific results by providing access to information about the sources and methods which were used to derive them. Visualization and provenance techniques, although rarely used in combination, may further increase scientists' understanding of results since the scientists may be able to use a single tool to see and evaluate result derivation processes including any final or partial result. In this paper we introduce Probe-It!: a visualization tool for scientific provenance information that enables scientists to move the visualization focus from intermediate and final results to provenance back and forth. To evaluate the benefits of Probe-It!, in the context of maps, this paper presents a quantitative user study on how the tool was used by scientists to discriminate between quality results and results with known imperfections. The study demonstrates that only a very small percentage of the scientists tested can identify imperfections using maps without the help of knowledge provenance and that most scientists, whether GIS experts, subject matter experts (i.e., experts on gravity data maps) or not, can identify and explain several kinds of map imperfections when using maps together with knowledge provenance visualization.