Untidy Data: The Unreasonable Effectiveness of Tables
Untidy Data: The Unreasonable Effectiveness of Tables
复制标题
数据不整齐：表格的不合理有效性
DOI：
10.1109/tvcg.2021.3114830
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发表时间：
2021
影响因子：
5.2
通讯作者：
Melanie Tory
中科院分区：
文献类型：
--
作者：
L. Bartram;M. Correll;Melanie Tory
处理表格形式的数据通常被认为是意义生成管道中的一个准备和繁琐的步骤；一种为更复杂的可视化和分析工具准备数据的方法。但对许多人来说，电子表格——最基本的表格工具——仍然是他们信息生态系统的重要组成部分，允许他们以更复杂的工具隐藏或抽象的方式与数据交互。对于数据工作者来说尤其如此[61]，他们将数据作为工作的一部分，但不认为自己是专业分析师或数据科学家。我们报告了一项关于这些工人如何与他们的数据互动和推理的定性研究。我们的研究结果表明，在线性分析流程的初始阶段，数据表服务于更广泛的目的，而不仅仅是数据清理：用户希望在整个分析过程中看到并“掌握”底层数据，对其进行重塑和扩展以支持意义构建。它们重新组织、标记、分层细节，并在基础数据的上下文中生成备选项。这些直接交互和人类可读的表表示形式构成了构建数据含义和数据处理方式理解的丰富且重要的认知部分。我们认为交互式表本身就是一个重要的可视化习语；它们提供的直接数据交互为可视化分析提供了丰富的设计空间；与目前可视化分析工具所支持的相比，更灵活的人机交互可以丰富这种意义。
Working with data in table form is usually considered a preparatory and tedious step in the sensemaking pipeline; a way of getting the data ready for more sophisticated visualization and analytical tools. But for many people, spreadsheets – the quintessential table tool – remain a critical part of their information ecosystem, allowing them to interact with their data in ways that are hidden or abstracted in more complex tools. This is particularly true for data workers [61], people who work with data as part of their job but do not identify as professional analysts or data scientists. We report on a qualitative study of how these workers interact with and reason about their data. Our findings show that data tables serve a broader purpose beyond data cleanup at the initial stage of a linear analytic flow: users want to see and “get their hands on” the underlying data throughout the analytics process, reshaping and augmenting it to support sensemaking. They reorganize, mark up, layer on levels of detail, and spawn alternatives within the context of the base data. These direct interactions and human-readable table representations form a rich and cognitively important part of building understanding of what the data mean and what they can do with it. We argue that interactive tables are an important visualization idiom in their own right; that the direct data interaction they afford offers a fertile design space for visual analytics; and that sense making can be enriched by more flexible human-data interaction than is currently supported in visual analytics tools.
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影响因子：
2.5
作者：
Younghoon Kim;M. Correll;Jeffrey Heer
通讯作者：
Younghoon Kim;M. Correll;Jeffrey Heer
DOI：
10.1109/tvcg.2011.250
发表时间：
2011-12-01
影响因子：
5.2
作者：
Lex, Alexander;Schulz, Hans-Joerg;Schmalstieg, Dieter
通讯作者：
Schmalstieg, Dieter
DOI：
--
发表时间：
--
期刊：
--
影响因子：
--
作者：
Thomas Musich;Olivia O 'connell;Maria Paz Gonzalez-Perez;Olivia O 'connell;M. Gonzalez-Perez;Paz
通讯作者：
Thomas Musich;Olivia O 'connell;Maria Paz Gonzalez-Perez;Olivia O 'connell;M. Gonzalez-Perez;Paz
Taggle：将表格数据可视化中的概述和详细信息相结合
影响因子：
2.3
作者：
Furmanova, Katarina;Gratzl, Samuel;Stitz, Holger;Zichner, Thomas;Jaresova, Miroslava;Lex, Alexander;Streit, Marc
通讯作者：
Streit, Marc