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Research directions in data wrangling: Visualizations and transformations for usable and credible data

机译:数据争用的研究方向:可用数据和可信数据的可视化和转换

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摘要

In spite of advances in technologies for working with data, analysts still spend an inordinate amount of time diagnosing data quality issues and manipulating data into a usable form. This process of 'data wrangling' often constitutes the most tedious and time-consuming aspect of analysis. Though data cleaning and integration are longstanding issues in the database community, relatively little research has explored how interactive visualization can advance the state of the art. In this article, we review the challenges and opportunities associated with addressing data quality issues. We argue that analysts might more effectively wrangle data through new interactive systems that integrate data verification, transformation, and visualization. We identify a number of outstanding research questions, including how appropriate visual encodings can facilitate apprehension of missing data, discrepant values, and uncertainty; how interactive visualizations might facilitate data transform specification; and how recorded provenance and social interaction might enable wider reuse, verification, and modification of data transformations.
机译:尽管处理数据的技术有所进步,但分析人员仍然花费大量时间来诊断数据质量问题并将数据处理为可用形式。 “数据整理”的过程通常构成分析中最繁琐且耗时的方面。尽管数据清理和集成是数据库社区中长期存在的问题,但相对较少的研究探索了交互式可视化如何推动技术发展。在本文中,我们回顾了与解决数据质量问题相关的挑战和机遇。我们认为,分析师可能会通过集成了数据验证,转换和可视化的新型交互式系统来更有效地处理数据。我们确定了许多悬而未决的研究问题,包括适当的视觉编码如何促进对缺失数据,差异值和不确定性的理解;交互式可视化如何促进数据转换规范;以及记录的出处和社交互动如何使数据转换更广泛地重复使用,验证和修改。

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