启用变更探索:远景文件

Proceedings of the ExploreDB'17. International Workshop on Exploratory Search in Databases and the Web (4th : 2017 : Chicago, Ill.) Pub Date : 2017-05-14 DOI:10.1145/3077331.3077340

Tobias Bleifuß, T. Johnson, D. Kalashnikov, Felix Naumann, Vladislav Shkapenyuk, D. Srivastava

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引用次数: 1

摘要

数据和元数据遭受许多不同类型的变化:值被插入、删除或更新;实体出现又消失;添加属性或重新使用属性等。明确地识别、探索和评估这种变化可以提醒数据摄取过程中的变化，可以帮助评估数据质量，并且可以随着时间的推移提高对数据集及其行为的总体理解。我们提出了一个独立于数据模型的框架来形式化这种变化。我们的更改多维数据集支持探索和发现这些更改，以揭示数据集随时间的行为。

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Enabling Change Exploration: Vision Paper

Data and metadata suffer many different kinds of change: values are inserted, deleted or updated; entities appear and disappear; properties are added or re-purposed, etc. Explicitly recognizing, exploring, and evaluating such change can alert to changes in data ingestion procedures, can help assess data quality, and can improve the general understanding of the dataset and its behavior over time. We propose a data model-independent framework to formalize such change. Our change-cube enables exploration and discovery of such changes to reveal dataset behavior over time.

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来源期刊

Proceedings of the ExploreDB'17. International Workshop on Exploratory Search in Databases and the Web (4th : 2017 : Chicago, Ill.)

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