Exploring Change - A New Dimension of Data Analytics
Exploring Change - A New Dimension of Data Analytics
复制标题
探索变革——数据分析的新维度
DOI：
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复制
发表时间：
2018
影响因子：
2.5
通讯作者：
D. Srivastava
中科院分区：
文献类型：
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作者：
Tobias Bleifuß;Leon Bornemann;T. Johnson;D. Kalashnikov;Felix Naumann;D. Srivastava
数据集中的数据和元数据经历了许多不同类型的变化。值被插入、删除或更新；行出现和消失；添加列或重新调整用途等。在这种动态情况下，用户可能会提出许多与数据集更改相关的问题，例如数据的哪些部分值得信赖，哪些部分不可信？用户会想：最近几分钟、几天或几年发生了多少变化？在哪些时间点做出了什么样的改变？数据有多脏？是否需要进行数据清洗？数据改变的事实可能暗示着不同的隐藏过程或议程：频繁更新的城市名称可能会引起争议；最近更改姓名的人可能会成为破坏行为的目标；等等。我们展示了从认识和探索这种变化中受益的各种用例。
我们设想了一种系统和方法来交互式地探索这种变化，解决
变异性
大数据挑战的维度。为此，我们提出了一个捕获变化的模型以及探索动态数据以识别显着变化的过程。我们提供探索原语以及激励性示例和数据波动性的衡量标准。我们确定了使我们的愿景成为现实所需解决的技术挑战，并为数据管理社区提出了未来工作的方向。
Data and metadata in datasets experience many different kinds of change. Values are inserted, deleted or updated; rows appear and disappear; columns are added or repurposed, etc. In such a dynamic situation, users might have many questions related to changes in the dataset, for instance which parts of the data are trustworthy and which are not? Users will wonder: How many changes have there been in the recent minutes, days or years? What kind of changes were made at which points of time? How dirty is the data? Is data cleansing required? The fact that data changed can hint at different hidden processes or agendas: a frequently crowd-updated city name may be controversial; a person whose name has been recently changed may be the target of vandalism; and so on. We show various use cases that benefit from recognizing and exploring such change.
We envision a system and methods to interactively explore such change, addressing the
variability
dimension of big data challenges. To this end, we propose a model to capture change and the process of exploring dynamic data to identify salient changes. We provide exploration primitives along with motivational examples and measures for the volatility of data. We identify technical challenges that need to be addressed to make our vision a reality, and propose directions of future work for the data management community.