Data Quality - The Role of Empiricism

被引：22

作者：

Sadiq, Shazia ^{[1
]}

Dasu, Tamraparni ^{[2
]}

Dong, Xin Luna ^{[3
]}

Freire, Juliana ^{[4
]}

Ilyas, Ihab F. ^{[5
]}

Link, Sebastian ^{[6
]}

Miller, Renee J. ^{[7
]}

Naumann, Felix ^{[8
]}

Zhou, Xiaofang ^{[1
]}

Srivastava, Divesh ^{[2
]}

机构：

[1] Univ Queensland, Brisbane, Qld, Australia

[2] AT&T Labs Res, Florham Pk, NJ USA

[3] Amazon, Seattle, WA USA

[4] NYU, New York, NY 10003 USA

[5] Univ Waterloo, Waterloo, ON, Canada

[6] Univ Auckland, Auckland, New Zealand

[7] Univ Toronto, Toronto, ON, Canada

[8] Univ Potsdam, Hasso Plattner Inst, Potsdam, Germany

来源：

SIGMOD RECORD | 2017年 / 46卷 / 04期

关键词：

DISCOVERY;

D O I：

10.1145/3186549.3186559

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We outline a call to action for promoting empiricism in data quality research. The action points result from an analysis of the landscape of data quality research. The landscape exhibits two dimensions of empiricism in data quality research relating to type of metrics and scope of method. Our study indicates the presence of a data continuum ranging from real to synthetic data, which has implications for how data quality methods are evaluated. The dimensions of empiricism and their inter-relationships provide a means of positioning data quality research, and help expose limitations, gaps and opportunities.

引用

页码：35 / 43

页数：9

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