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Incomplete data management: a survey

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Abstract

Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query incomplete data incurs big challenges. For example, the queries struggling with incomplete data usually have dissatisfying query results due to the improper incompleteness handling methods. In this paper, we systematically review the management of incomplete data, including modelling, indexing, querying, and handling methods in terms of incomplete data. We also overview several application scenarios of incomplete data, and summarize the existing systems related to incomplete data. It is our hope that this survey could provide insights to the database community on how incomplete data is managed, and inspire database researchers to develop more advanced processing techniques and tools to cope with the issues resulting from incomplete data in the real world.

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Acknowledgements

This work was supported in part by the National Key Basic Research Program of China (973 Program) (2015CB352502), the National Natural Science Foundation of China (NSFC) (Grant Nos. 61522208, 61379033, and 61472348), and the Fundamental Research Funds for the Central Universities.

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  1. College of Computer Science, Zhejiang University, Hangzhou, 310027, China

    Xiaoye Miao, Yunjun Gao, Su Guo & Wanqi Liu

  2. The Key Lab of Big Data Intelligent Computing of Zhejiang Province, Zhejiang University, Hangzhou, 310027, China

    Yunjun Gao

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  1. Xiaoye Miao
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Correspondence to Yunjun Gao.

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Xiaoye Miao received the BS degree in computer science from Xi’an Jiaotong University, China in 2012. She is currently working toward the PhDdegree in the College of Computer Science, Zhejiang University, China. Her research interests include uncertain and incomplete databases.

Yunjun Gao received the PhD degree in computer science from Zhejiang University (ZJU), China in 2008. He is currently a professor in the College of Computer Science, ZJU. His research interests include spatiotemporal databases, metric and incomplete/ uncertain data management, database usability, and geo-social data processing. He is an awardee of the NSFC Excellent Young Scholars Program in 2015, a member of the ACM and the IEEE, and a senior member of the CCF.

Su Guo received the BS degree in computer science from Xidian University, China in 2016. She is currently working toward the MS degree in the College of Computer Science, Zhejiang University, China. Her research interests include incomplete databases and query processing.

Wanqi Liu is currently working toward the BS degree in the College of Computer Science, Zhejiang University, China. Her research interests include query processing and incomplete databases.

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Miao, X., Gao, Y., Guo, S. et al. Incomplete data management: a survey. Front. Comput. Sci. 12, 4–25 (2018). https://doi.org/10.1007/s11704-016-6195-x

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