国内外大数据质量研究述评
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摘要
作为前沿性研究领域,大数据质量研究是大数据研究的核心内容之一,也是各界关注的焦点问题。本文以国内外大数据质量研究文献为对象,从基本内涵、质量管理、质量评价、应用实践等角度对相关研究进行梳理与综述,分析国内外相关研究进展。研究发现,大数据质量诸方面研究均是以大数据特征为基础,以大数据质量基本属性为核心,与其应用目标及适用情境相结合,形成有别于常规数据质量理论的、具有复杂性和多维度的理论体系。同时发现,大数据质量本质研究、与技术环境和人文环境相结合研究、基于宏观视角的国家层面和战略层面研究等将是大数据质量研究领域未来的研究趋势与研究重点。
As a frontier research field, big data quality research is one of the core contents of big data research; it is also the focus of attention from all walks of life. Based on the literature on big data quality, this paper uses synthesis methods to examine the progress of relevant domestic and international research in terms of its basic implications, quality management, quality evaluation, and application practice. The results show that the study of big data quality is based on big data characteristics, with the basic attributes of big data quality as the core, combined with its application goals and applicable scenarios. It finally forms a complex and multidimensional theoretical system that is different from the conventional data quality theory. At the same time, the results indicate that the study of the essence of big data quality, the combination of technical and human environment, and research on the national and strategic levels based on a macro perspective will be the future research trends and research focus of big data quality research.
As a frontier research field, big data quality research is one of the core contents of big data research; it is also the focus of attention from all walks of life. Based on the literature on big data quality, this paper uses synthesis methods to examine the progress of relevant domestic and international research in terms of its basic implications, quality management, quality evaluation, and application practice. The results show that the study of big data quality is based on big data characteristics, with the basic attributes of big data quality as the core, combined with its application goals and applicable scenarios. It finally forms a complex and multidimensional theoretical system that is different from the conventional data quality theory. At the same time, the results indicate that the study of the essence of big data quality, the combination of technical and human environment, and research on the national and strategic levels based on a macro perspective will be the future research trends and research focus of big data quality research.
引文
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[20]Haryadi A F.Requirements on and antecedents of big data quali‐ty:An empirical examination to improve big data quality in finan‐cial service organizations[D].Delft:Delft University of Technolo‐gy,2016:13.
[21]Glowalla P,Balazy P,Basten D,et al.Process-driven data quality management-An application of the combined conceptual life cy‐cle model[C]//Proceedings of the 2014 47th Hawaii International Conference on System Sciences.Washington DC:IEEE Comput‐er Society,2014:4700-4709.
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[23]Soares S.Big data governance[M]//An Emerging Imperative.MC Press,2012.
[24]Aggarwal A.Data quality evaluation framework to assess the di‐mensions of 3V’s of big data[J].International Journal of Emerg‐ing Technology and Advanced Engineering,2017,7(10):503-506.
[25]Toivonen M.Big data quality challenges in the context of busi‐ness analytics[D].Helsinki:University of Helsinki,2015:47-48.
[26]Kl?s M,Trendowicz A,Jedlitschka A.What makes big data dif‐ferent from a data quality assessment perspective?Practical chal‐lenges for data and information quality research[R].ODQ201530 March 2015,Garching,Germany.
[27]Ardagna D,Cappiello C,SamáW,et al.Context-aware data qual‐ity assessment for big data[J].Future Generation Computer Sys‐tems,2018,89:548-562.
[28]张绍华,潘蓉,宗宇伟.大数据治理与服务[M].上海:上海科学技术出版社,2016:120.
[29]Juddoo S.Overview of data quality challenges in the context of Big Data[C]//Proceedings of the 2015 International Conference on Computing,Communication and Security.IEEE,2015:1-9.
[30]Sneed H M,Erdoes K.Testing big data(assuring the quality of large databases)[C]//Proceedings of the 2015 IEEE Eighth Inter‐national Conference on Software Testing,Verification and Valida‐tion Workshops.IEEE,2015:1-6.
[31]Liedtke C A.Quality,analytics,and big data[R].Strategic Im‐provement Systems,2016.
[32]蔡莉,朱扬勇.大数据质量[M].上海:上海科学技术出版社,2017:5.
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