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Data Quality Management in Institutional Research Output Data Center

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Database Systems for Advanced Applications (DASFAA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11448))

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Abstract

Institutional research output data center will store normative and convinced scholar’s research output data, and it will effectively support dynamic presentation of research output, reveal institutional academic publication in multiple dimensions, advance open access, and provide data support for subject evaluation and discipline development.

In this paper, we propose a data quality management framework to build institutional research output data center, and put forward relevant technical solution for different data governance problems, such as department name similarity estimation in data matching, author name disambiguous problem in data merging and security issue in data exchange. We also introduce some learning algorithms such as text distance and community detection with matrix factorization. Comparing with different ways, our methods achieve good performance in quality manage processing.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Levenshtein_distance/.

  2. 2.

    http://webofknowledge.com/.

  3. 3.

    https://oauth.net/.

  4. 4.

    https://orcid.org/.

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Acknowledgments

This work was supported by NSFC (Grant No. 61772330), the Science and Technology Commission of Shanghai Municipality (Grant No. 16JC1402800), China Next Generation Internet IPv6 project (Grant No. NGII20170609), the Social Science Planning of Shanghai (Grant No. 2018BTQ002), and Arts and Science Cross Special Fund of Shanghai JiaoTong University (Grant No. 15JCMY08).

Author information

Authors and Affiliations

  1. Library, Shanghai Jiaotong University, Shanghai, China

    Xiaohua Shi & Zhuoyuan Xing

  2. Department of Computer Science, Shanghai JiaoTong University, Shanghai, China

    Xiaohua Shi & Hongtao Lu

Authors
  1. Xiaohua Shi
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  2. Zhuoyuan Xing
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  3. Hongtao Lu
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Corresponding author

Correspondence to Xiaohua Shi .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Guoliang Li

  2. Duke University, Durham, NC, USA

    Jun Yang

  3. University of Porto, Porto, Portugal

    Joao Gama

  4. Chiang Mai University, Chiang Mai, Thailand

    Juggapong Natwichai

  5. Beihang University, Beijing, China

    Yongxin Tong

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Shi, X., Xing, Z., Lu, H. (2019). Data Quality Management in Institutional Research Output Data Center. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11448. Springer, Cham. https://doi.org/10.1007/978-3-030-18590-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-18590-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18589-3

  • Online ISBN: 978-3-030-18590-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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