Research and Application of Power Grid Data Blood Relationship Analysis

Ming Liu; Shijin Liu; Lihua Sun; Hongyu Ding; Chuanrong Lu; Yang Zhang; Tiancheng Qian

doi:10.2991/978-94-6463-064-0_32

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Research and Application of Power Grid Data Blood Relationship Analysis

Authors

Ming Liu¹^{, *}, Shijin Liu¹, Lihua Sun¹, Hongyu Ding¹, Chuanrong Lu¹, Yang Zhang¹, Tiancheng Qian¹

¹Nanjing NARI Information and Communication Technology Co., Ltd., Nanjing, China

^*Corresponding author. Email: liuming@sgepri.sgcc.com.cn

Corresponding Author

Ming Liu

Available Online 27 December 2022.

DOI: 10.2991/978-94-6463-064-0_32 How to use a DOI?
Keywords: power grid data center; power grid big data; data lineage; data governance; visualization
Abstract: State Grid Corporation of China implements the digital transformation strategy, integrates the resources of various data islands in various power fields under the traditional model, and quickly forms the capabilities of data governance and data services. The implementation process will encounter problems such as difficulty in obtaining big data metadata, data quality, and data traceability. This paper proposes a power grid data lineage analysis method, which performs metadata management, data extraction, data transformation, data calculation, etc. on the data at the source data end (especially for power grid big data) to generate bloodline data. See the data source link for the model object. The results show that the blood relationship analysis function can be beneficial to the tracking and positioning of data problems, to the diversified analysis of data, to the data governance of the big data platform, and to effectively solve the pain points of data display in the national network data center.
Copyright: © 2023 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series: Atlantis Highlights in Computer Sciences
Publication Date: 27 December 2022
ISBN: 978-94-6463-064-0
ISSN: 2589-4900
DOI: 10.2991/978-94-6463-064-0_32 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Ming Liu
AU  - Shijin Liu
AU  - Lihua Sun
AU  - Hongyu Ding
AU  - Chuanrong Lu
AU  - Yang Zhang
AU  - Tiancheng Qian
PY  - 2022
DA  - 2022/12/27
TI  - Research and Application of Power Grid Data Blood Relationship Analysis
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 277
EP  - 286
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_32
DO  - 10.2991/978-94-6463-064-0_32
ID  - Liu2022
ER  -

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