Power Data Integration Method Based on Database-table Metadata Semantic. Issue 1 (1st January 2022)

• Record Type: Journal Article
• Authors: Zheng, Lei; Pan, Jianhong; Zhang, Kai
• Is Part Of: Journal of physics. Volume 2179:Issue 1(2022)
• Publication Date: 2022-01-01
• Subjects: Metadata -- Database-table semantic -- Data asset -- Jaccard similarity -- Edit distance.; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2179/1/012028
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Aiming at the characteristic of power data with multiple sources, wide distribution and complex association, this paper proposes a power data integration method based on Database-Table Metadata Semantic (DTMS), which can realize the integration of grid data at the metadata layer. Firstly, based on the structure of the database, the semantic expression is established between database and table; Secondly, this paper combines the Jaccard distance similarity method and the edit distance similarity method to achieve semantic matching between metadata and technical terms, which can solve the shortcomings of the single similarity method. Finally, according to the characteristics of power data assets, a power data integration scheme based on DTMS is proposed for multi-source power data integration. Through experiments, the accuracy of the algorithm in this paper has reached 95.8%.