Research on classification and hierarchical management of industrial data based on entropy method-TOPSIS theory

Abstract

In the era of accelerating digitalization, digital infrastructure is one of the most popular topics today, and digital infrastructure dominated by the industrial sector has become the vanguard of development. In response to this, industrial companies and platform companies attach importance to industrial data. Increasingly, the classification and hierarchical management of industrial data has become an indispensable procedure for the effective processing and safety management of industrial data. This article classifies the vertical data of each domain from the general process of industrial production, namely R&D, production, operation and maintenance, management and other classification domains, and according to the industrial production, self-economic benefits and social benefits brought by industrial data. Potential impact on industrial data can be classified by horizontal data classification of primary data, secondary data, and tertiary data from data features such as data importance, tamper-proof, and anti-corruption, and use entropy weight method to calculate the weight of each indicator feature and evaluate the data importance, and finally apply TOPSIS theory for data grading.