Research on the Influencing Factors of Scientific Data Reuse in the Field of Machine Learning Based on Information Adoption Model
Based on the Information Adoption Model,this paper constructs a model of factors influencing scientific data reuse in the field of machine learning.We select two types of scientific data platforms—open science community platforms and scientific data sharing platforms—to collect data.Then we empirically examine the impact of dataset content quality and data source credibility on scientific data reuse,as well as the moderating effect of platform types on the relationship between data source credibility and scientific data reuse.This paper is of great significance for improving the construction of scientific data platforms and promoting the reuse of scientific data.
Scientific data reuseInformation adoption modelField of machine learningPlatform typesInfluencing factors
万方数据
维普
