In response to the diverse, highly heterogeneous, and complex characteristics of educational big data sources and the privacy ethics requirements of data application services, technologies based on crowdsourcing have been developed for educational resource data fusion, semantic fusion of educational scenarios and learning spaces, co construction and sharing of educational cloud resources, ethical and security protection of educational data, etc., to achieve multi-source data fusion and sharing and data service privacy protection.