Exploration of Data Reuse Patterns Based on Scientific Data Lifecycle in Big Data Environment

In the realm of big data, the volume of research data in universities is expanding rapidly. However, the lack of data collaboration results in data isolation, hindering the realization of their potential value. This study aims to enhance data interoperability and promote data reuse by developing a comprehensive metadata scheme, which facilitates standardized descriptions of scientific data metadata throughout the entire process, from data generation to citation. Additionally, by delineating the data governance process encompassing data collection, processing and handling, archival and management, as well as data utilization and sharing, a data management cloud platform is established based on data reuse patterns. This platform incorporates features for data retrieval, storage and management, and data monitoring, ensuring the seamless continuity of research management efforts.