Abstract:

[Objective] The advent of big data has given rise to a new research paradigm, termed the "Convergence Science" paradigm, which addresses significant technological challenges through the fusion of multidisciplinary data. Collaborative analysis and application of scientific data across disciplines have become crucial for maximizing its value, making cross-center trustworthy data sharing a key issue in constructing scientific data centers. [Methods] Considering the characteristics and challenges of scientific data centers, including heterogeneous data from multiple sources, large volumes, dispersed resources, strong expertise, and clear intellectual property rights, this paper proposes a technical framework for cross-center trustworthy sharing of scientific data. This framework includes key technologies such as scientific data modeling and interoperability methods, dual-identifier fusion resolution, trustworthy storage and certification, and data ownership and circulation traceability. [Results] This framework's effectiveness has been confirmed in the context of data sharing spanning five scientific data centers. [Conclusions] This framework provides a feasible technical path for cross-center trusted sharing of scientific data in the new paradigm of convergence science.

Key words: scientific data, convergence science, trusted sharing, interoperability, identifier resolution