Trusted Data Space System of Smart Libraries from the Perspective of Value Chain Synergy

[Purpose/Significance] From the perspective of value chain collaboration, a trusted data space system adapted to the characteristics of smart library scenarios is constructed, aiming to solve the systematic problems such as fragmented cross-domain integration, a lack of trusted guarantee, and inefficient value transformation in current library data governance. The study will contribute to improving the theoretical framework for governing library data. It also provides practical guidance on balancing the contradiction between data circulation and security, as well as on releasing the operational value of data elements. This helps smart libraries to strengthen their core functions in terms of public cultural service provision and knowledge empowerment. [Method/Process] Adopting a public value approach, we analyzed the coupling logic and value dimension of technical collaboration, rights and responsibilities, and scenario adaptation in the value chain links, as well as the hierarchical improvement laws of the data, knowledge, service and ecosystem layers. This was based on clarifying the four core elements of the trusted data space of smart libraries: data, subject, technology and system. We also examined the characteristics of trusted collaboration and value progression. The collaborative optimization process was examined in conjunctionwas with the links between the various stages of the data lifecycle. The path of expansion for the cross-chain ecosystem was constructed through collaboration between libraries, industry links, and social empowerment. We ensure a high degree of compatibility with the scene requirements of smart libraries. [Results/Conclusions] The trusted data space system of smart libraries consolidates the foundation of data trustworthiness through technological integration, activates the efficiency of the value network through the collaboration of subjects, consolidates the basis of operation guarantee through institutional norms, and extends the coverage boundary of services through value transformation, thus forming a governance pattern of four-dimensional interaction among technology, subjects, systems, and values. Based on this, four collaborative strategies, namely ecological niche reconstruction, capability leap, dynamic risk governance and value closed loop, are proposed. These strategies ultimately facilitate a systematic transition from the aggregation of data resources to the co-creation of ecological value. In the future, the element configuration and collaborative mechanism of the trusted data space can be optimized in combination with the service positioning of different libraries. The goal can be achieved through pilot construction, which will allow us to collect practical data, verify the system's feasibility and effectiveness, and explore the integrated application path of AI large models and trusted data spaces.