联邦服务:基于分布式数据共治的智能服务范式

Federated services:smart service paradigm based on distributed data co-governance

随着数字化转型的加速,数据已成为驱动科技创新与经济增长的核心要素。然而,广泛存在的数据孤岛现象严重阻碍了跨领域、跨组织间的数据流通与合作,使得数据供应难以满足多样化的用户需求,数据的供需匹配面临严峻挑战。作为联邦生态的核心环节和对外赋能的重要窗口,联邦服务基于分布式数据共治原则,促进了跨领域、跨组织的数据流通与协同,为智能的供需匹配提供了一种有效的技术框架。首先,探讨联邦服务在联邦生态中的重要地位以及与联邦生态各环节的关系。其次,提出联邦服务的5层基本框架,并探讨其核心优势。在此基础上,提出联邦服务的关键支撑技术,主要包括区块链和去中心化自治组织与运营、大语言模型和场景工程、分布式计算和边缘计算、加密技术和隐私计算。最后,以数据与场景的供需匹配为应用案例,介绍联邦服务如何实现智能的供需匹配。提出的联邦服务理论与技术对于构建基于分布式数据共治的智能服务范式具有重要意义。

The acceleration of digital transformation has made data a core element driving technological innovation and economic growth.However,the widespread phenomenon of data island severely hinders data circulation and collabora‐tion across different fields and organizations,making it difficult for data supply to meet the diverse needs of users,thus creating a dilemma in matching data supply and demand.Serving as the core link in the federated ecology and an impor‐tant window for external empowerment,federated services provide an innovative solution for data circulation and utiliza‐tion under the principle of distributed data co-governance,thereby enabling the intelligent matching of supply and de‐mand.Firstly,this paper delves into the pivotal role of federated services within the federated ecology,and examines the relationship between federated services and federated ecology’s key components.Secondly,it presents a five-layer basic framework of federated services and discusses its core advantages.On this basis,the paper proposes the key supporting technologies for federated services,including blockchain and decentralized autonomous organizations and operations,large language models and scenario engineering,distributed computing and edge computing,as well as encryption technology and privacy computing.Finally,taking the supply-demand matching problem of data and scenarios as a case study,the pa‐per illustrates how federated services achieve intelligent matching of demand and supply.The federated services proposed in this paper holds significant implications for constructing a smart service paradigm based on distributed data co-governance.