联邦服务：基于分布式数据共治的智能服务范式

贾晓丰; 秦蕊; 王寿文; 齐红威; 王飞跃; 李娟娟; 章敏; 梁小龙

doi:10.11959/j.issn.2096-6652.202416

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联邦服务：基于分布式数据共治的智能服务范式

学术论文 | 更新时间：2024-08-06

- 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
- 智能科学与技术学报 2024年6卷第2期页码：210-219
- 作者机构：
  
  1.北京市大数据中心，北京 100101
  2.中国科学院自动化研究所多模态人工智能系统全国重点实验室，北京 100190
  3.中国科学院自动化研究所复杂重点系统管理与控制国家实验室，北京 100190
  4.澳门科技大学创新工程学院，澳门 999078
  5.数据堂（北京）科技股份有限公司，北京 100192
- 作者简介：
  
  [ "贾晓丰（1985- ），男，博士，北京市大数据中心数据管理部负责人、教授级高级工程师，主要研究方向为复杂系统数据治理、联邦智能。" ]
  [ "秦蕊（1983- ），女，博士，中国科学院自动化研究所多模态人工智能系统全国重点实验室副研究员，主要研究方向为区块链智能、DAO与平行管理。" ]
  [ "王寿文（1986- ），男，澳门科技大学创新工程学院博士生，主要研究方向为复杂系统与平行智能、区块链智能、智能合约及基于DAO的管理与治理。" ]
  [ "齐红威（1975- ），男，博士，数据堂（北京）科技股份有限公司创始人兼CEO，正高级工程师，中国自动化学会联邦数据与联邦智能专委会主任，主要研究方向为人工智能数据采集、处理以及联邦数据。" ]
  [ "王飞跃（1961- ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任，主要研究方向为平行系统的方法与应用、社会计算、平行智能、知识自动化。" ]
  [ "李娟娟（1986- ），女，博士，中国科学院自动化研究所多模态人工智能系统全国重点实验室副研究员，主要研究方向为区块链智能、DAO与平行管理。" ]
  [ "章敏（1992- ），女，北京市大数据中心数据管理部高级工程师，主要研究方向为数据治理、知识工程、联邦智能。" ]
  [ "梁小龙（1987- ），男，博士，多模态人工智能系统全国重点实验室助理研究员，主要研究方向平行智能、区块链与DAO。" ]
- 基金信息：
  
  国家重点研发计划项目(2021YFB2104800);国家自然科学基金项目(62103411);澳门特别行政区科学技术发展基金项目(0093/2023/RIA2;0050/2020/A1)
- DOI：10.11959/j.issn.2096-6652.202416
  中图分类号： C931
- 收稿：2024-03-02，
  
  修回：2024-05-24，
  
  纸质出版：2024-06-15
- 稿件说明：
移动端阅览
贾晓丰,秦蕊,王寿文等.联邦服务：基于分布式数据共治的智能服务范式[J].智能科学与技术学报,2024,06(02):210-219.

JIA Xiaofeng,QIN Rui,WANG Shouwen,et al.Federated services: smart service paradigm based on distributed data co-governance[J].Chinese Journal of Intelligent Science and Technology,2024,06(02):210-219.
贾晓丰,秦蕊,王寿文等.联邦服务：基于分布式数据共治的智能服务范式[J].智能科学与技术学报,2024,06(02):210-219. DOI： 10.11959/j.issn.2096-6652.202416.

JIA Xiaofeng,QIN Rui,WANG Shouwen,et al.Federated services: smart service paradigm based on distributed data co-governance[J].Chinese Journal of Intelligent Science and Technology,2024,06(02):210-219. DOI： 10.11959/j.issn.2096-6652.202416.

摘要

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。

Abstract

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 collaboration 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 important window for external empowerment

federated services provide an innovative solution for data circulation and utilization under the principle of distributed data co-governance

thereby enabling the intelligent matching of supply and demand. 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 paper 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.

关键词

Keywords

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