基于云原生的地理空间知识库管理关键技术与服务方法研究  

Critical Technologies and Service Approaches for Cloud-Native Geospatial Knowledge Base Management

作　　者：仲腾 张雪英[1,2] 许沛 曹敏 陈碧宇[3] 刘启亮 王曙[5] 杨宜舟[6] ZHONG Teng;ZHANG Xueying;XU Pei;CAO Min;CHEN Biyu;LIU Qiliang;WANG Shu;YANG Yizhou(Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023;Key Laboratory of Virtual Geographic Environment(Ministry of Education),Nanjing Normal University,Nanjing 210023,China;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;Department of Geo-informatics,Central South University,Changsha 410083,China;State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;Beijing GEOWAY Software Co.,Ltd.,Beijing 100043,China)

机构地区：[1]南京师范大学虚拟地理环境教育部重点实验室,南京210023 [2]江苏省地理信息资源开发与利用协同创新中心,南京210023 [3]武汉大学测绘遥感信息工程国家重点实验室,武汉430079 [4]中南大学地理信息系,长沙410083 [5]中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京100101 [6]北京吉威空间信息股份有限公司,北京100043

出　　处：《地球信息科学学报》2024年第9期2013-2025,共13页Journal of Geo-information Science

基　　金：国家重点研发计划项目(2021YFB3900903)。

摘　　要：地理空间知识的本质在于揭示地理事物和现象的时空分布、时空变化过程及其相互作用规律。地理空间知识库管理系统(GeoKGMS)以“图-文-数”一体化的地理空间知识库引擎为核心,致力于支撑地理空间知识资源的高效汇聚、地理空间知识图谱的自动构建和一站式地理空间知识工程建设,旨在形成新一代地理信息系统(GIS)的重要基础平台。本文重点阐述了基于云原生的地理空间知识库管理关键技术,包括云原生的地理空间知识库微服务统一调度技术、人机协同的地理空间知识图谱构建技术、地理空间知识图谱时空混合编码技术、以及多模态地理空间知识存储技术。在此基础上,设计了GeoKGMS的服务框架,实现了地理空间知识库管理、多模态地理空间知识抽取、地理空间知识图谱人机协同构建、地理空间知识推理、地理空间知识图谱质量评估和地理空间知识可视化六大管理服务功能。以喀斯特地貌知识图谱为例,充分发挥机器挖掘和专家知识的优势,实现了可持续的地理空间知识图谱工程化协同共建。The essence of geospatial knowledge lies in unveiling the spatiotemporal distribution,dynamics of change,and interaction patterns of geographical entities and phenomena.However,existing knowledge base management platforms often overlook the specific needs of geospatial knowledge representation and lack the capability to handle the unique attributes of geospatial data,making it challenging to meet the requirements for constructing and applying geospatial knowledge graphs.The Geospatial Knowledge Base Management System(GeoKGMS)is designed on the basis of an integrated geospatial knowledge base engine that efficiently aggregates geospatial knowledge resources across various modalities—'Image-Text-Number'—automates the construction of geospatial knowledge graphs,and facilitates a one-stop geospatial knowledge engineering process.This paper elucidates four key technologies for managing geospatial knowledge bases.First,the cloudnative geospatial knowledge base microservice unified scheduling technology decomposes the large geospatial knowledge base management system into fine-grained,independently operable,and deployable microservices.By comprehensively managing the lifecycle of the geospatial knowledge base,service classification and orchestration methods are determined to achieve unified scheduling of these microservices.Second,a humancomputer collaborative geospatial knowledge graph construction method is proposed,supporting the sustainable,collaborative construction of geospatial knowledge graph engineering.Third,the spatiotemporal hybrid encoding technology of the geospatial knowledge graph achieves unified representation of geospatial knowledge by integrating multimodal geospatial data and spatiotemporal information.Fourth,a multimodal geospatial knowledge integrated storage and large-scale spatiotemporal graph partitioning technology is proposed to address the challenges of efficiently managing complex structured geospatial knowledge and retrieving largescale spatiotemporal knowledge tuples.Based on these ke

关 键 词：云原生 地理空间知识 知识库管理 人机协同知识图谱构建 知识推理 知识检索 知识存储 知识质量评估 

分 类 号：P208[天文地球—地图制图学与地理信息工程]