时空知识中心的研究进展与应用

doi:10.11947/j.AGCS.2021.20210160

摘要/Abstract

摘要： 时空知识是对实体空间位置、形态、分布、关系、运动、变化、趋势等信息进行概括和凝练，形成具有时间和空间特性的知识。时空知识中心是时空知识获取、积累、创造、演化和利用的服务平台或环境。构建时空知识中心是智能化测绘面临的机遇和挑战，相关研究还处在起步探索阶段，尚无可供借鉴的、成熟的建设和服务模式。本文瞄准测绘“两服务，两支撑”的基本定位，借鉴国内外知识中心建设的实践，融入智能化测绘的有关理念，提出时空知识中心概念、内涵、技术框架、主体实现方法及研究进展，指出时空知识中心是现有地理信息中心智能化转型升级的发展方向。

关键词: 时空知识中心, 空间型知识图谱, 时空数据生态, 时空知识库

Abstract: Spatiotemporal knowledge is the knowledge with temporal and spatial characteristics formed by summarizing and condensing the information of spatial location, shape, distribution, relationship, movement, change and trend of entity.Spatiotemporal knowledge center is a service platform or environment for acquiring, accumulating, creating, evolving and utilizing spatiotemporal knowledge.The construction of space-time knowledge center is an opportunity and challenge for intelligent mapping. The relevant research is still in the initial stage of exploration, and there is no mature construction and service mode to be used for reference.This article aims at the new needs of natural resource management for surveying and mapping services, draws on the practice of knowledge center construction at home and abroad, incorporates the relevant concepts of intelligent surveying and mapping, and proposes the concept, connotation, technical framework, subject realization methods and research progress of the spatiotemporal knowledge center, and finally introduces the future development direction of spatiotemporal knowledge center from three aspects of development trend, key technology and engineering application.

Key words: spatiotemporal knowledge center, spatial knowledge graph, spatiotemporal data ecology, spatiotemporal knowledge data base

中图分类号:

P208

刘万增, 陈军, 翟曦, 李然, 王新鹏, 赵勇, 朱秀丽, 徐柱, 赵婷婷, 彭云璐, 慎利. 时空知识中心的研究进展与应用[J]. 测绘学报, 2021, 50(9): 1183-1193.

LIU Wanzeng, CHEN Jun, ZHAI Xi, LI Ran, WANG Xinpeng, ZHAO Yong, ZHU Xiuli, XU Zhu, ZHAO Tingting, PENG Yunlu, SHEN Li. Research progress and application of spatiotemporal knowledge center[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(9): 1183-1193.

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: http://xb.chinasmp.com/CN/10.11947/j.AGCS.2021.20210160

http://xb.chinasmp.com/CN/Y2021/V50/I9/1183

参考文献

[1] 阮于洲, 贾丹. 新体制下基础测绘生产服务体系若干思考[J]. 测绘科学, 2020(3):182-186. RUAN Yuzhou, JIA Dan. Some thoughts on reconstruction of basic surveying and mapping system[J]. Science of Surveying and Mapping, 2020,45(3):182-186.
[2] 陈军, 刘万增, 武昊, 等. 基础地理知识服务的基本问题与研究方向[J]. 武汉大学学报(信息科学版), 2019, 44(1):41-50. CHEN Jun, LIU Wanzeng, WU Hao, et al. Basic issues and research agenda of geospatial knowledge service[J]. Geomatics and Information Science of Wuhan University, 2019,44(1):41-50.
[3] 刘经南, 郭文飞, 郭迟, 等. 智能时代泛在测绘的再思考[J]. 测绘学报, 2020, 49(4):5-16. LIU Jingnan, GUO Wenfei, GUO Chi, et al. Rethinking ubiquitous mapping in the intelligent age[J]. Acta Geodaetica et Cartographica Sinica, 2020,49(4):5-16.
[4] 李德仁. 论时空大数据的智能处理与服务[J]. 地球信息科学学报, 2019, 21(12):1825-1831. LI Deren. The intelligent processing and service of spatiotemporal big data[J]. Journal of Geo-information Science, 2019,21(12):1825-1831.
[5] 林珲, 游兰, 胡传博, 等. 时空大数据时代的地理知识工程展望[J]. 武汉大学学报(信息科学版), 2018, 43(12):2205-2211. LIN Hui, YOU Lan, HU Chuanbo, et al. Prospect of geo-knowledge engineering in the era of spatio-temporal big data[J]. Geomatics and Information Science of Wuhan University, 2018,43(12):2205-2211.
[6] 杨宏山, 闫正龙, 白穆. 陕西时空大数据资源体系构建关键问题研究[J]. 测绘科学, 2019,44(12):184-188. YANG Hongshan, YAN Zhenglong, BAI Mu. Research on key issues of spatio-temporal big data resource system construction of Shaanxi[J]. Science of Surveying and Mapping, 2019,44(12):184-188.
[7] 杨宏山, 邓国庆. 自然资源管理中测绘地理信息工作的若干思考[J]. 测绘科学, 2020, 45(12):185-194. YANG Hongshan, DENG Guoqing. Some considerations about integrating surveying mapping and geospatial information into natural resources management[J]. Science of Surveying and Mapping, 2020,45(12):185-194.
[8] 蒋秉川, 万刚, 许剑, 等. 多源异构数据的大规模地理知识图谱构建[J]. 测绘学报, 2018,47(8):29-39. JIANG Bingchuan, WANG Gang, XU Jian, et al. Geographic knowledge graph building extracted from multi-sourced heterogeneous data[J]. Acta Geodaetica et Cartogrphica Sinica, 2018,47(8):29-39.
[9] JANEIRO R D.Intelligent operation center[EB/OL]. 2013-03-25[2021-02-03]. http://asmarterplanet.com/blog/2012/03/smarterleadership-how-rio-dejaneiro-created-anintelligent-operations-center.html.
[10] 谢友柏. 基于互联网的设计知识服务研究——分析中国工程科技知识中心(CKCEST)的功能[J]. 中国机械工程, 2017,28(6):631-640. XIE Youbai. Design knowledge service via internet: an analysis on the functions of China knowledge center for engineering sciences and technology(CKCEST)[J]. China Mechanical Engineering, 2017,28(6):631-640.
[11] 杜清运, 任福. 空间信息的自然语言表达模型[J]. 武汉大学学报(信息科学版), 2014,39(6): 682-688. DU Qingyun, REN Fu. Representation model of spatial information in natural language[J]. Geomatics and Information Science of Wuhan University, 2014,39(6):682-688.
[12] 龚健雅, 耿晶, 吴华意. 地理空间知识服务概论[J]. 武汉大学学报(信息科学版), 2014,39(8):883-890. GONG Jianya, GENG Jing, WU Huayi. Geospatial knowledge service: a review[J]. Geomatics and Information Science of Wuhan University, 2014,39(8):883-890.
[13] GORE A. The digital Earth: understanding our planet in the 21st century[J]. Photogrammetric Engineering & Remote Sensing, 1998,65(5): 1-4.
[14] ZHUANG Yueting, WU Fei, CHEN Chun, et al. Challenges and opportunities: from big data to knowledge in AI 2.0[J]. Frontiers of Information Technology & Electronic Engineering, 2017(4): 3-14.
[15] 门理想, 王丛虎. 中国地方政府数据开放建设成效的影响因素探究——基于生态系统理论框架[J]. 现代情报, 2021,41(2):152-161. MEN Lixiang, WANG Conghu. Research on the influencing factors of Chinese local governments’ data opening[J]. Journal of Modern Information, 2021,41(2):152-161.
[16] LIU Zikui. View and comments on the data ecosystem: “ocean of data”[J]. Engineering, 2020,6(6):604-608.
[17] 刘志勇, 何忠江, 刘敬龙, 等. 统一数据湖技术研究和建设方案[J]. 电信科学, 2021,37(1):121-128. LIU Zhiyong, HE Zhongjiang, LIU Jinglong, et al. Technology research and construction scheme of unified data lake[J]. Telecommunication Science, 2021,37(1):121-128.
[18] 高伟江, 王美琴. 网络环境下基于“知识港”理论的高校图书馆建设[J]. 新世纪图书馆, 2008(2):21-24. GAO Weijiang, WANG Meiqin. Building academic library based on the theory foundation of “knowledge port” under the internet enviornment[J]. New Century Library, 2008(2): 21-24.
[19] 朱庆, 曾浩炜, 丁雨淋, 等. 重大滑坡隐患分析方法综述[J]. 测绘学报, 2019, 48(12):1551-1561. ZHU Qing, ZENG Haowei, DING Yulin, et al. A review of major potential landslide hazards analysis[J]. Acta Geodaetica et Cartographica Sinica, 2019,48(12):1551-1561.
[20] 刘峤, 李杨, 段宏, 等. 知识图谱构建技术综述[J]. 计算机研究与发展, 2016, 53(3):582-600. LIU Qiao, LI Yang, DUAN Hong, et al. Knowledge graph construction techniques[J]. Journal of Computer Research and Development, 2016,53(3):582-600.
[21] TRIVEDI R, DAI H, WANG Y, et al. Know-evolve: deep temporal reasoning for dynamic knowledge graphs[C]//Proceedings of 2017 International Conference on Machine Learning (ICML). Sydney:[s.n.], 2017: 3462-3471.
[22] 王家耀. 时空大数据时代的地图学[J]. 测绘学报, 2017, 46(10):1226-1237. WANG Jiayao. Cartography in the age of spatio-temporal big data[J]. Acta Geodaetica et Cartographica Sinica, 2017,46(10):1226-1237.
[23] LI Z, GAO P, XU Z. Information theory of cartography: an information-theoretic framework for cartographic communication[J]. Journal of Geodesy and Geoinformation Science, 2021,4(1):1-16.
[24] 袁国铭, 李洪奇, 樊波. 关于知识工程的发展综述[J]. 计算技术与自动化, 2011, 30(1):138-143. YUAN Guoming, LI Hongqi, FAN Bo. Survey on development of knowledge engineering system[J]. Computing Technology and Automation, 2011,30(1):138-143.
[25] 刘俊楠, 刘海砚, 陈晓慧, 等. 基于地理空间数据的知识图谱构建技术研究[J]. 中文信息学报, 2020, 34(11):33-40. LIU Junnan, LIU Haiyan, CHEN Xiaohui, et al. Construction of knowledge graph based on geo-spatial data[J]. Journal of Chinese Information Processing, 2020,34(11):33-40.
[26] SUCHANEK F M, KASNECI G, WEIKUM A G. YAGO:a large ontology from Wikipedia and wordnet[J]. Web Semantics Science Services & Agents on the World Wide Web, 2008,6(3):203-217.
[27] KARALIS N, MANDILARAS G, KOUBARAKIS M. Extending the YAGO2 knowledge graph with precise geospatial knowledge[C]//Proceedings of the 18th International Semantic Web Conference. Auckland: Springer, 2019.
[28] MAHDISOLTANI F, BIEGA J, SUCHANEK F S. YAGO3: a knowledge base from multilingual Wikipedias[C]//Proceedings of the 7th Biennial Conference on Innovative Data Systems Research. San Francisco: Springer, 2015.
[29] HOFFART J, SUCHANEK F M, BERBERICH K, et al. YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia[J]. Artificial Intelligence, 2013,194(1):28-61.
[30] 马忠贵, 倪润宇, 余开航. 知识图谱的最新进展、关键技术和挑战[J]. 工程科学学报, 2020, 42(10):1254-1266. MA Zhonggui, NI Runyu, YU Kaihang. Recent advances, key techniques and future challenges of knowledge graph[J]. Chinese Journal of Engineering, 2020,42(10):1254-1266.
[31] 陆峰, 余丽, 仇培元. 论地理知识图谱[J]. 地球信息科学学报, 2017, 19(6):723-734. LU Feng, YU Li, QIU Peiyuan. On geographic knowledge graph[J]. Journal of Geo-information Science, 2017,19(6):723-734.
[32] 邱均平. 专题——知识组织的热点与前沿[J]. 情报理论与实践, 2015, 38(1):1. QIU Junping. Topic: hotspots and frontiers of knowledge organization[J]. Information Studies: Theory & Application, 2015,38(1):1.
[33] 王昊奋, 漆桂林, 陈华钧. 知识图谱:方法、实践与应用[M].北京: 电子工业出版社, 2020. WAN Haofen, QI Guilin, CHEN Huajun. Knowledge graph: method, practice and application[M]. Beijing: Publishing House of Electronics Industry, 2020.
[34] 闾国年, 袁林旺, 俞肇元. 地理学视角下测绘地理信息再透视[J]. 测绘学报, 2017,46(10):1549-1556. LÜ Guonian, YUAN Linwang, YU Zhaoyuan. Surveying and mapping geographical information from the perspective of geography[J]. Acta Geodaetica et Cartographica Sinica, 2017,46(10):1549-1556.
[35] 任加新, 刘万增, 李志林, 等. 利用卷积神经网络进行“问题地图”智能检测[J]. 武汉大学学报(信息科学版), 2020, 46(4):1-9. REN Jiaxin, LIU Wanzeng, LI Zhilin, et al. Intelligent detection of “problematic map” using convolutional neural network[J]. Geomatics and Information Science of Wuhan University, 2020, 46(4):1-9.