测绘通报 ›› 2017, Vol. 0 ›› Issue (2): 10-13,24.doi: 10.13474/j.cnki.11-2246.2017.0039

• 学术研究 • 上一篇    下一篇

构建面向个性化服务的特大城市云空间数据中心

陶迎春1,2,3, 刘光2,3, 庞京辉2,3, 吴爱华2,3, 赵凌美2,3   

  1. 1. 北京大学地球与空间科学学院, 北京 100871;
    2. 北京市测绘设计研究院, 北京 100038;
    3. 城市空间信息工程北京重点实验室, 北京 100038
  • 收稿日期:2016-05-30 出版日期:2017-02-25 发布日期:2017-03-01
  • 作者简介:陶迎春(1983-),女,博士生,工程师,主要研究方向为GIS技术。E-mail:taoyc@bism.cn
  • 基金资助:

    测绘地理信息公益性行业科研专项(201512011)

Construction of Mega City Cloud Spatial Data Center with Personalized Services

TAO Yingchun1,2,3, LIU Guang2,3, PANG Jinghui2,3, WU Aihua2,3, ZHAO Lingmei2,3   

  1. 1. Peking University, Beijing 100871, China;
    2. Beijing Institute of Surveying and Mapping, Beijing 100038, China;
    3. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100038, China
  • Received:2016-05-30 Online:2017-02-25 Published:2017-03-01

摘要:

特大城市测绘地理信息数据具有数据海量、增长快速、多源异构、频繁使用的特点。随着大数据和Web2.0时代的到来,传统的空间数据存储管理与共享服务模式存在成果缺乏整合和挖掘、空间信息服务被动且无差别性等缺点,难以满足用户不断提高的空间数据内容、服务响应速度和服务质量的要求,也难以适应因人而异的个性化空间信息服务的需求。本文对个性化服务和云空间数据中心构建的关键技术进行了研究,提出了个性化空间数据情境应用模式,以及一种基于Web客户端的个人异构空间数据在线集成方法,基于NoSQL实现了个人空间数据与传统空间数据服务集成,并以北京市为例基于私有云构建了安全可靠、高效运行、可扩展、用户参与度高、提供个性化服务的特大城市云空间数据中心。

关键词: 个性化服务, 空间数据情景式应用, 异构空间数据在线集成, 云空间数据中心

Abstract:

The geographic information data of mega city has the characteristics of massive volume, rapid accumulation, heterogeneous and being frequent used. In the era of big data and Web2.0, traditional storage and management of spatial data and sharing service mode lacks of data integration and mining, as well as passively serves customers without differences. It is difficult to meet the increasing requirements of richer spatial data content, quicker response and higher quality. And it is difficult to adapt to individualized demand of spatial information service. In this paper, the key technologies of personalized services and cloud spatial data centre construction have been researched, personalized situational data application mode is proposed, a method of online heterogeneous space data integration has been described, individual spatial data and traditional spatial data service integration is realized based on NoSQL. Taking Beijing as an example, a mega cities space cloud data centre based on private cloud has been built, which is reliable, efficient, expandable and has high participation degree and provides personalized spatial services.

Key words: personalized service, situational application of spatial data, online integration of heterogeneous spatial data, cloud spatial data centre

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