Please wait a minute...
img img
高级检索
地球科学进展  2005, Vol. 20 Issue (2): 166-172    DOI: 10.11867/j.issn.1001-8166.2005.02.0166
研究论文     
地学数据产品的开发、发布与共享
廖顺宝,孙九林,李泽辉,马 琳,彭 梅
中国科学院地理科学与资源研究所,北京 100101
DEVELOPMENT, PUBLISHING AND SHARING OF DATA PRODUCTS FOR GEO-SCIENCES
LIAO Shunbao; SUN Jiulin; LI Ze-hui; MA Lin; PENG Mei
Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
 全文: PDF(230 KB)  
摘要:

数据是科学研究的基础,数据共享可以最大程度地发挥数据的使用价值,数据是实现数据共享最基本的要素。地学数据具有空间性、综合性、时间性、海量性、多源性等特点。属性数据、遥感数据、矢量数据是加工生产地学数据产品的重要数据源,属性数据空间化是加工、生产地学数据产品的重要技术手段。地学数据共享发布平台应当具备用户管理、数据目录查询、元数据管理、数据查询与浏览、数据下载等基本功能。推进科学数据共享,必须要有相应的政策措施保证,必须建立公正、合理的数据工作评价体系。

关键词: 地学数据开发共享    
Abstract:

Data is the foundation of scientific research, and in the mean time, it is the result of scientific research. Data sharing can make data more usefully valuable to a great extent. Data sharing is a systematic engineering which includes not only data itself but also software platform for data sharing, technical standards, sharing policy, administrative mechanism and data service. Data is the most basic and important element in data sharing engineering. Geo-science data have attributes of space, time, integration, great capacity and multi-sources. It is costly work to capture geo-science data. Therefore, it is more necessary to share them among different organizations or scientists. Tabular data, remotely sensed data and vector data are most important and often used types of geo-science data. Because of limitations of various kinds of original data, such as statistical data, remotely sensed spectral data(e.g. TM, NOAA-AVHRR,MODIS), map data and so on, besides them, series of data sets should be developed to meet the need of basic and forward research for geo-science. By means of spatialisation technique, observed data from observation stations can be used to calculate data in areas without observation stations and statistical data from administrative divisions can be re-assigned to regular grid, for example, one kilometer by one kilometer. Through various algorithms, remotely sensed spectral data can be used to produce data sets with obvious geo-science sense, for example, Vegetation Index (VI) and Net Primary Production(NPP).The software platform is important technological support for geo-science data sharing. It should be easy to use and include the following fundamental functions: (a) users management; (b) data catalogue query; (c) metadata management; (d) data query and view; and (e) data download.In order to promote scientific data sharing, relevant policies, measures and standards should be drawn up. Reasonable appraising system for people who are engaged in work of data should be set up to encourage they devote themselves to data sharing. 

Key words: Geo-sciences    Data    Production    Sharing.
收稿日期: 2003-11-10 出版日期: 2005-02-25
:  TP75  
基金资助:

国家科学数据共享工程项目“中国地球系统科学数据共享服务网建设”(编号:2003DEA2C010);中国科学院知识创新工程项目“中国自然资源数据库”(编号:INF105-SDB-1-18)资助.

通讯作者: 廖顺宝     E-mail: liaosb@igsnrr.ac.cn
作者简介: 廖顺宝(1966-),男,四川德阳人,副研究员,主要从事遥感与地理信息系统应用以及地学数据产品开发方面的研究.Email:liaosb@igsnrr.ac.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
廖顺宝
彭梅
孙九林
马琳
李泽辉

引用本文:

廖顺宝;孙九林;李泽辉;马琳;彭梅. 地学数据产品的开发、发布与共享[J]. 地球科学进展, 2005, 20(2): 166-172.

LIAO Shunbao;SUN Jiulin;LI Ze-hui;MA Lin;PENG Mei. DEVELOPMENT, PUBLISHING AND SHARING OF DATA PRODUCTS FOR GEO-SCIENCES. Advances in Earth Science, 2005, 20(2): 166-172.

链接本文:

http://www.adearth.ac.cn/CN/10.11867/j.issn.1001-8166.2005.02.0166        http://www.adearth.ac.cn/CN/Y2005/V20/I2/166

[1]Liao Shunbao.Scientific data sharing and its solutions based on internet[J].Science & Technology Review,2002:(1):25-27.[廖顺宝.科学数据共享及其在互联网上实现的技术途径[J].科技导报,2002,(1):25-27.]
[2]Sun Shu.Learn new things by reviewing the past, carry on the past and open a way for future-A special issue of review and forecast on subjects related to geoscience(preface)[J] .Advances in Earth Science,2001,16(5):597-598.[孙枢.温故知新继往开来——地球科学有关学科回顾与展望专辑(序)[J].地球科学进展,2001,16(5):597-598.]
[3]Liao Shunbao, Sun Jiulin.GIS based spatialisation of population census data in Qinghai-Tibet Plateau[J].Acta Geographica Sinica,2003,58(1):25-33.[廖顺宝,孙九林.基于GIS的青藏高原人口统计数据空间化[J].地理学报,2003,58(1):25-33.]
[4]Liao Shunbao, Li Zehui.Study on spatialisation of population census data based on relationship between population distribution and land use-Taking Tibet as an example[J].Journal of Natural Resources,2003,(6):659-665.[廖顺宝,李泽辉.基于人口分布与土地利用关系的人口数据空间化研究——以西藏自治区为例[J].自然资源学报,2003,(6):659-665.]
[5]Liao Shunbao, Li Zehui .A methodology of spatialisation of observed data based on GIS[J].Progress in Geography,2003,22(1):87-93.[廖顺宝,李泽辉.基于GIS的定位观测数据空间化[J].地理科学进展,2003,22(1):87-93.]
[6]Sun Jiabing, Shu Ning, Guan Zequn.Fundamentals, Methods and Application of Remote Sensing [M].Beijing: Publishing House of Survey and Mapping,1997.[孙家柄,舒宁,关泽群.遥感原理、方法和应用[M].北京:测绘出版社,1997.]
[7]Zheng Du.Forming Environment and Development of Qinghai-Tibet Plateau[M] .Shijiazhuang: Hebei Publishing House of Science and Technology,2003.[郑度.青藏高原形成环境与发展[M].石家庄:河北科学技术出版社,2003.]
[8]Liu Chuang, Ge Chenghui.Characteristics and application of remote sensed data from U.S. EOS-MODIS[J].Remete Sensing Information,2000,(3):45-48.[刘闯,葛成辉.美国对地观测系统(EOS)中分辨率成像光谱仪(MODIS)遥感数据的特点与应用[J].遥感信息,2000,(3):45-48.]
[9]Yin Gongbai, Wang Jiayao,Tian Desen, et al.Tian Desen,An Introduction to Map[M].Beijing: Publishing House of Survey and Mapping,1991.[尹贡白,王家耀,田德森,等.地图概论[M].北京:测绘出版社,1991.]
[10]Zhao Junxi, Liu Honglin.Usually used theories and methods for study on spatial data quality[J].Map,2001,(4):16-18 .[赵军喜,刘宏林.研究空间数据质量的常用理论和方法[J].地图,2001,(4):16-18 .]

[1] 张小双, 刘洁. 岩石圈三维结构模型综合与可视化——以青藏高原东缘为例[J]. 地球科学进展, 2017, 32(9): 996-1005.
[2] 王根, 张华, 杨寅. 高光谱大气红外探测器AIRS资料质量控制研究进展[J]. 地球科学进展, 2017, 32(2): 139-150.
[3] 张春灌, 袁炳强, 张国利. 最新全球重力数据库V23中陆域重力资料质量评估[J]. 地球科学进展, 2017, 32(1): 75-82.
[4] 范小杉, 何萍, 董敬儒. 基于项目可持续发展规划的海岸带生态承载力评价研究进展[J]. 地球科学进展, 2017, 32(1): 90-100.
[5] 葛人峰, 侍茂崇. “船时共享航次计划”——国家自然科学基金委员会的重大创建[J]. 地球科学进展, 2016, 31(4): 428-435.
[6] 邬群勇, 孙梅, 崔磊. 时空数据模型研究综述[J]. 地球科学进展, 2016, 31(10): 1001-1011.
[7] 杨婧, 王金荣, 张旗, 陈万峰, 潘振杰, 焦守涛, 王淑华. 弧后盆地玄武岩(BABB)数据挖掘:与MORB及IAB的对比[J]. 地球科学进展, 2016, 31(1): 66-77.
[8] 杨秋明. 10~30 d延伸期天气预报方法研究进展与展望[J]. 地球科学进展, 2015, 30(9): 970-984.
[9] 谢榕, 刘亚文, 李翔翔. 大数据环境下卫星对地观测数据集成系统的关键技术[J]. 地球科学进展, 2015, 30(8): 855-862.
[10] 兰鑫宇, 郭子祺, 田野, 雷霞, 王婕. 土壤湿度遥感估算同化研究综述[J]. 地球科学进展, 2015, 30(6): 668-679.
[11] 刘仲兰, 李江海, 姜佳奇, 于涵. 四川峨眉山地质遗迹及其地学意义[J]. 地球科学进展, 2015, 30(6): 691-699.
[12] 毛伏平, 张述文, 叶丹, 杨茜茜. 模式时间关联误差对集合平方根滤波估算土壤湿度的影响[J]. 地球科学进展, 2015, 30(6): 700-708.
[13] 韩成鸣, 李耀东, 史小康. 云分析预报方法研究进展[J]. 地球科学进展, 2015, 30(4): 505-516.
[14] 郭晨, 秦勇, 卢玲玲. 黔西红梅井田煤层气有序开发的水文地质条件[J]. 地球科学进展, 2015, 30(4): 456-464.
[15] 陆志翔, 肖洪浪, 邹松兵, 任娟, 张志强. 黑河流域近两千年人—水—生态演变研究进展[J]. 地球科学进展, 2015, 30(3): 396-406.