国家重要监测数据整合平台的建设
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摘要
目的开发国家重要监测数据整合平台。方法基于数据的时空特征和生物学特征,采用J2EE(Java2平台企业版)体系的B/S(浏览器/服务器)架构设计和JAVA编程技术开发平台。结果实现了多源、多尺度的重要病媒生物、重要病媒传染病、入侵动植物、病原微生物、生物安全组学等国家重要监测数据的查询与可视化平台开发,平台主要功能包括平台介绍、分类数据库查询可视化、数据整合查询可视化、登革热预测预警等功能。结论国家重要监测数据整合平台的建设,有利于解决数据标准不一、管理分散、质量参差不齐等问题,有利于多部门、多单位之间数据交换和共享。
Objective To construct a national important surveillance data integration platform. Methods Based on the spatiotemporal characteristics and biological characteristics of national important surveillance data, the B/S(browser/server)architecture design and JAVA programming technology development platform of J2 EE(Java 2 Platform Enterprise Edition)system were adopted to construct this platform. Results A query and visualization platform of national important surveillance data such as multi-source and multi-scale important vector data, important vector-borne diseases, invasive animals and plants, pathogenic microorganisms, and biosafety profile was developed. The main functions of the platform included platform introduction, sub-database query and visualization, data integration query and visualization, and dengue fever prediction and early warning. Conclusion The construction of a national important surveillance data integration platform helps to solve problems such as different data standards, decentralized management, and uneven quality. It is conducive to better data exchange and sharing between multiple departments and multiple units.
Objective To construct a national important surveillance data integration platform. Methods Based on the spatiotemporal characteristics and biological characteristics of national important surveillance data, the B/S(browser/server)architecture design and JAVA programming technology development platform of J2 EE(Java 2 Platform Enterprise Edition)system were adopted to construct this platform. Results A query and visualization platform of national important surveillance data such as multi-source and multi-scale important vector data, important vector-borne diseases, invasive animals and plants, pathogenic microorganisms, and biosafety profile was developed. The main functions of the platform included platform introduction, sub-database query and visualization, data integration query and visualization, and dengue fever prediction and early warning. Conclusion The construction of a national important surveillance data integration platform helps to solve problems such as different data standards, decentralized management, and uneven quality. It is conducive to better data exchange and sharing between multiple departments and multiple units.
引文
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[15]邹晓妮,吴菲,李静静,等.医院内法定传染病信息推送平台开发与实现[J].中国卫生信息管理,2014,11(6):596-601.
[16]李梅,苗润莲,张岸,等.基于GIS的京津冀科技资源数字地图服务平台构建[J].现代情报,2017,37(6):172-177. DOI:10.3969/j.issn.1008-0821.2017.06.028.
[17]唐健,沈陈华,周国峰,等.国土资源数据整合方案设计及其实现研究[J].中国土地科学,2009,23(9):72-78. DOI:10.3969/j.issn.1001-8158.2009.09.014.
[2]黄华南.基于GIS的国土房产数据整合方案设计[J].测绘通报,2007(10):64-66. DOI:10.3969/j.issn.0494-0911.2007.10.020.
[3]张李军,刘寿福,黄东海,等.南京市城乡地籍数据整合若干问题探讨[J].安徽农业科学,2015,43(1):295-297. DOI:10.3969/j.issn.0517-6611.2015.01.101.
[4]荣芳.基于数据整合的地籍信息系统设计与实现[J].地理空间信息,2015,13(6):36-37,43. DOI:10.3969/j.issn.1672-4623.2015.06.012.
[5]刘志杰,金秉福,张瑞端,等.海底沉积物碎屑矿物数据整合技术研究[J].海洋通报,2015,34(6):657-662. DOI:10.11840/j.issn.1001-6392.2015.06.008.
[6] Ma Z,Hart MM,Redmond RL. Mapping vegetation across large geographic areas:integration of remote sensing and GIS to classify multisource data[J]. Photogramm Eng Remote Sens,2001,67(3):295-307.
[7]李勇,包世泰,周品,等. ECDIS与GIS数据集成研究[J].测绘科学,2007,32(4):135-137. DOI:10.3771/j.issn.1009-2307.2007.04.050.
[8] Karnatak HC,Shukla R,Sharma VK,et al. Spatial mashup technology and real time data integration in geo-web application using open source GIS-a case study for disaster management[J].Geocarto Int,2012,27(6):499-514. DOI:10.1080/10106049.2011.650651.
[9] Salleh SA,Hamid JRA,Ariffin IM. Investigation of potential integration of spectroradiometer data with GIS technology:the spectro-GIS tools[J]. IOP Conf Ser Earth Environ Sci,2014,18(1):012053. DOI:10.1088/1755-1315/18/1/012053.
[10] Goble C,Stevens R. State of the nation in data integration for bioinformatics[J]. J Biomed Inform,2008,41(5):687-693.DOI:10.1016/j.jbi.2008.01.008.
[11] Seoane JA,Aguiar-Pulido V,Munteanu CR,et al. Biomedical data integration in computational drug design and bioinformatics[J]. Curr Comput Aided Drug Des,2013,9(1):108-117. DOI:10.2174/15734099112089990011.
[12] Fagan A,Culhane AC,Higgins DG. A multivariate analysis approach to the integration of proteomic and gene expression data[J]. Proteomics,2007,7(13):2162-2171. DOI:10.1002/pmic.200600898.
[13] Rezola A,Pey J,Tobalina L,et al. Advances in network-based metabolic pathway analysis and gene expression data integration[J]. Brief Bioinform,2015,16(2):265-279. DOI:10.1093/bib/bbu009.
[14] de la Prieta F,Rodríguez S,Bajo J,et al. Data integration in cloud computing environment[C]//Proceedings of the 4th International Workshop on Knowledge Discovery,Knowledge Management and Decision Support. Mazatlan,Mexico:Atlantis Press,2013:180-185.
[15]邹晓妮,吴菲,李静静,等.医院内法定传染病信息推送平台开发与实现[J].中国卫生信息管理,2014,11(6):596-601.
[16]李梅,苗润莲,张岸,等.基于GIS的京津冀科技资源数字地图服务平台构建[J].现代情报,2017,37(6):172-177. DOI:10.3969/j.issn.1008-0821.2017.06.028.
[17]唐健,沈陈华,周国峰,等.国土资源数据整合方案设计及其实现研究[J].中国土地科学,2009,23(9):72-78. DOI:10.3969/j.issn.1001-8158.2009.09.014.
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