Progresses and Prospects in Geospatial Big Data for E-government

doi:10.11947/j.AGCS.2017.20170320

Abstract

Abstract: In recent years, geospatial big data have attracted great attention from industry, academia, research and government sectors, and even have triggered a lot of industry changes. Geospatial big data for E-government provide new means for government information management and decision making. This paper analyzes the concepts and characteristics of geospatial big data for E-government, mainly reviews the key technologies in geospatial big data for E-government, including data integration, storage and management, data mining and analysis, visualization, and decision support service technologies. Finally, the bottleneck problems and technical challenges of geospatial big data for E-government are discussed.

Key words: geospatial big data for E-government, data integration, storage and management, data analysis and data mining, visualization, decision support service technologies

CLC Number:

P208

LIU Jiping, ZHANG Fuhao, XU Shenghua. Progresses and Prospects in Geospatial Big Data for E-government[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1678-1687.

References

[1] DOCTOROW C. Big Data:Welcome to the Petacentre[J]. Nature, 2008, 455(7209):16-21.
[2] REICHMAN O J, JONES M B, SCHILDHAUER M P. Challenges and Opportunities of Open Data in Ecology[J]. Science, 2011, 331(6018):703-705.
[3] ZHENG Yu, CAPRA L, WOLFSON O, et al. Urban Computing:Concepts, Methodologies, and Applications[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2014, 5(3):38.
[4] ZHENG Yu. Trajectory Data Mining:An Overview[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2015, 6(3):29.
[5] ZHENG Yu. Methodologies for Cross-domain Data Fusion:An Overview[J]. IEEE Transactions on Big Data, 2015, 1(1):16-34.
[6] 刘纪平, 刘钊, 王亮. 基于功能协同的电子政务空间信息服务[J]. 测绘学报, 2006, 35(4):299-302. LIU Jiping, LIU Zhao, WANG Liang. Research on the Spatial Information Service for E-government Based on Function Collaboration[J]. Acta Geodaetica et Cartographica Sinica, 2006, 35(4):299-302.
[7] 刘纪平, 张福浩, 王亮, 等. 面向大数据的空间信息决策支持服务研究与展望[J]. 测绘科学, 2014, 39(5):8-12, 17. LIU Jiping, ZHANG Fuhao, WANG Liang, et al. Research and Prospect on Spatial Decision Support Service Based on Big Data[J], Science of Surveying and Mapping, 2014, 39(5):8-12, 17.
[8] LIU J P, XU S H, ZHANG F H, et al. Research and Implementation of Government Geographic Information Service Platform[J]. Journal of Earth Science and Engineering, 2011, 1(2):48-54.
[9] 刘纪平, 张福浩, 王亮, 等. 电子政务地理信息服务[M]. 北京:测绘出版社, 2014. LIU Jiping, ZHANG Fuhao, WANG Liang, et al. Geographic Information Service for E-government[M]. Beijing:Surveying and Mapping Press, 2014.
[10] 赵彬彬. 多尺度矢量地图空间目标匹配方法及其应用研究[D]. 长沙:中南大学, 2011. ZHAO Binbin. A Study on Multi-scale Vector Map Objects Matching Method and Its Application[D]. Changsha:Central South University, 2011.
[11] 张云菲. 多源道路网与兴趣点的一致性整合方法[D]. 武汉:武汉大学, 2015. ZHANG Yunfei. Methods for Congruent Conflation of Multi-source Road Networks and POIs[D]. Wuhan:Wuhan University, 2015.
[12] SAALFELD A. Conflation Automated Map Compilation[J]. International Journal of Geographical Information Systems, 1988, 2(3):217-228.
[13] MICHALOWSKI M, AMBITE J L, THAKKAR S, et al. Retrieving and Semantically Integrating Heterogeneous Data from the Web[J]. IEEE Intelligent Systems, 2004, 19(3):72-79.
[14] LONGLEY P A, GOODCHILD M F, MAGUIRE D J, et al. Geographic Information Systems and Science[M]. 2nd ed.[S.l.]:John Wiley & Sons, 2005.
[15] CASADO M L. Some Basic Mathematical Constraints for the Geometric Conflation Problem[C]//Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. Lisboa:Instituto Geográfico Português, 2006:264-274.
[16] HEARST M A, LEVY A Y, KNOBLOCK C, et al. Information Integration[J]. IEEE Intelligent Systems and Their Applications, 1998, 13(5):12-24.
[17] MAY W, LAUSEN G. A Uniform Framework for Integration of Information from the Web[J]. Information Systems, 2004, 29(1):59-91.
[18] SESTER M, VON GÖSSELN G, KIELER B. Identification and Adjustment of Corresponding Objects in Data sets of Different Origin[C]//Proceedings of the 10th AGILE International Conference on Geographic Information Science. Denmark:Aalborg University, 2007.
[19] DALYOT S, DAHINDEN T, SCHULZE M J, et al. Integrating Network Structures of Different Geometric Representations[J]. Survey Review, 2013, 45(333):428-440.
[20] 陈军, 王东华, 商瑶玲, 等. 国家1:50000数据库更新工程总体设计研究与技术创新[J]. 测绘学报, 2010, 39(1):7-10. CHEN Jun, WANG Donghua, SHANG Yaoling, et al. Master Design and Technical Development for National 1:50000 Topographic Data-Base Updating Engineering in China[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(1):7-10.
[21] DOERR M, HUNTER J, LAGOZE C. Towards A Core Ontology for Information Integration[J]. Journal of Digital Information, 2003, 4(1).
[22] BUTENUTH M, GÖSSELN G V, TIEDGE M, et al. Integration of Heterogeneous Geospatial Data in a Federated Database[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2007, 62(5):328-346.
[23] 谢潇. 语义感知的地理视频大数据自适应关联组织方法[J]. 测绘学报, 2016, 45(10):1260. DOI:10.11947/j.AGCS.2016.20160327. XIE Xiao. A Semantics-aware Self-adaptive Associated Organization Method of GeoVideo Big Data[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(10):1260. DOI:10.11947/j.AGCS.2016.20160327.
[24] 唐炉亮, 杨雪, 牛乐, 等. 一种众源车载GPS轨迹大数据自适应滤选方法[J]. 测绘学报, 2016, 45(12):1455-1463. DOI:10.11947/j.AGCS.2016.20160117. TANG Luliang, YANG Xue, NIU Le, et al. An Adaptive Filtering Method Based on Crowdsourced Big Trace Data[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(12):1455-1463. DOI:10.11947/j.AGCS.2016.20160117.
[25] ZHENG Yu, XIE Xing, MA Weiying. GeoLife:A Collaborative Social Networking Service among User, Location and Trajectory[J]. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 2010, 33(2):32-39.
[26] DU Heshan, ANAND S, ALECHINA N, et al. Geospatial Information Integration for Authoritative and Crowd Sourced Road Vector Data[J]. Transactions in GIS, 2012, 16(4):455-476.
[27] LI Jun, QIN Qiming, HAN Jiawei, et al. Mining Trajectory Data and Geotagged Data in Social Media for Road Map Inference[J]. Transactions in GIS, 2015, 19(1):1-18.
[28] 范建永, 龙明, 熊伟. 基于HBase的矢量空间数据分布式存储研究[J]. 地理与地理信息科学, 2012, 28(5):39-42. FAN Jianyong, LONG Ming, XIONG Wei. Research of Vector Spatial Data Distributed Storage Based on HBase[J]. Geography and Geo-Information Science, 2012, 28(5):39-42.
[29] WANG Yonggang, WANG Sheng. Research and Implementation on Spatial Data Storage and Operation Based on Hadoop Platform[C]//Proceedings of the 2nd ⅡTA International Conference on Geoscience and Remote Sensing. Qingdao:IEEE, 2010:275-278.
[30] GUNARATHNE T, WU T L, QIU J, et al. MapReduce in the Clouds for Science[C]//Proceedings of the 2nd International Conference on Cloud Computing Technology and Science. Indianapolis:IEEE, 2010:565-572.
[31] DUTTA H, KAMIL A, POOLEERY M, et al. Distributed Storage of Large-scale Multidimensional Electroencephalogram Data Using Hadoop and HBase[M]//FIORE S, ALOISIO G. Grid and Cloud Database Management. Berlin Heidelberg:Springer, 2011:331-347.
[32] 丁琛. 基于HBase的空间数据分布式存储和并行查询算法研究[D]. 南京:南京师范大学, 2014. DING Chen. Research on Distributed Storage and Parallel Query Algorithm of Spatial Data in HBase[J]. Nanjing:Nanjing Normal University, 2014.
[33] THUSOO A, SARMA J S, JAIN N, et al. Hive:A Warehousing Solution over a Map-reduce Framework[J]. Proceedings of the VLDB Endowment, 2009, 2(2):1626-1629.
[34] HAN Bo, ZHANG Yanxia, ZHONG Shoubo, et al. Astronomical Data Fusion Tool Based on PostgreSQL[J]. Research in Astronomy and Astrophysics, 2016, 16(11):178.
[35] JAYALAKSHMI T S, CHETHANA C. A Semantic Search Engine for Indexing and Retrieval of Relevant Text Documents[J]. International Journal of Advance Research in Computer Science and Management Studies, 2016, 4(5):7-11.
[36] 王珊, 王会举, 覃雄派, 等. 架构大数据:挑战、现状与展望[J]. 计算机学报, 2011, 34(10):1741-1752. WANG Shan, WANG Huiju, QIN Xiongpai, et al. Architecting Big Data:Challenges, Studies and Forecasts[J]. Chinese Journal of Computers, 2011, 34(10):1741-1752.
[37] TerraFly[EB/OL]. http://www.TerraFly.FIU.edu.
[38] AJI A, WANG Fusheng. High Performance Spatial Query Processing for Large Scale Scientific Data[C]//Proceedings of the on SIGMOD/PODS 2012 PhD Symposium. Scottsdale, Arizona, USA:ACM, 2012:9-14.
[39] 张书彬, 韩冀中, 刘志勇, 等. 基于MapReduce实现空间查询的研究[J]. 高技术通讯, 2010, 20(7):719-726. ZHANG Shubin, HAN Jizhong, LIU Zhiyong, et al. Research on Implementing Spatial Queries Based on MapReduce[J]. Chinese High Technology Letters, 2010, 20(7):719-726.
[40] TAO Yufei, SHENG Cheng, PEI Jian. On K-skip Shortest Paths[C]//Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data. Athens, Greece:ACM, 2011:421-432.
[41] TAO Yufei, HU Xiaocheng, CHOI D W, et al. Approximate MaxRS in Spatial Databases[J]. Proceedings of the VLDB Endowment, 2013, 6(13):1546-1557.
[42] 李德仁, 王树良, 李德毅. 空间数据挖掘理论与应用[M]. 2版. 北京:科学出版社, 2013. LI Deren, WANG Shuliang, LI Deyi. Spatial Data Mining Theory and Application[J]. 2nd ed. Beijing:Science Press, 2013.
[43] 王树良, 丁刚毅, 钟鸣. 大数据下的空间数据挖掘思考[J]. 中国电子科学研究院学报, 2013, 8(1):8-17. WANG Shuliang, DING Gangyi, ZHONG Ming. On Spatial Data Mining under Big Data[J]. Journal of China Academy of Electronics and Information Technology, 2013, 8(1):8-17.
[44] ZHANG Junbo, ZHENG Yu, QI Dekang. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction[C]//Proceedings of the 31st AAAI Conference on Artificial Intelligence. San Francisco, California, USA:AAAI, 2017.
[45] LUO Ping, LIN Fen, XIONG Yuhong, et al. Towards Combining Web Classification and Web Information Extraction:A Case Study[C]//Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Paris, France:ACM, 2009:1235-1244.
[46] 奚雪峰, 周国栋. 面向自然语言处理的深度学习研究[J]. 自动化学报, 2016, 42(10):1445-1465. XI Xuefeng, ZHOU Guodong. A Survey on Deep Learning for Natural Language Processing[J]. Acta Automatica Sinica, 2016, 42(10):1445-1465.
[47] 陈岚. 基于因子分析和聚类分析的省级政府门户网站评估[J]. 电子政务, 2010(2):95-100. CHEN Lan. Evaluation of Provincial Government Portal Based on Factor Analysis and Cluster Analysis[J]. E-Government, 2010(2):95-100.
[48] 何占军, 刘启亮, 邓敏, 等. 显著空间同位模式的多尺度挖掘方法[J]. 测绘学报, 2016, 45(11):1335-1341. DOI:10.11947/j.AGCS.2016.20150371. HE Zhanjun, LIU Qiliang, DENG Min, et al. A Multi-scale Method for Mining Significant Spatial Co-location Patterns[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(11):1335-1341. DOI:10.11947/j.AGCS.2016.20150371.
[49] 赵仲秋, 季海峰, 高隽, 等. 基于稀疏编码多尺度空间潜在语义分析的图像分类[J]. 计算机学报, 2014, 37(6):1251-1260. ZHAO Zhongqiu, JI Haifeng, GAO Jun, et al. Sparse Coding Based Multi-scale Spatial Latent Semantic Analysis for Image Classification[J]. Chinese Journal of Computers, 2014, 37(6):1251-1260.
[50] LIU Jiping, XU Shenghua, ZHANG Fuhao, et al. A Hybrid Genetic-ant Colony Optimization Algorithm for the Optimal Path Selection[J]. Intelligent Automation & Soft Computing, 2017, 23(2):235-242.
[51] LIU Jiping, YANG Yi, XU Shenghua, et al. A Geographically Temporal Weighted Regression Approach with Travel Distance for House Price Estimation[J]. Entropy, 2016, 18(8):303.
[52] 赵阳阳, 刘纪平, 徐胜华, 等. 一种基于半监督学习的地理加权回归方法[J]. 测绘学报, 2017, 46(1):123-129. DOI:10.11947/j.AGCS.2017.20150470. ZHAO Yangyang, LIU Jiping, XU Shenghua, et al. A Geographic Weighted Regression Method Based on Semi-Supervised Learning[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(1):123-129. DOI:10.11947/j.AGCS.2017.20150470.
[53] 胡庆武, 王明, 李清泉. 利用位置签到数据探索城市热点与商圈[J]. 测绘学报, 2014, 43(3):314-321. DOI:10.13485/j.cnki.11-2089.2014.0045. HU Qingwu, WANG Ming, LI Qingquan. Urban Hotspot and Commercial Area Exploration with Check-in Data[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(3):314-321. DOI:10.13485/j.cnki.11-2089.2014.0045.
[54] KEIM D, QU Huamin, MA K L. Big-data Visualization[J]. IEEE Computer Graphics and Applications, 2013, 33(4):20-21.
[55] HEY T, GANNON D, PINKELMAN J. The Future of Data-intensive Science[J]. Computer, 2012, 45(5):81-82.
[56] DEMAR U, VIRRANTAUS K. Space-time Density of Trajectories:Exploring Spatio-Temporal Patterns in Movement Data[J]. International Journal of Geographical Information Science, 2010, 24(10):1527-1542.
[57] TOMINSKI C, SCHUMANN H, ANDRIENKO G, et al. Stacking-based Visualization of Trajectory Attribute Data[J]. IEEE Transactions on visualization and Computer Graphics, 2012, 18(12):2565-2574.
[58] VIEGAS F B, WATTENBERG M, FEINBERG J. Participatory Visualization with Wordle[J]. IEEE Transactions on Visualization and Computer Graphics, 2009, 15(6). DOI:10.1109/TVCG.2009.171.
[59] CUI Weiwei, WU Yingcai, LIU Shixia, et al. Context Preserving Dynamic Word Cloud Visualization[C]//Proceedings of 2010 IEEE Pacific Visualization Symposium. Taipei:IEEE, 2010:121-128.
[60] GOU Liang, ZHANG Xiaolong. TreeNetViz:Revealing Patterns of Networks over Tree Structures[J]. IEEE Transactions on Visualization and Computer Graphics, 2011, 17(12):2449-2458.
[61] 任磊, 王威信, 滕东兴, 等. 面向海量层次信息可视化的嵌套圆鱼眼视图[J]. 计算机辅助设计与图形学学报, 2008, 20(3):298-303, 309. REN Lei, WANG Weixin, TENG Dongxing, et al. Fisheye View for Visualization of Large Tree by Packing Nested Circles[J]. Journal of Computer-Aided Design & Computer Graphics, 2008, 20(3):298-303, 309.
[62] SELASSIE D, HELLER B, HEER J. Divided Edge Bundling for Directional Network Data[J]. IEEE Transactions on Visualization and Computer Graphics, 2011, 17(12):2354-2363.
[63] ABELLO J, VAN HAM F, KRISHNAN N. ASK-GraphView:A Large Scale Graph Visualization System[J]. IEEE Transactions on Visualization and Computer Graphics, 2006, 12(5):669-676.
[64] SHEN Xuehua, TAN Bin, ZHAI Chengxiang. Implicit User Modeling for Personalized Search[C]//Proceedings of the 14th ACM International Conference on Information and Knowledge Management. Bremen, Germany:ACM, 2005:824-831.
[65] ZHOU Xiaoming, CONATI C. Inferring User Goals from Personality and Behavior in A Causal Model of User Affect[C]//Proceedings of the 8th International Conference on Intelligent User Interfaces. Miami, Florida, USA:ACM, 2003:211-218.
[66] LIU Fang, YU C, MENG Weiyi. Personalized Web Search by Mapping User Queries to Categories[C]//Proceedings of the 11th International Conference on Information and Knowledge Management. McLean, Virginia, USA:ACM, 2002:558-565.
[67] 林博. 基于用户查询意图识别的个性化搜索方法研究[D]. 湘潭:湘潭大学, 2015. LIN Bo. Research of Personalized Search Based on User Query Intent Identification[D]. Xiangtan:Xiangtan University, 2015.
[68] 刘纪平, 栗斌, 石丽红, 等. 一种本体驱动的地理空间事件相关信息自动检索方法[J]. 测绘学报, 2011, 40(4):502-508. LIU Jiping, LI Bin, SHI Lihong, et al. An Automated Retrieval Method of Geo-spatial Event Information Based on Ontology[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(4):502-508.
[69] 冯方向. 基于深度学习的跨模态检索研究[D]. 北京:北京邮电大学, 2015. FENG Fangxiang. Deep Learning for Cross-Modal Retrieval[J]. Beijing:Beijing University of Posts and Telecommunications, 2015.
[70] HU Jian, WANG Gang, LOCHOVSKY F, et al. Understanding User's Query Intent with Wikipedia[C]//Proceedings of the 18th International Conference on World Wide Web. Madrid:ACM, 2009:471-480.
[71] BOLLACKER K D, LAWRENCE S, GILES C L. Discovering Relevant Scientific Literature on the Web[J]. IEEE Intelligent Systems and their Applications, 2000, 15(2):42-47.
[72] SARWAR B, KARYPIS G, KONSTAN J, et al. Item-based Collaborative Filtering Recommendation Algorithms[C]//Proceedings of the 10th International Conference on World Wide Web. Hong Kong, China:ACM, 2001:285-295.
[73] WANG Hao,WANG Naiyan,YEUNG D Y.Collaborative Deep Learning For Recommender Systems[C]//Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA:ACM, 2015:1235-1244.
[74] JAMALI M, ESTER M. TrustWalker:A Random Walk Model for Combining Trust-based and Item-based Recommendation[C]//Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Paris, France:ACM, 2009:397-406.
[75] MA Hao, KING I, LYU M R. Learning to Recommend with Social Trust Ensemble[C]//Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval. Boston, MA, USA:ACM, 2009:203-210.
[76] CHENG Chen, YANG Haiqin, KING I, et al. Fused Matrix Factorization with Geographical and Social Influence in Location-based Social Networks[C]//Proceedings of the 26th AAAI Conference on Artificial Intelligence. Toronto, Ontario, Canada:AAAI, 2012(12):1.
[77] YE Mao, YIN Peifeng, LEE W C, et al. Exploiting Geographical Influence for Collaborative Point-of-interest Recommendation[C]//Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval. Beijing:ACM, 2011:325-334.