Crowdsourcing Spatio-Temporal Data Model Considering Reputation

ZHOU Xiaoguang; ZHAO Yijiang; LI Guangqiang; ZHANG Pan

doi:10.13203/j.whugis20150378

Volume 43 Issue 1

Jan. 2018

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2018 > 43(1): 10-16. > DOI: 10.13203/j.whugis20150378

ZHOU Xiaoguang, ZHAO Yijiang, LI Guangqiang, ZHANG Pan. Crowdsourcing Spatio-Temporal Data Model Considering Reputation[J]. Geomatics and Information Science of Wuhan University, 2018, 43(1): 10-16. DOI: 10.13203/j.whugis20150378

Citation:

PDF (3997 KB)

Crowdsourcing Spatio-Temporal Data Model Considering Reputation

1.
School of Geosciences and Info-physics, Central South University, Changsha 410083, China
2.
Key Lab of Knowledge Processing and Networked Manufacturing, Hunan University of Science and Technology, Xiangtan 411201, China

Funds:

The National Natural Science Foundation of China 41371366

More Information

Author Bio:
ZHOU Xiaoguang, PhD, professor, specializes in spatio-temporal data modelling, updating and service. E-mail:zxgcsu@foxmail.com
Corresponding author:
ZHAO Yijiang, PhD, lecturer, specializes in volunteered geographic information. E-mail: zhaoyijiang@163.com
Received Date: October 13, 2015
Published Date: January 04, 2018

Graphical Abstract

Abstract

Abstract

Crowdsourcing data are contributed by non-professionals incorporating new properties such as the contributor's reputation, ans degree of trust in the contributed geographic objects. Furthermore, a crowdsourced geographic object usually has multiple versions when it is modified by several volunteers, so a mechanism for evaluating the reputation of a contributor is an alternative way to select the most creditable version. These new issues cannot be expressed and processed in traditional spatio-temporal data models. Therefore, a new crowdsourcing spatio-temporal data model is proposed in this paper, which takes reputation into consideration. The main elements in crowdsourcing data, e.g., geographic object, object status, object version, contributor, reputation, and evenst that change the state of an entity in the real world or the object in information system and their interaction mechanisms were analyzed. An object-oriented approach was used to design a crowdsourcing data model, and a UML diagram of this crowdsourcing spatio-temporal data model considering degree of trust is presented. The reputation related operations and their linkage relationships were analyzed, and eight reputation linkage operation rules were established. A prototype system using this crowdsourcing spatio-temporal data model was developed to verify the effectiveness of the model.
- crowdsourcing data,
- trust degree,
- spatio-temporal data model,
- version,
- operation

FullText(HTML)

References (20)

References

[1]	李德仁, 钱新林.浅论自发地理信息的数据管理[J].武汉大学学报·信息科学版, 2010, 35(4):379-383 http://ch.whu.edu.cn/CN/abstract/abstract913.shtml Li Deren, Qian Xinlin. A Brief Introduction of Data Management for Volunteered Geographic Information[J].Geomatics and information science of Wuhan university, 2010, 35(4):379-383 http://ch.whu.edu.cn/CN/abstract/abstract913.shtml
[2]	Goodchild M F, Li L. Assuring the Quality of Volunteered Geographic Information[J].Spatial Statistics, 2012, 1:110-120 doi: 10.1016/j.spasta.2012.03.002
[3]	钱新林. 面向自发地理信息的空间数据表达与管理方法研究[D]. 武汉: 武汉大学, 2011 http://cdmd.cnki.com.cn/Article/CDMD-10486-1012314285.htm Qian Xinlin. Research on the Representation and Management of Geospatial Data from Volunteered Geographic Information[D]. Wuhan: Wuhan university, 2011 http://cdmd.cnki.com.cn/Article/CDMD-10486-1012314285.htm
[4]	王明, 李清泉, 胡庆武, 等.面向众源开放街道地图空间数据的质量评价方法[J].武汉大学学报·信息科学版, 2013, 38(12):1490-1494 http://ch.whu.edu.cn/CN/abstract/abstract2823.shtml Wang Ming, Li Qingquan, Hu Qingwu, et al. Quality Analysis on Crowd Sourcing Geographic Data with Open Street Map Data[J].Geomatics and information science of Wuhan university, 2013, 38(12):1490-1494 http://ch.whu.edu.cn/CN/abstract/abstract2823.shtml
[5]	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 http://d.wanfangdata.com.cn/Periodical_chxb201001002.aspx Chen Jun, Wang Donghua, Shan 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 http://d.wanfangdata.com.cn/Periodical_chxb201001002.aspx
[6]	单杰, 秦昆, 黄长青, 等.众源地理数据处理与分析方法探讨[J].武汉大学学报·信息科学版, 2014, 39(4):390-396 http://ch.whu.edu.cn/CN/abstract/abstract2966.shtml Shan Jie, Qin Kun, Huang Changqing, et al. Methods of Crowd Sourcing Geographic Data Processing and Analysis[J].Geomatics and information science of Wuhan university, 2014, 39(4):390-396 http://ch.whu.edu.cn/CN/abstract/abstract2966.shtml
[7]	Grira J, Bédard Y, Roche S. Spatial Data Uncertainty in the VGI World:Going From Consumer to Producer[J].Geomatica, 2010, 64(1):61-72 https://www.researchgate.net/profile/Yvan_Bedard/publication/268346931_Spatial_data_uncertainty_in_the_VGI_world_Going_from_consumer_to_producer/links/54e4d5d50cf276cec1726351/Spatial-data-uncertainty-in-the-VGI-world-Going-from-consumer-to-producer.pdf
[8]	Bishr M, Mantelas L. A Trust and Reputation Model for Filtering and Classifying Knowledge About Urban Growth[J]. GeoJournal, 2008, 72(3-4):229-237 doi: 10.1007/s10708-008-9182-4
[9]	Keβler C, de Groot R T A. Trust as a Proxy Measure for the Quality of Volunteered Geographic Information in the Case of OpenStreetMap[M]//Geographic information science at the heart of Europe. Berlin, Germany: Springer, 2013
[10]	赵肄江, 周晓光.地理信息志愿者信誉度评估的版本相似度模型——以面目标为例[J].测绘学报, 2015, 44(5):578-584 http://or.nsfc.gov.cn/handle/00001903-5/257288 Zhao Yijiang, Zhou Xiaoguang. Version Similarity-based Model for Volunteers' Reputation of Volunteered Geographic Information[J]. Acta Eodaetica et Cartographica Sinica, 2015, 44(5):578-584 http://or.nsfc.gov.cn/handle/00001903-5/257288
[11]	周晓光.地籍数据库增量更新[M].北京:测绘出版社, 2007 Zhou Xiaoguang. Incremental Updating of Cadastral Database[M]. Beijing:Surveying and Mapping Press, 2007
[12]	Langran G. A Review of Temporal Database Research and its Use in GIS Applications[J]. International Journal of Geographical Information System, 1989, 3(3):215-232 doi: 10.1080/02693798908941509
[13]	舒红. Gail Langran时空数据模型的统一[J].武汉大学学报·信息科学版, 2007, 32(8):723-726 http://ch.whu.edu.cn/CN/abstract/abstract1954.shtml Shu Hong. A Unification of Gail Langran's Spatio-temporal Data Models[J]. Geomatics and Information Science of Wuhan University, 2007, 32(8):723-726 http://ch.whu.edu.cn/CN/abstract/abstract1954.shtml
[14]	蒋捷, 陈军.基于事件的土地划拨时空数据库若干思考[J].测绘学报, 2000, 29(1):64-70 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=chxb200001010&dbname=CJFD&dbcode=CJFQ Jiang Jie, Chen Jun. Event-based Spatio-temporal Database Design for Land Subdivision System[J]. Acta Geodaetica et Cartographica Sinica, 2000, 29(1):64-70 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=chxb200001010&dbname=CJFD&dbcode=CJFQ
[15]	薛存金, 周成虎, 苏奋振, 等.面向过程的时空数据模型研究[J].测绘学报, 2010, 39(1):95-101 http://d.wanfangdata.com.cn/Periodical_chxb201001017.aspx Xue Cunjin, Zhou Chenghu, Su Fenzhen, et al. Research on Process-oriented Spatio-temporal Data Model[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(1):95-101 http://d.wanfangdata.com.cn/Periodical_chxb201001017.aspx
[16]	孟令奎, 赵春宇, 林志勇, 等.基于地理事件时变序列的时空数据模型研究与实现[J].武汉大学学报·信息科学版, 2003, 28(2):202-207 http://ch.whu.edu.cn/CN/abstract/abstract4821.shtml Meng Lingkui, Zhao Chunyu, Lin Zhiyong, et al. Research and Implementation of Spatio-temporal Data Model Based on Time-varying Sequence of Geographical Events[J]. Geomatics and Information Science of Wuhan University, 2003, 28(2):202-207 http://ch.whu.edu.cn/CN/abstract/abstract4821.shtml
[17]	雷起宏, 刘耀林, 尹章才, 等.基于加权图的地籍时空数据描述模型研究[J].武汉大学学报·信息科学版, 2006, 31(7):640-642 http://ch.whu.edu.cn/CN/abstract/abstract2511.shtml Lei Qihong, Liu Yaolin, Yin Zhangcai, et al. Spatio-Temporal Data Model in Cadastral Information System Based on Weighted Graph[J].Geomatics and Information Science of Wuhan University, 2006, 31(7):640-642, 652 http://ch.whu.edu.cn/CN/abstract/abstract2511.shtml
[18]	龚健雅, 李小龙, 吴华意.实时GIS时空数据模型[J].测绘学报, 2014, 43(3):226-232 https://www.wenkuxiazai.com/doc/17859b8e50e2524de5187eea-5.html Gong Jianya, Li Xiaolong, Wu Huayi. Spatio-temporal Data Model for Real-time GIS[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(3):226-232 https://www.wenkuxiazai.com/doc/17859b8e50e2524de5187eea-5.html
[19]	张恒才, 陆锋, 陈洁.移动对象时空轨迹及社交关系一体化数据模型[J].武汉大学学报·信息科学版, 2014, 39(06):711-718 http://ch.whu.edu.cn/CN/abstract/abstract3005.shtml Zhang Hengcai, Lu Feng, Chen Jie. An Integrated Data Model for Spatial-Temporal Trajectories and the Social Relationships of Moving Objects[J].Geomatics and Information Science of Wuhan University, 2014, 39(06):711-718 http://ch.whu.edu.cn/CN/abstract/abstract3005.shtml
[20]	Mooney P, Corcoran P. Characteristics of Heavily Edited Objects in OpenStreetMap[J]. Future Internet, 2012, 4(1):285-305 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.452.1174

[1]	HUO Liang, DUAN Yuanjing, ZHU Yi, SHEN Tao, ZHANG Xiaoyong, ZHAI Jialei, FU Jiying. Multi-scale Expression Method for Urban 3D Model Considering Local Features[J]. Geomatics and Information Science of Wuhan University, 2020, 45(8): 1282-1287. DOI: 10.13203/j.whugis20200148
[2]	LI Jian, ZHOU Qu, CHEN Xiaoling, TIAN Liqiao, LI Tingting. Spatial Scale Study on Quantitative Remote Sensing of Highly Dynamic Coastal/Inland Waters[J]. Geomatics and Information Science of Wuhan University, 2018, 43(6): 937-942. DOI: 10.13203/j.whugis20160174
[3]	YAN Xiongfeng, AI Tinghua, ZHANG Xiang, YANG Wei. A Vector Pyramid Model to Support Continuous Multi-scale Representation of Spatial Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(4): 502-508. DOI: 10.13203/j.whugis20150723
[4]	NIU Jiqiang, XU Feng, YAO Gaowei, FAN Yong, LIN Hao. Quantitative Evaluation Model of the Uncertainty of Multi-scale Space Topological Relations Based on Rough-Set[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 756-761, 781. DOI: 10.13203/j.whugis20140904
[5]	LIU Pengcheng, AI Tinghua, BI Xu. Multi-scale Representation Model for Contour Based on Fourier Series[J]. Geomatics and Information Science of Wuhan University, 2013, 38(2): 221-224.
[6]	YOU Hongjian. SAR Change Detection by Multi-scale Segmentation and Optimization[J]. Geomatics and Information Science of Wuhan University, 2011, 36(5): 531-534.
[7]	CHENG Changxiu. A Multi-scale Spatial Index Method[J]. Geomatics and Information Science of Wuhan University, 2009, 34(5): 597-601.
[8]	YANG Bisheng, SUN Li. Adaptive Multi-scale Visualizations of Road Network for Navigation[J]. Geomatics and Information Science of Wuhan University, 2008, 33(4): 363-366.
[9]	YANG Zuqiao, GUO Qingsheng. Multi-scale Representation of DEM Based on Lifting Scheme[J]. Geomatics and Information Science of Wuhan University, 2003, 28(4): 496-498.
[10]	WU Fan, ZHU Guorui. Multi-scale Representation and Automatic Generalization of Relief Based on Wavelet Analysis[J]. Geomatics and Information Science of Wuhan University, 2001, 26(2): 170-176.

Cited By

Cited by

Periodical cited type(15)

1.	肖泽辉，季青，庞小平，闫忠男. 利用海洋2B卫星数据反演南极海冰表面积雪厚度. 测绘地理信息. 2024(06): 64-68 .
2.	张颖，刘建强，石立坚，蒋城飞. 极地海冰观测卫星的发展现状与展望. 遥感技术与应用. 2024(06): 1339-1352 .
3.	陈国栋，陈钰，金涛勇，张志杰，李黎. 利用Cryosat-2 SAR模式数据确定北冰洋海平面模型. 大地测量与地球动力学. 2023(06): 606-611+621 .
4.	于亚冉，王丽华，张梦悦. 基于CryoSat-2的北极海冰类型分类. 测绘与空间地理信息. 2022(01): 147-150 .
5.	陈国栋，梁圣豪，孟子淇，朱家亨. 利用Cryosat-2数据确定格陵兰冰盖高程和体积变化. 苏州科技大学学报(自然科学版). 2022(01): 66-70+76 .
6.	屈猛，赵羲，庞小平，雷瑞波. 北极冰间水道区域的物理过程和遥感观测研究进展. 地球科学进展. 2022(04): 382-391 .
7.	高翔，庞小平，季青. 利用CryoSat-2测高数据研究南极威德尔海海冰出水高度时空变化. 武汉大学学报(信息科学版). 2021(01): 125-132 .
8.	张婷，张杰，张晰. 基于CryoSat-2数据的2014—2018年北极海冰厚度分析. 海洋科学进展. 2020(03): 425-434 .
9.	王志勇，王丽华，张晰，孙伟富，刘健. 雷达高度计在海冰厚度探测中的研究进展. 遥感信息. 2020(05): 1-8 .
10.	满富康，夏文韬，张杰，柯长青. 基于OSI-SAF微波遥感数据的北极一年冰和多年冰研究. 极地研究. 2019(01): 69-83 .
11.	吴星泉，张胜军，车德福. 利用CryoSat-2卫星测高资料确定北极海冰干舷高. 测绘通报. 2019(07): 64-68 .
12.	庞小平，刘清全，季青. 北极一年海冰表面积雪深度遥感反演与时序分析. 武汉大学学报(信息科学版). 2018(07): 971-977 .
13.	蒋广敏，戴利，代欣. 基于改进遗传算法的镀层氧化膜厚度测量研究. 周口师范学院学报. 2018(05): 121-124 .
14.	王蔓蔓，柯长青，邵珠德. 基于CryoSat-2卫星测高数据的北极海冰体积估算方法. 海洋学报. 2017(03): 135-144 .
15.	袁乐先，李斐，张胜凯，朱婷婷，左耀文. 利用ICESat/GLAS数据研究北极海冰干舷高度. 武汉大学学报(信息科学版). 2016(09): 1176-1182 .

Other cited types(20)

Get Citation

PDF

XML

Article views PDF downloads Cited by(35)

Crowdsourcing Spatio-Temporal Data Model Considering Reputation

Abstract

References

Related Articles

Cited by

Periodical cited type(15)

Other cited types(20)

Catalog

Related

Crowdsourcing Spatio-Temporal Data Model Considering Reputation

Abstract

References

Related Articles

Cited by

Periodical cited type(15)

Other cited types(20)

Catalog

Related

Export File

Citation

Format

Content