顾及信誉的众源时空数据模型  

Crowdsourcing Spatio-Temporal Data Model Considering Reputation

作　　者：周晓光[1] 赵肄江[1,2] 李光强 张攀[1] 

机构地区：[1]中南大学地球科学与信息物理学院,湖南长沙410083 [2]湖南科技大学知识处理与网络化制造湖南省普通高校重点实验室,湖南湘潭411201

出　　处：《武汉大学学报（信息科学版）》2018年第1期10-16,共7页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(41371366)~~

摘　　要：提出了一种顾及信誉度的众源时空数据模型。在分析众源时空数据中地理要素、目标状态、对象版本、贡献者、信誉度、改变现实空间实体或信息空间对象状态的事件等要素间的相互作用机理的基础上,采用面向对象方法设计了一种顾及信誉度的众源时空数据组织方法,用UML对其进行描述,分析了与信誉度相关操作及其联动关系,得出了8条联动规则。开发了顾及信誉度的众源时空数据管理原型系统,验证了所提模型的有效性。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.

关 键 词：众源数据 信誉度 时空数据模型 版本 操作 

分 类 号：P208[天文地球—地图制图学与地理信息工程]