{"title":"数据库支持空间概括万维网和移动应用程序","authors":"Xiaofang Zhou, S. Prasher, M. Kitsuregawa","doi":"10.1109/WISE.2002.1181660","DOIUrl":null,"url":null,"abstract":"The need for using spatial vector data for Web-based and mobile applications has been increasing rapidly. Vector spatial data is difficult to generalise (that is, to derive a suitable level of detail, or LoD, of the data for a given application). In a client-server environment, excessive details of spatial data cannot always be appreciated on the client side, but could consume a significant amount of resources on both the server and the client side, not to mention the extra cost of data transfer. Spatial data generalisation has been investigated extensively in the area of cartography. Most cartographical generalisation algorithms, however, are post-query operations where all the data, including unneeded data, is retrieved from the database for simplification. We incorporate spatial data simplification algorithms into query processing within DBMS. This novel approach targets primarily Web-based and mobile spatial applications that stand to benefit from early data reduction. Experiments on real data reveal significant performance improvements for our approach.","PeriodicalId":392999,"journal":{"name":"Proceedings of the Third International Conference on Web Information Systems Engineering, 2002. WISE 2002.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Database support for spatial generalisation for WWW and mobile applications\",\"authors\":\"Xiaofang Zhou, S. Prasher, M. Kitsuregawa\",\"doi\":\"10.1109/WISE.2002.1181660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The need for using spatial vector data for Web-based and mobile applications has been increasing rapidly. Vector spatial data is difficult to generalise (that is, to derive a suitable level of detail, or LoD, of the data for a given application). In a client-server environment, excessive details of spatial data cannot always be appreciated on the client side, but could consume a significant amount of resources on both the server and the client side, not to mention the extra cost of data transfer. Spatial data generalisation has been investigated extensively in the area of cartography. Most cartographical generalisation algorithms, however, are post-query operations where all the data, including unneeded data, is retrieved from the database for simplification. We incorporate spatial data simplification algorithms into query processing within DBMS. This novel approach targets primarily Web-based and mobile spatial applications that stand to benefit from early data reduction. Experiments on real data reveal significant performance improvements for our approach.\",\"PeriodicalId\":392999,\"journal\":{\"name\":\"Proceedings of the Third International Conference on Web Information Systems Engineering, 2002. WISE 2002.\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third International Conference on Web Information Systems Engineering, 2002. WISE 2002.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISE.2002.1181660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third International Conference on Web Information Systems Engineering, 2002. WISE 2002.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISE.2002.1181660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Database support for spatial generalisation for WWW and mobile applications
The need for using spatial vector data for Web-based and mobile applications has been increasing rapidly. Vector spatial data is difficult to generalise (that is, to derive a suitable level of detail, or LoD, of the data for a given application). In a client-server environment, excessive details of spatial data cannot always be appreciated on the client side, but could consume a significant amount of resources on both the server and the client side, not to mention the extra cost of data transfer. Spatial data generalisation has been investigated extensively in the area of cartography. Most cartographical generalisation algorithms, however, are post-query operations where all the data, including unneeded data, is retrieved from the database for simplification. We incorporate spatial data simplification algorithms into query processing within DBMS. This novel approach targets primarily Web-based and mobile spatial applications that stand to benefit from early data reduction. Experiments on real data reveal significant performance improvements for our approach.