{"title":"A multi dimensional design framework for querying spatial data using concept lattice","authors":"A. Tripathy, Lizashree Mishra, P. Patra","doi":"10.1109/IADCC.2010.5422922","DOIUrl":null,"url":null,"abstract":"Data Warehouses (DWs) and On-Line Analytical Processing (OLAP) systems rely on a multidimensional model that includes dimensions and measures. Such model allows expressing users' requirements for supporting the decision-making process. Spatial related data has been used for a long time; however, spatial dimensions have not been fully exploited. To exploit the full potential of the spatial and temporal data for analysis spatial dimensions is a necessity for building a data warehouse. It has been observed that OLAP possesses a certain potential to support spatio-temporal analysis. However, without a spatial framework for viewing and manipulating the geometric component of the spatial data, the analysis remains incomplete. This paper presents a multi dimensional design framework adapted for effective spatio-temporal exploration and analysis. This includes an extension of a conceptual model with spatial dimensions to enable spatial analysis. The proposed design framework addresses the problem of spatial and temporal data integration by providing information to facilitate data analysis in a Spatial Data Warehouse (SDW) that uniformly handles all types of data.","PeriodicalId":249763,"journal":{"name":"2010 IEEE 2nd International Advance Computing Conference (IACC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 2nd International Advance Computing Conference (IACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IADCC.2010.5422922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Data Warehouses (DWs) and On-Line Analytical Processing (OLAP) systems rely on a multidimensional model that includes dimensions and measures. Such model allows expressing users' requirements for supporting the decision-making process. Spatial related data has been used for a long time; however, spatial dimensions have not been fully exploited. To exploit the full potential of the spatial and temporal data for analysis spatial dimensions is a necessity for building a data warehouse. It has been observed that OLAP possesses a certain potential to support spatio-temporal analysis. However, without a spatial framework for viewing and manipulating the geometric component of the spatial data, the analysis remains incomplete. This paper presents a multi dimensional design framework adapted for effective spatio-temporal exploration and analysis. This includes an extension of a conceptual model with spatial dimensions to enable spatial analysis. The proposed design framework addresses the problem of spatial and temporal data integration by providing information to facilitate data analysis in a Spatial Data Warehouse (SDW) that uniformly handles all types of data.