{"title":"The Model-Driven Architecture for the Trajectory Data Warehouse Modeling","authors":"Noura Azaiez, J. Akaichi","doi":"10.4018/ijdwm.2020100102","DOIUrl":null,"url":null,"abstract":"Business Intelligence includes the concept of data warehousing to support decision making. As the ETL process presents the core of the warehousing technology, it is responsible for pulling data out of the source systems and placing it into a data warehouse. Given the technology development in the field of geographical information systems, pervasive systems, and the positioning systems, the traditional warehouse features become unable to handle the mobility aspect integrated in the warehousing chain. Therefore, the trajectory or the mobility data gathered from the mobile object movements have to be managed through what is called the trajectory ELT. For this purpose, the authors emphasize the power of the model-driven architecture approach to achieve the whole transformation task, in this case transforming trajectory data source model that describes the resulting trajectories into trajectory data mart models. The authors illustrate the proposed approach with an epilepsy patient state case study.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Warehousing and Mining","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/ijdwm.2020100102","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 1
Abstract
Business Intelligence includes the concept of data warehousing to support decision making. As the ETL process presents the core of the warehousing technology, it is responsible for pulling data out of the source systems and placing it into a data warehouse. Given the technology development in the field of geographical information systems, pervasive systems, and the positioning systems, the traditional warehouse features become unable to handle the mobility aspect integrated in the warehousing chain. Therefore, the trajectory or the mobility data gathered from the mobile object movements have to be managed through what is called the trajectory ELT. For this purpose, the authors emphasize the power of the model-driven architecture approach to achieve the whole transformation task, in this case transforming trajectory data source model that describes the resulting trajectories into trajectory data mart models. The authors illustrate the proposed approach with an epilepsy patient state case study.
期刊介绍:
The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving