Conceptual Model and Design of Semantic Trajectory Data Warehouse

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING International Journal of Data Warehousing and Mining Pub Date : 2020-07-01 DOI:10.4018/ijdwm.2020070106

M. Kwakye

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引用次数: 5

Abstract

Thetrajectorypatternsofamovingobjectinaspatio-temporaldomainoffersvariedinformationin termsofthemanagementofthedatageneratedfromthemovement.Thequeryresultsoftrajectory objects from thedatawarehouse areusuallynot enough to answer certain trendbehaviours and meaningfulinferenceswithouttheassociatedsemanticinformationofthetrajectoryobjectorthe geospatialenvironmentwithinaspecifiedpurposeorcontext.Thisarticleformulatesanddesignsa genericontologymodellingframeworkthatservesasthebackgroundmodelplatformforthedesignof asemanticdatawarehousefortrajectories.Themethodologyunderpinsonhighergranularityofdata asaresultofpre-processedandextract-transformed-load(ETL)datasoastoofferefficientsemantic inferencetotheunderlyingtrajectorydata.Moreover,themodellingapproachoutlinesthethematic dimensionsthatofferadesignplatformforpredictivetrendanalysisandknowledgediscoveryinthe trajectorydynamicsanddataprocessingformovingobjects. KeyWoRDS Generic Trajectory Ontology, Multidimensional Entity Relationship, Semantic Annotations, Semantic Trajectory Data Warehouse, Spatio-Temporal Data Modelling

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语义轨迹数据仓库的概念模型与设计

Thetrajectorypatternsofamovingobjectinaspatio-temporaldomainoffersvariedinformationin termsofthemanagementofthedatageneratedfromthemovement。Thequeryresultsoftrajectory objects_从_ thedatawarehouse areusuallynot足够_回答_某些_ trendbehaviours和_ meaningfulinferenceswithouttheassociatedsemanticinformationofthetrajectoryobjectorthe geospatialenvironmentwithinaspecifiedpurposeorcontext。Thisarticleformulatesanddesignsa genericontologymodellingframeworkthatservesasthebackgroundmodelplatformforthedesignof asemanticdatawarehousefortrajectories。Themethodologyunderpinsonhighergranularityofdata asaresultofpre-processedandextract-transformed-load(ETL)datasoastoofferefficientsemantic inferencetotheunderlyingtrajectorydata。Moreover，themodellingapproachoutlinesthethematic dimensionsthatofferadesignplatformforpredictivetrendanalysisandknowledgediscoveryinthe trajectorydynamicsanddataprocessingformovingobjects。关键词:通用轨迹本体，多维实体关系，语义标注，语义轨迹数据仓库，时空数据建模

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

>12 weeks

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