Spatial Data Warehouse Multidimensional Design Approach and Geo-Decisional Tool for Road Accidents Analysis

Road accidents is a complex and dangerous phenomenon, which requires a deep analysis of a large amount of information available in several databases of the concerned national public and private institutions. To help on fighting against this phenomenon, we propose a design approach of a spatial data warehouse dedicated to OLAP and SOLAP road accident analysis. The design method is driven by the metadata that allows expressing the needs by taking into account the available data. Our approach can be classified as a supply-driven method; its nine steps cover the lifecycle of the design, from the sources metadata extraction to the physical model of the spatial data warehouse. To validate our approach, our developed spatial data warehouse is backed up with a decisional tool allowing OLAP and SOLAP analysis. We present some results of our experiments at an administrative district level scale.

[1]  Stefano Paraboschi,et al.  Designing data marts for data warehouses , 2001, TSEM.

[2]  Ibrahim Yilmaz,et al.  Geographical information systems aided traffic accident analysis system case study: city of Afyonkarahisar. , 2008, Accident; analysis and prevention.

[3]  Alberto Guarnieri,et al.  Collaborative Web-GIS Design: A Case Study for Road Risk Analysis and Monitoring , 2011, Trans. GIS.

[4]  T. Kiran Kumar,et al.  Traffic accident analysis using GIS- a case study , 2014 .

[5]  Abdelrahman Karrar,et al.  A Proposed Framework for Using GIS to Enhance Traffic Safety in Sudan: A Case Study , 2016 .

[6]  Alberto Abelló,et al.  Multidimensional Design by Examples , 2006, DaWaK.

[7]  Zaia Alimazighi,et al.  A New Multidimensional Design Method Based on Meta Model Assistance , 2017, Int. J. Knowl. Based Organ..

[8]  Zaia Alimazighi,et al.  Spatial data warehouse and geospatial decision making tool for efficient road risk analysis , 2014, 2014 1st International Conference on Information and Communication Technologies for Disaster Management (ICT-DM).

[9]  Sandro Bimonte,et al.  Conceptual design and implementation of spatial data warehouses integrating regular grids of points , 2017, Int. J. Digit. Earth.

[10]  Daniel L. Moody,et al.  From enterprise models to dimensional models: a methodology for data warehouse and data mart design , 2000, DMDW.

[11]  Alberto Abelló,et al.  Automatic validation of requirements to support multidimensional design , 2010, Data Knowl. Eng..

[12]  Il-Yeol Song,et al.  Multidimensional Modeling with UML Package Diagrams , 2002, ER.

[13]  Isabelle Comyn-Wattiau,et al.  A UML-based data warehouse design method , 2006, Decis. Support Syst..

[14]  Shenjun Yao,et al.  Traffic collisions in space: four decades of advancement in applied GIS , 2016, Ann. GIS.

[15]  K. Vivekanandan,et al.  A Tool for Data Warehouse Multidimensional Schema Design using Ontology , 2013 .

[16]  Pan Ning.  Study of Multi-Dimensional Traffic Accident Analysis System Based on GIS , 2010 .

[17]  W. H. Inmon,et al.  Building the Data Warehouse,3rd Edition , 2002 .

[18]  Dalibor Pešić,et al.  Towards an analytical information system of traffic accidents in the function of traffic safety monitoring , 2012 .

[19]  W. H. Inmon,et al.  Building the data warehouse (2nd ed.) , 1996 .

[20]  Zaia Alimazighi,et al.  De la Conception d'un Entrepôt de Données Spatiales à un Outil Géo-Décisionnel pour une Meilleure Analyse du Risque Routier , 2013, INFORSID.

[21]  N. Deshpande,et al.  Accident Mapping And Analysis Using Geographical Information Systems , 2011 .

[22]  Yvan Bédard,et al.  Merging Hypermedia GIS with Spatial On-Line Analytical Processing: Towards Hypermedia SOLAP , 2006 .

[23]  Jean Stephane,et al.  Ontology-based structured web data warehouses for sustainable interoperability: requirement modeling, design methodology and tool , 2012 .

[24]  Ping-Yu Hsu,et al.  A grain preservation translation algorithm: From ER diagram to multidimensional model , 2007, Inf. Sci..

[25]  Stephen R. Gardner.  Building the data warehouse , 1998, CACM.

[26]  Mickaël Baron,et al.  Ontology-based structured web data warehouses for sustainable interoperability: requirement modeling, design methodology and tool , 2012, Comput. Ind..