A First Framework for Mutually Enhancing Chorem and Spatial OLAP Systems

Spatial OLAP systems aim to interactively analyze huge volumes of geo-referenced data. They allow decision-makers to on-line explore and visualize warehoused spatial using pivot tables, graphical displays and interactive maps. On the other hand, it has been recently shown that chorem maps represent an excellent geovisualzation technique to summarize spatial phenomena. Therefore, in this paper we introduce a framework being capable to merge the interactive analysis capability of SOLAP systems and the potentiality of a chorem-based visual notation in terms of visual summary. We also propose a general architecture based on standards to automatically extract and visualize chorems from SDWs according to our framework.

[1]  Daniel A. Keim,et al.  Challenges in Visual Data Analysis , 2006, Tenth International Conference on Information Visualisation (IV'06).

[2]  V. D. Fatto Visual summaries of geographic databases by chorems , 2009 .

[3]  Ralph Kimball,et al.  The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses , 1996 .

[4]  Sylvie Lardon,et al.  Méthodologie de diagnostic pour le projet de territoire : une approche par les modèles spatiaux , 2005 .

[5]  Yvan Bédard,et al.  Spatial Online Analytical Processing (SOLAP): Concepts, Architectures, and Solutions from a Geomatics Engineering Perspective , 2007 .

[6]  Paul U. Lee,et al.  Wayfinding choremes - a language for modeling conceptual route knowledge , 2005, J. Vis. Lang. Comput..

[7]  Sandro Bimonte A generic geovisualization model for spatial OLAP and its implementation in a standards-based architecture , 2014, Ingénierie des Systèmes d Inf..

[8]  W. H. Inmon,et al.  Building the data warehouse , 1992 .

[9]  Sandro Bimonte,et al.  Integration of Spatial Networks in Data Warehouses: A UML Profile , 2013, ICCSA.

[10]  Maribel Yasmina Santos,et al.  Spatial Clustering in SOLAP Systems to Enhance Map Visualization , 2012, Int. J. Data Warehous. Min..

[11]  Mark Gahegan,et al.  Geovisualization for knowledge construction and decision support , 2004, IEEE Computer Graphics and Applications.

[12]  Davide De Chiara,et al.  A chorem-based approach for visually analyzing spatial data , 2011, J. Vis. Lang. Comput..

[13]  Monica Sebillo,et al.  A chorem-based approach for visually synthesizing complex phenomena , 2008, Inf. Vis..

[14]  Sandro Bimonte,et al.  Conceptual model for spatial data cubes: A UML profile and its automatic implementation , 2015, Comput. Stand. Interfaces.