SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data

Rivest, Sonia; Bédard, Yvan; Proulx, Marie-Josée; Nadeau, Martin; Hubert, Frédéric; Pastor, Julien

doi:10.1016/j.isprsjprs.2005.10.002

Cited by 128 publications

(87 citation statements)

References 21 publications

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“…SOVAT [15] combines OLAP and GIS capabilities; its interface supports spatial drill-down and roll-up operations as well as drill-out, that allows users to submit queries based on both numerical and spatial aggregation. Finally, in [14] a two-level prototype (JMap) is proposed where the GUI and the query engine are collapsed in the same module. JMap supports both tabular and diagrammatic views; different types of maps can be shown, in particular, multimaps, complex thematic maps, and maps with superimposed diagrams.…”

Section: Location Intelligence In the Literaturementioning

confidence: 99%

Lily: A Geo-Enhanced Library for Location Intelligence

Golfarelli

Mantovani

Ravaldi

et al. 2013

Data Warehousing and Knowledge Discovery

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Abstract. Location intelligence is a set of tools and techniques to integrate a geographical dimension into BI platforms, aimed at enhancing their capability of better monitoring and interpreting business events. Though most commercial data warehouse tools have implemented spatial extensions to support GIS integration, the user experience with spatial data is still mostly limited to the visualization of maps labeled with numerical indicators. To overcome this limit we developed Lily, a geo-enhanced library that adds true location intelligence capabilities to existing BI platforms. Lily provides end-users with a highly-interactive interface that seamlessly achieves a bidirectional integration between the BI and the geospatial worlds, so as to enable advanced analytical features that truly take into account the spatial dimension. In this paper we describe Lily from a functional and architectural point of view, and show an example where Lily is coupled with the Oracle Suite to be used for location intelligence in the field of telecommunications.

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Section: Location Intelligence In the Literaturementioning

confidence: 99%

Lily: A Geo-Enhanced Library for Location Intelligence

Golfarelli

Mantovani

Ravaldi

et al. 2013

Data Warehousing and Knowledge Discovery

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“…The logical SDW design models aim to provide support for spatial data dimensions [29], spatial measures [30][31][32][33] and spatial aggregations [34]. The concept of spatial measures (with a specific geometric part) is either defined as references to spatial objects [35,23] or as the results of topological, distance or metric operations [24,23], or as values associated with a spatial data dimension in the data cube [31,36].…”

Section: Related Workmentioning

confidence: 99%

“…The major implementations of SOLAP tools can be broadly classified as OLAP dominant, GIS dominant, or integrated OLAP and GIS solutions [33]. OLAP approaches provide means for aggregation of data, while GIS approaches focus on geometric operations and visual data selections while limiting multidimensional data analysis.…”

Section: Related Workmentioning

confidence: 99%

On the Requirements for User-Centric Spatial Data Warehousing and SOLAP

Viswanathan

Schneider

2011

Database Systems for Adanced Applications

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Abstract. Data warehouses and OLAP systems help to analyze complex multidimensional data and provide decision support. With the availability of large amounts of spatial data in recent years, several new models have been proposed to enable the integration of spatial data in data warehouses and to help analyze such data. This is often achieved by a combination of GIS and spatial analysis tools with OLAP and database systems, with the primary goal of supporting spatial analysis dimensions, spatial measures and spatial aggregation operations. However, this poses several new challenges related to spatial data modeling in a multidimensional context, such as the need for new spatial aggregation operations and ensuring consistent and valid results. In this paper, we review the existing modeling strategies for spatial data warehouses and SOLAP in all three levels: conceptual, logical and implementation. While studying these models, we gather the most essential requirements for handling spatial data in data warehouses and use insights from spatial databases to provide a "meta-framework" for modeling spatial data warehouses. This strategy keeps the user as the focal point and achieves a clear abstraction of the data for all stakeholders in the system. Our goal is to make analysis more user-friendly and pave the way for a clear conceptual model that defines new multidimensional abstract data types (ADTs) and operations to support spatial data in data warehouses.

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“…A GDW can be spatially queried and processed by a Spatial OLAP (SOLAP) tool that allows easy and fast exploration of very large geospatial data repositories and offers a set of visualization techniques such as maps, tables and diagrams (Bédard, 1997;Bédard, 2005;Rivest et al, 2005) Additionally to OLAP operators (e.g. drill-down, roll-up, slice and dice, pivot and drill across), different authors have proposed a number of SOLAP operators.…”

Section: Geographic Data Warehouses and Spatial On-line Analytical Prmentioning

confidence: 99%

“…There are also final products which aim to bring some SOLAP functionalities to users of DW/OLAP software packages. Among commercial solutions, Rivest et al (2005) presented JMap® Spatial OLAP Extension, one of the most complete existing SOLAP tools with regard to the set of SOLAP operators and geovisualization techniques provided. Pentaho Google Maps Dashboard (Pentaho, 2010a) is part of an open-source and commercial package for Business Intelligence which allows to plot colored point symbols reflecting localizations of objects of interest and a numerical measure regarding them.…”

Section: Related Work On Geovisualization In Solap Toolsmentioning

confidence: 99%

GlobeOLAP - Improving the Geospatial Realism in Multidimensional Analysis Environment

Ferraz

Santos

2010

Proceedings of the 12th International Conference on Enterprise Information Systems

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Abstract:The combination of Geographic Data Warehouses (GDW) and Spatial OLAP (SOLAP) provide efficient browsing and storing of very large spatio-temporal databases. However, some advanced techniques of geovisualization are not well supported in many of these tools. Three-dimensional Thematic Mapping through Virtual Globes is one of them, and it can provide a friendly but powerful mechanism for summarize visually huge amounts of geospatial-analytical data and their changes over time. This paper shows the GlobeOLAP, a prototype of a Web-based SOLAP tool that allows the customized generation of many types of Thematic Maps to be visualized three-dimensionally in a Virtual Globe (Google Earth), together with the traditional tabular view. This tool can improve management decisions by allowing managers to identify patterns and build knowledge in a spatial realistic environment.

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SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data

Cited by 128 publications

References 21 publications

Lily: A Geo-Enhanced Library for Location Intelligence

Lily: A Geo-Enhanced Library for Location Intelligence

On the Requirements for User-Centric Spatial Data Warehousing and SOLAP

GlobeOLAP - Improving the Geospatial Realism in Multidimensional Analysis Environment

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