Spatial OLAP

ICSOLAP: UML Profile for desigining conceptual models for complex Spatial OLAP applications

(result of the Ph. Kamal Boulil)

Spatial Data Warehouse and SOLAP systems allow analyzing huge volume of georeferenced data. SOLAP applications are usually complex needing advanced static and dynamic modelling properties. In particular, SOLAP applications require: multi-granular measures and complex aggregations based on aggregate functions depending on dimensions, hierarchies and levels. In this demo paper, motivated by the lack of conceptual spatio-multidimensional models based on standard languages and supporting such complex modelling requirements, we present a new UML profile for complex spatial data cubes. We implement our profile in the commercial CASE tool called MagicDraw. Using a real environmental case study, we show the theoretical and technical effectiveness of our proposal.

Spatio-multidimensional integrity constraints tool

(result of the Ph. Kamal Boulil)

Spatial OLAP systems are Business Intelligence technologies allowing efficient and interactive analysis of large spatial data cubes. In this type of systems the correctness of analysis depends on: the warehoused data quality, how aggregations are performed and how data cubes are explored. In this paper we study quality control techniques (based on integrity constraints) related to exploration of spatial data cubes. We extend our UML framework previously proposed with a UML profile allowing the conceptual design of several classes of exploration integrity constraints. We also propose a tool for their automatic implementation.

SOLAP tool

Spatial Warehouse (SDW) and Spatial On-Line Analytical Processing (SOLAP) systems are technologies intended to support geographic business intelligence. SOLAP clients provide a cartographic representation of facts on maps, and perform SOP operations through simple user interactions with the maps. Services are unassociated, loosely coupled units of functionality that are self-contained. A Service Oriented Architecture (SOA) is an architectural design pattern where each tier is defined by means of a set of web services. (Un)luckly, there is currently no standard approach to implement SOA solution for visualizing the results of SOLAP queries. Existing SOLAP clients are not flexible and provide closed ad-hoc implementation policies for the visualization of SOLAP queries, which is an important obstacle to interoperability. In this paper we propose a data model for the cartographic visualization of SOLAP queries. Based on this model, we present a new SOA architecture for SOLAP systems where the SOLAP client is totally based on standard data representations (e.g. XMLA, SLD, etc.), and cartographic visualization web services (XMLA, WMS, etc.).

Pivot4J configuration

JPivot configuration

ChoremOLAP tool

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 system 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 propose a general architecture based on standards to automatically extract and visualize chorems from SDWs.