department of computer science federal university of são...
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5012th International Conference on Enterprise Information Systems – ICEIS 2010
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Database Group
Department of Computer Science
Federal University of São Carlos
São Carlos – SP, Brazil
12th International Conference on Enterprise Information Systems – ICEIS 2010 /
Database GroupOutline
Motivations and Goals
Multidimensional Analysis Environments
(Geographic) Data Warehouse and (Spatial) OLAP
Geovisualization in GDW/SOLAP Tools
Virtual Globes and Thematic Maps
The GlobeOLAP Prototype
Architecture
Study Case
Demonstration
Discussion
Advantages and issues
References
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Database GroupMotivations
The WebPIDE Project (CAPES/INEP grant) challenges:
Extracting, integrating and visualizing many gigabytes of data from
national educational evaluations
Multidimensional data
Geospatial and temporal data
Need for user-friendly solution
Limitations in geovisualization
modules of multidimensional analysis
tools
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Database GroupGoals of this paper
Investigate the introduction of two functionalities in
multidimensional analysis tools:
Virtual globes (e.g. Google Earth)
Custom thematic maps
Discuss advantages and potential issues
Propose an architecture
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Database GroupData Warehouse and OLAP
Widely used for decision support
Priotize efficient querying of huge amounts of integrated and
historical data
Mutidimensional modeling
Star Schema
Attribute hierarquies
Redundancy!
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Dimensions
Facts
Measures
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Database GroupData Warehouse and OLAP
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Database GroupData Warehouse and OLAP
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+ JPivot
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Geographic Data Warehouse and Spatial OLAP
Allows a geospatial perspective in multidimensional
analysis
Georreferenced geometries are maitained in one or more
dimensions, or at least in one measure.
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Geovisualization in GDW/SOLAP tools Geobrowsers
It can be seen as the Geographic Information System (GIS)
visualization module
Results from multidimensional queries in maps
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Database Group2D Geobrowsers
Existing 2D geobrowsers:
Google Maps API
Bing Maps API
Yahoo! Maps Web Services
ESRI ArcGIS Online / WebMapping API
OpenLayers API
Functionalities: pan, zoom, layer control, descriptions of
features, geospatial web services (geocoding, route
calculation, local search).
Two main types of images: street/boundaries maps and
remote sensing images
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Database Group3D Geobrowsers: Virtual Globes
Existing Virtual Globes:
Google Earth
NASA World Wind
Marble
Skyline Global
Three-dimensional model of the Earth surface
The same tiles from 2D Geobrowsers, but now with an
orientation angle of Perspective Ortographic projection.
Camera controlling inclination and rotation of the view
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Database GroupThematic Maps
Main type of map for analysis of summarized and
contextualized (both geographically and thematically)
data
Representation of the spatial distribution of phenomena
at specific points in time
GDW/SOLAP and Thematic Maps convergence:
Every dimension or measure can be seen as a theme
Data aggregation by (S)OLAP operatiors goes toward a theme
refining
Thematic Maps can be an efficient geospatial and analytical
summary of data from a GDW
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June 10, 2010 5013
“Rivet” from Stolte et al. (2002)
Related works
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June 10, 2010 5014
“SOVAT” from Scotch and Parmanto (2005)
Related works
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June 10, 2010 5015
“Jmap Spatial OLAP Extension” from Rivest et al. (2005)
Related works
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June 10, 2010 5016
“OLAP for ArcGIS,”
ESRI
Related works
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June 10, 2010 5017
Bimonte et al. (2007)
JPivot showing tabular data
Map View
Related works
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June 10, 2010 5018
Di Martino et al. (2009)
Related works
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June 10, 2010 5019
Related works
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Database GroupGlobeOLAP prototype
Combining Virtual Globes and Thematic Maps technologies
in GDW/SOLAP environments!
Architecture
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Database GroupStudy Case
Goal of the study case:
Investigate the feasibility of integrating Virtual Globes + 3D
Thematic Maps + GDW/SOLAP environments
Materials:
Raw data from national evaluations, applied on brazilian students
by the government ministry of education
ONTOPTool (Hernandes, 2010), for cleaning data
PostgreSQL 8.4 + PostGIS 1.4, as our database
DEAR tool (Siqueira, 2008), for loading data into PostgreSQL
Pentaho Mondrian 3.2 + JPivot, as OLAP server and Pivot Table
Java 1.6 + Tomcat 6.0, as platform for Mondrian
Schema Workbench 3.2, for generating XML schemas for the GDW
Google Earth API, as our Virtual Globe
Thematic Map Engine 1.6 (Sandvik, 2008), as our map generator
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Database GroupStudy Case
We choose to start
with data from SAEB
(Evaluation System for
Basic Education)
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Database GroupStudy Case
By slicing „Test Year=2003‟, choosing
Localization as column and Avg Proficiency
as a measure, we can answer the following
question: “Which are proficiency average the
students have in each state in 2003?”
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Database GroupStudy Case
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Database GroupStudy Case
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Database GroupDemonstration
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Database GroupDiscussion
Advantages of Virtual Globes + GDW
Richer environment, more details
More space for information
Provides a familiar environment for complex analysis
Reduce area distortions
Advantages of Thematic Maps + GDW
Efficient geospatial and analytical summary of data from a GDW
Thematic maps can be overlayed for multidimensional analysis
Advantages of the third dimension in Thematic Maps
Emphasize and detail a bi-dimensional visual variable
[Slocum, 2005; Sandvik, 2008; Shepherd, 2008; Tiede and Lang, 2010]
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Database GroupDiscussion
Potential issues
Too many non-essential visual variables may produce a confusing
map
Dynamic scaling may prejudice human hability of estimating
volumes
Virtual globes usually demands more user interaction
[Monmonier, 1996; Slocum, 2005; Goodchild, 2008; Shepherd, 2008]
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Database GroupDiscussion
Some partial solutions (future works)
Allowing users to choose between 2D map or Virtual Globe
Use of two side-by-side Virtual Globes
Use of perspective control in non-Globe 3D maps
[Monmonier, 1996; Slocum, 2005; Goodchild, 2008; Shepherd, 2008]
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Database GroupDiscussion
It is possible to use three-dimensional Thematic Maps and
Virtual Globes for geovisualization of multidimensional
queries
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