department of computer science federal university of são...

5012th International Conference on Enterprise Information Systems – ICEIS 2010

/

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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+ JPivot


Database Group

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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Database Group

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


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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We choose to start

with data from SAEB

(Evaluation System for

Basic Education)

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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 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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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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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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It is possible to use three-dimensional Thematic Maps and

Virtual Globes for geovisualization of multidimensional

queries

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Database GroupReferences

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