integrating gis and olap: a new way to unlock geospatial data for decision-making

Philadelphia, May 2–4, 2005

www.locationintelligence.net

Integrating GIS and OLAP:a New Way to Unlock Geospatial Datafor Decision-making

Dr. Yvan BedardProfessorLaval UniversityQuebec City, Canada

Industrial Research Chairin Geospatial Databases

for Decision-Support



Presentation Plan

• Origins and characteristics of Spatial OLAP (SOLAP) applications

• Approaches to develop SOLAP applications (definition, pros/cons)– GIS-centric– OLAP-centric– Integrated SOLAP

• Benefits and future directions



Origins of SOLAP

• Organisations worldwide invest hundreds of millions of dollars annually to acquire large amounts of data about the land, its resources and uses

• These data however prove difficult to use by managers who need:– aggregated information - trends analysis– spatial comparisons - space-time correlations– fast synthesis over time - unexpected queries– interactive exploration - geogr. knowledge

discovery



Origins of SOLAP

• GIS data have a transactional nature– Transactional databases are oriented towards

data:• acquisition• storing• updating• integrity checking• minimal querying, with the help of an expert

Ex. Normalized relational databases



Origins of SOLAP• Decision-makers need data with an

« analytical » nature – Decision-support databases are oriented

towards data aggregation, data summarization with several levels of granularity in time, space and themes

• Integrating GIS and OLAP has become a very promising field. It offers new possibilities that are just starting to emerge.



Origins of SOLAP

• BI offers the foundations to build the data rich environment needed for SOLAP

DBMS

Decisional nature of data

Geospatial nature of data

Geospatial

Non-geospatial

Not Aggregatedaggregated

GIS

DWDM

OLAP

GDWGDM

SOLAP

DW= data warehouseDM = datamartG = Geospatial



Origins of SOLAP• 1996-2000: pionneering

– early prototypes in universities• Laval U. - Simon Fraser U. - U. Minnesota

• 2001-2004: early adopters– advanced prototypes in universities– first applications in industry

• 2005-... : maturing– larger number of ad hoc applications– SOLAP technologies to facilitate the development of

SOLAP applications



Characteristics of SOLAP Applications• Provides a high level of interactivity

– response times < 10 seconds independently of• the level of data aggregation• today's vs historic data• measured vs simulated data

• Ease-of-use and intuitiveness– requires no SQL-type query language– no need to know the underlying data structure

• Supports intuitive, interactive and synchronized exploration of spatio-temporal data for different levels of granularity in maps, tables and charts that are synchronized at will



Experiences since 1996• Besides developing theoretical concepts, we have

experimented with several technologies to build SOLAP applications

• Experiments in:– forestry - agriculture - public health– transport - search & rescue - sports– recruitment - archeology - etc.

• Experiments with:– MapX - ArcGIS - Geomedia - SoftMap– Oracle- Access - SQL-Server – Proclarity - Cognos - etc.



Example: Quebec Public Health

•K-MapX•ProClarity•MS-SQL Server•VBScript development

Analysing hospitali-sation and death statistics with regards to respira-tory diseases, cancer, etc.



Example: Transport Quebec

•Geomedia WebMap•ProClarity•MS-SQL Server•VB development

Analysing accident quantities and severities with regards to road conditions, traffic, topography, etc.



Example: Montmorency Forest

•ArcGIS 3D•ProClarity•MS-SQL Server•VB development

3D analysis of forest stands with regards to tree species, age, drainage, etc.



Results• Applications using GIS+OLAP were limited

– insufficient data exploration capabilities– limited visualization customization– too slow in certain cases to support interactivity– do not always fit in the map updating workflow

• Applications required months of programming• We decided to design and develop our own

integrated SOLAP technology in Java – commercial name: JMap Spatial OLAP Extension



Example: Laval Univ. recruitment

•JMap Spatial OLAP•Oracle 10g + spatial

Analysing students statistics with regards to origin, last diploma, language, etc.



Example: Olympic sports

•JMap Spatial OLAP•Oracle 10g + spatial

Analysing performances with regards to position, trajectory, weather conditions, technique, etc.



Example: Canadian Coast Guard•JMap Spatial OLAP•Oracle 10g + spatial

Analysing search and rescue data with regards to position, boat characteristics, weather conditions, pilot experience, etc.



Approaches to Develop SOLAP Applications

• Ad hoc, proprietary programming specific to one application

• Combining GIS + OLAP capabilities– GIS-centric– OLAP-centric– Integrated SOLAP

-The dominant tool offers its full capabilities but gets minimal capabilities from the other tool-GUI provided by the dominant tool




• Ad hoc, proprietary programming– typically used to develop one application for a very

specific need without using OLAP and GIS libraries• Advantages

– can perfectly fit the needs, no less no more• Disadvantages

– very expensive– very long delays before delivering– hard to maintain– very difficult to modify for other purposes– silo application




• OLAP-centric– Application developed along the OLAP tool and server– OLAP functions are predominant and GIS functions are

kept to a minimum• zoom, pan, select, layer on/off for example• sometimes, minimal spatial drill

• Advantages– supports OLAP exploration and visualization– uses OLAP server capabilities– OK for simple map viewing and exploration need




OLAP-centric• Disadvantages

– requires complex analysis to provide an elegant and efficient user interface

– typically requires months of programming• recent alliances between OLAP and GIS providers simplify

this development

– limited number of spatial dimensions and analysis

– limited interaction and difficult map updates




• GIS-centric– Application developed along the GIS and a DBMS– GIS functions are predominant and OLAP functions are

kept to a minimum• drill down and up in a table for example

• Advantages– supports GIS thematic mapping– uses spatial analysis capabilities– OK when maps are of primary importance while

table/chart viewing, tabular exploration needs are simple




GIS-centric• Disadvantages

– requires complex analysis to provide an elegant and efficient user interface

– typically requires months of programming• recent alliances between OLAP and GIS providers simplify

this development

– must include explicit data to manage the spatial dimension hierarchies in the data cube

– limited interaction




• Integrated SOLAP– high level of functionnality for both spatial and non-spatial data

and views– sophisticated integration and synchronization of OLAP and GIS

functions

• Advantages– better user interface– more interactive and sophisticated functions– works the same way in maps, charts and tables– can be implemented in hours without programming by using a

generic stand-alone software built especially to develop SOLAP applications: SOLAP technology (ex. JMap Spatial OLAP)

• works with or without underlying GIS and OLAP




Integrated SOLAP• Advantages

– fits in the map update workflow– supports spatial analysis– synchronized exploration of data between maps, tables and

charts

• Disadvantages– when not using SOLAP technology, it requires complex analysis

to provide an elegant and efficient user interface– when not using SOLAP technology, it typically requires several

months of programming• recent alliances between OLAP and GIS providers simplify this development



Benefits of SOLAP applications

• In our projects, positive results in many applications have been achieved, such as:– cutting by a factor of 10 the time required to produce maps

and reports that summarize key information– allowing new users having never heard of GIS to produce

hundred of thousands of synchronized maps, reports and tables on demand with only three hours of training

– providing keyboardless access to geospatial data at different levels of detail with a facility never achieved before



Metadata+

Ontologies

GeospatialData

Acquisition

BusinessIntelligence

InteroperableDatabases

Web Mapping

SolutionProviders

DVP

R&D inGIS + BI

Dataproviders

Users

Chair

HQ

Future Directions: enrich the integration of "S"+"OLAP" + related products

Kheops

Intelec

Holonics

DefenceCanada

TransportQuebec

NRCan

Syntell

Quebec Hydro

New NSERCIndustrial Chairon BI+Geomatics3M US$2005-09

Laval U.



Conclusion• This presentation has

– introduced SOLAP• characteristics• origins• examples

– presented 4 approaches to develop SOLAP applications• ad hoc - OLAP-centric - GIS-centric - Integrated SOLAP

– identified advantages and disadvantages of each approach to help identify the best strategy to combine GIS and OLAP for a given need

• All solutions have advantages and inconvenients, but 8 years of experimentation has proved that using an off-the-shelf integrated SOLAP technology significantly improves the results while leading to a major reduction in time and development cost

• More R&D will bring even better solutions



Thank you !

Industrial Research Chairin Geospatial Databases

for Decision-Support http://mdspatialdb.chair.scg.ulaval.ca

http://www.crg.ulaval.ca

http://sirs.scg.ulaval.ca/yvanbedard/Yvan Bedard, PhD

integrating gis and olap: a new way to unlock geospatial data for decision-making

Documents

data warehousedm

temporal data

data summarization

usesthese data

data rich environment

large amounts of data

solap applicationsexperiments

access sql