Open source Geospatial Business Intelligence in action with GeoMondrian and SOLAPLayers!

Open source Geospatial Business
Intelligence in action with
GeoMondrian and SOLAPLayers!

FOSS4G 2010

Dr. Thierry Badard, CTO
Spatialytics inc.
Quebec, Canada
tbadard@spatialytics.com

Barcelona, Spain – Sept 9th, 2010

What are GeoMondrian & SOLAPLayers?

●
It is part of the geospatial BI software stack developed
initially by the GeoSOA research group at Laval
University in Quebec …
– GeoKettle
– GeoMondrian
– SOLAPLayers

●
But are now developed and supported by Spatialytics
– http://www.spatialytics.org (open source community)
– http://www.spatialytics.com (professional support, training)
●
OK but … what is geospatial BI? ;-)

As you probably know …

●
Business Intelligence applications are usually used to
better understand historical, current and future
aspects of business operations in a company.
●
The applications typically offer ways to mine
database- and spreadsheet-centric data, and
produce graphical, table-based and other types of
analytics regarding business operations.
●
They support the decision process and allow to take
more informed decision!

Data visualization to support decision …

As you probably know …
● Business Intelligence applications are usually used to better
understand historical, current and future aspects
of business operations in a company.
● The applications typically offer ways to mine database- and
spreadsheet-centric data, and produce graphical, table-based and
other types of analytics regarding business operations.
● They support the decision process and allow to take more informed
decision!
● Rely on an architecture with robust components and applications:
− ETL tools & data warehousing (DW)
− On-line Analytical Processing (OLAP) servers and clients
− Reporting tools & dashboards
− Data mining

Classical architecture of a BI
infrastructure

• Transactional databases
• Web ressources
• XML, flat files, proprietary file
formats (Excel spreadsheets, …)
• LDAP
•…

The Data Warehouse: the crucial/central part!

●
Repository of an organization’s historical data, for analysis
purposes.
●
Primarily destined to analysts and decision makers.
●
Separate from operational (OLTP) systems (source data)
− But often stored in relational DBMS: Oracle, MSSQL,

PostgreSQL, MySQL, Ingres, …
●
Contents are often presented in a summarized form (e.g.
key performance indicators, dashboards, OLAP client
applications, reports).
− Need to define some metrics/measures

The Data Warehouse: the crucial/central part!

●
Optimized for:
− Large volumes of data (up to terabytes);
− Fast response (<10 s) to analytical queries (vs. update speed for transactional DB):
− de-normalized data schemas (e.g. star or snowflake schemas),
− Introduces some redundancy to avoid time consuming JOIN queries
− all data are stored in the DW across time (no corrections),
− summary (aggregate) data at different levels of details and/or time scales,
− (multi)dimensional modeling (a dimension per analysis axis).
− All data are interrelated according to the analysis axes (OLAP datacube paradigm)
●
Focus is thus more on the analysis / correlation of large amount of data
than on retrieving/updating a precise set of data!
●
Specific methods to propagate updates into the DW needed!

MDX query language
● MDX stands for MultiDimensional eXpressions
● Multidimensional query language
● De facto standard from Microsoft for SQL Server OLAP Services
(now Analysis Services)
● Also implemented by other OLAP servers (Essbase, Mondrian) and
clients (Proclarity, Excel PivotTables, Cognos, JPivot, …)
● MDX is for OLAP data cubes what SQL is for relational databases
● Looks like a SQL query but relies on a different model (close to the
one used in spreadsheets)
● SELECT
{ [Measures].[Store Sales] } ON COLUMNS,
{ [Date].[2002], [Date].[2003] } ON ROWS
FROM Sales
WHERE ( [Store].[USA].[CA] )

Results representation
●
SELECT
{ [Product].[All Products].[Drink],
[Product].[All Products].[Food] } ON COLUMNS,
{ [Store].[All Stores].[USA].[WA].[Yakima].[Store 23],
[Store].[All Stores].[USA].[CA].[Beverly Hills].[Store 6],
[Store].[All Stores].[USA].[OR].[Portland].[Store 11] } ON ROWS
FROM Warehouse
WHERE ([Time].[1997], [Measures].[Units Shipped])

• OLAP client software propose:
− Alternate representation modes (pie charts, diagrams, etc.)
− Different tools to refine queries/explore data
− Drill down, roll up, pivot, …

− Based on operators provided by MDX

Geospatial BI adds maps and spatial
analysis!

Require to consistently integrate the geospatial component in all parts of the architecture!

Why merge BI and GIS software?
●
Because …

“About eighty percent of all data
stored in corporate databases
has a spatial component” [Franklin
1992]

Franklin, C. 1992. An Introduction to Geographic Information
Systems: Linking Maps to Databases. Database, April, pp. 13-21

Why merge BI and GIS software?
●
Enable the exploration of spatial relations between data
− To take into account all aspects of data
− And then take informed decisions

●
Some phenomena can only be observed and interpreted
by representing them on a map!
− Spatial distribution,
− Spatiotemporal evolution,
− etc.

To implement true geo-analytical tools …

Pentaho open source BI software stack
●
http://www.pentaho.org

Pentaho open source BI software stack
●
Pentaho (http://www.pentaho.org) Pentaho
Reporting

Kettle Mondrian

Weka

+ CDF: Community Dashboard Framework
+ Other projects: olap4j, JPivot, Halogen, …

Spatialytics open source geospatial BI
stack
●
Spatialytics (http://www.spatialytics.com)

& integration in various
dashboard and
reporting tools

Spatial S
• PostGIS
• Oracle Spatial

GeoKNIME
Spatial

GeoMondrian
●
GeoMondrian is a "spatially-enabled" version of
Pentaho Analysis Services (Mondrian)
●
GeoMondrian brings to the Mondrian OLAP
server what PostGIS brings to the PostgreSQL
DBMS
– i.e. a consistent and powerful support for geospatial
data.

●
Licensed under the EPL
●
http://www.geo-mondrian.org

GeoMondrian
●
As far as we know, it is the first implementation of a true
Spatial OLAP (SOLAP) Server
− And it is an open source project! ;-)
●
Provides a consistent integration of spatial objects into the
OLAP data cube structure
− Instead of fetching them from an external spatial DBMS, web
service or a GIS file
●
Implements a native Geometry data type
●
Provides first spatial extensions to the MDX language
− Add spatial analysis capabilities to the analytical queries
●
At present, it only supports PostGIS datawarehouses
− But other DBMS will be supported in the next version!

Spatially enabled MDX
●
Goal: bring to Mondrian and MDX what SQL spatial
extensions do for relational DBMS (i.e. Simple Features for
SQL and implementations such as PostGIS).
●
Example query: filter spatial dimension members based on
distance from a feature
− SELECT
{[Measures].[Population]} on columns,
Filter(
{[Unite geographique].[Region economique].members},
ST_Distance([Unitegeographique].CurrentMember.Properties("geom"),
[Unite geographique].[Province].[Ontario].Properties("geom")) < 2.0
) on rows
FROM [Recensements]
WHERE [Temps].[Rencensement 2001 (2001-2003)].[2001]

Spatially enabled MDX
●
Many more possibilities:
− in-line geometry constructors (from WKT)
− member filters based on topological predicates
(intersects, contains, within, …)
− spatial calculated members and measures (e.g.
aggregates of spatial features, buffers)
− calculations based on scalar attributes derived from
spatial features (area, length, distance, …)

SOLAPLayers
●
SOLAPLayers is a lightweight cartographic component
(framework) which enables navigation in geospatial (Spatial
OLAP or SOLAP) data cubes, such as those handled by
GeoMondrian.
●
It aims to be integrated into existing dashboard frameworks
in order to produce interactive geo-analytical dashboards.
●
Such dashboards help in supporting the decision making
process by including the geospatial dimension in the
analysis of enterprise data.
●
First version stems from a GSoC 2008 project performed
under the umbrella of OSGeo.
●
Licensed under BSD (client part) and EPL (server part).
●
http://www.solaplayers.org

SOLAPLayers v1
●
Version 1 was based on OpenLayers and Dojo
●
It allows:
− the connection with a Spatial OLAP server such as
GeoMondrian,
− some basic navigation capabilities in the geospatial
data cubes,
− and the cartographic representation of some measures
as static or dynamic choropleth maps, maps with
proportional symbols.

SOLAPLayers v1
●
Version 1 was a mostly proof of concept!
●
It presents important limitations:
− Allows only the cartographic representation (no crosstabs or
charts)
− Works only for one measure and the spatial dimension !
− Offers limited navigation capabilities in the geospatial
data cubes
− Is able to connect to GeoMondrian only
− Extending the framework is difficult due to the
lack of flexibility and the poor documentation of Dojo,
− Integration with other currently used geo-web and dashboard
frameworks was difficult
− ...

SOLAPLayers 2.0
●
So, SOLAPLayers has undergone (and is still
undergoing ;-) ) a deep re-engineering!
●
Version 2 is fully based on ExtJS/GeoExt (and hence
OpenLayers)
− It will make its integration with other geo/web and
BI/dashboard frameworks easier
− It provides some new ExtJS components dedicated to
GeoBI!
− Based on the philosophy for the development of
applications adopted by these geo-web frameworks, it
allows an easier creation/maintenance of the produced geo-
analytical dashboards!
− Like ExtJS, it supports internationalization!

SOLAPLayers 2.0 – Architecture
1 Built-in or LDAP
Server
SOLAP Server Authentication

Native or XML/A
OLAP4J
MDX

Client
Server
SOLAPJSON

1 Built-in or LDAP
Server

Native or XML/A
OLAP4J
MDX
OLAP Server
Client
Native or XML/A Server
SOLAPJSON
2

Geospatial data source
(WFS, DBMS, ...)

1 Built-in or LDAP
Server

Native or XML/A
OLAP4J
MDX
OLAP Server
Client
SOLAPJSON
2

Bridge architecture
Geospatial data source •
Maximize what is in place in organisations
(WFS, DBMS, ...) •
But, no Geo-MDX capabilities available!

1 Built-in or LDAP
Server

Native or XML/A
OLAP4J
MDX
OLAP Server
Client
SOLAPJSON
2

3
(WFS, DBMS, ...) Geospatial data source
(WFS, DBMS, ...)

1 Built-in or LDAP
Server

Native or XML/A
OLAP4J
MDX
OLAP Server
Client
SOLAPJSON
2
•
For simple geo-dashboards
•
Based on transactional data
3 •
Thematic mapping
(WFS, DBMS, ...) Geospatial data source •
No Geo-MDX and drill-down
(WFS, DBMS, ...) or roll-up capabilities!

SOLAPLayers 2.0 – Geo-dashboard made easy!
1 Define the template of the dashboard in a HTML file

1 Define the template of the dashboard in a HTML file

Define your dashboard components in a JS
2 file and map it to the div in the HTML file

3
Enjoy! ;-)

SOLAPLayers – Sum up & roadmap
● As GeoExt which provides Geospatial extensions to ExtJS,
SOLAPLayers provides GeoBI extensions to ExtJS
● So, to make it simple: SOLAPLayers = GeoBIExt!
● At present, it provides the main components for creating
geo-analytical dashboards
– Map, crosstab, column chart, line chart, ...
– But, many more to come and to develop!
● Cube explorer, query builder, time slider/navigator, gauges, score cards, social graphs, ...

– Advanced interaction capabilities and settings will be added to each components!
– Additional thematic mapping capabilities are also required: multi-maps, ...

● Beta of version 2.0 to be released by the end of October 2010
● We anticipate to have a first stable version in January 2011

Questions?
● Thanks for your attention and do not hesitate to ask for
more demos and to contact us for possible collaborations!
● Contact:
Dr. Thierry Badard, CTO
Spatialytics inc.
Quebec, Canada
Email: tbadard@spatialytics.com
Web: http://www.spatialytics.org
http://www.spatialytics.com
Twitter: tbadard & spatialytics

http://www.geokettle.org Twitter : geokettle

http://www.geo-mondrian.org Twitter : geomondrian

http://www.solaplayers.org Twitter : solaplayers

Open source Geospatial Business Intelligence in action with GeoMondrian and SOLAPLayers!

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