Analyzing demographic and economic simulation model results: a Semi-Automatic Spatial OLAP Approach Hadj Mahboubi, Sandro Bimonte, Guillaume Deffuant - Research Centre on Technologies, information systems and processes for agriculture (Cemagref,), Clermont Ferrand

1. Analyzing demographic and economic
simulation model results: a Semi-
Automatic Spatial OLAP Approach
Hadj Mahboubi, Sandro Bimonte and Guillaume Deffuant
-----
Cemagref, Clermont-Ferrand center, France
GeoAnMod 2011
Santander - 06-19-2011

2. Context
Urbanization
Simulation models
Risk management
- Study of complex social dynamics and
policy scenarios
…
- Used in various contexts
- Produce spatial and temporal data
PRIMA simulation model "develop a method for scaling down the
analysis of policy impacts on multifunctional land uses and on the
economic activities"
The goal is to analyze the evolution of the populations according to the
structural policies of the municipalities.
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3. Objective
o Provide decision-makers (stakeholder/simulation modelers) with
dedicated tools that allow them exploring model results through
cartographic and tabular displays
o Allow a multidimensional analysis of results issued from the
(PRIMA) simulation model
Exploit Spatial Data Warehouses and SOLAP technologies
SIG
SOLAP
OLAP
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4. Outline
Context
Spatial data warehousing and SOLAP ? simulation
modeling ?
Requirements for the analysis of simulation results
Spatial-multidimensional analysis of simulation results
SimOLAP tool
Conclusion and perspectives
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5. Spatial Data warehouses and SOLAP
o Data warehouses: designed to support business intelligence and
knowledge discovery
o Defined as “a subject-oriented, integrated, non-volatile and time-
variant collection of data stored in a single site repository and
collected from multiple sources” (Inmon, 2005)
o OLAP and Spatial-OLAP
OLAP (Online Analytical Processing) (Rafanelli, 2003)
SOLAP (Spatial OLAP): combines OLAP and Geographic
Information Systems (GIS) functionalities in a unique coherent
framework (Bédard, 1997).
o Organized according the multidimensional schema (conceptual
representation)
Fact : analysis subject
Dimensions : analysis axes
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6. Spatial Data warehouses and SOLAP
Example of a spatial-multidimensional schema
Dimension
Facts
-What is the total of destroyed areas per year and per country ?
-…
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7. Spatial Data warehouses and SOLAP
Typical relational SOLAP architecture
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8. Spatial Data warehouses and SOLAP
Example of a visualization using a SOLAP tool
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9. Modeling complex spatial dynamics
Study of complex phenomena and scenarios, such as
urbanization, risk management, etc.
Yield to the development of more and more complex models,
coupling sub-models of different types.
- Understanding the behavior of such models through an
analytical analysis of the equations has become unfeasible
because of their complexity.
- Produce huge volume of data
o Several time-steps
o Models have refined spatial and time resolutions
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10. Outline
Context
Definitions : spatial data warehousing and simulation
modeling
Requirements for the analysis of simulation results
Spatial-multidimensional analysis of simulation results
SimOLAP tool
Conclusion and perspectives
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11. Requirements for an SOLAP tool
o Manage huge amounts of simulation result data produced by
simulation models
o Extract and construct indicators as well as cartographic visualizations
o Overcome limitations of existing tools:
Lack of relational storage support to grant scalability, structured data
representation and efficient querying
Current GIS are efficient for cartographic data visualization, but :
• They are not especially designed for the analysis of huge volumes of data
• They do not support geo-visualization techniques for interactive exploration
and analysis of multidimensional spatial data
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12. Requirements for an SOLAP tool
Growing need to develop tools that:
o Build spatial data cubes on which SOLAP operations can be performed
avoid experts' intervention and reduce the design task complexity.
o Provide facilities allowing modelers to specify their analysis needs
by themselves and deriving the adequate spatial data cubes accordingly.
o Provide flexibility and interactivity. Indeed, the analysis requirements
on the same simulation results may change over time and can depend
strongly on the user. This leads to the construction of different spatial
data cubes in an iterative manner.
o Exploit methods that efficiently handle non classical data to build
appropriate data cubes. Indeed, simulation results can be considered as
semi-structured data and are usually stored in text files.
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13. Outline
Context
Definitions : spatial data warehousing and simulation
modeling
Requirements for the analysis of simulation resultas
Spatial-multidimensional analysis of simulation results
SimOLAP tool
Conclusion and perspectives
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14. Spatial-multidimensional analysis of results
Capture the simulation modeler analysis needs.
o Performed using the simulation result structure captured during the
simulation runs.
o It is built based on the tree result structure
o Structure is presented to the users by means of an interactive visual
interface that allows users to select an item to analyze
Derive the multidimensional schema. SimOLAP generates a
multidimensional schema using the selected item as fact and
automatically deriving dimensions and measures from the simulation
result structure.
Built the appropriate spatial data cube in a SOLAP tool.
SimOLAP also automatically implements the spatial data cube for the
previous generated multidimensional schema, and feeds it with
simulation results.
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15. Spatial-multidimensional analysis of results
Results from
simulation
model
Data and
structures Spatial data cubes
Results exploration and
comparison of models
Simulation model
execution environment SOLAP tool
User
Simulation modelers/stakeholder
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16. Spatial-multidimensional analysis of results
Structure Transformation
algorithm
Spatial data cubes
Specify the Results exploration and
analysis need Visualization
et analysis comparison of models
Simulation model
execution environment SOLAP tool
User
Simulation modelers/stakeholder
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17. Spatial-multidimensional analysis of results
PRIMA simulation model Multidimensional schema structures
data structure
Municipalities
Households Type
TimeSteps Individuals
Municipalities TimeSteps Status
(1)
…
avg(Age)
(2) min(Age)
Households
Type Individuals
Simulation result Generic
(1) Municipalities Type
data model (2)
Households
Status Age
TimeSteps Status
…
min(size) avg(size)
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18. Outline
Context
Definitions : spatial data warehousing and simulation
modeling
Requirements for the analysis of simulation resultas
Spatial-multidimensional analysis
SimOLAP tool
Conclusion and perspectives
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19. Spatial-multidimensional analysis of results
SimOLAP architecture
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20. Spatial-multidimensional analysis of results
Visualization using JRubik OLAP tool;
The interactive graphic user interface
of the "Analysis needs definition component".
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21. Outline
Context
Definitions : spatial data warehousing and simulation
modeling
Requirements for the analysis of simulation resultas
Spatial-multidimensional analysis
SimOLAP : the tool
Conclusion and perspectives
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22. Conclusion
Address recent needs for managing and analyzing
simulation results
o Efficient methods and techniques for explorative data analysis:
SOLAP technologies
o A tool that semi-automatically implements spatial data cubes for
exploring the results of simulation models
o Helps users to easily specify their analysis needs and the
automatic implementation of the corresponding spatial data cube
o the analysis and the visualization of the spatial data cubes are
carried out using appropriate SOLAP client
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23. Perspectives
Develop specific data structures to derive the multidimensional
schema and spatial data cubes
o input, scenarios
o experimental design factors
Improve the geo-visualization interfaces in SOLAP tools
o Enable a better perception and visualization of the evolution and
dynamics on the results
Design and develop methods and tools dedicated to end-users
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