Analyzing demographic and economic simulation model results: a Semi-Automatic Spatial OLAP Approach

Hadj Mahboubi, Sandro Bimonte and Guillaume Deffuant

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Cemagref, Clermont-Ferrand center, France

GeoAnMod 2011

Santander - 06-19-2011

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Context

- Study of complex social dynamics and policy scenarios

- Used in various contexts

- Produce spatial and temporal data

Simulation models

Urbanization

Risk management

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 thestructural policies of the municipalities.

…

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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 technologi es

SOLAPOLAP

SIG

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Outline

� Context

� Spatial data warehousing and SOLAP ? simulation modeling ?

� Requirements for the analysis of simulation results

� Spatial-multidimensional analysis of simulation resu lts

� SimOLAP tool

� Conclusion and perspectives

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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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Spatial Data warehouses and SOLAP

� Example of a spatial-multidimensional schema

Facts

Dimension

-What is the total of destroyed areas per year and per country ?-…

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Spatial Data warehouses and SOLAP

Typical relational SOLAP architecture

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Spatial Data warehouses and SOLAP

Example of a visualization using a SOLAP tool

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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 m odels, coupling sub-models of different types.

- Understanding the behavior of such models through an analytical analysis of the equations has become unf easible because of their complexity.

- Produce huge volume of datao Several time-steps

o Models have refined spatial and time resolutions

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Outline

� Context

� Definitions : spatial data warehousing and simulati on modeling

� Requirements for the analysis of simulation results

� Spatial-multidimensional analysis of simulation resu lts

� SimOLAP tool

� Conclusion and perspectives

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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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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 the ir analysis needsby 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 classic al 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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Outline

� Context

� Definitions : spatial data warehousing and simulati on modeling

� Requirements for the analysis of simulation resultas

� Spatial-multidimensional analysis of simulation resu lts

� SimOLAP tool

� Conclusion and perspectives

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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 structureo 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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Results from simulation model

Data and structures

Results exploration and comparison of models

Spatial data cubes

User

SOLAP tool

Simulation modelers/stakeholder

Spatial-multidimensional analysis of results

Simulation model execution environment

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Simulation model execution environment SOLAP tool

StructureTransformation algorithm

Specify the analysis need Visualization

et analysis

Spatial-multidimensional analysis of results

Spatial data cubes

Results exploration and comparison of models

User

Simulation modelers/stakeholder

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PRIMA simulation model data structure

Multidimensional schema structures

Households

Type Individuals

Municipalities

TimeSteps

AgeStatus

Households Type

Individuals

TimeSteps

avg(Age)

Status

min(Age)

Type

Households

Municipalities

TimeSteps

avg(size)

Status

min(size)

…

…

(1)

(2)

(1)

(2)

Simulation result Generic data model

Spatial-multidimensional analysis of results

Municipalities

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Outline

� Context

� Definitions : spatial data warehousing and simulati on modeling

� Requirements for the analysis of simulation resultas

� Spatial-multidimensional analysis

� SimOLAP tool

� Conclusion and perspectives

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SimOLAP architecture

Spatial-multidimensional analysis of results

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The interactive graphic user interface of the "Analysis needs definition component".

Visualization using JRubik OLAP tool;

Spatial-multidimensional analysis of results

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Outline

� Context

� Definitions : spatial data warehousing and simulati on modeling

� Requirements for the analysis of simulation resultas

� Spatial-multidimensional analysis

� SimOLAP : the tool

� Conclusion and perspectives

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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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Perspectives

� Develop specific data structures to derive the mult idimensional schema and spatial data cubes

o input, scenarios o experimental design factors

� Improve the geo-visualization interfaces in SOLAP t ools

o Enable a better perception and visualization of the evolution and dynamics on the results

� Design and develop methods and tools dedicated to e nd-users