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

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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

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

  1. 1. Analyzing demographic and economic simulation model results: a Semi- Automatic Spatial OLAP ApproachHadj Mahboubi, Sandro Bimonte and Guillaume Deffuant ----- Cemagref, Clermont-Ferrand center, France GeoAnMod 2011 Santander - 06-19-2011
  2. 2. Context Urbanization Simulation models Risk management- Study of complex social dynamics andpolicy 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.GEO-AN-MOD 2011 H. Mahboubi et al. 2
  3. 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 OLAPGEO-AN-MOD 2011 H. Mahboubi et al. 3
  4. 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 perspectivesGEO-AN-MOD 2011 H. Mahboubi et al. 4
  5. 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 axesGEO-AN-MOD 2011 H. Mahboubi et al. 5
  6. 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 ?-… GEO-AN-MOD 2011 H. Mahboubi et al. 6
  7. 7. Spatial Data warehouses and SOLAP Typical relational SOLAP architectureGEO-AN-MOD 2011 H. Mahboubi et al. 7
  8. 8. Spatial Data warehouses and SOLAP Example of a visualization using a SOLAP toolGEO-AN-MOD 2011 H. Mahboubi et al. 8
  9. 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 resolutionsGEO-AN-MOD 2011 H. Mahboubi et al. 9
  10. 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 perspectivesGEO-AN-MOD 2011 H. Mahboubi et al. 10
  11. 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 dataGEO-AN-MOD 2011 H. Mahboubi et al. 11
  12. 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.GEO-AN-MOD 2011 H. Mahboubi et al. 12
  13. 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 perspectivesGEO-AN-MOD 2011 H. Mahboubi et al. 13
  14. 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.GEO-AN-MOD 2011 H. Mahboubi et al. 14
  15. 15. Spatial-multidimensional analysis of results Results from simulation model Data and structures Spatial data cubes Results exploration and comparison of modelsSimulation modelexecution environment SOLAP tool User Simulation modelers/stakeholder GEO-AN-MOD 2011 H. Mahboubi et al. 15
  16. 16. Spatial-multidimensional analysis of results Structure Transformation algorithm Spatial data cubes Specify the Results exploration and analysis need Visualization et analysis comparison of modelsSimulation modelexecution environment SOLAP tool User Simulation modelers/stakeholder GEO-AN-MOD 2011 H. Mahboubi et al. 16
  17. 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 IndividualsSimulation result Generic (1) Municipalities Typedata model (2) Households Status Age TimeSteps Status … min(size) avg(size) GEO-AN-MOD 2011 H. Mahboubi et al. 17
  18. 18. Outline Context Definitions : spatial data warehousing and simulation modeling Requirements for the analysis of simulation resultas Spatial-multidimensional analysis SimOLAP tool Conclusion and perspectivesGEO-AN-MOD 2011 H. Mahboubi et al. 18
  19. 19. Spatial-multidimensional analysis of results SimOLAP architectureGEO-AN-MOD 2011 H. Mahboubi et al. 19
  20. 20. Spatial-multidimensional analysis of results Visualization using JRubik OLAP tool;The interactive graphic user interfaceof the "Analysis needs definition component". GEO-AN-MOD 2011 H. Mahboubi et al. 20
  21. 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 perspectivesGEO-AN-MOD 2011 H. Mahboubi et al. 21
  22. 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 clientGEO-AN-MOD 2011 H. Mahboubi et al. 22
  23. 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-usersGEO-AN-MOD 2011 H. Mahboubi et al. 23

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