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Long Term Data Base & Data Navigator II ESPON SEMINAR 14 -15 November 2006 Long Term Data Base & Data Navigator II ESPON SEMINAR 14 -15 November 2006 Dipoli Conference Centre, Espoo, Finland Joël Boulier, Claude Grasland Laboratoire Géographie-cités (Paris) – HYPERCARTE Research Group Marc Guerrien, Nicolas Lambert CNRS UMS RIATE (Paris) – HYPERCARTE Research Group Jérôme Gensel, Bogdan Moisuc, Marlène Villanova-Oliver Laboratoire LSR-IMAG (Grenoble) – HYPERCARTE Research Group

Context n ESPON 3. 2 Programme (European Commission 2002 -2006) ¨ Long Term (ESPON) Context n ESPON 3. 2 Programme (European Commission 2002 -2006) ¨ Long Term (ESPON) Data. Base n n n Provide scenario builders quantitative inputs on selected topics at regional level for years 1980, 2000 and 2020 Try to establish a sustainable framework for the ESPON Database in the future ESPON II, taking into account various problems encountered (missing values, changing territorial units, etc. ) HYPERCARTE Research Group ¨ ¨ ¨ 2 Research Labs in Geography: Géographie-Cités and UMS RIATE 2 Research Labs in Computer Science: LSR-IMAG and ID-IMAG Goals: Advanced Methods and Tools for Spatial Analysis Involved in ESPON 3. 1, 3. 4. 3 and 3. 2 Software n n Available: Hyper. Atlas (application ESPON Hyper. Atlas ESPON 3. 1) Soon to come: Hyper. Admin, Hyper. Smooth, LTDB

LTDB: Objectives n Objective 1: Provide a framework for long-term storage of thematic and LTDB: Objectives n Objective 1: Provide a framework for long-term storage of thematic and geometric data for the territorial units composing a given area, at different levels ¨ This implies tackling several issues: ¨ n n Evolutivity rely on a flexible schema Data quality keep trace of the quality of the data Usability make it usable by other people than its designers, possibly as a shared resource Objective 2: ¨ Provide a framework for a reliable estimation of missing indicator values n n ¨ To fill-up informational gaps To simulate past or/and future hypothetical situations This implies designing several components: n n n A set of generalized estimation methods A set of generalized estimation strategies A mechanism for evaluating the quality of the estimated data

ESTI…mate n Postulate: All statistical information managed by the LTDB can be described according ESTI…mate n Postulate: All statistical information managed by the LTDB can be described according to four dimensions E, S, T and I ¨ ¨ n (E)space: the spatial unit to which the statistical information is attached (S)ource: the statistical institute which has produced the information (T)ime: a period or an instant which dates the information (I)ndicator: a thematic definition of the variable … And then come more general problems ¨ Instability of the administrative structures n n n ¨ Heterogeneity of the sources n ¨ The source S does not provide any value for the given (E, T, I) Missing values n n The name and/or the borderline of E can have changed someday… W. Germany + E. Germany Czechoslovakia Czech Republic + Slovakia Côtes du Nord Côtes d'Armor Isère 1960 Isère 2006 and Rhône 1960 Rhône 2006 At time T, no value for E and I whatever S … How to Cope with Reality?

LTDB: General Architecture Legend Hierarchy of concepts Rule-based expert system Indicator Formulae Knowledge base LTDB: General Architecture Legend Hierarchy of concepts Rule-based expert system Indicator Formulae Knowledge base Geographic Ontology Application Management Module Indicator Ontology Estimation Module Database Method Hierarchy Estimation Strategies Knowledge base Spatio-Temporal Database Data Management Module

LTDB: Architecture Components n n n Geographic Ontology: a gazetteer containing names of geographic LTDB: Architecture Components n n n Geographic Ontology: a gazetteer containing names of geographic entities and some relations between them Indicator Ontology: a classification hierarchy of themes and indicators with some relations between them (aggregation, broader term, etc. ) Indicator Formulae Knowledge Base: a set of mathematical rules for calculating new indicators using existing ones Method Hierarchy: a classification of estimation methods Estimation Strategy Knowledge Base: a set of rules allowing the system to choose the most appropriate estimation method in a given situation Spatio-Temporal Database: a relational database containing the whole set of geographic entities with their known indicator values

LTDB Schema LTDB Schema

Estimation Methods n E, S, T and I define a hypercube of information… with Estimation Methods n E, S, T and I define a hypercube of information… with holes (missing values) n We need ESTImation methods To fill up missing values of the past ¨ To predict future values ¨ n So far, (simple) ESTImations methods have been proposed Estimation methods based on one-dimension: E, S, T or I ¨ Estimation methods based two (or more) dimensions: ES, SI, ET… ¨ n The Method Hierarchy and the Estimation Strategy Knowledge Base will be designed to extend this set of methods

LTDB: First and Future Developments n A first prototype has been developed Implementation of LTDB: First and Future Developments n A first prototype has been developed Implementation of the database schema in the open source POSTGRES DBMS ¨ Data acquisition mechanisms in Java ¨ The LTDB framework imports and exports data files in various formats (excel, dbf. . . ) ¨

LTDB: First and Future Developments n Short Term Estimation methods hierarchy using AROM (an LTDB: First and Future Developments n Short Term Estimation methods hierarchy using AROM (an Object-Based Knowledge Representation System) ¨ Indicator formulae knowledge base in AROM ¨ Estimation strategy knowledge base with AROMTasks ¨ Test and validation through an incremental approach: start with an example with a small set of indicators and some estimation methods, adding more indicators later ¨ n Mid term ¨ LTDB as a research project of the HYPERCARTE Research Group, will be integrated into the Hyper. Atlas and Hyper. Admin software n n In the case of the ESPON Hyper. Atlas, this will allow the visualization (by simply moving a cursor on a time line, for instance) of the evolution of the ratio of two indicators through past, present, but also future time Long term ¨ in order to perform simulations that validate different scenarios, LTDB will integrate estimation methods relying on different parameters which convey tendencies, hypothesis and assumptions corresponding to these scenarios

Data Navigator II n General objective: produce a handbook on data acquisition and harmonization, Data Navigator II n General objective: produce a handbook on data acquisition and harmonization, with a focus on themes investigated by the ESPON Program n Applied research n This project can be seen as an application and a validation test for the LTDB structure through European Databases (ESPON DB, …)

Work in Progress n Three workpackages have been determined ¨ WP 1: Use and Work in Progress n Three workpackages have been determined ¨ WP 1: Use and practices of data collection in ESPON I n n ¨ WP 2: Choice of data model for ESPON II n n ¨ Short survey on practices of some TPG's (IGEAT) Problem of national data collections (TIGRIS) Practical example of data integration between environmental and socio economic data (Géographie-cités & LSR-IMAG) Choice of the best solution for data modeling and data integration (Géographie-cités & LSR-IMAG) WP 3: Handbook for data collection n Practical rules for harmonization (time and space, thematic harmonization) Practical rules for the use of national sources Recommendations for ESPON II : one or two databases

Integration of environmental and socio economic data Question: How many m 2 of forest Integration of environmental and socio economic data Question: How many m 2 of forest are accessible for a European citizen? n NUTS 23_99 CLC 00_forest

Integration of environmental and socio economic data Forest area per inhabitant in 2000 Integration of environmental and socio economic data Forest area per inhabitant in 2000

Integration of environmental and socio economic data Potential of forest area per inhabitant within Integration of environmental and socio economic data Potential of forest area per inhabitant within a 10 km radius in 2000

How far do we get? n n ESPON Database in its current structure is How far do we get? n n ESPON Database in its current structure is a repository for a huge set of European indicators Long Term Database relies on a structured schema designed for the import of different kinds of indicators (different sources, different grids, different census times, …) Two different approaches (from philosophical & technical points of view) ¨ During the development of LTDB, we have experienced that to extract and import some indicators from a data source is not a trivial task (ESPON Database included) ¨

Coupling LTDB and ESPON Database? n n n The acquisition process (values from the Coupling LTDB and ESPON Database? n n n The acquisition process (values from the ESPON Database) has to be automated A ‘wrapper’ dedicated to the ESPON Data Base which will enable the import of incomplete sets of indicators from the ESPON Database into LTDB This wrapper exploits a meta description of the schema of the imported source of data (in this case ESPON Database) To update the LTDB with ESPON data, a complete description of the structuration of the ESPON Database is needed A cooperation between authors of LTDB and ESPON Databases will be beneficial for both tools in the future…

Long Term Data Base & Data Navigator Thank You for Your Attention… Questions? Joël Long Term Data Base & Data Navigator Thank You for Your Attention… Questions? Joël Boulier, Claude Grasland {joel. boulier, claude. [email protected] cnrs. fr} Marc Guerrien, Nicolas Lambert {marc. guerrien, nicolas. lambert}@ums-riate. org Jérôme Gensel, Bogdan Moisuc, Marlène Villanova-Oliver {jerome. gensel, bogdan. moisuc, marlene. villanova}@imag. fr

LTDB Schema Temporal name Temporal object Proximity/similarity Temporal value of Indicators with anmeasure matrix LTDB Schema Temporal name Temporal object Proximity/similarity Temporal value of Indicators with anmeasure matrix internal some indicator for identifier some GU Temporal code Reliability of the Temporal spatial system source representation Temporal splitting and merging of GU’s Code depending on Composition relation between Database or Temporal a code system GU’s, depends on process hierarchical genealogy the hierarchy of a value organization of GU’s Providing organism

Open Questions n Evolution of the conceptual model of the LTDB? Terminology (semantic units, Open Questions n Evolution of the conceptual model of the LTDB? Terminology (semantic units, spatial inclusion or aggregation, …) ¨ Partial space inclusion: what does it mean? ¨ n Data importation from different sources? Data from different sources will be imported ¨ Needs an interface for facilitating the importation of heterogeneous data (tools developped for Hyper. Admin could serve…) ¨ n Sources? ESPON database (BBR) ¨ Corine Land Cover ¨ United Nations ¨ … ¨