1. Time for a new Tandem? Marja Tammilehto-Luode

2. Bled 20082Marja Tammilehto-Luode Time for a new Tandem Reflections of the study about grids and blobs Tandem studies - Tandem I - content and conclusions Tandem II - content and conclusions Results and next step

3. Bled 20083Marja Tammilehto-Luode Tandem studies a joint initiative by NSIs (ONS,SF,SS) In search for a common Geographical Base to compare Statistics across the EU cooperative action carried out in 2000-2003 funded by a grant from the Commission (85%) Tandem I 2000-2002, three parties, individual grants Tandem II 2002-2003, three parties a joint grant Tandem I, ? Tandem II, 15 staff months according to work plan

4. Bled 20084Marja Tammilehto-Luode Tandem I Point of departure: A need for more comparable territorial divisions for statistics to visualise data more effectively to combine and compare data on different spatial units to combine or compare data on different spatial scales to make better statistical/spatial analysis of data (to test spatial patterns and trends

5. Bled 20085Marja Tammilehto-Luode The study of two parallel approaches Regular tessellation approach Statistics Finlands responsibility study of methods to construct grid- based statistics tests of candidate methods with empirical data construction of a prototype tests on a prototype with a user case Irregular tessellation approach Office of National Statistics in UKs responsibility study of methods of zoning design tests with ZDES (Zone Design System) by Leeds University with empirical data tests on a prototype with a user case

6. Bled 20086Marja Tammilehto-Luode Input areas Building blocks Output areas Regular tessellationIrregular tessellation

7. Bled 20087Marja Tammilehto-Luode

8. Bled 20088Marja Tammilehto-Luode

9. Bled 20089Marja Tammilehto-Luode Tandem I: Work packages WP1: A Professional context WP2: A Theoretical Assessment WP3: A Practical Assessment WP4: Results and recommendations

10. Bled 200810Marja Tammilehto-Luode Tandem I: Conclusions need for methods to optimise intermediate territorial divisions - to make/standardise building blocks need for two parallel approaches - regular tessellation and irregular tessellation approach harmonised methods for spatial analysis (delineation for example) are as important as comparable data itself need for special disclosure control methods

11. Bled 200811Marja Tammilehto-Luode Tandem I - Report Backer, L., Tammilehto-Luode, M., Gublin, P. (2002). Tandem GIS _I. A Feasibility study towards a common geographical base for statistics across European Union Eurostat working papers: Http://europe.eu.int/comm/eurostat/Public/

12. Bled 200812Marja Tammilehto-Luode The first report: http://europa.eu.int/comm/eurostat/Public/ datashop/print-catalogue/EN?catalogue =Eurostat&collection=12-Working% 20papers%20and%20studies [Theme: General Statistics] (Issue Date: 18/09/2002) PDF -file 154 pages with pictures 200 pages

13. Bled 200813Marja Tammilehto-Luode Objectives of Tandem II Further development of methods introduced in Tandem_GIS I Test with data of new variables and different kind of georeferences and different scale of analysis Case studies -to highlight contrasts between geographical areas -to improve clustering methods and production of better estimates -to develop methods to transform data of different territorial divisions

14. Bled 200814Marja Tammilehto-Luode Tandem II: Content of Action How to build/a strategy for an SSAS (System of Small Area Statistics) for Europe Development of delineation methods Comparison of grid-based and polygon-based approaches in zoning/delineation Guidelines for dissemination of small area statistics

15. Bled 200815Marja Tammilehto-Luode Building Blocks or Methods Data Grids and Blobs Comparable Statistics Comparable territorial areas Comparable territorial statistics = SSAS

16. Bled 200816Marja Tammilehto-Luode A vision of SSAS in the year 2010 Phase I – Consolidation, Standardisation and Collaborative Research (2004 – 2008) -a common framework for spatial referencing, standard definitions and methods to construct building blocks... Phase II – Dissemination and Local implementation (2006 – 2010 -recommendations, guidelines available Phase III – SSAS (2010 - ), -a catalogue of SSAS, easy-to use tools, documented user cases, recommended methods for spatial analysis

17. Bled 200817Marja Tammilehto-Luode EU strategy for SSAS Eurostat guides, intrepreters, investigates NSIs and NMAs Best practices -applying data, features and methods ESPON and others networks Inspire, harmonisation rules Ongoing feedback Tuning of the strategy

18. Bled 200818Marja Tammilehto-Luode Development of delineation methods Case studies WP3: Delineation by Automated Zoning Method (AZM) WP4: Delineation by Interpolation (Kriging) WP5: Delineation by AZM and Kriging

19. Bled 200819Marja Tammilehto-Luode Comparison of AZM and Kriging AZM (ZDES, University of Newcastle, UK) Area-based input data Area optimisation by certain criteria Creates comparable data by chosen constraints Problems - Computing time - Islands - Definition of number of output areas Kriging (Surfer, ArcGIS…) Point-based input data Creates continuous surface by predicting cell values Isolines of certain values for delineation Problems - Several interpolation methods available - may give different results - Dependent on coverage of data

20. Bled 200820Marja Tammilehto-Luode Comparison of grid-based and polygon-based approaches Grid-based approach Best with accurate data (total coverage), otherwise estimation needed Spatial, comparable building blocks AZM, Kriging and classification applicable Applicable to different scales and resolutions Polygon-based data Small area statistics (smaller than NUTS5) - otherwise spatial analysis not valuable AZM - when boundaries known (low resolution) Kriging when boundaries unknown (low to high resolution) Building blocks could be optimised first by AZM

21. Bled 200821Marja Tammilehto-Luode Guidelines for dissemination of small area statistics International/European.. Harmonised data - Need for reference data - Focus on metadata - Standard data model, storage format, output format - Common grid net Collaborative agreement - Formal project with proper funds - Focus on harmonised data specifications and common standards - Co-operation with mapping authorities may be fruitful - Third party may be needed to facilitate and optimise sharing, trading and extensive use of multinational data

22. Bled 200822Marja Tammilehto-Luode Guidelines for dissemination of small area statistics Quality and disclosure control - Different practice in each country - Essential part of good statistics - Emerging international standards (ISO 11913-11915) - Requires further studies/research both nationally and internationally - High expectations on INSPIRE National and/or international guidelines - International guidelines can never compensate national standards - National guidelines should adopt international concepts, definitions, classifications, metadata descriptions….

23. Bled 200823Marja Tammilehto-Luode Guidelines for dissemination of small area statistics International - standardised grid net necessary - Common origo - Proper projections for different scales - For joining data from different areas (horizontally) - For joining data from different data sources (vertically) - For data capture, spatial analysis International guidelines to enable better access to data

24. Bled 200824Marja Tammilehto-Luode

25. Bled 200825Marja Tammilehto-Luode

26. Bled 200826Marja Tammilehto-Luode

27. Bled 200827Marja Tammilehto-Luode

28. Bled 200828Marja Tammilehto-Luode Conclusions SSAS - Framework of spatial data of NSIs needed Harmonisation with ESDI and INSPIRE with emphasis on analytical information Top-down co-ordination - Bottom-up implementation Restructuring and refinement of current systems Focus on user needs and case studies Standards for Data, Features and Methods Scalability, comparability, delineation, confidentiality, quality, easy-to-use procedures...

29. Bled 200829Marja Tammilehto-Luode Conclusions SSAS - Framework of spatial data of NSIs needed Harmonisation with ESDI and INSPIRE with emphasis on analytical information Top-down co-ordination - Bottom-up implementation Restructuring and refinement of current systems Focus on user needs and case studies Standards for Data, Features and Methods Scalability, comparability, delineation, confidentiality, quality, easy-to-use procedures...

30. Bled 200830Marja Tammilehto-Luode Tandem II - Report Tandem II: Tammilehto-Luode, M., Ralphs, M., Backer, L. (2003). Tandem II. Towards a common geographical base for statistics across Europe. The final report. 25 pages + Appendices 256 pages.

31. Bled 200831Marja Tammilehto-Luode

32. Bled 200832Marja Tammilehto-Luode Results Better understanding of spatial statistics traditional regional statistics cannot describe properly regional changes of distribution of welfare -example of BKT/inhabitants of London more precise allocation of multi problematic areas may cause better follow up of potential actions more precise allocation of social actions may save governmental spending small building blocks for other/flexible territorial statistics solutions for regional timeseries use of spatial analysis INSPIRE

33. Bled 200833Marja Tammilehto-Luode Results Long term general strategy to build SSAS (a system of small area statistics) for Europe Development of delineation methods Comparison of grid-based and polygon-based approach in zooning /delineating Guidelines for dissemination of small area statistics

34. Bled 200834Marja Tammilehto-Luode Results a proposal for a Eurogrid - a software to make it prototype of population grid data, a hierarchy of grids - by aggregation and disaggregation methods European gridclub - number of members growing(?) several references (citations) in other publications - many focusing the census 2010

35. Bled 200835Marja Tammilehto-Luode

36. Bled 200836Marja Tammilehto-Luode GEOSTAT?