The federal geo-platform:

Transcription

1 The federal geo-platform: Targeting the statistical community Nathalie Delattre (IGN Belgium), Pierre Jamagne (Statistics Belgium), Ann Crabbé (KULeuven/SADL) INSPIRE Conference, Strasbourg 6-8 septembre 2017

2 Outline 1.Setting the scene 2.Data Transformation & Validation on Statistics 3. Conclusions 1. Setting the scene: the federal geo-platform and the collaboration approach 2. INSPIRE data transformation and validation process on Statistics 3. Conclusions

3 1.1 INSPIRE Technical Infrastructure 1.Setting the scene Plateform implemented and maintained by NGI (NMA) + Support Potential other applications from BOSA Geoportal Secure access mechanisms Federal services Federal metadata Federal data

4 1.2 The federal partners 1.Setting the scene 10 departments as data & services providers Royal Meteorological Institute of Belgium Statistics Belgium & Continental Platform National Geographic Institute Royal Belgian Institute of Natural Sciences Belgian Interregional Environment Agency

5 1.3 Federal INSPIRE datasets 1.Setting the scene

6 1.4 Working with federal partners 1.Setting the scene security mechanisms, cloud system (BOSA) expertises and consultance (identifying datasets) technical support / helpdesk (Geonetwork) National Geographic Institute as geobroker supports: INSPIRE validation / quality control best practices exchange, training, workshops setting up and hosting services on demand federal discovery service + Monitoring & Reporting

7 1.5 Introducing FPS Economy 1.Setting the scene Economi c Potential Compet ition III.1 Statistical Units : 1. Statistical districts 2. Functional Urban areas, cities, subcitydistricts (Urban Audit) Inspire SPOC Statistics Belgium SMEs Policy Supervision and Mediation Energy Quality & Security Regulation and Organisation of the Market Telecomm unications and Informatio n Society Data Provider for the continental platform III.10 Population distribution: 1. Population on 1 km² grid cells 2. Population per Statistical District III. 21 Mineral ressources: 1. Sand and Gravel extractions North Sea

8 1.6 Best practices about tasks division 1.Setting the scene INSPIRE Metadata (.xml) delivered to IGN in 4 languages : EN/FR/NL/DE validate the metadata & recommendations for improvement FPS Economy NGI Bilateral agreement FPS Economy NGI

9 1.7. The federal geo-catalogue 1.Setting the scene

10 2.1 Data workflow 1. 2.Data Transformation & Validation on Statistics Data sources Shapefiles with required attributes Data Mapping HALE Data export GML HALE INSPIRE GML file Internal view check QGIS, wordpad, GML viewer N OK Y WFS service Deegree INSPIRE compliant GML file Y OK N Validation JRC Validation tools and/or schematron

11 2.2 Data Transformation on Statistical Units 1. 2.Data Transformation & Validation on Statistics Belgium = Statistical Sectors KISS option for beginners: only mandatory information Output: 1 file /country Source Shapefiles 52 Mb Data tranformation INSPIRE GML 133Mb Rather easy and straithforwards Usable and readable ( QGIS)

12 2.3 Data transformation on Population Distribution (PD) 1. 2.Data Transformation & Validation on Statistics INSPIRE data model with a one polygon geometry Issue in data transformation HALE RAM capacities Solutions: PD values per statistical sector (19 782) PD values per grid 1km (32 000) Data tranformation Virtual machine : 32Gb RAM, 64 bits, 2.3 Ghz 1 GML file (65 Mb ) 5 GML files ( 12Mb each) Chosen option: the minimum number of GML files, the better regarding the data maintenance One polygon One record

13 2.4 Findings 1. 2.Data Transformation & Validation on Statistics Data transformation process on Statistical Units (SU) Data transformation process for Population Distribution (PD) 1 geometric feature (Record big size) Usable and readable from usual GIS tools? Statistic Community promotes other format INSPIRE data specifications for Population Distribution fit for purpose? Change proposals: Integrate geometric features from Statistical Units Or tabular data (Access, excell, ) to be linked to theme Statistical Units Or format used by NSI to transfer their statistical data to Eurostat

14 2.5 Data Validation Process (1) 1. 2.Data Transformation & Validation on Statistics GML file INSPIRE (1) Visual Check Avoid rubbish file GML format Data Specifications (in general)

15 2.5 Data Validation Process (2) 1. 2.Data Transformation & Validation on Statistics GML file INSPIRE (1) Visual Check (2) Used for general conformance (2) Issue in interpreting «possible» errors. Actual error Used TGs more restrictive than IRs Implementation interpretation (ETS) Bugs OK (2) JRC validation tools (3) Schematron implementation based on ATS OK GML file INSPIRE compliant

16 3. Conclusions Conclusions Technical Data Specifications understanding : too complicated for non UML/GML expert. Data providers need support and training (GML/UML/HALE) in INSPIRE data transformation INSPIRE thematic cluster and HALE forum helpful. INSPIRE data specifications on Population Distribution fit for purpose? JRC validation tools promising (but BETA version) -> caution with error interpretation Organisational framework in tasks sharing and work flow procedures are key for good success, but might take a while.

17 Contact: Nathalie Delattre : INSPIRE programme manager National Geographical Institute of Belgium nathalie.delattre@ngi.be See: Contact: Pierre Jamagne: Attaché Géographe Responsable SIG Statistics Belgium pierre.jamagne@economie.fgov.be