Presentation on theme: "Ekkehard Petri GISCO Eurostat 1 Update on EUROSTAT activities A second hand experience."— Presentation transcript:
Ekkehard Petri GISCO Eurostat 1 Update on EUROSTAT activities A second hand experience
07 October 2010 EFGS Meeting 2010 Den Haag 2 LUCAS Census 2010 SDMX
07 October 2010 EFGS Meeting 2010 Den Haag 3 LUCAS data collection process 1 100 000 points LAND COVER classes 1 ARABLE LAND 2 PERMANENT CROPS 3 GRASSLAND 4 WOODED AREAS AND SHRUBLAND 5 BARE LAND, RARE VEGET. 6 ARTIFICIAL LAND 7 WATER First phase sample for stratification: orthophoto interpretation 2km grid Ground survey Parameters Land cover Land use pictures etc. Sample of around 260,000 pts Second phase sample: in-situ data collection
07 October 2010 EFGS Meeting 2010 Den Haag 4 Definition of sample size by strata –Optimal size by NUTS2 and strata based on fixed precisions for a set of LC classes targeted by country Points selection –LUCAS 2006 sample points included as much as possible (land cover/use changes can be detected) –Maximisation of the distance between points –Exclusion of remote points and points above 1000m Sampling strategy: Second phase sampling design
07 October 2010 EFGS Meeting 2010 Den Haag 5 A10Artificial Built-up areas A20Artificial non built-up areas B10Cereals (+ triticale) B20Root crops B30Non permanent industrial crops B40Dry pulses, vegetables and flowers B50Fodder crops B70Fruit trees & berries B8Other Permanent Crops C10Broadleaved and evergreen woodland C20Coniferous woodland C30Mixed woodland D10Shrubland with sparse tree cover D20Shrubland without tree cover E10Grassland with sparse tree/shrub cover E20Grassland without tree cover E30Spontaneous vegetation F00Bare Land G10Inland water bodies G20Inland running water G30Coastal water bodies G50Glacier, permanent snow H10Inland marshes H20Peatbogs H30Salt-marshes H40Salines H50Intertidal flats Land Cover nomenclature LUCAS 2009 A10 Artificial Built-up areas A11Buildings with one to three floors A12Buildings with more than three floors A13Greenhouses A20 Artificial non-built up areas A21Non built-up area features A22Non built-up linear features
07 October 2010 EFGS Meeting 2010 Den Haag 6 U110Agriculture ( + Kitchen garden + Fallow land) U120Forestry U130Fishing U140Mining, Quarrying U150Hunting U210Energy production U220Industry & Manufacturing U310Transport, communication, … U320Water & waste treatment U330Construction U340Commerce, Finance, Business U350Community Services U360Recreation, Leisure, Sport U370Residential U400Unused Land Use nomenclature LUCAS 2009
07 October 2010 EFGS Meeting 2010 Den Haag 8 Data availability per country/year
07 October 2010 EFGS Meeting 2010 Den Haag 9 Census
07 October 2010 EFGS Meeting 2010 Den Haag 10 EU census goals Comparability of census data on the EU level Same reference year (first time: 2011) Same topics (variables) Use of harmonized definitions and technical specifications Use of identical breakdowns of the topics Unified dissemination programme (hypercubes) =>Common Baseline across countries Transparent quality of census results Quality reports Detailed tables on quality of the data Metadata
07 October 2010 EFGS Meeting 2010 Den Haag 11 EU census limits What does the regulation not provide? No access to microdata No possibility to define geographical areas flexibly No harmonised confidentiality control No normative minimum quality requirements (quality thresholds) No consolidation of census results form different Member States BUT Member States are free to do more!
07 October 2010 EFGS Meeting 2010 Den Haag 12 NUTS2: Year of arrival in the country Educational attainment Location of place of work Current activity status Occupation Industry Status in employment Tenure status of households Housing arrangements Type of ownership (of dwellings) Water supply system, Toilet facilities, Bathing facilities, Type of heating What data for what geographical area?
07 October 2010 EFGS Meeting 2010 Den Haag 13 Population topics Sex Age Legal marital status Country/place of birth Country of citizenship Place of usual residence one year prior to the census (Size of the) Locality Household status Type of private household Size of private household Family status Type of family nucleus Size of family nucleus Total population Place of usual residence Relationships between household members What data for what geographical area ? LAU 2 Housing topics Occupancy status of conventional dwellings Number of occupants Useful floor space and/or Number of rooms Density standard Dwellings by type of building Dwellings by period of construction Type of living quarters Location of living quarters
07 October 2010 EFGS Meeting 2010 Den Haag 14 What we can NOT do for GISCO ? The municipalities as smallest geographical area for the census data to be transmitted to Eurostat (LAU 2 level) are fixed. No flexibility to define areas freely. After long and detailed consultation with the Census experts from the Member States, the foreseen obligatory statistical programme represents a balance between the desirable and the feasible. Eurostat does not have access to census microdata. Confidentiality control is done by the NSI.
07 October 2010 EFGS Meeting 2010 Den Haag 15 Usage of common definitions, technical specifications and breakdowns makes census data better comparable at the European level. Intensive description and quality reporting of the NSI on the data sources and methodology they use to do the population and housing census. This might help to develop small area reporting systems. Key topics will be required for the LAU 2 level. It is likely that some of the data might also be available for even smaller areas in some Member States. Eurostat organizes a task force on Census Data Disclosure Control which aims at proposing best methodology and practice to protect census data with minimum damage to disseminated results. The Census Hub might be used to exchange and disseminate small area data from censuses. What we can do for GISCO ?
07 October 2010 EFGS Meeting 2010 Den Haag 16 Census Hub project: architecture WS database WS database WS database
07 October 2010 EFGS Meeting 2010 Den Haag 17 The Census Hub project The Census Hub project aims to build a new IT infrastructure to achieve the data exchange between the National Statistical Institutes (NSI), Eurostat and the users of census data using SDMX standards. Data sharing architecture Based on the agreed hyper-cubes with harmonised data Confidentiality problems handled at national level A data user browses the hub to define a dataset of interest via structural metadata (dimensions, attributes, measures, code lists, etc). Data are retrieved directly from the interested Member States systems
07 October 2010 EFGS Meeting 2010 Den Haag 18 Present and ongoing activities Pilot project in Germany, Ireland, Italy and Portugal Guideline explaining how to implement an SDMX MSs architecture in the Census Hub context available
07 October 2010 EFGS Meeting 2010 Den Haag 19 SDMX
07 October 2010 EFGS Meeting 2010 Den Haag 20 What is SDMX Statistical Data and Metadata Exchange SDMX preferred standard for exchange and sharing of data and metadata in the global statistical community Sponsors include –European Central Bank (ECB) –Eurostat –Organisation for Economic Co-operation and Development (OECD) –United Nations Statistical Division (UNSD)
07 October 2010 EFGS Meeting 2010 Den Haag 21 Benefits from SDMX standards Covers potentially all statistical domains Open to all stakeholders Are neutral in terms of underlying commercial technologies Demography and the Census hub already implemented
07 October 2010 EFGS Meeting 2010 Den Haag 22 SDMX is not just a data transmission format… Similarities with INSPIRE are substantial SDMX components Information model for data and metadata Syntax for automatic exchange of data and metadata Information model for data and metadata Syntax for automatic exchange of data and metadata Guidelines to Harmonise Contents IT Architectures for data exchange IT tools to support implementation and to disseminate SDMX data
07 October 2010 EFGS Meeting 2010 Den Haag 23 SDMX Components: Information Model Statistical data Metadata –Structural –Conceptual –Quality –Methodology Data exchange process
07 October 2010 EFGS Meeting 2010 Den Haag 24 SDMX Information Model Dataset Structure Definition DSD Dataset Structure Definition DSD Data Structural Metadata Structural Metadata Dimensions (ex: country, variable/topic, year) Dimensions (ex: country, variable/topic, year) Attributes (ex: unit of measure) Attributes (ex: unit of measure) Code lists Metadata about an individual value, a time series or a group of time series Provides a way of modelling statistical data, metadata and data exchange processes. Describe
07 October 2010 EFGS Meeting 2010 Den Haag 25 SDMX Components: IT Tools SDMX Registry Tools to create data definitions and metadata Tools to convert and validate data and metadata Tools to visualise data and metadata Training available from Eurostat http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2 733,61942355,2733_61942368&_dad=portal&_schema =PORTAL http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2 733,61942355,2733_61942368&_dad=portal&_schema =PORTAL
07 October 2010 EFGS Meeting 2010 Den Haag 26 SDMX Registry Repository Structural metadata CodeLists ConceptSchemes DSDs Provision of information Dataflows Provision agreements Accessible via a Web Service accepting SDMX-ML messages Graphical User Interface (GUI) for user interaction over the Web DSW – standalone Java GUI