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National reference metadata

Slovenia

Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.

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Census 2011 round (cens_11r)

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Statistical Office of the Republic of Slovenia (SURS)

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27 December 2013

The EU programme for the 2011 population and housing censuses include data on persons, private households, family nuclei, conventional dwellings and living quarters

Persons enumerated in the 2011 census are those who were usually resident in the territory of the reporting country at the census reference date. Usual residence means the place where a person normally spends the daily period of rest, regardless of temporary absences for purposes of recreation, holidays, visits to friends and relatives, business, medical treatment or religious pilgrimage

Data are available at different levels of geographical detail: national, NUTS2, NUTS3 and local administrative units (LAU2)

1 January 2011

Counts of statistical units

Main steps of data compilation were:

  1. Input database loading – data from 19 different sources stored in almost 30 databases were prepared (most of them as txt files  and copied to the database using Oracle SQL Loader, some of them already existed in Oracle database)
  2. Data integration - Three main Oracle tables (Buildings, Dwellings, Population) and auxiliary Population Household table were set up. Besides that, metadata tables for every basic table were formed. The most comprehensive process here is the intersection of population, household and dwelling data and transfer of data between tables. All data in individual data file had to be verified in advance and must be formally correct using the census classifications and codebooks. The first and the most demanding part of the data integration were establishing links between Oracle tables and connectivity for further processing. Due to missing information on household and/or dwelling numbers we needed to develop a series of algorithms, which have been included in the integration process in order to come to a solution for density of population or households and dwellings. Population stock has been determined in advance according to the regular statistical procedures on quarterly population statistics – independent statistical process already existed in the Statistical Office to produce data on persons as an input file to the census from Central Population Register. As a consequence there was no more record deletion or record imputation for population in later stages.
  3. Data corrections phase –for data on household structure (relation to the reference person) almost manual coding applied in case of missing data on PIN's of parents and spouses (mostly for foreigners) while all other corrections were automated using generic metadata driven application already existed in the Statistical Office. The interface for manual corrections which also includes the surnames allows correction of very few strictly approved variables.
  4. Missing data imputations –the logical imputations based on the rules derived from other already known values of connected topics were mostly used. As only for small parts of the target population data after logical imputations were not available the decision was made for almost complete data imputation using donor-based imputation methods (the only exceptions were data on occupation and industry for persons employed abroad).

Families within each household were generated automatically by using matrixes of relations between household members and using PIN's of parents/spouses. In majority of multi-persons households (93%) there is only 1 family.

Data on population and housing censuses are disseminated every decade

31 March 2014

Statistics are completely comparable between geographical areas.