UK residents by broad country of birth and citizenship groups, broken down by UK country, local authority, unitary authority, metropolitan and London boroughs, and counties. Estimates from the Annual Population Survey.

The database includes a list of 1577 weed plant taxa found in cultivated fields of France and UK, along with basic ecological and biogeographical information. The database is a CSV file in which the columns are separated with comma, and the decimal sign is ".". It can be imported in R with the command "tax.discoweed <- read.csv("tax.discoweed_18Dec2017_zenodo.csv", header=T, sep=",", dec=".", stringsAsFactors = F)"

Taxonomic information is based on TaxRef v10 (Gargominy et al. 2016), - 'taxref10.CD_REF' = code of the accepted name of the taxon in TaxRef, - 'binome.discoweed' = corresponding latine name, - 'family' = family name (following APG III), - 'taxo' = taxonomic rank of the taxon, either 'binome' (species level) or 'infra' (infraspecific level), - 'binome.discoweed.noinfra' = latine name of the superior taxon at species level (different from 'binome.discoweed' for infrataxa), - 'taxref10.CD_REF.noinfra' = code of the accepted name of the superior taxon at species level.

The presence of each taxon in one or several of the following data sources is reported: - Species list from a reference flora (observations in cultivated fields over the long term, without sampling protocol), * 'jauzein' = national and comprehensive flora in France (Jauzein 1995), - Species lists from plot-based inventories in cultivated fields, * 'za' = regional survey in 'Zone Atelier Plaine & Val de Sèvre' in SW France (Gaba et al. 2010), * 'biovigilance' = national survey of cultivated fields in France (Biovigilance, Fried et al. 2008), * 'fse' = Farm Scale Evaluations in England and Scotland, UK (Perry, Rothery, Clark et al., 2003), * 'farmbio' = Farm4Bio survey, farms in south east and south west of England, UK (Holland et al., 2013) - Reference list of segetal species (species specialist of arable fields), * 'cambacedes' = reference list in France (Cambacedes et al. 2002)

Life form information is extracted from Julve (2014) and provided in the column 'lifeform'. The classification follows a simplified Raunkiaer classification (therophyte, hemicryptophyte, geophyte, phanerophyte-chamaephyte and liana). Regularly biannual plants are included in hemicryptophytes, while plants that can be both annual and biannual are assigned to therophytes.

Biogeographic zones are also extracted from Julve (2014) and provided in the column 'biogeo'. The main categories are 'atlantic', 'circumboreal', 'cosmopolitan, 'Eurasian', 'European', 'holarctic', 'introduced', 'Mediterranean', 'orophyte' and 'subtropical'. In some cases, a precision is included within brackets after the category name. For instance, 'introduced(North America)' indicates that the taxon is introduced from North America. In addition, some taxa are local endemics ('Aquitanian', 'Catalan', 'Corsican', 'corso-sard', 'ligure', 'Provencal'). A single taxon is classified 'arctic-alpine'.

Red list status of weed taxa is derived for France and UK: - 'red.FR' is the status following the assessment of the French National Museum of Natural History (2012), - 'red.UK' is based on the Red List of vascular plants of Cheffings and Farrell (2005), last updated in 2006. The categories are coded following the IUCN nomenclature.

A habitat index is provided in column 'module', derived from a network-based analysis of plant communities in open herbaceous vegetation in France (Divgrass database, Violle et al. 2015, Carboni et al. 2016). The main habitat categories of weeds are coded following the Divgrass classification, - 1 = Dry calcareous grasslands - 3 = Mesic grasslands - 5 = Ruderal and trampled grasslands - 9 = Mesophilous and nitrophilous fringes (hedgerows, forest edges...) Taxa belonging to other habitats in Divgrass are coded 99, while the taxa absent from Divgrass have a 'NA' value.

Two indexes of ecological specialization are provided based on the frequency of weed taxa in different habitats of the Divgrass database. The indexes are network-based metrics proposed by Guimera and Amaral (2005), - c = coefficient of participation, i.e., the propensity of taxa to be present in diverse habitats, from 0 (specialist, present in a single habitat) to 1 (generalist equally represented in all habitats), - z = within-module degree, i.e., a standardized measure of the frequency of a taxon in its habitat; it is negatve when the taxon is less frequent than average in this habitat, and positive otherwise; the index scales as a number of standard deviations from the mean.

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

Abstract copyright UK Data Service and data collection copyright owner.

The European State Finance Database (ESFD) is an international collaborative research project for the collection of data in European fiscal history. There are no strict geographical or chronological boundaries to the collection, although data for this collection comprise the period between c.1200 to c.1815. The purpose of the ESFD was to establish a significant database of European financial and fiscal records. The data are drawn from the main extant sources of a number of European countries, as the evidence and the state of scholarship permit. The aim was to collect the data made available by scholars, whether drawing upon their published or unpublished archival research, or from other published material.
The ESFD project at the University of Leicester serves also to assist scholars working with the data by providing statistical manipulations of data and high quality graphical outputs for publication. The broad aim of the project was to act as a facilitator for a general methodological and statistical advance in the area of European fiscal history, with data capture and the interpretation of data in key publications as the measurable indicators of that advance. The data were originally deposited at the UK Data Archive in SAS transport format and as ASCII files; however, data files in this new edition have been saved as tab delimited files. Furthermore, this new edition features documentation in the form of a single file containing essential data file metadata, source details and notes of interest for particular files.

Main Topics:

The files in this dataset relate to the files held in the Leicester database in the directory /rjb/*.*.
File Information
g138cod1.* Direct taxation in the pays d'elections, 1594-1647
g138cod2.* Direct taxation in the generalites of Chalons, Caen and Rouen, 1597-1643
g138eld1.* Levy of the taille in the election of Paris, 1615-1787
g138elm1.* Value in millions of hectolitres of wheat of levy of taille in the election of Paris, 1615-1787
g138elm2.* The levy of taille in the election of Paris and in the generalites of Chalons, Caen and Rouen, 1597-1643
g138fd01.* Direct taxation from the pays d'elections and the pays d'impositions, 1789
g138fd02.* Total French expenditure, 1801-1844
g138fd03.* Total French expenditure, 1815-1849
g138fd04.* French revenues, 1815-1849
g138fd05.* French government expenditure, 1815-1850
g138fd06.* French government revenues from taxation, 1815-1850
g138fd07.* The value of the taille in France, 1461-1609
g138fd08.* Life rents and tontines, 1733-1788
g138fd09.* Estimates of direct taxes and surtaxes collected in France, 1792-1829
g138fd10.* Retrospective budgets of the Ancien Regime; Etats au vrai of the Ancien Regime
g138fd11.* Central government revenues and expenditures, 1727-1768
g138fm01.* The value of the taille in France, 1461-1609, in millions of hectolitres of wheat, harvest and calendar years
g138fm02.* Revenue from direct taxation, total taxation and total revenue in France, 1815-29
g138ged1.* Repartition of the taille between elections of the generalite of Paris, 1688-1712

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

Contained within the 2nd Edition (1915) of the Atlas of Canada is a plate map that shows 2 maps. The first map shows the origin of the population in Manitoba and Saskatchewan, circa 1911. The second map shows the origin of the population in British Columbia and Alberta, circa 1911A varying number of ethnic groups are shown, but always included are: English, Scotch [Scottish], Irish, French and German. People of British origin predominate in all provinces, except Quebec, where the French predominate. There is a cosmopolitan population due to immigration from Great Britain and Europe, but British are the predominating people in British Columbia and Alberta. Major railway systems are displayed, which extend into the U.S. The map presents the rectangular survey system, which records the land that is available to the public. This grid like system is divided into sections, townships, range, and meridian from mid-Manitoba to Alberta.

Abstract copyright UK Data Service and data collection copyright owner. To collect socio-economic data in order to investigate theories concerning the causes of coups. Main Topics: Variables Country, % population living in rural areas/working in agriculture 1970, % growth rate of GNP per capita (U.S. dollars) 1970, number of people for each physician 1970, % population illiterate 1970, number of radio sets/newspaper circulation per 1000 inhabitants 1970, density of population 1970, GNP per capita (U.S. dollars), % military personnel per 1000 population 1970, whether has own army, annual defence budget as % of GNP per capita 1970, extent of bilateral aid per capita (U.S. dollars), whether had coup d'etat 1950-1970, whether has been a colony for any period 1950-1970, whether has had coup previously, largest % population having same religion, whether had coup between 1960-1970, % population living in urban areas 1965, newspaper circulation per 1000 population 1965, number of people per physician 1965, % population having received education 1965, number of radio sets per 1000 population 1965, SNP per capita 1965 (U.S. dollars), whether had coup 1950-Jan 1971/1950-1966/1961-1966, number of riots since 1948-1967, number of major 'irregular power transfers' 1950-1968 (Taylor and Hudson), whether has military agreements with France 1950-1970, whether has had internal physical conflict on grounds of ethnic or language differences, whether receives aid, whether defends itself, whether became independent since 1 Jan 1966, number of major 'irregular power transfers' where a coup has taken place, major commodity exported as % of value of all exports 1968, whether product has one year gestation period, amount of external trade in relation to rest of world 1968 (U.S. dollars), major % exports to one country 1968, whether has trade with communist countries, whether ex-British/ex-French colony, whether has had monarch/emperor/sultan (not constitutional), whether has fought external war/civil war 1950-1970, whether has military agreements with U.S./U.K./U.S.S.R./ France, four major commodities exported as % of all exports, whether imports and exports major % of commodities from U.S.S.R./France/U.K./U.S.A. 1968.

This table contains 25 series, with data for years 1955 - 2013 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Last permanent residence (25 items: Total immigrants; France; Great Britain; Total Europe ...).

BackgroundTinnitus is a common problem in patients with a cochlear implant (CI). Between 4% and 25% of CI recipients experience a moderate to severe tinnitus handicap. However, apart from handicap scores, little is known about the real-life impact tinnitus has on those with CIs. We aimed to explore the impact of tinnitus on adult CI recipients, situations impacting tinnitus, tinnitus-related difficulties and their management strategies, using an exploratory sequential mixed-method approach.MethodsA 2-week web-based forum was conducted using Cochlear Ltd.’s online platform, Cochlear Conversation. A thematic analysis was conducted on the data from the forum discussion to develop key themes and sub-themes. To quantify themes and sub-themes identified, a survey was developed in English with face validity using cognitive interviews, then translated into French, German and Dutch and disseminated on the Cochlear Conversation platform, in six countries (Australia, France, Germany, New Zealand, the Netherlands and United Kingdom). Participants were adult CI recipients experiencing tinnitus who received a Cochlear Ltd. CI after 18 years of age.ResultsFour key themes were identified using thematic analysis of the discussion forum: tinnitus experience, situations impacting tinnitus, difficulties associated with tinnitus and tinnitus management. Among the 414 participants of the survey, tinnitus burden on average was a moderate problem without their sound processor and not a problem with the sound processor on. Fatigue, stress, concentration, group conversation and hearing difficulties were the most frequently reported difficulties and was reported to intensify when not wearing the sound processor. For most CI recipients, tinnitus seemed to increase when performing a hearing test, during a CI programming session, or when tired, stressed, or sick. To manage their tinnitus, participants reported turning on their sound processor and avoiding noisy environments.ConclusionThe qualitative analysis showed that tinnitus can affect everyday life of CI recipients in various ways and highlighted the heterogeneity in their tinnitus experiences. The survey findings extended this to show that tinnitus impact, related difficulties, and management strategies often depend on sound processor use. This exploratory sequential mixed-method study provided a better understanding of the potential benefits of sound processor use, and thus of intracochlear electrical stimulation, on the impact of tinnitus.

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 7th version of the 2008 Cross-Sectional User Database (UDB) as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Abstract

In 2009, the EU-SILC instrument covered all EU Member States plus Iceland, Turkey, Norway and Switzerland. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 7th version of the 2009 Cross-Sectional User Database (UDB) as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Abstract

In 2012, the EU-SILC instrument covered all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

This is the 3rd version of the 2012 Cross-Sectional User Database as released in July 2015.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United Kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed