This dataset provides Census 2021 estimates for the number of households in Northern Ireland. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

To find out how Data Zones and Super Data Zones have been developed, and how other Northern Ireland geographies can be approximated, please read the notes here

The quality assurance report can be found here

This report presents findings from the carers’ module of the Continuous Household Survey (CHS), carried out over the year 1st April 2008 – 31st March 2009. The CHS provides a regular source of information on a wide range of social and economic issues within Northern Ireland, and has been running since 1983. The home care module was included in the CHS with a view to collecting information on the current ability of respondents to perform a number of selected activities and to ascertain if they had any help with these activities from a relative, friend or neighbour. The opportunity was also used to find out if those requiring help had considered a home care package and to gather the views of any current home care service users about the service they receive. Source agency: Health, Social Service and Public Safety (Northern Ireland) Designation: National Statistics Language: English Alternative title: CHS 2008/09 - Domiciliary Care Module

This dataset provides Census 2021 estimates for the number of usual residents in Northern Ireland. The dataset also shows the population density, as well as the size of the geographical area. The estimates and area boundaries are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

To find out how Data Zones and Super Data Zones have been developed, and how other Northern Ireland geographies can be approximated, please read the notes here

The quality assurance report can be found here

The trend-based projections include a range of variants based on different assumptions about future levels of migration. The projections are produced for all local authorities in England & Wales and nationally for Scotland and Northern Ireland. The datasets include summary workbooks for London boroughs and detailed component of change outputs for all model areas.

The most recent set of trend-based population projections currently available are the 2020-based variant projections (September 2021).

The 2020-based projections comprise 4 principal variants which have been produced using different assumptions about future levels of domestic and international migration. Variant projections have been produced in order to assist users in understanding current uncertainty about future population growth. A full explanation of the differences between these projections is available in the supporting documentation.

Additionally, the trend-based projections also project the future number of households at local authority level by converting the projected population into households. Different sets of trend-based Household projections have been created using both the 2014-based DCLG household projection model and the 2018-based ONS household model so that users can compare the results of using these two different methodologies.

• Documentation page
• Back to projections homepage

National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991. The Understanding Society: Calendar Year Dataset, 2022, is designed for analysts to conduct cross-sectional analysis for the 2022 calendar year. The Calendar Year datasets combine data collected in a specific year from across multiple waves and these are released as separate calendar year studies, with appropriate analysis weights, starting with the 2020 Calendar Year dataset. Each subsequent year, an additional yearly study is released. The Calendar Year data is designed to enable timely cross-sectional analysis of individuals and households in a calendar year. Such analysis can, however, only involve variables that are collected in every wave (excluding rotating content, which is only collected in some of the waves). Due to overlapping fieldwork, the data files combine data collected in the three waves that make up a calendar year. Analysis cannot be restricted to data collected in one wave during a calendar year, as this subset will not be representative of the population. Further details and guidance on this study can be found in the document 9333_main_survey_calendar_year_user_guide_2022. These calendar year datasets should be used for cross-sectional analysis only. For those interested in longitudinal analyses using Understanding Society please access the main survey datasets: End User Licence version or Special Licence version. Understanding Society: the UK Household Longitudinal Study, started in 2009 with a general population sample (GPS) of UK residents living in private households of around 26,000 households and an ethnic minority boost sample (EMBS) of 4,000 households. All members of these responding households and their descendants became part of the core sample who were eligible to be interviewed every year. Anyone who joined these households after this initial wave was also interviewed as long as they lived with these core sample members to provide the household context. At each annual interview, some basic demographic information was collected about every household member, information about the household is collected from one household member, all 16+-year-old household members are eligible for adult interviews, 10-15-year-old household members are eligible for youth interviews, and some information is collected about 0-9 year-olds from their parents or guardians. Since 1991 until 2008/9 a similar survey, the British Household Panel Survey (BHPS), was fielded. The surviving members of this survey sample were incorporated into Understanding Society in 2010. In 2015, an immigrant and ethnic minority boost sample (IEMBS) of around 2,500 households was added. In 2022, a GPS boost sample (GPS2) of around 5,700 households was added. To know more about the sample design, following rules, interview modes, incentives, consent, and questionnaire content, please see the study overview and user guide. Co-funders In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency. End User Licence and Special Licence versions: There are two versions of the Calendar Year 2022 data. One is available under the standard End User Licence (EUL) agreement (SN 9333), and the other is a Special Licence (SL) version (SN 9334). The SL version contains month and year of birth variables instead of just age, more detailed country and occupation coding for a number of variables and various income variables have not been top-coded (see document 9333_eul_vs_sl_variable_differences for more details). Users are advised first to obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. The main longitudinal versions of the Understanding Society study may be found under SNs 6614 (EUL) and 6931 (SL).

Dataset population: Dwellings

Dwellings

A household's accommodation (a household space) is defined as being in a shared dwelling if it has accommodation type 'part of a converted or shared house', not all the rooms (including bathroom and toilet, if any) are behind a door that only that household can use and there is at least one other such household space at the same address with which it can be combined to form the shared dwelling.

If any of these conditions are not met, the household space forms an unshared dwelling. Therefore a dwelling can consist of one household space (an unshared dwelling) or two or more household spaces (a shared dwelling).

The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP. The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage. The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage. Secure Access FRS data In addition to the standard End User Licence (EUL) version, Secure Access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 9256. Prospective users of the Secure Access version of the FRS will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.FRS, HBAI and PIThe FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503, respectively. The Secure Access versions are held under SN 7196 and 9257 (see above). The FRS aims to: support the monitoring of the social security programmesupport the costing and modelling of changes to National Insurance contributions and social security benefitsprovide better information for the forecasting of benefit expenditure From April 2002, the FRS was extended to include Northern Ireland. Latest edition:For the second edition (October 2014) the data have been re-grossed following revision of the FRS grossing methodology to take account of the 2011 Census mid-year population estimates. New variable GROSS4 has been added to the dataset. In August 2019, at the depositor's request, the Pensioners' Income (PI) dataset (pianon) previously held with the FRS was moved to a separate PI series study, SN 8503. Household characteristics (composition, tenure type); tenure and housing costs including Council Tax, mortgages, insurance, water and sewage rates; school milk and meals; educational grants and loans; children in education; informal care (given and received); childcare; occupation and employment; health restrictions on work; children's health; wage details; self-employed earnings; personal and occupational pension schemes; income and benefit receipt; income from pensions and trusts, royalties and allowances, maintenance and other sources; income tax payments and refunds; National Insurance contributions; earnings from odd jobs; children's earnings; interest and dividends; investments; National Savings products; assets; prescriptions. Standard Measures Standard Occupational Classification

This dataset provides Census 2021 estimates for the number of usual residents in Northern Ireland. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

To find out how Data Zones and Super Data Zones have been developed, and how other Northern Ireland geographies can be approximated, please read the notes here

The quality assurance report can be found here

Projected indicators included are derived from the published 2018-based household projections for England and 2018-based household projections for Scotland for the years 2018 up to 2043. The indicators are the percentage of one-person households, in which the householder is aged 65 years and over and the percentage of one-person households, in which the householder is aged 85 years and over. This dataset has been produced by the Ageing Analysis Team for inclusion in the subnational ageing tool, which was published on July 20, 2020 (see link in Related datasets). The tool is interactive, and users can compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. Note on data availability: England, Wales, Scotland and Northern Ireland independently publish subnational household projections. Each country publishes a different set of age breakdowns and only England and Scotland provide the breakdowns required to calculate the indicators included above.

Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: Calendar Year Dataset, 2022, is designed for analysts to conduct cross-sectional analysis for the 2022 calendar year. The Calendar Year datasets combine data collected in a specific year from across multiple waves and these are released as separate calendar year studies, with appropriate analysis weights, starting with the 2020 Calendar Year dataset. Each subsequent year, an additional yearly study is released.

The Calendar Year data is designed to enable timely cross-sectional analysis of individuals and households in a calendar year. Such analysis can, however, only involve variables that are collected in every wave (excluding rotating content, which is only collected in some of the waves). Due to overlapping fieldwork, the data files combine data collected in the three waves that make up a calendar year. Analysis cannot be restricted to data collected in one wave during a calendar year, as this subset will not be representative of the population. Further details and guidance on this study can be found in the document 9333_main_survey_calendar_year_user_guide_2022.

These calendar year datasets should be used for cross-sectional analysis only. For those interested in longitudinal analyses using Understanding Society please access the main survey datasets: End User Licence version or Special Licence version.

Understanding Society: the UK Household Longitudinal Study, started in 2009 with a general population sample (GPS) of UK residents living in private households of around 26,000 households and an ethnic minority boost sample (EMBS) of 4,000 households. All members of these responding households and their descendants became part of the core sample who were eligible to be interviewed every year. Anyone who joined these households after this initial wave was also interviewed as long as they lived with these core sample members to provide the household context. At each annual interview, some basic demographic information was collected about every household member, information about the household is collected from one household member, all 16+-year-old household members are eligible for adult interviews, 10-15-year-old household members are eligible for youth interviews, and some information is collected about 0-9 year-olds from their parents or guardians. Since 1991 until 2008/9 a similar survey, the British Household Panel Survey (BHPS), was fielded. The surviving members of this survey sample were incorporated into Understanding Society in 2010. In 2015, an immigrant and ethnic minority boost sample (IEMBS) of around 2,500 households was added. In 2022, a GPS boost sample (GPS2) of around 5,700 households was added. To know more about the sample design, following rules, interview modes, incentives, consent, and questionnaire content, please see the study overview and user guide.

Co-funders

In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency.

End User Licence and Special Licence versions:

There are two versions of the Calendar Year 2022 data. One is available under the standard End User Licence (EUL) agreement (SN 9333), and the other is a Special Licence (SL) version (SN 9334). The SL version contains month and year of birth variables instead of just age, more detailed country and occupation coding for a number of variables and various income variables have not been top-coded (see document 9333_eul_vs_sl_variable_differences for more details). Users are advised first to obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. The main longitudinal versions of the Understanding Society study may be found under SNs 6614 (EUL) and 6931 (SL).

Low- and Medium-level geographical identifiers produced for the mainstage longitudinal dataset can be used with this Calendar Year 2022 dataset, subject to SL access conditions. See the User Guide for further details.

Suitable data analysis software

These data are provided by the depositor in Stata format. Users are strongly advised to analyse them in Stata. Transfer to other formats may result in unforeseen issues. Stata SE or MP software is needed to analyse the larger files, which contain about 1,800 variables.

Context Well, what happened was that I was looking for a semi-definite easy-to-read list of international football matches and couldn't find anything decent. So I took it upon myself to collect it for my own use. I might as well share it.

Content This dataset includes 41,586 results of international football matches starting from the very first official match in 1972 up to 2019. The matches range from FIFA World Cup to FIFI Wild Cup to regular friendly matches. The matches are strictly men's full internationals and the data does not include Olympic Games or matches where at least one of the teams was the nation's B-team, U-23 or a league select team.

results.csv includes the following columns:

date - date of the match home_team - the name of the home team away_team - the name of the away team home_score - full-time home team score including extra time, not including penalty-shootouts away_score - full-time away team score including extra time, not including penalty-shootouts tournament - the name of the tournament city - the name of the city/town/administrative unit where the match was played country - the name of the country where the match was played neutral - TRUE/FALSE column indicating whether the match was played at a neutral venue Note on team and country names: For home and away teams the current name of the team has been used. For example, when in 1882 a team who called themselves Ireland played against England, in this dataset, it is called Northern Ireland because the current team of Northern Ireland is the successor of the 1882 Ireland team. This is done so it is easier to track the history and statistics of teams.

For country names, the name of the country at the time of the match is used. So when Ghana played in Accra, Gold Coast in the 1950s, even though the names of the home team and the country don't match, it was a home match for Ghana. This is indicated by the neutral column, which says FALSE for those matches, meaning it was not at a neutral venue.

Acknowledgements The data is gathered from several sources including but not limited to Wikipedia, fifa.com, rsssf.com and individual football associations' websites.

Inspiration Some directions to take when exploring the data:

Who is the best team of all time Which teams dominated different eras of football What trends have there been in international football throughout the ages - home advantage, total goals scored, distribution of teams' strength etc Can we say anything about geopolitics from football fixtures - how has the number of countries changed, which teams like to play each other Which countries host the most matches where they themselves are not participating in How much, if at all, does hosting a major tournament help a country's chances in the tournament Which teams are the most active in playing friendlies and friendly tournaments - does it help or hurt them The world's your oyster, my friend.

Contribute If you notice a mistake or the results are being updated fast enough for your liking, you can fix that by submitting a pull request.

Projected indicators included are derived from the published 2018-based subnational population projections for England, Wales, Scotland and Northern Ireland up to the year 2043. The indicators are the projected percentage of the population aged 65 years and over, 85 years and over, 0 to 15 years, 16 to 64 years, 16 years to State Pension age, State Pension age and over, median age and the Old Age Dependency Ratio (the number of people of State Pension age per 1000 of those aged 16 years to below State Pension age).

This dataset has been produced by the Ageing Analysis Team for inclusion in the subnational ageing tool, which was published on July 20, 2020 (see link in Related datasets). The tool is interactive, and users can compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu.

Note on data sources: England, Wales, Scotland and Northern Ireland independently publish subnational population projections and the data available here are a compilation of these datasets. The ONS publish national level data for the UK, England, Wales and England & Wales, which has been included. National level data for Scotland and Northern Ireland have been taken from their subnational population projections datasets.

Techsalerator’s Business Technographic Data for the United Kingdom: Unlocking Insights into the UK’s Technology Landscape

Techsalerator’s Business Technographic Data for the United Kingdom provides a detailed and comprehensive dataset essential for businesses, market analysts, and technology vendors looking to understand and engage with companies operating in the UK. This dataset offers in-depth insights into the country's technological ecosystem, capturing data related to technology stacks, digital tools, and IT infrastructure used by UK businesses.

Please reach out to us at info@techsalerator.com or visit Techsalerator Contact.

Top 5 Most Utilized Data Fields

• Company Name: This field lists the names of companies in the UK, enabling technology vendors to target potential clients and allowing analysts to assess technology adoption trends within specific businesses.

• Technology Stack: This field provides details on the technologies and software solutions utilized by a company, such as ERP systems, CRM platforms, and cloud services. Understanding the technology stack is crucial to evaluating a company’s digital capabilities and identifying opportunities for IT upgrades or sales.

• Deployment Status: This field indicates whether the technology is currently deployed, in the pipeline for future implementation, or under evaluation. Vendors can use this information to gauge the level of tech adoption among UK businesses.

• Industry Sector: This field specifies the industry in which the company operates, such as finance, healthcare, retail, or manufacturing. Sector-based insights allow vendors to tailor solutions to the unique challenges and trends in each market.

• Geographic Location: This field identifies the company’s headquarters or key operational areas within the UK. Geographic data aids in regional market analysis and helps vendors understand localized tech adoption patterns across England, Scotland, Wales, and Northern Ireland.

Top 5 Technology Trends in the United Kingdom

• Financial Technology (FinTech): The UK is a global leader in FinTech innovation, with companies leveraging technologies like blockchain, digital banking platforms, and AI-driven financial services to enhance customer experiences and optimize back-office processes.

• Artificial Intelligence and Machine Learning: AI and machine learning technologies are being integrated across industries, from healthcare diagnostics and legal tech to e-commerce personalization and logistics automation, driving operational efficiency and innovation.

• Cloud Computing and IT Infrastructure: Cloud adoption is soaring in the UK, with businesses shifting to cloud-based solutions for scalability, flexibility, and cost-efficiency. Sectors like finance, retail, and education are increasingly relying on cloud infrastructure for digital transformation.

• Cybersecurity: As digital ecosystems expand, the demand for cybersecurity solutions is growing. UK companies are investing heavily in data protection, encryption, and threat detection technologies to safeguard against the rising risks of cyberattacks and data breaches.

• Sustainability Tech: There is a growing focus on green technologies, particularly renewable energy solutions and carbon reduction initiatives. UK businesses, especially in manufacturing and energy sectors, are adopting tech-driven sustainability strategies to meet regulatory demands and reduce their carbon footprints.

Top 5 Companies with Notable Technographic Data in the United Kingdom

• HSBC: As one of the largest banking institutions globally, HSBC is leveraging cutting-edge financial technologies, AI, and cybersecurity solutions to drive its digital banking services and ensure secure, streamlined customer interactions.

• BT Group: The UK's leading telecom provider, BT is at the forefront of expanding the country’s digital infrastructure, rolling out 5G networks and increasing the availability of high-speed broadband services to support businesses and consumers.

• Tesco: A major player in the retail sector, Tesco has embraced e-commerce, mobile apps, and AI-driven customer insights to optimize its supply chain, improve customer experiences, and enhance operational efficiency across its vast network.

• BP: An energy giant, BP is heavily investing in renewable energy technologies and digital solutions to meet sustainability goals. The company is also utilizing AI, IoT, and big data analytics to optimize operations and reduce carbon emissions.

• Unilever: A global leader in consumer goods, Unilever is leveraging cloud computing, data analytics, and AI to drive innovation in product development, improve supply chain efficiencies, and better understand customer behavior.

Accessing Techsalerator’s Business Technographic Data

For those interested in acce...

Both indicators included have been derived from the published 2019 mid-year population estimates for the UK, England, Wales, Scotland and Northern Ireland. These are sex ratios for people aged 65 years and over and 85 years and over. A sex ratio shows the number of males in the population for every 100 females.

This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which was published in July 2020. The tool enables users to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu.

Dataset population: Households

Classification of household deprivation

The dimensions of deprivation used to classify households are indicators based on four selected household characteristics. A household is deprived in a dimension if they meet one or more of the following conditions:

• Employment: Where any member of a household, who is not a full-time student, is either unemployed or long-term sick.
• Education: No person in the household has at least Level 2 education (see highest level of qualification), and no person aged 16 to 18 is a full-time student.
• Health and disability: Any person in the household has general health that is 'bad' or 'very bad' or has a long-term health problem.
• Housing: The household's accommodation is either overcrowded, with an occupancy rating -1 or less, or is in a shared dwelling, or has no central heating.

A household is classified as being deprived in none, or one to four of these dimensions in any combination.

This file contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom as at August 2022 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. To download the zip file click the Download button. The NSPL relates both current and terminated postcodes to a range of current statutory geographies via ‘best-fit’ allocation from the 2021 Census Output Areas (national parks and Workplace Zones are exempt from ‘best-fit’ and use ‘exact-fit’ allocations) for England and Wales. Scotland and Northern Ireland has the 2011 Census Output AreasIt supports the production of area based statistics from postcoded data. The NSPL is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The NSPL is issued quarterly. (File size - 184 MB).

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: Calendar Year Dataset, 2022: Special Licence Access, is designed for analysts to conduct cross-sectional analysis for the 2022 calendar year. The Calendar Year datasets combine data collected in a specific year from across multiple waves and these are released as separate calendar year studies, with appropriate analysis weights, starting with the 2020 Calendar Year dataset. Each subsequent year, an additional yearly study is released.

The Calendar Year data is designed to enable timely cross-sectional analysis of individuals and households in a calendar year. Such analysis can however, only involve variables that are collected in every wave (excluding rotating content which is only collected in some of the waves). Due to overlapping fieldwork the data files combine data collected in the three waves that make up a calendar year. Analysis cannot be restricted to data collected in one wave during a calendar year, as this subset will not be representative of the population. Further details and guidance on this study can be found in the document 9334_main_survey_calendar_year_user_guide_2022.

These calendar year datasets should be used for cross-sectional analysis only. For those interested in longitudinal analyses using Understanding Society please access the main survey datasets: End User Licence version or Special Licence version.

Understanding Society: the UK Household Longitudinal Study, started in 2009 with a general population sample (GPS) of UK residents living in private households of around 26,000 households and an ethnic minority boost sample (EMBS) of 4,000 households. All members of these responding households and their descendants became part of the core sample who were eligible to be interviewed every year. Anyone who joined these households after this initial wave, were also interviewed as long as they lived with these core sample members to provide the household context. At each annual interview, some basic demographic information was collected about every household member, information about the household is collected from one household member, all 16+ year old household members are eligible for adult interviews, 10-15 year old household members are eligible for youth interviews, and some information is collected about 0-9 year olds from their parents or guardians. Since 1991 until 2008/9 a similar survey, the British Household Panel Survey (BHPS), was fielded. The surviving members of this survey sample were incorporated into Understanding Society in 2010. In 2015, an immigrant and ethnic minority boost sample (IEMBS) of around 2,500 households was added. In 2022 a GPS boost sample (GPS2) of around 5,700 households was added. To know more about the sample design, following rules, interview modes, incentives, consent, questionnaire content please see the study overview and user guide.

Co-funders

In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency.

End User Licence and Special Licence versions:

There are two versions of the Calendar Year 2022 data. One is available under the standard End User Licence (EUL) agreement (SN 9333), and the other is a Special Licence (SL) version (SN 9334). The SL version contains month and year of birth variables instead of just age, more detailed country and occupation coding for a number of variables and various income variables have not been top-coded (see 9334_eul_vs_sl_variable_differences for more details). Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. The main longitudinal versions of the Understanding Society study may be found under SNs 6614 (EUL) and 6931 (SL).

Low- and Medium-level geographical identifiers produced for the mainstage longitudinal dataset can be used with this Calendar Year 2022 dataset, subject to SL access conditions. See the User Guide for further details.

Suitable data analysis software

These data are provided by the depositor in Stata format. Users are strongly advised to analyse them in Stata. Transfer to other formats may result in unforeseen issues. Stata SE or MP software is needed to analyse the larger files, which contain about 1,800 variables.