Exports in the United Kingdom increased to 75997 GBP Million in March from 75570 GBP Million in February of 2025. This dataset provides - United Kingdom Exports - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Quarterly summary of balance of payments accounts including the current account, capital transfers, transactions and levels of UK external assets and liabilities.

Experimental dataset providing a breakdown of UK trade in services by industry, country and service type on a balance of payments basis. Data are subject to disclosure control.

For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.

Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022

APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.

APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Every single day, all over the world, human beings perform music in front of other human beings. This happens in public and private areas, large and small, in what is probably the most widespread communal cultural activity that we engage in, and yet almost none of it is recorded. There is some information available about famous performances by major artists which occasionally includes setlists, but even this is patchy and reliant on enthusiastic fans, and the fact that it is concentrated on such a tiny subset of performances ignores the vast majority of what actually goes on. This dataset provides a tiny snapshot of some of this other activity. It contains details of the one thousand gigs I performed between 3 February 1988 and 2 February 2023, derived mostly from the database used to run my website, www.mjhibbett.co.uk, with the addition of some private data held about merchandising sales at gigs. My hope is that providing this data for analysis will encourage others to do the same, and thus start to provide a more balanced view of live music performance.

The UK Innovation Survey (UKIS) provides the main source of information on business innovation in the UK. The survey data is a major resource for research into the nature and functioning of the innovation system and for policy formation. It is used widely across government, regions and by the research community. The UKIS also represents the UK's contribution to the Europe-wide Community Innovation Survey (CIS). Like many innovation surveys across Europe, the UKIS follows general guidelines set out in the Organisation for Economic Co-operation and Development (OECD) publication known as the Oslo Manual (OECD 2005). This manual provides guidelines on the conduct of innovation surveys, including statistical procedures and a review of the range of concepts that fall together under the umbrella term "innovation".

Geographical references: postcodes
The postcodes included in the first edition of these data (i.e. data files prior to 2008-2010) are pseudo-anonymised postcodes. The real postcodes were not available due to the potential risk of identification of the observations. However, these replacement postcodes retain the inherent nested characteristics of real postcodes. In the dataset, the variable of the replacement postcode is 'new_PC'.

The first two editions only include the first half of an observation's anonymised (or real) postcode (sometimes referred to as the outward code). Researchers who are interested in analysing data by more disaggregated geographies (e.g. ward, output area) are advised that this is not possible using the first half of the postcode. Full, real postcodes are available from the third edition onwards, with the exception of .UKIS12, for which only the first half of the postcodes (outward codes) are available.

For Secure Lab projects applying for access to this study as well as to SN 6697 Business Structure Database and/or SN 7683 Business Structure Database Longitudinal, only postcode-free versions of the data will be made available.

Linking to other business studies
These data contain Inter-Departmental Business Register (IDBR) reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

Latest edition information
For the ninth edition (September 2024) data and documentation for UKIS 2023 (also known as UKIS 13), covering the period 2020 to 2022, were added to the study.

The data comprises a GIS layers representing the permeability of Superficial geological deposits for Great Britain. The permeability data has been derived from DiGMap-GB (Digital Geological Map Data of Great Britain), and therefore reflects the scale of DiGMap-GB. For the majority of the Great Britain, the scale is 1:50,000, however in areas where the geology is not mapped to this scale, the next best available scale, 1:625:000, is used. The data is updated annually, or after a major new release of DiGMap-GB. The permeability data describes the fresh water flow through geological deposits and the ability of a lithostratigraphical unit to transmit water. Maximum and minimum permeability indices are given for each geological unit to indicate the range in permeability likely to be encountered and the predominant flow mechanism (fracture or intergranular). Neither of the assigned values takes into account the thickness of either the unsaturated or saturated part of the lithostratigraphical unit. The data can be used freely internally, but is licensed for commercial use. It is best displayed using a desktop GIS, and is available in vector format as ESRI shapefiles and MapInfo TAB files.

The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan.

The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565.

Survey and Biomeasures Data (GN 33004):
To date there have been ten attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137), the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669), and the tenth sweep was conducted in 2020-24 when the respondents were aged 60-64 (held under SN 9412).

A Secure Access version of the NCSD is available under SN 9413, containing detailed sensitive variables not available under Safeguarded access (currently only sweep 10 data). Variables include uncommon health conditions (including age at diagnosis), full employment codes and income/finance details, and specific life circumstances (e.g. pregnancy details, year/age of emigration from GB).

Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.

From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.

Linked Geographical Data (GN 33497):
A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies.

Linked Administrative Data (GN 33396):
A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.

Multi-omics Data and Risk Scores Data (GN 33592)
Proteomics analyses were run on the blood samples collected from NCDS participants in 2002-2004 and are available under SL SN 9254. Metabolomics analyses were conducted on respondents of sweep 10 and are available under SL SN 9411.

Additional Sub-Studies (GN 33562):
In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website.

The National Child Development Study: Linked Health Administrative Datasets (Hospital Episode Statistics), England, 1997-2023: Secure Access includes data files from the NHS Digital HES database for those cohort members who provided consent to health data linkage in the Age 50 sweep. The HES database contains information about all hospital admissions in England. The following linked HES data are available:

1) Accident and Emergency (A&E)
The A&E dataset details each attendance to an Accident and Emergency care facility in England, between 01-04-2007 and 31-03-2020 (inclusive). It includes major A&E departments, single speciality A&E departments, minor injury units and walk-in centres in England.

2) Admitted Patient Care (APC)
The APC data summarises episodes of care for admitted patients, where the episode occurred between 01-04-1997 and 31-03-2023 (inclusive).

3) Critical Care (CC)
The CC dataset covers records of critical care activity between 01-04-2009 and 31-03-2023 (inclusive).

4) Out Patient (OP)
The OP dataset lists the outpatient appointments between 01-04-2003 and 31-03-2023 (inclusive).

5) Emergency Care Dataset (ECDS)
The ECDS lists the emergency care appointments between 01-04-2020 and 31-03-2023 (inclusive).

6) Consent data
The consents dataset describes consent to linkage, and is current at the time of deposit.

CLS/ NHS Digital Sub-licence agreement
NHS Digital has given CLS permission for onward sharing of the NCDS/HES dataset via the UKDS Secure Lab. In order to ensure data minimisation, NHS Digital requires that researchers only access the HES variables needed for their approved research project. Therefore, the HES linked data provided by the UKDS to approved researchers will be subject to sub-setting of variables. The researcher will need to request a specific sub-set of variables from the NCDS/HES data dictionary, which will subsequently be made available within their UKDS Secure Account. Once the researcher has finished their research, the UKDS will delete the tailored dataset for that specific project. Any party wishing to access the data deposited at the UK Data Service will be required to enter into a Licence agreement with CLS (UCL), in addition to the agreements signed with the UKDS, provided in the application pack.

CLS Hospital Episode Statistics data access update July 2025

From March 2027, HES data linked to all four CLS studies will no longer be available via the UK Data Service. For projects ending before March 2027, uses should continue to apply via UKDS. However, if access to a wider range of linked Longitudinal Population Studies data is needed, UKLLC might be more suitable. For projects ending after March 2027, users must apply via UKLLC.

Latest edition information
For the third edition (April 2025), the data have been updated to include linked data for the financial years 2017-2022. In addition, a new dataset for Emergency Care (ECDS) episodes has been added, along with a dataset detailing the consent for linkage. Furthermore, the study documentation has also been updated.

Monthly export country-by-commodity data on the UK's trade in goods, including trade by all countries and selected commodities, non-seasonally adjusted.

Imports in the United Kingdom decreased to 79693 GBP Million in March from 80426 GBP Million in February of 2025. This dataset provides - United Kingdom Imports - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The period of the study was characterised by major improvements in financial institutions and transport. The objectives of the study were to see how pricing behaviour changed as a result of this. Since the prices are weekly and by county, it is possible to see how seasonality and regional patterns changed over time. Quantifying the effects of these changes should enable us to see their relative importance in promoting economic growth. The general aim of our research has been to increase our understanding of market integration and its effect on economic performance - particularly in the context of financial markets and commodity markets. Our specific objectives were (i) to create a major dataset of eighteenth and nineteenth century grain prices which can be used within our research project and which could also potentially be useful for other researchers; (ii) to estimate an econometric model to quantify the changes in financial markets, especially the spread of country banks (iii) to estimate an econometric model to measure the effects of transport networks; (iv) to use our results from to estimate the social welfare gains from market integration and to relate the improvements in market integration to the major changes in agricultural practice.

The dataset for "Media Context and the 2017 General Election: How Traditional and Social Media Shape Elections" consists of an analysis of media coverage of the 2017 British General Election. Media included are national newspapers, local newspapers, national and regional television news, and radio. The complete list of outlets is included in the codebooks. This study was conducted as part of the ESRC Media in Context and the 2017 General Election award, which extends the analysis of the 2015 election, data available under SN 8176.

In 2017 the electoral context had shifted from two years earlier, with a majority Conservative government, different leaders of almost all the major parties, Brexit as both the main issue (prior to the terrorist bomb in Manchester) and the ostensible reason the election was called, the possibility of the incumbent government gaining the largest proportion of the vote in a generation, and a growing distrust of polling data and the media e.g., ‘fake news’ and Twitter bots. This provided us with the opportunity to re-examine media coverage and extend our aims in four ways, by: 1) Looking at media coverage and its effects on different leaders and different issues than in 2015, e.g., Theresa May, Jeremy Corbyn, and Brexit; 2) Comparing the drivers of coverage of the election in traditional and social media, how they interact, and their effects in an era of “fake news” and “post-truth democracy” ; 3) Drawing links between key narratives in the 2015 post-election media coverage that led to the EU referendum and key narratives on Brexit in the 2017 campaign; 4) Identifying the aspects of media and media effects that vary between a competitive and an uncompetitive election at the national level and those that stay constant.

Data collection was for the following additional objectives: 1. To extend the longitudinal data set using the methods we established for the 2015 media content, capturing traditional and social media coverage of the 2017 election beginning on April 18th, 2017, the day Theresa May announced her intention to call an election and ending with the Queen’s speech on June 21st. 2. As in ES/M010775/1, to link traditional media content and social media analysis from 2017 to questions in the British Election Study, both allowing examination of media effects in 2017, and, for the same respondents, in 2015 for comparison.

The data set contain network survey statistics from the county of Nottinghamshire for four major UK mobile operators. The data are collected from September 2022 till December 2022 and contain both 4G-LTE and 5G-NSA network information and their corresponding GPS location.

Digital vector boundaries for Major Towns and Cities in England and Wales in 2015. The Major Towns and Cities (TCITY) statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data. 112 TCITY

More ONS 2011 Boundaries can be found here http://geoportal.statistics.gov.uk/

All these products are supplied under the Open Government Licence and Ordnance Survey Open Data terms and conditions.

Contains both Ordnance Survey and ONS Intellectual Property Rights.

Abstract copyright UK Data Service and data collection copyright owner.

The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online.

This study assembles historical data from the National Insurance system, plus some data from trade union welfare systems gathered and published by the Board of Trade Labour Department. The data were computerised by the Great Britain Historical GIS Project. They form part of the Great Britain Historical Database, which contains a wide range of geographically-located statistics, selected to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain, generally at sub-county scales.

Most of the data here was originally published by the Ministry of Labour, either in the Labour Gazette, later the Employment Gazette, or in the specialised Local Unemployment Index (LUI), published between 1927 and 1939. The largest dataset here is a complete transcription of the LUI data for each January, April, July and October from January 1927 to July 1939 inclusive, the most detailed information that exists on the geography of the inter-war depression, other than the 1931 census.

Unlike census data, these data concern a wide range of regions, "divisions", "districts", towns and sometimes areas within towns, seldom defined (the LUI data do list counties). The study therefore also includes two specially constructed gazetteers which attempt to provide towns and areas within towns with point coordinates. Another limitation is that these data generally provide counts of the unemployed, but not counts of the insured, or numbers in work, so calculation of rates often requires data from other sources such as the census. The study also includes two transcriptions from unpublished tabulations in the National Archives, relating to unemployment in 1928 and 1933.

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

For the second edition (February 2024), the data was updated; data running up to 1974 has been added and the former study 3711 has been incorporated.

- Trade Union Unemployment Percentages for four sectors (capenters and joiners, engineers, printing, and shipbuilding), 1902-14.

- Annual unemployment rates 1923-38 for 8 "divisions".

- Local Unemployment Index, 1927-39 arranged by age and sex.

- Unemployment statistics 1945-74 for towns and development areas from the Labour Gazette.

- Unpublished data on casuals, temporarily stopped, etc in 1928.

- Unpublished data on composition of the unemployed in January,1933 arranged by sex.

- Local government districts which were Special Areas in 1934.

Secure Access versions of Next Steps have more restrictive access conditions than Safeguarded versions available under the standard End User Licence (see 'Access' section).

Secure Access versions of the Next Steps include:

• sensitive variables from the questionnaire data for Sweeps 1-9. These are available under Secure Access SN 8656.
  
• National Pupil Database (NPD) linked data at Key Stages 2, 3, 4 and 5, England. These are available under SN 7104.
• Linked Individualised Learner Records learner and learning aims datasets for academic years 2005 to 2014, England. These are available under SN 8577.
  
• detailed geographic indicators for Sweep 1 and Sweep 8 (2001 Census Boundaries) are available under SN 8189, geographic indicators for Sweep 8 and 9 (2011 Census Boundaries) are available under SN 8190, and geographic indicators for Sweep 9 (2021 Census Boundaries) are available under SN 9337. The Sweep 1 geography file was previously held under SN 7104.
• Linked Health Administrative Datasets (Hospital Episode Statistics) for financial years 1997-2022 held under SN 8681.
• Linked Student Loans Company Records for years 2007-2021 held under SN 8848.

SN 5545 - Next Steps: Sweeps 1-9, 2004-2023 includes the main Next Steps survey data from Sweep 1 (age 14) to Sweep 9 (age 32).

Latest edition information
For the eighteenth edition (February 2025), the Sweep 9 Derived Variables data file has been updated with some newly derived variables categorised under the household (W9DCHNO12, W9DTOTCH, W9DTOTOWNCH) and education (W9DAQLVLH, W9DVQLVLH) sections. The Longitudinal data file have been updated with changes to the weight variables. Three out of the four weights in the previous version have been removed. W9FINWTALLB has been renamed to W9FINWT in line with previous sweeps. The user guide has been updated to reflect these changes. Furthermore, the derived variables user guide has been merged into the main user guide and can be accessed via Appendix 1.

Breaking down local authority level annual gross value added (GVA) statistics to lower levels of geography. These are official statistics in development.

The Marine Hard Substrate dataset maps areas of rock or hard substrate outcropping or within 0.5m of the sea-bed. The interpretation was based on a variety of data sourced from within the British Geological Survey and externally. Data consulted includes archive sample and seismic records, side scan sonar, multibeam bathymetry and Olex datasets. The distribution of hard substrate at the seabed, or within 0.5 m is important in dictating the benthic assemblages found in certain areas. Therefore, an understanding of the distribution of these substrates is of primary importance in marine planning and designation of Marine Conservation Zones (MCZs) under the Marine and Coastal Access Act, 2009. In addition, a number of other users will value these data, including marine renewable companies, aggregate companies, the fishing and oil and gas industries. In order to address this issue it was necessary to update British Geological Survey sea-bed mapping to delineate areas where rock, boulders or cobbles are present at, or within 0.5m of the sea-bed surface. A polygon shape file showing areas of rock or hard substrate at, or within 0.5m of the sea-bed has been developed. The dataset has been created as vector polygons and are available in a range of GIS formats, including ArcGIS (.shp), ArcInfo Coverages and MapInfo (.tab). More specialised formats may be available but may incur additional processing costs.