Service sector data highlighting the UK's major trading partners, which services are common to a number of industries and the geographical breakdown on services and industries. Source agency: Office for National Statistics Designation: Official Statistics not designated as National Statistics Language: English Alternative title: TIS

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.

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.

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.

The primary aim of the research project was to present an overview of Britain's relative competitive performance in the postwar period. Previous research in this area has concentrated on either the total economy or on manufacturing. The aim of the project was to broaden the scope of research by examining competitive performance for all sectors of the aggregate economy. To do so, a dataset was constructed to enable measurement of productivity (both labour and total factor productivity) and unit labour costs comparing Britain to four of her major competitors, i.e. the US, France, Germany and Japan. The research was concerned with to what extent the performance at the aggregate economy level was affected by the inclusion of non-market services (health, education and government), which are poorly measured in the national accounts. Differences in performance between service sectors and production industries were also analysed.

The United Kingdom recorded a trade deficit of 5260 GBP Million in July of 2025. This dataset provides - United Kingdom Balance of Trade - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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

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.

Latest edition information

For the second edition (January 2024), a new version of the data file was deposited, with smoking variables added.

Major Development Sites in York. For further information about major development sites please visit the City of York Council website. *Please note that the data published within this dataset is a live API link to CYC's GIS server. Any changes made to the master copy of the data will be immediately reflected in the resources of this dataset.The date shown in the "Last Updated" field of each GIS resource reflects when the data was first published.

The data comprises GIS layers representing the permeability of mass movement 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,. The data is updated annually, or after a major new release of DiGMap-GB. The permeability data describes the fresh water flow through mass movement deposits and the ability of a 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 NCDS 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.

Abstract copyright UK Data Service and data collection copyright owner. The main aims and objectives of the research project from which this dataset arose were: (1) To examine patterns of plant location throughout Britain over the period 1932-38; (2) To examine patterns of plant location in the Greater London region over the interwar period; (3) To explore the extent and nature of local clustering of new manufacturing plants in interwar Britain; (4) To explore the nature of locational externalities in major clusters of new manufacturing plants in interwar Britain; (5) To assess the contribution of new manufacturing plant location to regional change in Britain over the interwar period. Main Topics: This project examined patterns of industrial location and clustering for new manufacturing plants in interwar Britain. The dataset provides plant-level data on new manufacturing plants (together with some non-manufacturing plants, such as repair and servicing facilities) established throughout Britain from 1932-38, and in the London region (together with some adjacent localities) for the whole of the interwar period. These were assembled from two contemporary sources: the Board of Trade’s annual 1932-38 Surveys of Industrial Development, and a register compiled by the Greater London Regional Development Committee. The data are limited to plants with an initial employment of at least 25 people. They include each plant’s location, a description of its output, its sector (coded by three digit 1980 Standard Industrial Classification), and its initial employment (mainly within bands of 100). For plants established between 1932 and 1938, information is also available regarding whether the plant was a branch plant of the firm in question, or was opened as a result of a transfer of production from another locality. The national 1932-38 data also include information on extensions of production for existing plants (where these involve the employment of at least 25 people). The data are entered into two Excel files, one covering the national 1932-38 data and the other providing 1919-38 data for the London region and some adjacent areas. Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research. Purposive selection/case studies Transcription of existing materials

Data are available for each junction to junction link on the major road network (motorways and A roads). Data are also available for the sample of points on the minor road network (B, C and unclassified roads) that are counted each year, and these counts are used to produce estimates of traffic growth on minor roads.

The data are produced for every year, and are in three formats: a) the raw manual count data collected by trained enumerators; b) Annual Average Daily Flows (AADFs) for count points on major roads and minor roads; and c) traffic figures for major roads only. Explanatory notes (metadata) are available for each dataset, and in one combined note.

A description of how annual road traffic estimates are produced is available at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/270083/contents-page.pdf

This dataset was kindly released by the British Department of Transportation. You can find the original dataset here.

The Giant’s Causeway and Causeway Coast site was inscribed as a World Heritage Site (WHS) by the United Nations Educational, Scientific and Cultural Organisation (UNESCO) in 1986. The site is of outstanding universal value and meets two of the criteria set out in the World Heritage Convention, namely it: i). is an outstanding example representing major stages of the earth’s history, including the record of life, significant on-going geological processes in the development of landforms, or significant geomorphic or physiographic features. ii). contains superlative natural phenomena or areas of exceptional natural beauty and aesthetic importance. The Site occupies approximately 70ha of land and encompasses a further 160ha of sea along the North Antrim Coast.

GVA estimates for middle layer super output areas, travel to work areas (TTWA), towns and cities, integrated care board and health board areas, parliamentary and devolved government constituencies, highlands and islands area offices, and bespoke areas. Productivity estimates are for TTWA, and towns and cities. These are official statistics in development.

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 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.

This synthetic dataset includes 16,276 patients admitted for drug overdose from 2016 to 2022, featuring comprehensive patient demographics, comorbidities coded by ICD-10 and SNOMED-CT, and detailed admission data from the index event onward. Information on clinical outcomes, primary diagnoses, psychiatric referrals, and all treatments (e.g., fluids, blood products, procedures) is included.

The dataset was generated using the SDV package's HMA1 synthesizer. The real data was pre-processed, with metadata defining schema, primary/foreign keys, and inter-table relationships, guiding the synthesizer in learning data structure and dependencies. This approach produced synthetic data that mirrors the original’s statistical properties, supporting privacy-preserving analysis and model training.

Geography: The West Midlands has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Explore the "iHerb Products Dataset," a valuable resource that provides detailed insights into the extensive range of health and wellness products available on iHerb, a leading online retailer specializing in natural products.

This dataset includes comprehensive information about various products, including supplements, vitamins, beauty products, and personal care items.

Key Features:

• Extensive Product Listings: Contains a wide variety of health and wellness products, offering a broad overview of the items available on iHerb across different categories.
• Detailed Information: Each product entry includes essential details such as product names, brands, categories, descriptions, prices, ingredients, customer reviews, and ratings.
• Insights into Market Trends: Analyze trends in the health and wellness market, including popular product categories, top-rated brands, customer preferences, and pricing strategies.
• Ideal for Research and Analysis: This dataset is perfect for researchers, data analysts, and e-commerce professionals interested in studying consumer behavior, understanding market trends, or optimizing product offerings in the health and wellness sector.

The iHerb Products Dataset offers valuable insights into the diverse range of health and wellness products, making it a crucial resource for businesses, researchers, and consumers alike. Utilize this dataset to stay updated on market trends, explore consumer preferences, and gain a deeper understanding of the health and wellness market dynamics.

This file contains the digital vector boundaries for the Major Towns and Cities in England and Wales, as at December 2015. Version 2 includes centroid data in the attributes table.The boundaries available are: (BGG) Generalised Grid (50m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.REST URL of ArcGIS for INSPIRE View Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Major_Towns_and_Cities_(Dec_2015)_Boundaries_V2/MapServerREST URL of ArcGIS for INSPIRE Feature DownloadService – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Major_Towns_and_Cities_Dec_2015_Boundaries_V2/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Major_Towns_and_Cities_Dec_2015_Boundaries_V2_2022/FeatureServer