IMPORTANT: This deposit contains a range of supplementary material related to the deposit of the SIPHER Synthetic Population for Individuals, 2019-2021 (https://doi.org/10.5255/UKDA-SN-9277-1). See the shared readme file for a detailed description describing this deposit. Please note that this deposit does not contain the SIPHER Synthetic Population dataset, or any other Understanding Society survey datasets.

The lack of a centralised and comprehensive register-based system in Great Britain limits opportunities for studying the interaction of aspects such as health, employment, benefit payments, or housing quality at the level of individuals and households. At the same time, the data that exist, is typically strictly controlled and only available in safe haven environments under a “create-and-destroy” model. In particular when testing policy options via simulation models where results are required swiftly, these limitations can present major hurdles to coproduction and collaborative work connecting researchers, policymakers, and key stakeholders. In some cases, survey data can provide a suitable alternative to the lack of readily available administrative data. However, survey data does typically not allow for a small-area perspective. Although special license area-level linkages of survey data can offer more detailed spatial information, the data’s coverage and statistical power might be too low for meaningful analysis.

Through a linkage with the UK Household Longitudinal Study (Understanding Society, SN 6614, wave k), the SIPHER Synthetic Population allows for the creation of a survey-based full-scale synthetic population for all of Great Britain. By drawing on data reflecting “real” survey respondents, the dataset represents over 50 million synthetic (i.e. “not real”) individuals. As a digital twin of the adult population in Great Britain, the SIPHER Synthetic population provides a novel source of microdata for understanding “status quo” and modelling “what if” scenarios (e.g., via static/dynamic microsimulation model), as well as other exploratory analyses where a granular geographical resolution is required

As the SIPHER Synthetic Population is the outcome of a statistical creation process, all results obtained from this dataset should always be treated as “model output” - including basic descriptive statistics. Here, the SIPHER Synthetic Population should not replace the underlying Understanding Society survey data for standard statistical analyses (e.g., standard regression analysis, longitudinal multi-wave analysis). Please see the respective User Guide provided for this dataset for further information on creation and validation.

This research was conducted as part of the Systems Science in Public Health and Health Economics Research - SIPHER Consortium and we thank the whole team for valuable input and discussions that have informed this work.

The United Kingdom Data Center Storage Market Report is Segmented by Storage Technology (Network Attached Storage (NAS), Storage Area Network (SAN), Direct Attached Storage (DAS), and Other Technologies), by Storage Type (Traditional Storage, All-Flash Storage, and Hybrid Storage), by End-User (IT & Telecommunication, BFSI, Government, Media & Entertainment and Other End-Users). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

[The spreadsheet is organised into two parts. The first contains a broad set of annual data covering the UK national accounts and other financial and macroeconomic data stretching back in some cases to the late 17th century. The second and third sections cover the available monthly and quarterly data for the UK to facilitate higher frequency analysis on the macroeconomy and the financial system. The spreadsheet attempts to provide continuous historical time series for most variables up to the present day by making various assumptions about how to link the historical components together. But we also have provided the various chains of raw historical data and retained all our calculations in the spreadsheet so that the method of calculating the continuous times series is clear and users can construct their own composite estimates by using different linking procedures., This dataset contains a broad set of historical data covering the UK national accounts and other financial and macroeconomic data stretching back in some cases to the late 17th century.]

The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.

Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.

BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

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 BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets
Secure Access versions of BCS70 have more restrictive access conditions than versions available under the standard End User Licence (EUL).

SN 9115 - 1970 British Cohort Study: Sweeps 1-11, 1970-2024: Secure Access currently includes sensitive survey data from Sweep 10 and 11, as well as Activity Histories data.

Researchers applying for access to the Secure Access BCS70 datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the BCS70 Series Access web page).

Latest edition information
For the third edition (March 2025), sensitive data from the Sweep 11, age 51 survey have been added.

The Annual Survey of Hours and Earnings (ASHE) is one of the largest surveys of the earnings of individuals in the UK. Data on the wages, paid hours of work, and pensions arrangements of nearly one per cent of the working population are collected. Other variables relating to age, occupation and industrial classification are also available. The ASHE sample is drawn from National Insurance records for working individuals, and the survey forms are sent to their respective employers to complete.

While limited in terms of personal characteristics compared to surveys such as the Labour Force Survey, the ASHE is useful not only because of its larger sample size, but also the responses regarding wages and hours are considered to be more accurate, since the responses are provided by employers rather than from employees themselves. A further advantage of the ASHE is that data for the same individuals are collected year after year. It is therefore possible to construct a panel dataset of responses for each individual running back as far as 1997, and to track how occupations, earnings and working hours change for individuals over time. Furthermore, using the unique business identifiers, it is possible to combine ASHE data with data from other business surveys, such as the Annual Business Survey (UK Data Archive SN 7451).

The ASHE replaced the New Earnings Survey (NES, SN 6704) in 2004. NES was developed in the 1970s in response to the policy needs of the time. The survey had changed very little in its thirty-year history. ASHE datasets for the years 1997-2003 were derived using ASHE methodologies applied to NES data.

The ASHE improves on the NES in the following ways:

• the NES questionnaire allowed too much variation in employer responses, leading to wide variations in the data
• weightings have been introduced to take account of the population size (significant biases were a known problem in NES data)
• the significant numbers of employees who change jobs between the sample selection and survey reference dates are retained in the ASHE sample, whereas these were dropped from the NES

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.

Observations from Northern Ireland
The ASHE data held by the UK Data Archive include very few observations from Northern Ireland. Users requiring access to Northern Ireland data are advised to contact the Northern Ireland Statistics and Research Agency, who administer this aspect of the survey.

Local unit reference variable, luref
The local unit reference variable 'luref', is generated to indicate multiple occurrences of the same local unit for disclosure checking purposes. It is inconsistent across years and is not an IDBR reference number. It should not be used to link ASHE with other business datasets.

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.

Latest Edition Information
For the twenty-sixth edition (February 2025), the data file 'ashegb_2023r_2024p_pc' has been added, along with the accompanying data dictionary.

UK Data Service (UKDS) provides unified access to the UK's largest collection of social, economic and population data for research and teaching purposes covering a range of different disciplines. The majority of our data are fully anonymised, unless otherwise specified in the relevant online catalogue records, and are therefore not suitable for genealogical users or family historians. The UK Data Service is funded by the Economic and Social Research Council (ESRC) to meet the data needs of researchers, students and teachers from all sectors, including academia, central and local government, charities and foundations, independent research centres, think tanks, and business consultants and the commercial sector.

The United Kingdom Data Center Rack Market is Segmented by Rack Size (Quarter Rack, Half Rack, Full Rack), by End User (IT & Telecommunication, BFSI, Government, and Media & Entertainment). The Market Sizes and Forecasts are Provided in Terms of Volume (units) for all the Above Segments.

From September to November 2023, Google.com was the leading website in the United Kingdom with more than 4.98 billion monthly visits. The search engine was also popular in its UK top-level domain, with Google.co.uk reaching 255 million views and placing tenth in the ranking. YouTube and Facebook were the most visited social media platforms, ranking second and fourth most visited websites in the country.

Snapshot img

UK Data Center Market Size 2024-2028

The UK data center market size is forecast to increase by USD 37.87 billion, at a CAGR of 21.8% between 2023 and 2028.

Several key trends are shaping the industry's growth. The proliferation of smartphones and the increasing adoption of hybrid cloud are driving the demand for data center services. Moreover, the development of smart city infrastructure necessitates the deployment of reliable and efficient data centers. Energy efficiency is a significant concern, with data centers implementing advanced electrical and mechanical infrastructure to reduce power consumption. Artificial intelligence (AI) and machine learning are also transforming data centers, necessitating hyper-scalability and automation. Physical data centers continue to be the backbone of digital operations, with Tier 3 data centers offering the ideal balance between reliability and cost-effectiveness. 
The market analysis report highlights these trends and their impact on the data center landscape. Colocation remains a popular option for businesses seeking to reduce capital expenditures while maintaining control over their IT infrastructure. The report provides insights into the challenges and opportunities in the market, including the need for continuous innovation and the importance of maintaining a strong electrical and mechanical infrastructure.

What will be the Size of the Market During the Forecast Period?

Request Free Sample

The market is witnessing significant growth, driven by the increasing demand for digital transformation, remote working, and the integration of advanced technologies such as 5G networks, big data, and the Internet of Things (IoT). This evolution is reshaping the landscape of data center infrastructure, with a focus on efficiency, scalability, and security. Multi-tenant data centers are gaining popularity due to their cost-effective solutions and flexibility. These facilities offer shared resources, enabling businesses to scale their IT infrastructure as needed. 
The electrical and mechanical infrastructure of these data centers is being upgraded to accommodate the demands of high-performance computing, generative AI, and deep learning. Enterprise data centers are also undergoing transformations, with a shift towards hyperscale and cloud data centers. Hyperscale data centers are designed to handle large amounts of data and offer economies of scale, while cloud data centers provide on-demand access to computing resources. Micro data centers are being adopted for edge computing applications, enabling faster data processing and reduced latency. Data security is a critical concern in the market. Advanced security measures, such as access control systems, firewalls, and encryption technologies, are being implemented to protect digital data.
Server storage devices and networking equipment are being upgraded to support the latest security protocols. The data center rating system is becoming increasingly important, as businesses seek to ensure the reliability and efficiency of their data center infrastructure. Corporate data centers are being evaluated based on various metrics, including power usage effectiveness (PUE), cooling efficiency, and availability. The integration of renewable energy sources, such as solar and wind power, is another trend in the market. This is driven by the need to reduce carbon emissions and improve sustainability. Data centers are also adopting energy-efficient technologies, such as liquid cooling and free cooling, to reduce energy consumption.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments. ComponentIT infrastructurePower managementMechanical constructionGeneral constructionSecurity solutionsTypeOn-premiseHyperscaleHPCColocationEdgeDesignTraditionalContainerizedModularGeographyUK

By Component Insights

The IT infrastructure segment is estimated to witness significant growth during the forecast period. In the realm of Information Technology (IT), a data center infrastructure refers to the complete setup of hardware, software, and solutions necessary for establishing or expanding a data center. This infrastructure encompasses server architecture, storage solutions, software-defined data centers (SDDC), network configurations, converged infrastructure, backup and recovery software, automation tools, and data center infrastructure management (DCIM) systems. The escalating requirement for computational power and storage capacity to manage the burgeoning data traffic fuels the demand for advanced IT infrastructure.

Get a glance at the share of various segments. Download the PDF Sample

The IT infrastructure segment was valued at USD 11.19 billion in 2018. Businesses are increasingly

Trusted access and training to use the UK's largest collection of economic, population and social research data for teaching, learning and public benefit.

History Data Service, UK Data Archive is a book publisher. They published 1 books in our database by 1 different authors between 2001 and 2001.

Crime data and neighbourhood policing information from all forces in England and Wales to the Public. This data is what is behind the police.uk website.

The Police API allows you to retrieve information about neighbourhood areas in all 43 English & Welsh police forces. All forces are required to keep this data accurate and up to date, so the API provides a rich and definitive data source for crime statistics at both street and neighourhood level.

The API is implemented as a standard XML REST web service using HTTP GET/POST requests.

The monthly data dumps can be downloaded using URLs structured consistently in the following format: https://data.police.uk/data/archive/[year]-[month].zip However because the data file is over 19 million rows, we also provide Custom CSV Download and JSON API helper interfaces so you can easily access subsets of the data. Generally, we recommend working with one of these interfaces instead of the full data dump.

The Participation Survey is a continuous push-to-web survey of adults aged 16 and over in England. It serves as a successor to the Taking Part survey, which ran for 16 years as a continuous face to face survey. Paper surveys are available for those not digitally engaged. Fieldwork started in October 2021 and it is envisaged that the survey will be a key evidence source for Department for Digital, Culture, Media and Sport (DCMS) and its sectors by providing statistically representative national estimates of adult engagement with the DCMS sectors. The survey’s main objectives are to:

• Provide a central, reliable evidence source that can be used to analyse cultural, digital, and sporting engagement, providing a clear picture of why people do or do not engage.
• Provide data at a county level to meet user needs, including providing evidence for the levelling up agenda.
• Underpin further research on driving engagement and the value and benefits of engagement.

Further information on the survey can be found on the gov.uk Participation Survey webpage.

Three versions of the Participation Survey 2022-2023 are available:

• This open access version (SN 9126). This version is freely available to download and does not require UK Data Service registration.
• A safeguarded dataset (SN 9125), which includes some additional detail. It is only available to registered UKDS users who have agreed to abide by the conditions of the End User Licence.
• A Secure Access version containing all years (SN 9014), which contains further detailed information. Access to this version is very restricted and requires UKDS registration, completion of an extensive application form, approval from the depositor, and successful completion of a Safe Researcher Training course before access can be granted. Users are advised to first download the safeguarded version (SN 9125) to check whether it includes sufficient detail for their research, before considering making an application for the Secure Access version.

Details of all variables available for the version concerned can be found in the UKDS Data Dictionary - see the Documentation section.

The UK data center market is experiencing robust growth, projected to reach £22.53 billion in 2025, expanding at a compound annual growth rate (CAGR) of 21.8% from 2025 to 2033. This surge is driven by several factors. The increasing adoption of cloud computing and digital transformation initiatives across various sectors, including finance, healthcare, and technology, fuels the demand for robust and scalable data center infrastructure. Furthermore, the UK government's ongoing investments in digital infrastructure and its strategic location as a major European hub for international businesses are significant catalysts. Growth is also fuelled by the rising demand for edge computing, enabling faster data processing and reduced latency for applications requiring real-time responsiveness. The increasing need for robust cybersecurity measures also contributes to market expansion, as businesses prioritize data protection and compliance with stringent regulations. However, the market isn't without challenges. Rising energy costs pose a significant restraint, impacting operational expenses and potentially hindering profitability. Competition among established players and new entrants is intensifying, leading to price pressures and the need for continuous innovation. Furthermore, securing sufficient land and skilled labor for data center construction can pose challenges in certain regions, potentially delaying project timelines and increasing costs. Despite these constraints, the long-term outlook for the UK data center market remains positive, propelled by continuous technological advancements and the unwavering growth of digital economies. Key segments, including IT infrastructure, power management, and security solutions, will experience significant expansion, attracting investment and driving further innovation within the sector. Major players like Amazon, Microsoft, and Equinix are expected to maintain a strong competitive position, leveraging their extensive experience and resources to capture market share.

Tables describing the international trends and logistic regression modelling results, that helps to explain the statistical significance of a range of factors on the likelihood of inactivity.

This dataset is about books and is filtered where the book publisher includes History Data Service, UK Data Archive. It has 7 columns such as author, BNB id, book, book publisher, and ISBN. The data is ordered by publication date (descending).

The UK data center rack market is anticipated to grow at a CAGR of 11.5% during the forecast period from 2025 to 2033. The market was valued at XX million in 2025 and is projected to reach XX million by 2033. The growth of the market is attributed to the increasing demand for data centers due to the rapid adoption of cloud and virtualization technologies. Additionally, the growing need for data storage and processing in various industries, such as IT & telecommunication, BFSI, and government, is further driving the market growth. The market is segmented based on rack size into quarter rack, half rack, and full rack. The full rack segment is expected to dominate the market during the forecast period due to its high capacity and scalability. Additionally, the increasing adoption of high-density servers is expected to boost the demand for full racks. Geographically, the UK data center rack market is segmented into North America, Europe, Asia Pacific, and the Rest of the World. The European region is expected to hold a significant share of the market during the forecast period due to the presence of a large number of data centers in the region. Recent developments include: August 2022: Colt Group Holdings Limited announced the opening of a new data center in Hayes, West London. This was expected to more than triple his existing footprint in the UK capital. The company was to build a new purpose-built 50MW data center on a 2.1-hectare data center campus called 'London 4'., March 2022: Kao Data announced plans for a second building on its campus in Harlow, UK. The company announced that construction of a second 10MW power plant outside London was then underway.. Key drivers for this market are: Rapid adoption of Cloud Services in United Kingdom, Significant growth in e-Commerce Data generation. Potential restraints include: Increasing number of Data Security Breaches, Low Availability of Resources. Notable trends are: Full Rack accounted for majority market share in 2022.

This dataset comprises 101 plain text files each containing the track data for one of the individual ants studied in the paper. The name of each file starts with the colony number (C1 to C3), the size of nest (small:35x28 mm or large: 55x44 mm) and the consecutive number of the individual ant for a colony and nest size. The ant track-data in each file are organised in three columns: Column 1: Time in seconds (absolute time) and is therefore comparable accorss ants. Column 2: x-coordinate in mm. Column 3: y-coordinate in mm. The centre of the nest exit is located at (0.5* xmax, ymax). Complete download (zip, 11.4 MiB)