This is the Index of Place Names (IPN) in Great Britain as at December 2022 (published March 2023). The IPN was first produced after the 1831 Census; this new version has been greatly expanded in content and extent. Featuring over 100,000 entries, it lists the names of localities and geography areas throughout England, Scotland and Wales. The IPN is published annually and with an updated and informative user guide giving a full rundown and explanation of the contents (File Size - 7 MB).(Note: Updated version 1.1 (published May 2023) reflects the change in registration districts from Northamptonshire to North Northamptonshire and West Northamptonshire.)

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).

Towns in England and Wales: towns list, cities list, classification and population data.

This data-set contains all data resources, either directly downloadable via this platform or as links to external databases, to execute the generic modeling tool as described in D5.4

• 0 generic model
  file: d5.4-generic-model_february-2020.pdf
  Report with methodology and source code for the generic model
• 1.1 COPERNICUS
  https://land.copernicus.eu/local/urban-atlas/urban-atlas-2012?tab=download.%20
  The European Urban Atlas provides reliable, inter-comparable, high-resolution land use and land cover data for 800 Functional Urban Area (FUA) for the 2012 reference year in EEA39 countries.
• 1.2a 1km grid shapefiles for NOx emissions in EU
  The shapefiles are: nox.dbf nox.prj nox.shp nox.shx
• 1.2b 1km grid shapefiles for PM10 emissions in EU
  The shapefiles are: pm10.dbf pm10.prj pm10.shp pm10.shx
• 2.1 Eurostat energy consumption data
  https://ec.europa.eu/eurostat/web/energy/data/database?p_p_id=NavTreeportletprod_WAR_NavTreeportletprod_INSTANCE_QAMy7Pe6HwI1&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&p_p_col_id=column-2&p_p_col_count=1
• 2.2 JODI gas consumption data
  https://www.jodidata.org/gas/database/data-downloads.aspx
  Complete data series for all products, flows and countries, from January 2009 to one month-old can be downloaded, for free, in a beta version of .csv format.
• 2.3 Meteo data UK
  https://www.metoffice.gov.uk/services/data/datapoint/datapoint-products
• 2.4 Meteo data NL
  https://www.knmi.nl/nederland-nu/klimatologie/daggegevens
• 2.5 hourly electricity load profiles
  https://data.open-power-system-data.org/time_series/
• 3.1 fleet data
  file: 200210_summary_fleet_2016.csv
  Summary of historical fleet for EU28+NO by age and vehicle type: Diesel, CNG, Petrol, Electric, PHEV, LPG
• 3.2 modal shares
  file: 200210_summary_shares.csv
  This data set holds the modal share of different modes, for EU cities at level of vehicle kilometers. Modes considered: bus car heavy duty truck >32t heavy duty truck 16-32t heavy duty truck 3_5-7_5t heavy duty truck 7_5-16t light duty truck metro/tram moped motorcycle passenger train slow mode van
• 3.3 emission factors
  file: 200212_summary_copert_ef.xlsx
  Emission factor for passenger cars (in g/km )from COPERT V, urban conditions. Data dimensions: 1. type: diesel, petrol, CNG, LPG, PHEV (in line with fleet data) 2. pollutant: NOx or PM 3. Peak/off-peak: (P/OP) 4. year of built: YOB
• 5.1 Crude death rates
  http://apps.who.int/healthinfo/statistics/mortality/causeofdeath_query/start.php
  the total number of deaths in a country per year per 1,000 people broken down by age cohort and sex
• 5.2 UN population data
  https://population.un.org/wpp/Download/Standard/Population/
  the number of inhabitants at country level broken down by age cohort and sex the time a person has lived broken down by age cohort and sex, and country

The project aimed to thoroughly examine the rural geographies of gentrification in France, the UK, and the USA through a comparative study of its theory, forms, and dynamics. It sought to determine whether rural gentrification could be used as a concept to explain changes in rural areas in these countries. he project began by using the concept of "sociologies of translation" to understand how the term "rural gentrification" was used in academic, policy, and popular discourses in the past and present in these countries. To identify the presence and use of social assets within rural gentrification, an asset-based theory was developed. National datasets were mapped using empirical indicators and comparable measures of rural, urban, and peri-urban spaces to analyse the geographies of gentrification in these countries and develop a typology of rural gentrification. The archive consists of the UK element of the International Rural Gentrification (iRGENT) project The dataset contains material from a questionnaire survey conducted in 9 villages, located in 6 local authority Districts in England

This dataset comprises point data showing Bristol City Council Household Waste Recycling Centre locations

Population and household characteristics by built-up area (BUA) size classification and individual BUAs, England (excluding London) and Wales, Census 2021. Data are available at a country, BUA size classification and individual BUA level.

This dataset comprises polygon data showing the extent & location of all Common Land & Village Greens within Bristol. Commons are typically unfenced land in private ownership with development / land use protected by legislation, although commoners may be granted specific rights. Village Greens are generally areas where local residents go for exercise, lawful sports & pastimes. Some Village Greens also have rights of common over them but enjoy separate statutory protection.

This dataset is a combination of the The GeoInformation Groups' Cities Revealed UK building heights and UK individual building classes datasets, although height information is lacking for some buildings, so users may wish to check the UK building heights database in these cases. This dataset provides outlines of building blocks with height information derived from the Cities Revealed LiDAR surveys, high-resolution aerial photography and other height data sources combined with Building Class data. The data were acquired by the Landmap project from The GeoInformation Group (TGG). The Joint Information Systems Committee (JISC) funded Landmap service which ran from 2001 to July 2014 collected and hosted a large amount of earth observation data for the majority of the UK, part of which was buildings data. After removal of JISC funding in 2013, the Landmap service is no longer operational, with the data now held at the NEODC.

When using these data please also add the following copyright statement: Cities Revealed © The GeoInformation Group yyyy

The Monmouth Rebellion of 1685 prompted the government in London to undertake a survey the following year to establish the number of guest beds and quantity of stabling available across England and Wales for billeting soldiers. This dataset represents an attempt to identify and geolocate all of the place-names noted in that survey.

Transcription was undertaken for CAMPOP by Jacob Field, with funding provided by Leigh Shaw-Taylor and Dan Bogart. Stephen Gadd is responsible for place-name identification and geolocation, matching place-names as far as possible to the Index Villaris, 1680 dataset, GB1900 labels, and OpenStreetMap nodes.

PLEASE NOTE: THIS PRE-RELEASE DOES NOT CONTAIN ANY DATA

DOI Abstract copyright UK Data Service and data collection copyright owner. For popular revolt in late-medieval English towns the assumption has been that little happened there. The theatre of medieval English class conflict, instead, was the countryside, where revolt has been studied more thoroughly in England than for any area of medieval Europe. From a reading of over ninety chronicles, the voluminous Calendar of Patent Rolls, and numerous other crown and municipal records, the project has redressed this imbalance. It has uncovered and analysed around 700 incidents of popular protest, 1196 and 1452. For the first time, moreover, research on English revolts in towns has been placed in a wider comparative continental context and has shown profound differences between England and the continent in the trajectories and character of revolt. Economic and ecological factors played less a role in sparking revolt in England than on the continent: the ebb and flow of English revolts, instead, was more dependent on high politics—dynastic and baronial conflict and at moments of weak kingship. The project has demonstrated that the difference in popular protest between England and the continent resulted from the precociousness of the English state, its structure of courts and law enforcement and the growth of centralized royal power over the two-and-a-half centuries of this study. Because of this development of repressive forces, the character of popular protest in late medieval England began to resemble more closely that found on the continent during the sixteenth and seventeenth centuries, when the gulf between the ruled and rulers had widened. Main Topics: The first table records revolts, popular protests and popular movements found in our survey of voluminous Calendar of Patent Rolls from the mid-thirteenth century to the end of their publication in 1452, including date of incident; type of document (pardon, commission of oyer et terminer, royal mandate, etc); place of the revolt's occurrence; complainant (mayor, bishop, king etc), number accused, occupations, summary of incident, penalties, comment. The second table records revolts et al. within over 90 chronicles survey: these include name of chronicler, type of movement, revolt, etc. such as tax revolt, student revolt, etc; date, place of incident, name of revolt (if given), such as Cade's Revolt; participants, such as craftsmen, burghers, etc; numbers involved (if given), leaders, chants, actions, cause, repression, comments=summary of case.

The data is anonymised transcripts of six focus groups. The study aimed to understand how new cycling and walking infrastructure and community activation projects might support modal shift to active travel amongst commuters and older adults making within-town journeys in market towns.

The Cities of Making project aimed to initiate and inform debate about the future of manufacturing in European cities. It provides insight into the past, present and potential future roles of manufacturing in the cities of Brussels, London and Rotterdam. The outputs of the project are intended primarily for an audience of policy makers and practitioners, and will be of particular interest to those in the fields of manufacturing and industry, spatial planning and urban design, environmental sustainability, and economic development. It may also be of interest to those involved in citizen engagement within those fields. This archive contains data collected during the UK portion of the Cities of Making research project. It includes transcripts of interviews with multiple key stakeholders, information gathered from workshops, and information on various manufacturing sites located in the region around London and the South East of England. Case study sites studied in detail are within the London boroughs of Hackney and Haringey, and also the Old Oak Common / Park Royal Development (OPDC) site. Geo spatial information is provided gathered from site visits and desk based research.Cities of Making explores opportunities for strengthening urban based manufacturing in European cities following years of decline and offshoring. Using a combination of strategic and action research, our ambition was to identify 'what works' in supporting a resilient and innovative industrial base, and to test those solutions in a real world setting. We took three areas as case study areas, London, Rotterdam and Brussels - each with a distinct industrial heritage. Within each city, the project partners conducted separate but parallel lines of inquiry, encompassing a city diagnosis, and an in-depth academic study. The project generated a comprehensive website, www.citiesofmaking.com, a book, Foundries for the Future, and a set of 50 'pattern' cards that can be used by relevant stakeholders to help develop transition plans to enable urban manufacturing. This project used a mixed-method approach to obtain primary data and to analyse both primary and secondary data. Primary data was obtained through questionnaires to key relevant stakeholders, i.e. companies’ owners, directors or staff. Secondary data was obtained from literature review, online databases, site visits to industrial focus areas, and aerial imaging. The analysis of primary and secondary data was conducted through a number of specialised tools such as network analysis, spatial analysis, material flow analysis (MFA), and strengths-weaknesses-opportunities-threats (SWOT) analysis. Additional methodological information can be found in the project book and in the cities reports both available from the main project website (www.citiesofmaking.com) and uploaded in the data archive.

Our UK Postcode Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

This file provides a rural-urban view of 2001 Lower Layer Super Output Areas (LSOA) in England and Wales. The ZIP file contains the Rural Urban Classification in XLSX and CSV format and includes a user guide. The files were originally from the NeSS website. Click on the Download button to download the ZIP file.The classification of rural and urban areas is the outcome of a project co-sponsored by:Office for National Statistics (ONS);Department for Environment, Food and Rural Affairs (Defra);Office of the Deputy Prime Minister (now Communities and Local Government);Countryside Agency (CA); andNational Assembly for Wales (NAW).The classification was developed in 2004 by a consortium co-ordinated by Prof. John Shepherd from Birkbeck College. The technical work was lead by Peter Bibby of University of Sheffield and the project also involved the University of Glamorgan and Geowise. The rural and urban classification of Output Areas, Super Output Areas (this dataset) and Wards has been provided to enable datasets to be analysed according to the classification. This provides a powerful tool for the development and monitoring of rural and urban policies.Please Note: Super Output Areas do not have all the same codes as the OA level Dataset. For SOAs and Wards the classifications for ‘Villages, Hamlets and Isolated Dwellings’ have been combined.Similar procedures to those used to classify Output Areas apply to the classification for the 34,378 Lower Layer Super Output Areas in the dataset. However the morphological classification differs in the number of categories as very few LSOAs can be classified as predominantly dispersed settlements. LSOAs are categorised into just three domains: urban 10k, town and fringe and villages, hamlets and isolated dwellings, using the key below:2005 Rural and Urban morphology indicator1 - denotes predominantly urban >10k2 - denotes predominantly town and fringe3 - denotes other rural (including village, hamlet and isolated dwellings)2005 Rural and Urban context indicator0 - denotes less sparsely populated areas1 - denotes sparsely populated areas

Abstract copyright UK Data Service and data collection copyright owner. A comparative study of the causes of new episodes of homelessness among people aged 50 or more years was undertaken in Boston, Massachusetts (USA), Melbourne, Australia, and four English cities. The aims were to make a substantial contribution to the predominantly American debate on the causes of homelessness, and to make practice recommendations for the improvement of prevention. The study had several objectives. It aimed to collect information about the antecedents, triggers and risk factors for becoming homeless in later life and about the national and local policy and service contexts. Furthermore, the researchers aimed to analyse and interpret the findings with reference to an integrated model of the causes of homelessness that represented structural and policy factors, including housing, health and social service organisation and delivery factors, and personal circumstances, events, problems and dysfunctions. The aim was to do this collaboratively, by drawing on the project partners' experience and knowledge. Finally, it was hoped to develop recommendations for housing, primary health care and social welfare organisations for the prevention of homelessness. This was to be done by identifying the common sequences and interactions of events that precede homelessness and their markers (or 'early warning' indicators) and by holding workshops in England with practitioners and their representative organisations on new ways of working. By the study of contrasting welfare and philanthropic regimes in a relatively homogeneous category of homeless incidence (i.e. recent cases among late middle-aged and older people), it was hoped that valuable insights into the relative contributions of the policy, service and personal factors would be obtained. The study focused on older people who had recently become homeless, purposely to gather detailed and reliable information about the prior and contextual circumstances. To have included people who had been homeless for several years would have reduced the quality of the data because of 'recall' problems. Users should note that data from the Australian sample for the study are not included in this dataset. Main Topics: The data file includes information about the English respondents and those from Boston. It was compiled in two stages. The first stage involved each project partner entering the pre-coded responses into the file. All partners then identified themes and created codes for the open-ended responses, and the resulting variables were added. Data quality-control procedures included blind checks of the data coding and keying. The first 200 variables pertain to information collected from the respondents. They comprise descriptive variables of the circumstances prior to homelessness, including housing tenure during the three years prior to the survey, previous homelessness, employment history, income, health and addiction problems, and contacts with family, friends and formal services. The respondents were asked to rate whether specific factors were implicated in becoming homeless, and where appropriate, a following open-ended question sought elaboration. The remaining variables comprise information collected from the respondents' 'key workers' about their understanding of the events and states that led to their clients becoming homeless. No sampling frame was available. The sample profiles have been compared with those of all homeless people (not just the recently homeless) in the study locations, most effectively in London and Boston. No gross biases were revealed. The samples represent a large percentage of the clients who presented to the collaborating organisations during the study period and who gave their informed consent to participate. Agreed definitions of homelessness were: sleeping on the streets or in temporary accommodation such as shelters; being without accommodation following eviction or discharge from prison or hospital; living temporarily with relatives or friends because the person has no accommodation, but only if the stay had not exceeded six months, and the person did not pay rent and was required to leave. People who had been previously homeless were included in the survey if they had been housed for at least 12 months prior to the current episode of homelessness. Face-to-face interview Self-completion the 'key workers' (case managers) completed questionnaires about their assessments of the respondents’ problems and of the events and states that led to homelessness. Further clarifications and checks were made by telephone.

This data collection contains data primarily from both the 1841 and 1851 Census of Ireland used in Fernihough and Ó Gráda (2022). Also contained, where available, are population counts from the 1821 and 1831 censuses. The data collection also includes an amended version of the Civil Parish Shapefile from townlands.ie (OpenStreetMap Ireland, 2020). Both data sources were adjusted to ensure concordance. The towlands.ie data is open data is open data, licensed under the Open Data Commons Open Database License (ODbL). Please contact Alan Fernihough for further details or queries. The “shapefile” files are the GIS files one needs to load the spatial boundaries. The census data is included in the “data.csv” file and one must merge this to the shapefiles to work with these data. However, this is a simple process. The file “load and join.R” is an example of how this could be performed using the R statistical software package.Was early 19th century Ireland overpopulated and fertility at an unsustainable level, or did other factors cause the Great Irish Famine? Did the famine-induced migration to Britain spread infectious diseases and have a substantial impact on British mortality rates? Similarly, what impact did the famine have on the British labour force and economy generally? This research project will answer these questions. The Great Famine was a watershed in global history. It was the last major famine to occur in a Western economy, and had long-run impacts. The enduring legacy of the famine has sparked the interest of numerous novelists and playwrights. Earlier this year, news that media group Channel 4 was considering commissioning a Great Famine-based sitcom stoked an intense public debate. Many felt that this would trivialise the tragedy. The length and breadth of this debate underlined the immense interest that still surrounds the famine. However, the spectrum of opinions as to the causes and consequences of the famine also highlighted the need for further historical research. Let the Data Speak Joel Mokyr's influential 1983 book Why Ireland Starved redefined famine research. Before, famine-related research was largely based on qualitative assessments that left ample room for both conjecture and, rhetoric, and errors. Unlike previous researchers, Mokyr, wanted to let the data decide whether or not it was Ireland's overpopulation that caused the famine. To do this he gathered data on the population density of Irish regions and found that it was Ireland's least densely populated regions that were the ones that suffered worse during the famine. Mokyr's test did not support the overpopulation theory (captured by what is known as the Malthusian model). I hasten to add that the Malthusian model cannot be considered to have been refuted by this finding. For one thing, the possibility that more sophisticated econometric techniques and improved data will reverse the finding cannot be ruled out. (Mokyr, 1983). Whilst striking, Mokyr's analysis was based on variation between relatively few data points (Ireland's 32 counties), as the quote above testifies. This study is motivated by the above quote. Better data (from over 3,000 civil parishes) and more sophisticated econometric techniques exist, and therefore Mokyr's findings can at last be re-evaluated, something this project will do. Mokyr's philosophy of letting the data speak, can also be applied to help uncover some of the Great Famine's consequences. Specifically, this project will quantify the impact that famine-induced migration had on Britain. The famine caused a mass movement of the Irish population to Britain. Before the famine, there were around 430,000 Irish born in Britain. By 1851, the Irish-born population had grown to 730,000. This crisis-driven mass-migration echoes Europe's migration crisis today, as people flea from war-torn and economically desolate nations in Africa and Asia. In this sense, the Great Irish Famine provides a form of historical natural experiment from which we can learn from and gain a greater understanding of the consequences of mass migrations. What effect did the Irish famine have on Britain? This research will use newly available census data (released as part of the ESRC-funded ICeM project) to uncover how the Irish famine influenced the British economy and labour force. For example, did the influx of Irish in certain cities such as Liverpool and Manchester boost demand and help to speed up economic growth, or did this migration depress the wages of locals and therefore stifle economic advancement? In addition, this project will also use newly available records of regional mortality to calculate what impact, if any, the Great Famine had on mortality in England and Wales. If the Irish famine caused elevated levels of mortality, this implies that the ultimate death toll of the Irish famine is underestimated. Parish-level data transcribed from published sources, the official census returns for 1841 and 1851. In addition, to 1821 and 1831 were partially transcribed where they could be satisfactorily matched. Spatial data (shapefiles) were downloaded from townlands.ie. Both the transcribed census returns and the townlands.ie shapefile were amended to ensure concordance between all of the sources. For example, in instances where a civil parish straddled two or more baronies the individual returns for the parish were aggregated to a single data observation, which was then matched to the corresponding townlands.ie spatial polygon. Variables from the 1841 and 1851 censuses are split according to total and rural portions of each parish. The census reports reported the non-rural (towns, villages, etc.) share of each parish separately. In parishes with no non-rural portions (villages, small towns, etc.) the totals for the complete and rural variables will be equal. 58 per cent of parishes fit this criteria.

This data set contains annual data and the most recent quarterly data on house building starts. From 2011/12 imputed data is included. Imputed data should not be seen as an estimate for the individual authority but is given on an authority basis to allow custom totals to be constructed.

House building data are collected at local authority district level, but it is important to treat figures at this level with care. House building is unevenly distributed both geographically and over time and patterns of housing development can produce clusters of new homes which make the figures at a low geographic level volatile and difficult to interpret.

For detailed definitions of all tenures, see definitions of housing terms on Housing Statistics

The district level and county figures are as reported by local authorities and the NHBC. Where a local authority has not submitted a quarterly return to DCLG, no figure has been presented for this local authority (and when relevant its county) for any 12-month period that includes the missing quarter.

England total figures include estimates for missing data returns from independent Approved Inspectors and Local Authorities, so the sum of district values may be slightly less than the England totals.

House building starts - A dwelling is counted as started on the date work begins on the laying of the foundation, including 'slabbing' for houses that require it, but not including site preparation. Thus when foundation work commences on a pair of semi-detached houses two houses are counted as started, and when work begins on a block of flats all the dwellings in that block are counted as started. The starts of houses in building schemes are usually phased over a period of weeks or even, in very large schemes, months.

Tenure – For the purposes of these statistics, the term tenure refers to the nature of the organisation responsible for the development of a new housing start or completion. It does not necessarily describe the terms of occupancy for the dwelling on completion. For example, some housing associations develop homes for sale on the open market. Such homes would be reported in the Housing Association tenure of these statistics, but would ultimately most likely be owned and occupied in the private sector.

Housing association - “Housing associations (HAs)” is used as the generic name for all social landlords not covered by local authorities (see below). In previous editions HAs were referred to as Registered Social Landlords (RSL), and the technical term (private) Registered Provider (pRP) of social housing is also sometimes used. The more all-encompassing description of ‘housing associations’ is now seen as more helpful to users of these statistics.

These data were derived from live table 253a (quarterly figures).

Geographical mobility of those who sat GCSEs in English state schools from 2008 to 2011. Data are linked to the town or city pupils lived in when they sat GCSEs. Compiled using the DfE’s Longitudinal Educational Outcomes.

Data on the educational attainment of young people who sat their GCSEs in English state schools in the 2012 to 2013 school year, from age 11 to age 22, compiled using the Longitudinal Educational Outcomes database from the Department for Education (DfE). Data are linked to the area a student lived in when they sat their GCSEs, including characteristics such as town size and income deprivation levels.