The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for Leicester and compare this with national statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsCar availabilityThis dataset provides Census 2021 estimates on the number of cars or vans available to members of households for England and Wales. The estimates are as at Census Day, 21 March 2021.Definition: The number of cars or vans owned or available for use by household members.Vehicles included:pick-ups, camper vans and motor homesvehicles that are temporarily not working vehicles that have failed their MOTvehicles owned or used by a lodgercompany cars or vans if they're available for private useVehicles not included:motorbikes, trikes, quad bikes or mobility scootersvehicles that have a Statutory Off Road Notification (SORN)vehicles owned or used only by a visitor vehicles that are kept at another address or not easily accessedThe number of cars or vans in an area relates only to households. Cars or vans used by communal establishment residents are not counted.Households with 10 to 20 cars or vans are counted as having only 10.Households with more than 20 cars or vans were treated as invalid and a value imputed.This dataset includes data for Leicester city and England overall.

As of September 2024, around seven in 10 potential UK car buyers highly or moderately valued parking or rear collision warning features when purchasing a car, should cost not be an issue. Blind-spot monitoring was the second most popular choice, with 64 percent of respondents finding it highly or moderately valuable.

Two datasets: 1) Dataset from an experiment run with female Poecilia reticulata to test for the existence of a 'Walk Away' strategy. The spreadsheet contains information on the condition (control vs experimental), the treatment (cooperation vs defection), the diet of the stimulus shoal (bloodworm vs Daphnia) and the proportion of time spent shoaling with an unfamiliar shoal for each focal fish (row label) (Fig. 1). 2) Dataset from an agent-based simulation model run to test for the ability of a 'Walk Away' rule to generate assortment by cooperative phenotype in a population consisting of 90 agents, 45 obligate co-operators and 45 obligate defectors (Figs. 2 and 3). The workbook contains three sheets: a) matrix of agent interactions with a walk away rule imposed; b) matrix of interactions in a nuetral model and c) agent phenotypes and thresholds by agent ID.

Unlocking insights into consumer behavior and retail dynamics, this comprehensive dataset captures the essence of transactions within a retail environment. Featuring ten essential columns, including CustomerID, ProductID, Quantity, Price, TransactionDate, PaymentMethod, StoreLocation, ProductCategory, DiscountApplied(%), and TotalAmount, this dataset encapsulates crucial information for retail analytics. Each entry provides a glimpse into the intricate interactions between customers, products, and sales channels, facilitating the exploration of purchasing patterns, popular products, pricing strategies, and regional preferences.

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By delving into the wealth of information contained within this dataset, analysts can uncover valuable insights to drive strategic decision-making. The TransactionDate column offers a temporal dimension, allowing for the identification of seasonal trends, peak purchasing periods, and the impact of marketing campaigns over time. PaymentMethod data sheds light on evolving consumer payment preferences and the effectiveness of different payment strategies. Moreover, the DiscountApplied(%) column provides insights into consumer responsiveness to promotions and discounts, enabling retailers to optimize their pricing strategies for maximum impact. With such rich and diverse data at their disposal, businesses can refine their marketing efforts, enhance customer experiences, and ultimately, thrive in today's competitive retail landscape.

Columns:

1. CustomerID: Unique identifier for each customer.
2. ProductID: Unique identifier for each product.
3. Quantity: The number of units purchased for a particular product.
4. Price: The unit price of the product.
5. TransactionDate: Date and time when the transaction occurred.
6. PaymentMethod: The method used by the customer to make the payment.
7. StoreLocation: The location where the transaction took place.
8. ProductCategory: Category to which the product belongs.
9. DiscountApplied(%): Percentage of the discount applied to the product.
10. TotalAmount: Total amount paid for the transaction.

According to a December 2024 survey, nearly a quarter of consumers in the United Kingdom would need a battery-electric vehicle to have a range of between 300 and 399 miles in order to consider purchasing it. In contrast, 13 percent of respondents mentioned they would never consider acquiring a BEV.

London is changing; with an expanding service-led economy, increasing wealth, consumption and leisure time for many of its residents and a growing multiplicity of tastes and preferences across a growing population. From November 3rd to December 1st, 4000 Londoners took part in Talk London’s Annual London Survey (ALS) to share their views on what makes London a great place to live, and what aspects of life in the capital could do with some improvement. The London Survey aims to address three key questions: To what extent are Londoners satisfied with their quality of life, and what drives this satisfaction? What do Londoners think are the most important drivers of a successful place to live and work? What does the balance of satisfaction and rank of different aspects of London life mean for experience and enjoyment of the city, and how can this be improved? Technical Details Results are based on interviews with 3861 London residents aged 18+ Interviews were carried out online via the Talk London community between 3rd November and 1st December 2015. Participants were self-selecting, and outreach undertaken via a number of known databases. This achieved a non-representative sample of Londoners. The data was weighted by age, gender and ethnicity to reflect the London population according to ONS data. Robustness was maintained through achieving a minimum quota of responses from each demographic group. This is the second London Survey conducted through Talk London for City Hall.

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Adaptive Driving Equipment Market 2024-2028

The adaptive driving equipment market size is forecast to increase by USD 1.51 billion with a growth at a CAGR of 7.71% between 2024 and 2028. The growth rate of the market depends on several factors such as the rising aging population, the increasing urbanization leading to increased demand for adaptive driving equipment, and the rising awareness about accessibility driving adaptive equipment.

The report includes a comprehensive outlook on the Adaptive Driving Equipment Market, offering forecasts for the industry segmented by Application, which comprises passenger car and commercial vehicle. Additionally, it categorizes Type into wheelchair and scooter lifts, wheelchair securements, hand controls, and swivel seatings, and covers Regions, including North America, Europe, APAC, South America, and Middle East and Africa. The report provides market size, historical data spanning from 2018 to 2022, and future projections, all presented in terms of value in USD million for each of the mentioned segments.

What will be the Size of the Adaptive Driving Equipment Market During the Forecast Period?

Adaptive Driving Equipment Market Forecast 2024-2028

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Adaptive Driving Equipment Market Dynamics

Driver- Rising aging population

As people age, they may experience mobility challenges, making it difficult to drive safely without assistance. The demand for adaptive driving solutions is increasing rapidly among the old age population. Older individuals often value their independence and autonomy. Adaptive driving equipment enables them to continue driving safely, maintaining a sense of self-sufficiency and freedom. Adaptive driving equipment contributes to an improved quality of life for seniors by enabling them to participate in social activities, run errands, and maintain a sense of normalcy, which is crucial for mental and emotional well-being.

Furthermore, age-related conditions, like reduced reaction times, diminished vision, or physical limitations, can impact driving ability. Adaptive driving equipment helps compensate for these challenges, allowing seniors to drive more comfortably. As technology becomes more user-friendly, seniors are increasingly adopting modern solutions. Adaptive driving equipment, incorporating user-friendly interfaces and advanced safety features, aligns with this trend. Therefore, the rising aging population is a key catalyst for the growth of the adaptive driving equipment market, driving innovation and solutions that cater to the mobility challenges associated with aging. Hence, the global adaptive driving equipment market is expected to grow during the forecast period.

Trends- Advancements in assistive technologies in driving adaptive equipment

There are various advancements carried out by the vendors in the global driving adaptive equipment market, such as autonomous driving features, smart Interfaces and connectivity, gesture recognition and voice controls, and sensor technologies, among others. Vendors are increasingly incorporating smart interfaces and connectivity options into adaptive equipment. This allows users to control various aspects of their vehicles using smartphones or other smart devices, improving convenience and accessibility. Advancements in gesture recognition and voice control technologies have made their way into driving adaptive equipment.

Moreover, vendors are also focusing on creating adaptive equipment with highly customizable controls. This allows users to tailor the driving experience to their specific needs and preferences, promoting inclusivity and user satisfaction. Some of the adaptive equipment vendors explore integration with wearable devices, such as smartwatches or specialized control devices. This integration enables users to interact with and control adaptive features more conveniently. Therefore, advancements in assistive technologies in driving adaptive equipment will drive the growth of the global adaptive driving equipment market during the forecast period.

Challenge- High cost of driving adaptive equipment

The cost of adaptive driving equipment can vary widely based on factors such as the type of equipment needed, the extent of vehicle modifications required, and the specific features chosen. Additionally, prices can vary depending on the region, service providers, and individual customization needs. The approximate costs for some of the common types of adaptive driving equipment include hand controls, spinner knobs, pedal extensions, lifts and ramps, and electronic mobility controls, among others.

Moreover, the actual cost can vary based on individual needs, vehicle type, and installation requirements. Also, expenses related to professional installation, consultations, and potential vehicle modifications are considered separately. Therefore, the high cost of driving adaptive equipment is exp

Fundus photography is a viable option for glaucoma population screening. In order to facilitate the development of computer-aided glaucoma detection systems, we publish this annotation dataset that contains manual annotations of glaucoma features for seven public fundus image data sets. All manual annotations are made by a specialised ophthalmologist. For each of the fundus images in the seven fundus datasets, the upper, the bottom, the left and the right boundary coordinates of the optic disc and the cup are stored in a .mat file with the corresponding fundus image name. The seven public fundus image data sets are: CHASEDB (https://blogs.kingston.ac.uk/retinal/chasedb1/), Diaretdb1_v_1_1 (https://www.it.lut.fi/project/imageret/diaretdb1/), DRINSHTI (http://cvit.iiit.ac.in/projects/mip/drishti-gs/mip-dataset2/Home.php), DRIONS-DB (http://www.ia.uned.es/~ejcarmona/DRIONS-DB.html), DRIVE (https://www.isi.uu.nl/Research/Databases/DRIVE/), HRF (https://www5.cs.fau.de/research/data/fundus-images/), and Messidor (http://www.adcis.net/en/Download-Third-Party/Messidor.html). Researchers are encouraged to use this set to train or validate their systems for automatic glaucoma detection. When you use this set, please cite our published paper:

Introducing Our Global Small Business Contact Data Solution

In today’s dynamic business landscape, connecting with small businesses is essential for growth. Our Global Small Business Contact Data provides you with the tools to reach and engage with millions of small business owners and decision-makers worldwide.

What Sets Our Data Apart?

Our data is specifically focused on small businesses, offering you a targeted and efficient way to connect with your ideal customers. With over 41 million verified contacts, including business emails and phone numbers, we prioritise accuracy to ensure your outreach is effective.

Our Data Collection Process

We employ a robust data collection process that combines the power of ten dynamic publication sites with our dedicated Contact Discovery Team. This dual approach guarantees a comprehensive and reliable database of small business contacts.

Applications Across Diverse Industries

Our data is versatile and applicable to a wide range of industries. Whether you’re in finance, technology, or retail, you can leverage our small business contact data to identify new opportunities, expand your customer base, and build strong partnerships.

Seamless Integration

Our small business database seamlessly integrates with our broader data collection framework. This allows you to access additional valuable insights, such as market trends and competitor analysis, to inform your business decisions.

Building Strong Relationships

Connecting with small business owners is about building relationships. Our data helps you identify key decision-makers and reach out to them directly. Whether you’re offering products, services, or partnerships, our data empowers you to connect with the right people at the right time.

Privacy and Security

We are committed to protecting your data and the privacy of our contacts. Our data collection and handling processes adhere to strict privacy regulations, ensuring your peace of mind.

Continuous Improvement

We are constantly enhancing our small business contact data solution to provide you with the most accurate and up-to-date information. Our commitment to quality ensures that you have the best possible data to support your business growth.

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Our small business contact data covers a wide range of countries, including the United States, Canada, the United Kingdom, Germany, France, Australia, Japan, China, India, Brazil, and many more.

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Our data spans across various industries, including finance, technology, healthcare, retail, energy, transportation, hospitality, and more.

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In addition to contact details, our database includes valuable information about business size and revenue, enabling you to target specific segments of the small business market.

Our Global Small Business Contact Data is more than just a list of contacts; it’s a powerful tool to help you achieve your business goals. By providing accurate, comprehensive, and actionable data, we empower you to connect with small businesses, build lasting relationships, and drive growth.

The National Diabetes Audit (NDA) is part of the National Clinical Audit and Patient Outcomes Programme (NCAPOP) which is commissioned by the Healthcare Quality Improvement Partnership (HQIP) and funded by NHS England and the Welsh Government. The NDA is managed by NHS Digital in partnership with Diabetes UK. The NDA measures the effectiveness of diabetes healthcare against NICE Clinical Guidelines and NICE Quality Standards, in England and Wales. The NDA collects and analyses data for use by a range of stakeholders to drive changes and improvements in the quality of services and health outcomes for people with diabetes. This short report details the top-level findings for the 2018-19 audit. The audit collected data during May and June 2019, for the period 01 January 2018 to 31 March 2019. The top-level findings below, along with supporting data at Clinical Commissioning Group (CCG), Local Health Board (LHB), GP practice and specialist diabetes service have been made available to provide data back to services in a timely manner that can help drive improvements in the quality of diabetes care locally. The full report, scheduled for 2020, will contain full key findings, recommendations and results of new analyses into HbA1c check frequencies and blood glucose drug cohorts. We will communicate to users when the date for this report has been finalised. A new method of collecting structured education attendance data was trialled for 2018-19. In addition to extracting education data from GP practice systems, structured education providers could submit data directly via the Clinical Audit Platform (CAP). Around 20 providers submitted, however only a small proportion of records were submitted with the required data. This exercise has shown the potential value of this additional collection and improvements to the process are being developed to improve future collections.

Ofcom's annual reports on the UK’s fixed broadband coverage, mobile and wifi network coverage, digital television, digital radio and internet infrastructure. Please see our terms of use for our licence conditions, and please refer to the Ofcom website to see the pdf 'About this data' documents.

High quality, widespread communications, fixed and mobile, are an engine of our economy and the pulse of our society. They are not nice-to-haves, but essential enablers of our working and social lives. As businesses and consumers drive an ever-increasing demand for communications, the infrastructure that serves them must keep pace with their demands and needs.

One of Ofcom’s roles is to make sure that the UK has the communications infrastructure it requires. This means making services available where people live and work; call connections being clear and robust; and data being down- and up-loaded at speeds that deliver a good experience. Ofcom is also responsible for providing clear, accurate, easy-to-use information. This equips businesses and consumers to make informed decisions about the services that can serve them best.

The Connected Nations Report (previously called the Infrastructure Report) charts the UK’s evolving communications infrastructure, and our progress towards becoming genuinely connected nations.

Where we can, we have made the data underlying the 2018 report available for download. Please see our terms of use for our licence conditions. If you have any questions or feedback on the data we have made available, please contact us at open.data@ofcom.org.uk.
The 2019 Media Nations data can be found on the Ofcom website in an interactive format.

To calculate the catchment areas of each airport we can do a drive-time analysis to see how many people can reach the airport in 30 minutes.Click Analysis button in the right-hand menuClick ToolsSelect Use ProximitySelect Generate Travel AreasYou can also search for 'Generate Travel Areas' in the search bar.Set Input layer to our Airport dataSet Travel Mode to Drive TimeSet cutoffs to 30 Cut off units to MinutesLeave the other variables as the defaultsGive the output a name (for this exercise it will need to be unique to you so add your initials!)Make sure it is being saved in your tidy folder!Click Run.The tool may take a minute or two to run. To view the progress hit the clock icon in the top tool bar.Click the button below to find out more about this analysis tool:

The Digitised Public Rights of Way data layer shows the locations of registered public rights of way in Nottinghamshire. It is derived from the paper sources that comprise the Definitive Map and Statement for Nottinghamshire, a legal document first drawn up in the 1950's, which the County Council has a statutory duty to keep under continuous review. The Definitive Map is conclusive evidence of the public rights shown, without prejudice to the possible existence of higher rights. However, if a way is not registered on the Definitive Map, it does not prove that public rights do not exist. The data is dynamic and legal processes exist so that ways may be extinguished, diverted or added to the map. In addition, the digital data is also being checked to ensure its accuracy, leading to continuous amendments being made. A public right of way is a way over which all members of the public have a right to pass and repass. They are public highways and comprise: Footpaths (a right of way on foot); Bridleways (a right of way on horseback, or to lead a horse, or to drive animals of any description and may also be used by members of the public on pedal cycles); Byways Open to All Traffic (a public carriageway, though mainly used as a footpath or bridleway); Restricted Byways (similar to a Byway Open to All Traffic, but with the public carriageway rights limited to those vehicles which are not mechanically propelled). It must be remembered that the original Definitive Map was drawn on Ordnance Survey 1:25,000 scale base maps. The subsequent working copy maps are drawn on Ordnance Survey 1:10,000 maps. It is in many cases difficult (if not impossible) to give a precise alignment without a good deal of interpretation and expertise. Even if you believe you are in no doubt, you should check the situation with the Definitive Map team. Please also see also the terms of use below.

The Scottish Government (SG) Urban Rural Classification provides a consistent way of defining urban and rural areas across Scotland. The classification aids policy development and the understanding of issues facing urban, rural and remote communities. It is based upon two main criteria: (i) population as defined by National Records of Scotland (NRS), and (ii) accessibility based on drive time analysis to differentiate between accessible and remote areas in Scotland. The classification can be analysed in a two, three, six or eight fold form. The two-fold classification simply distinguishes between urban and rural areas through two categories, urban and rural, while the three-fold classification splits the rural category between accessible and remote. Most commonly used is the 6-fold classification which distinguishes between urban, rural, and remote areas through six categories. The 8-fold classification further distinguishes between remote and very remote regions. The Classification is normally updated on a biennial basis, with the current dataset reflective of Census Day 2022. Data for previous versions are available for download in ESRI Shapefile format.

Abstract copyright UK Data Service and data collection copyright owner.The Citizenship Survey (known in the field as the Communities Study) ran from 2001 to 2010-2011. It began as the 'Home Office Citizenship Survey' (HOCS) before the responsibility moved to the new Communities and Local Government department (DCLG) in May 2006. The survey provided an evidence base for the work of DCLG, principally on the issues of community cohesion, civic engagement, race and faith, and volunteering. The survey was used extensively for developing policy and for performance measurement. It was also used more widely, by other government departments and external stakeholders to help inform their work around the issues covered in the survey. The survey was conducted on a biennial basis from 2001-2007. It moved to a continuous design in 2007 which means that data became available on a quarterly basis from April of that year. Quarter one data were collected between April and June; quarter two between July and September; quarter three between October and December and quarter four between January and March. Once collection for the four quarters was completed, a full aggregated dataset was made available, and the larger sample size allowed more detailed analysis. In January 2011, the DCLG announced that the Citizenship Survey was to close. As part of the drive to deliver cost savings across government and to reduce the fiscal deficit, research budgets were closely scrutinised to identify where savings can be made. For this reason, and the belief that priority data from this survey could either be dropped; collected less frequently; or collected via other means, the survey was cancelled. Fieldwork concluded on 31 March 2011, followed by publication of reports in the months after analysis of that data. Further information about the survey, including links to publications, can be found on the National Archives webarchive page for the Citizenship Survey. The Consultation outcome: the future of the citizenship survey statement can be viewed on the gov.uk website. The Community Life Survey, (held under GN 33475), which began in 2012-2013 and is conducted by the Cabinet Office, incorporates a small number of priority measures from the Citizenship Survey, in order that trends in these issues can continue to be tracked over time. For these measures the Community Life Survey findings are comparable to the Citizenship Survey findings. UK Data Archive holdings: End User Licence and Secure Access The Archive holds standard End User Licence (EUL) versions of the complete Citizenship Survey series from 2001-2011, held under SNs 4754, 5087, 5367, 5739, 6388, 6733 and 7111, and Secure Access versions of the 2005, 2007-2008, 2008-2009 and 2009-2010 and 2010-2011 waves (all held under SN 7403). The Secure Access datasets include extra variables that are not available in the standard EUL versions. They cover: more detailed and extensive household and demographic information; more detailed geographies, including Police Force Area, Local Authority Districts, Wards, Middle Layer Super Output Areas (MSOA) and Lower Layer Super Output Areas (LSOA); more detailed responses to questions covering violent extremism, immigration, and religion; and more detailed administrative variables. Prospective users of the Secure Access version of the Citizenship Survey will need to agree to rigorous Terms and Conditions, including applying for ESRC Accredited Researcher Status and attending a training session, in order to obtain permission to use that version Therefore, users are encouraged to download and inspect the EUL versions of the data prior to ordering the Secure Access versions. The Citizenship Survey, 2008-2009 dataset includes a total sample of 14,917 people aged 16 and over, resident in England and Wales. This comprised a core sample of 9,335 people and a minority ethnic boost of 5,582.