The National Population Database (NPD) is a point-based Geographical Information System (GIS) dataset that combines locational information from providers like the Ordnance Survey with population information about those locations, mainly sourced from Government statistics. The points (and sometimes polygons) represent individual buildings, so the NPD allows detailed local analysis for anywhere in Great Britain. The Health & Safety Laboratory (HSL) working with Staffordshire University originally created the NPD in 2004 to help its parent organisation, the Health and Safety Executive (HSE), assess the risks to society of major hazard sites e.g. oil refineries, chemical works and gas holders. Of particular interest to HSE were 'sensitive' populations e.g. schools and hospitals where the people at those locations may be more vulnerable to harm and potentially harder to evacuate in an emergency. The data is split into 5 themes: residential, sensitive populations, transport, workplaces and leisure. More information about the NPD can be found here: https://www.hsl.gov.uk/what-we-do/better-decisions/geoanalytics/national-population-database The NPD was created using various datasets available within Government as part of the Public Sector Mapping Agreement (PSMA) and contains other intellectual property so is only available under license and for a fee. Please contact the HSL GIS Team if you would like to discuss gaining access to the sample or full dataset.

The percentage of respondents to the Adult Social Care Survey (service users) who responded to the question "Thinking about how much contact you've had with people you like, which of the following statements best describes your social situation?" with the answer "I have as much social contact as I want with people I like".

This measure applies to those people in receipt, at the point that data are extracted, of long-term support services funded or managed by social services following a full assessment of need.

Rationale There is clear link between loneliness and poor mental and physical health. A key element of the Government's vision for social care is to tackle loneliness and social isolation, supporting people to remain connected to their communities and to develop and maintain connections to their friends and family. This measure will draw on self-reported levels of social contact as an indicator of social isolation for both users of social care and carers.

Definition of numerator The number of respondents to the Adult Social Care Survey (service users) who responded to the question "Thinking about how much contact you've had with people you like, which of the following statements best describes your social situation?" with the answer "I have as much social contact as I want with people I like".

Definition of denominator The number of people responding to the question "Thinking about how much contact you've had with people that you like" in the Adult Social Care Survey (service users).

Caveats

Note: Isles of Scilly and City of London are exempt from the survey as the number of service users within their area who met the survey eligibility criteria are generally too small to guarantee statistically robust results. However, City of London has submitted data in some years, including in the 2021 to 2022 dataset, when it had sufficient numbers for statistically robust reporting.

Lewisham Council did not submit data for 2021 to 2022 due to a change in staffing and lack of awareness of the ASCS. Hackney Council was unable to submit ASCS data for 2021 to 2022 due to a serious cyber attack. No data was available for Hackney for 2022 to 2023. To maintain comparability with previous years, NHS Digital used 2019 to 2020 data from Hackney in the England and regional aggregated totals. Further details are available in the Adult Social Care Activity and Finance data quality report.

Covid-19 has impacted adult social care data collections, processing, and quality assurance since March 2020. The 2020 to 2021 Adult Social Care survey was voluntary, and only 18 councils participated. Therefore, this indicator was not updated for that year in the Profile.

Kent and Wokingham councils did not conduct a survey in 2019 to 2020. Trafford Council's 2019 to 2020 data was incomplete and only reflects service users with learning disabilities. As the responses are not from a fully representative subset, caution is advised when reviewing this data. Several other councils also had sample sizes under 100 for this question in 2019 to 2020, and these are flagged with a 'value note' in the tool.

Further data quality details are provided in the annual survey reports: Personal Social Services Adult Social Care Survey.

Data are unavailable for the Isles of Scilly for all years and for the City of London in 2019 to 2020, 2017 to 2018, 2015 to 2016, 2013 to 2014, 2012 to 2013, and 2010 to 2011. Slough Council did not conduct the survey in 2012 to 2013, and Richmond Council did not conduct it in 2010 to 2011. The age 65+ version of this indicator is only displayed from 2014 to 2015 onwards.

Percentages are rounded to one decimal place and numbers to the nearest five. Different base values (sample sizes) for each group mean some figures may be more uncertain than others. Group characteristics, such as age, may also affect figures. For example, the age profile of the White ethnic group may differ from others, impacting outcome values in ethnicity breakdowns.

There were several changes to national adult social care data collections in the 2014 to 2015 reporting year. The main change was replacing the Referrals, Assessments and Packages of Care (RAP) return with the Short and Long Term services (SALT) collection, altering the survey's target population. Key changes include:

Exclusion of users whose only services are equipment, professional support, or short-term residential care.
Inclusion of ‘Full cost clients’ who pay fully for services but are assessed and supported by the local authority.

These changes may affect comparability with data from previous years and between local authorities, though they may also improve consistency across councils.

How much time do people spend on social media?

              As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in
              the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively.
              People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general.
              During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

This large dataset contains job descriptions and rankings among various criteria such as work-life balance, income, culture, etc. The data covers the various industries in the UK. Great dataset for multidimensional sentiment analysis.

This data set complements the Glassdoor dataset located [here].(https://www.kaggle.com/datasets/davidgauthier/glassdoor-job-reviews-2)

Please cite as: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=FQstpaoAAAAJ&citation_for_view=FQstpaoAAAAJ:UebtZRa9Y70C

Glassdoor Reviews

Glassdoor produces reports based upon the data collected from its users, on topics including work–life balance, CEO pay ratios, lists of the best office places and cultures, and the accuracy of corporate job searching maxims. Data from Glassdoor has also been used by outside sources to produce estimates on the effects of salary trends and changes on corporate revenues. Glassdoor also puts the conclusions of its research of other companies towards its own company policies. In 2015, Tom Lakin produced the first study of Glassdoor in the United Kingdom, concluding that Glassdoor is regarded by users as a more trustworthy source of information than career guides or official company documents.

Features

The columns correspond to the date of the review, the job name, the job location, the status of the reviewers, and the reviews. Reviews are divided in s sub-categories Career Opportunities, Comp & Benefits, Culture & Values, Senior Management, and Work/Life Balance. In addition, employees can add recommendations on the firm, the CEO, and the outlook.

Other information

Ranking for the recommendation of the firm, CEO approval, and outlook are allocated categories v, r, x, and o, with the following meanings: v - Positive, r - Mild, x - Negative, o - No opinion

Some examples of the textual data entries

MCDONALD-S I don't like working here,don't work here Headline: I don't like working here,don't work here Pros: Some people are nice,some free food,some of the managers are nice about 95% of the time Cons: 95% of people are mean to employees/customers,its not a clean place,people barely clean their hands of what i see,managers are mean,i got a stress rash because of this i can't get rid of it,they don't give me a little raise even though i do alot of crap there for them Rating: 1.0

KPMG Quit working people to death Headline: Quit working people to death Pros: Lots of PTO, Good company training Cons: long hours, clear disconnect between management and staff, as corporate as it gets Rating: 2.0

PRIMARK Sales assistant Headline: Sales assistant Pros: Lovely staff, managers are also very nice Cons: Hardwork, often rude customers, underpaid for u18 Rating: 3.0

J-P-MORGAN Life in JPM, Bangalore Headline: Life in JPM, Bangalore Pros: Good place to start, lots of opportunity. Cons: Be ready to put in a lot of efforts not a place to chill out. Rating: 4.0

VODAFONE Good to be here Headline: Good to be here Pros: Fast moving with technology. Leading Cons: There are areas you may want to avoid Rating: 5.0

The Access Network Map of England is a national composite dataset of Access layers, showing analysis of extent of Access provision for each Lower Super Output Area (LSOA), as a percentage or area coverage of access in England. The ‘Access Network Map’ was developed by Natural England to inform its work to improve opportunities for people to enjoy the natural environment. This map shows, across England, the relative abundance of accessible land in relation to where people live. Due to issues explained below, the map does not, and cannot, provide a definitive statement of where intervention is necessary. Rather, it should be used to identify areas of interest which require further exploration. Natural England believes that places where people can enjoy the natural environment should be improved and created where they are most wanted. Access Network Maps help support this work by providing means to assess the amount of accessible land available in relation to where people live. They combine all the available good quality data on access provision into a single dataset and relate this to population. This provides a common foundation for regional and national teams to use when targeting resources to improve public access to greenspace, or projects that rely on this resource. The Access Network Maps are compiled from the datasets available to Natural England which contain robust, nationally consistent data on land and routes that are normally available to the public and are free of charge. Datasets contained in the aggregated data:•
Agri-environment scheme permissive access (routes and open access)•
CROW access land (including registered common land and Section 16)•
Country Parks•
Cycleways (Sustrans Routes) including Local/Regional/National and Link Routes•
Doorstep Greens•
Local Nature Reserves•
Millennium Greens•
National Nature Reserves (accessible sites only)•
National Trails•
Public Rights of Way•
Forestry Commission ‘Woods for People’ data•
Village Greens – point data only Due to the quantity and complexity of data used, it is not possible to display clearly on a single map the precise boundary of accessible land for all areas. We therefore selected a unit which would be clearly visible at a variety of scales and calculated the total area (in hectares) of accessible land in each. The units we selected are ‘Lower Super Output Areas’ (LSOAs), which represent where approximately 1,500 people live based on postcode. To calculate the total area of accessible land for each we gave the linear routes a notional width of 3 metres so they could be measured in hectares. We then combined together all the datasets and calculated the total hectares of accessible land in each LSOA. For further information about this data see the following links:Access Network Mapping GuidanceAccess Network Mapping Metadata Full metadata can be viewed on data.gov.uk.

As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.

Context

Do you know what people love to watch on YouTube in UK? Here is the list of top 100 channels based on their number of subscribers

Content

This dataset contains top 100 ranking of YouTube channels watched in United Kingdom along with their username, category, subscriber count, total upload, and other stats

Inspiration

Digital marketing, Market analysis

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

This dataset is a subset of the Prescribing Information System (PIS) data for use with the BHDP project.

The information is supplied by Practitioner & Counter Fraud Services Division (P&CFS) who is responsible for the processing and pricing of all prescriptions dispensed in Scotland. These data are augmented with information on prescriptions written in Scotland that were dispensed elsewhere in the United Kingdom. GP’s write the vast majority of these prescriptions, with the remainder written by other authorised prescribers such as nurses and dentists. Also included in the dataset are prescriptions written in hospitals that are dispensed in the community. Note that prescriptions dispensed within hospitals are not included. Data includes CHI number, prescriber and dispenser details for community prescribing, costs and drug information. Data on practices (e.g. list size), organisational structures (e.g. practices within Community Health Partnerships (CHPs) and NHS Boards), prescribable items (e.g. manufacturer, formulation code, strength) are also included. Around 100 million data items are loaded per annum.

During a 2024 survey, 77 percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just 23 percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis.

              Social media: trust and consumption

              Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than 35 percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than 50 percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media.

              What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis.
              Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers.
              Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

Out of Area Mental Health Placements

Data from NHS & Independent Providers in England

By data.world's Admin [source]

About this dataset

This dataset provides a comprehensive look into the Out of Area Placements (OAPs) happening in the mental health services in England. It gives insight on placements from both NHS and independent providers, giving an overall picture of how these placements are happening across the country.

By taking a closer look at this report we can gain understanding into what is going on with OAPs around us – like which questions are being asked, breakdowns of how it’s divided and number to back it up. With this data we can better understand issues that affect our community and do our part to help support those in need

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides information on out of area placements in mental health services in England from both NHS and independent providers. The dataset contains data related to the number placements, as well as breakdowns by region and provider. With this data you can explore the trends for out of area placements in your region and compare those trends with national level figures.

This guide will show you how to get started exploring this dataset.

Step 1: Understand The Data Set Structure

The first step for getting started is to get a good understanding of the structure of the dataset itself in order to better understand what types of questions we can ask our data with. This dataset has several columns which have been listed below:

• Publication Type : This column provides information on what type of report is being referenced such as statistical bulletin or key facts & figures etc

• Publication Period: This column represents a period within a year moment which periods are expressed by either month, quarter or financial year etc..

• Publication Date: This column informs us when the publication was made available online expressed as a date format e.g 2018-04-02)

• Question : Here we will find measurements such as people waiting an average or median length times such that they answer certain question asked by officials.

• Breakdown1, BreakDown1Code, ‘Breakdown1Description’ : These columns provide extra context into specific highlights from results in further detail eg Breakdowns include areas like Age Group ,Nationality (for immigration statistics) gender for population statistics etc... where code values may appear something like “OAP_AGE_All” and descriptions appear like “Waiting Times All Ages respectively .

• BreakDown2, BreakDown2Code, 'Breakdown2Description':These are data attributes similar top BreakDown 1 but at even more granular level eg Doctor Specialty/Department, Treatment Type, Indicators (for regional/local analysis), Countries ..etc . It's important not note here that breakdown 2 has deeper break down against Breakdown 1 depending further detail asked while investigating deeper under specified parameters /results .Eg You might want drill down ages into age groups 0–4, 5–14 ,15-29....etc excluding 65+ corresponding breakdown codes might be OAP_AGE_0

Research Ideas

• Creating insight into regional differences in mental health out of area placements in order to identify if more funding is needed and implement programs to address the predisposing risk factors for those regions with higher out of area placement rates.
• Comparing the amount of expenditure allocated on out of area placements between different areas and provinces, so that extra funding may be given to areas which need it more.
• Examining the correlation between changes in funding or policy and its effects on out of area placements at both a national and local level, in order to assess whether certain policies are successful or not at curbing them such as introducing preventative measures before placement outside an individual's region is necessary

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a...

https://i2.wp.com/www.mon-livret.fr/wp-content/uploads/2021/10/crypto-Metaverse-696x392.png?resize=696%2C392&ssl=1" alt="">

Context

• The metaverse, a living and breathing space that blends physical and digital, is quickly evolving from a science fiction dream into a reality with endless possibilities. A world where people can interact virtually, create and exchange digital assets for real-world value, own digital land, engage with digitized real-world products and services, and much more.

• Major tech giants are beginning to recognize the viability and potential of metaverses, following Facebook’s groundbreaking Meta rebrand announcement. In addition to tech companies, entertainment brands like Disney have also announced plans to take the leap into virtual reality.

• While the media hype is deafening, your average netizen isn’t fully aware of what a metaverse is, how it operates and, most importantly—what benefits and opportunities it can offer them as a user.

https://cdn.images.express.co.uk/img/dynamic/22/590x/Metaverse-tokens-cryptocurrency-explained-ethereum-killers-new-coins-digital-currency-meta-news-1518777.jpg?r=1638256864800" alt="">

What Is The Metaverse?

• In its digital iteration, a metaverse is a virtual world based on blockchain technology. This all-encompassing space allows users to work and play in a virtual reflection of real-life and fantasy scenarios, an online reality, ranging from sci-fi and dragons to more practical and familiar settings like shopping centers, offices, and even homes.

• Users can access metaverses via computer, handheld device, or complete immersion with a VR headset. Those entering the metaverse get to experience living in a digital realm, where they will be able to work, play, shop, exercise, and socialize. Users will be able to create their own avatars based on face recognition, set up their own businesses of any kind, buy real estate, create in-world content and asset,s and attend concerts from real-world superstars—all in one virtual environment,

• With that said, a metaverse is a virtual world with a virtual economy. In most cases, it is an online reality powered by decentralized finance (DeFi), where users exchange value and assets via cryptocurrencies and Non-Fungible Tokens.

What Are Metaverse Tokens?

• Metaverse tokens are a unit of virtual currency used to make digital transactions within the metaverse. Since metaverses are built on the blockchain, transactions on underlying networks are near-instant. Blockchains are designed to ensure trust and security, making the metaverse the perfect environment for an economy free of corruption and financial fraud.

• Holders of metaverse tokens can access multiple services and applications inside the virtual space. Some tokens give special in-game abilities. Other tokens represent unique items, like clothing for virtual avatars or membership for a community. If you’ve played MMO games like World of Warcraft, the concept of in-game items and currencies are very familiar. However, unlike your traditional virtual world games, metaverse tokens have value inside and outside the virtual worlds. Metaverse tokens in the form of cryptocurrency can be exchanged for fiat currencies. Or if they’re an NFT, they can be used to authenticate ownership to tethered real-world assets like collectibles, works or art, or even cups of coffee.

• Some examples of metaverse tokens include SAND of the immensely popular Sandbox metaverse. In The Sandbox, users can create a virtual world driven by NFTs. Another token is MANA of the Decentraland project, where users can use MANA to purchase plots of digital real estate called “LAND”. It is even possible to monetize the plots of LAND purchased by renting them to other users for fixed fees. The ENJ token of the Enjin metaverse is the native asset of an ecosystem with the world’s largest game/app NFT networks.

Dataset Information

• The dataset brings 198 metaverse cryptos. Pls refer to the file Metaverse coins.csv to find the list of metaverse crypto coins.

• The dataset will be updated on a weekly basis with more and more additional metaverse tokens, Stay tuned ⏳