Visit Britain publish data relating to international visitors to the UK. They produce the data in two formats - individual spreadsheets for each region that are updated annually, and a single spreadsheet for all regions, containing less detail but updated quarterly. Data shows London totals for nights, visits, and spend. Data broken down by age, purpose, duration, mode and country. This data is also available from Visit Britain website, including the latest quarterly data for other regions. All data taken from the International Passenger Survey (IPS). Some additional data on domestic tourism can be found on the Visit Britain website, and Visit England both overnight tourism and Day visits pages. Data on accomodation occupancy levels is also available from Visit England. An overview of all tourism data for London can be found in this GLAE report 'Tourism in London' Further information can be found on the London and Partners website. Comparisons of international tourist arrivals with other world cities are produced by Euromonitor and in Mastercard's Global Destination Cities Index of 2012, 2013, 2014, and 2015. This dataset is included in the Greater London Authority's Night Time Observatory. Click here to find out more.

This Dataset shows the Alexa Top 100 International Websites, and provides metrics on the volume of traffic that these sites were able to handle. The Alexa top 100 lists the 100 most visited websites in the world and measures various statistical information. I have looked up the Headquarters, either through alexa, or a Whois Lookup to get street address with i was then able to geocode. I was only able to successfully geocode 85 of the top 100 sites throughout the world. Source of Data was Alexa.com, Source URL: http://www.alexa.com/site/ds/top_sites?ts_mode=global&lang=none Data was from October 12, 2007. Alexa is updated daily so to get more up to date information visit their site directly. they don't have maps though.

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

Jamaica number dataset makes your telemarketing more beneficial. Thus, this Jamaica number dataset has correct and up-to-date mobile numbers for direct marketing. As of 2024, there are about 3.27 Million mobile phone connections in Jamaica. This number is a bit higher than the total population, which is around 2.83 Million. Our List To Data website can assist in getting speedy replies from new clients for publicity. Besides, the Jamaica number dataset is effective for SMS marketing as well. As well as you have multiple chances to earn huge from other countries. So, using this contact number library is a perfect choice for reaching people in specific places. By using our library, you can enhance your marketing and find new B2C clients easily. Jamaica phone data is a great way to help your business grow. Also, this Jamaica phone data provides the most real and active phone numbers so you can easily reach people in Jamaica. Everybody can select who they want to contact based on their location, what their company does, or how big their company is. Further, the Jamaica phone data is very authentic and useful for finding new customers. At the same time, the sellers can deliver sales promotions and many offers to the consumers. Also, they can connect with the largest group of customers quickly in a selected area. List To Data includes contact leads for both businesses and individuals. Jamaica phone number list will make your business more profitable. Most importantly, a Jamaica phone number list plays a vital role in marketing and business, so take it now. Just visit our List To Data website today to get the most recent phone numbers for any business. With 95% precision, this contact book offers you contact numbers for many people who might want your services. So, the Jamaica phone number list is a great tool for reaching new customers through phone calls. In fact, you can pick from other packages on our website that fit your needs and budget. If your business is big or small, our mobile number data will help you in your entire journey. Ultimately, our team supplies this correct contact number cautiously as per your needs.

Likes and image data from the community art website Behance. This is a small, anonymized, version of a larger proprietary dataset.

Metadata includes

• appreciates (likes)

• timestamps

• extracted image features

Basic Statistics:

• Users: 63,497

• Items: 178,788

• Appreciates (likes): 1,000,000

Finland number dataset makes your SNS marketing more profitable. Thus, this Finland number dataset has correct and up-to-date mobile numbers for direct marketing. As of 2024, there are about 9.21 Million mobile phone connections in Finland. This number is a bit higher than the total population, which is around 5.55 Million. This List To Data can assist in getting speedy replies from new clients for advertising. Besides, the Finland number dataset is effective for SMS marketing as well. In addition, you have multiple chances to earn huge from other countries. Thus, using this contact number library is an ideal selection for reaching people in specific areas. By using this phone book, you can enhance your marketing and find new B2C clients easily. Finland phone data is a wonderful way to help your business grow. Also, this Finland phone data gives the most real and active phone numbers so you can easily reach people in Finland. Anyone can decide who they like to contact based on their location, what their company does, or how big their company is. Further, the Finland phone data is very faithful and useful for finding new customers. In other words, the sellers can give sales promotions and many offers to the consumers. Hence, they can connect with the largest group of customers quickly in a fixed area. Through the List To Data, both businesses and individuals can earn a better rerun on investment [ROI]. Finland phone number list will make your business more profitable. Even, it plays a vital role in marketing and business, so take the Finland phone number list now. So, visit our List To Data website today to obtain the most recent mobile numbers for your business. This phone book offers you 95% accurate contact numbers for many people who might want your services. Also, the Finland phone number list is a great tool for reaching new customers through phone calls. Moreover, you can pick from different packages on this website that fit your needs and budget. If buy it at a reasonable price, our mobile database will help you in your entire journey. Yet, our team supplies the correct contact number cautiously as per your needs.

First Impressions Dataset

The dataset contains 20,000 images of people. For each person, a first impression of them was created. The first impression is a text consisting of several sentences.

  💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on our website to buy the dataset






  Content

The dataset includes a folder with images of 20,000 people. The .csv file consists of columns:

image_id - the… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/first-impressions-dataset.

The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

Dataset Card for StereoSet

  Dataset Summary

StereoSet is a dataset that measures stereotype bias in language models. StereoSet consists of 17,000 sentences that measures model preferences across gender, race, religion, and profession.

  Supported Tasks and Leaderboards

multiple-choice question answering

  Languages

English (en)

  Dataset Structure





  Data Instances

intersentence

{'bias_type': 'race', 'context': 'Many people live in… See the full description on the dataset page: https://huggingface.co/datasets/McGill-NLP/stereoset.

Quarterly estimates of overseas residents’ visits and spending. Also includes data on nights, purpose, region of UK visited and mode of travel. Breakdowns by nationality and area of residence are covered. This dataset is published quarterly. The versions published for Quarters 1 (Jan to Mar), 2 (Apr to June) and 3 (July to Sept) are on a separate webpage under the name "Estimates of overseas residents' visits and spending".

This dataset contains the ground truth data used to evaluate the musical pitch, tempo and key estimation algorithms developed during the AudioCommons H2020 EU project and which are part of the Audio Commons Audio Extractor tool. It also includes ground truth information for the single-eventness audio descriptor also developed for the same tool.

This ground truth data has been used to generate the following documents:

• Deliverable D4.4: Evaluation report on the first prototype tool for the automatic semantic description of music samples
• Deliverable D4.10: Evaluation report on the second prototype tool for the automatic semantic description of music samples
• Deliverable D4.12: Release of tool for the automatic semantic description of music samples

All these documents are available in the materials section of the AudioCommons website.

All ground truth data in this repository is provided in the form of CSV files. Each CSV file corresponds to one of the individual datasets used in one or more evaluation tasks of the aforementioned deliverables. This repository does not include the audio files of each individual dataset, but includes references to the audio files. The following paragraphs describe the structure of the CSV files and give some notes about how to obtain the audio files in case these would be needed.

Structure of the CSV files

All CSV files in this repository (with the sole exception of SINGLE EVENT - Ground Truth.csv) feature the following 5 columns:

1. Audio reference: reference to the corresponding audio file. This will either be a string withe the filename, or the Freesound ID (for one dataset based on Freesound content). See below for details about how to obtain those files.
2. Audio reference type: will be one of Filename or Freesound ID, and specifies how the previous column should be interpreted.
3. Key annotation: tonality information as a string with the form "RootNote minor/major". Audio files with no ground truth annotation for tonality are left blank. Ground truth annotations are parsed from the original data source as described in the text of deliverables D4.4 and D4.10.
4. Tempo annotation: tempo information as an integer representing beats per minute. Audio files with no ground truth annotation for tempo are left blank. Ground truth annotations are parsed from the original data source as described in the text of deliverables D4.4 and D4.10. Note that integer values are used here because we only have tempo annotations for music loops which typically only feature integer tempo values.
5. Pitch annotation: pitch information as an integer representing the MIDI note number corresponding to annotated pitch's frequency. Audio files with no ground truth pitch for tempo are left blank. Ground truth annotations are parsed from the original data source as described in the text of deliverables D4.4 and D4.10.

The remaining CSV file, SINGLE EVENT - Ground Truth.csv, has only the following 2 columns:

• Freesound ID: sound ID used in Freesound to identify the audio clip.
• Single Event: boolean indicating whether the corresponding sound is considered to be a single event or not. Single event annotations were collected by the authors of the deliverables as described in deliverable D4.10.

How to get the audio data

In this section we provide some notes about how to obtain the audio files corresponding to the ground truth annotations provided here. Note that due to licensing restrictions we are not allowed to re-distribute the audio data corresponding to most of these ground truth annotations.

• Apple Loops (APPL): This dataset includes some of the music loops included in Apple's music software such as Logic or GarageBand. Access to these loops requires owning a license for the software. Detailed instructions about how to set up this dataset are provided here.
• Carlos Vaquero Instruments Dataset (CVAQ): This dataset includes single instrument recordings carried out by Carlos Vaquero as part of this master thesis. Sounds are available as Freesound packs and can be downloaded at this page: https://freesound.org/people/Carlos_Vaquero/packs
• Freesound Loops 4k (FSL4): This dataset set includes a selection of music loops taken from Freesound. Detailed instructions about how to set up this dataset are provided here.
• Giant Steps Key Dataset (GSKY): This dataset includes a selection of previews from Beatport annotated by key. Audio and original annotations available here.
• Good-sounds Dataset (GSND): This dataset contains monophonic recordings of instrument samples. Full description, original annotations and audio are available here.
• University of IOWA Musical Instrument Samples (IOWA): This dataset was created by the Electronic Music Studios of the University of IOWA and contains recordings of instrument samples. The dataset is available upon request by visiting this website.
• Mixcraft Loops (MIXL): This dataset includes some of the music loops included in Acoustica's Mixcraft music software. Access to these loops requires owning a license for the software. Detailed instructions about how to set up this dataset are provided here.
• NSynth Dataset Test and Validation sets (NSYT and NSYV): NSynth is a large-scale and high-quality dataset of annotated musical notes built with synthesized sounds by Google's Magenta team. Full dataset description including original annotations and audio files is available here.
• Philarmonia Orchestra Sound Samples Dataset (PHIL): This includes thousands of free, downloadable sound samples specially recorded by Philharmonia Orchestra players. Audio files are freely downloadable from the philarmonia orchestra website.
• Freesound Single Events Dataset (SINGLE EVENT): This includes a selection of Freesound audio clips representing audio signals containing either a single audio event or multiple ones. Original audio files can be retrieved by downloading individual audio clips from Freesound using the ID identifier provided in the CSV file. A similar procedure to that described here could be followed.

Data on the impact of the visitor economy on Calderdale's economy and employment. Also the number of visitors by number of people and number of days. All data provided by Global Tourism Solutions (UK) Ltd : STEAM reports and Visit Calderdale. For more information on the data please contact tourism@calderdale.gov.uk. For more information about the visitor economy in Calderdale please go to: Tourism and travel (Calderdale Council website). Visit Calderdale. For data prior to 2022 please go to Calderdale tourism - sector breakdown of trip expenditure. Calderdale tourism - business turnover derived from tourism and related expenditure.

Context

Data Set Information:

The dataset consists of feature vectors belonging to 12,330 sessions. The dataset was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.

Content

The dataset consists of 10 numerical and 8 categorical attributes. The 'Revenue' attribute can be used as the class label.

"Administrative", "Administrative Duration", "Informational", "Informational Duration", "Product Related" and "Product Related Duration" represent the number of different types of pages visited by the visitor in that session and total time spent in each of these page categories. The values of these features are derived from the URL information of the pages visited by the user and updated in real time when a user takes an action, e.g. moving from one page to another. The "Bounce Rate", "Exit Rate" and "Page Value" features represent the metrics measured by "Google Analytics" for each page in the e-commerce site. The value of "Bounce Rate" feature for a web page refers to the percentage of visitors who enter the site from that page and then leave ("bounce") without triggering any other requests to the analytics server during that session. The value of "Exit Rate" feature for a specific web page is calculated as for all pageviews to the page, the percentage that were the last in the session. The "Page Value" feature represents the average value for a web page that a user visited before completing an e-commerce transaction. The "Special Day" feature indicates the closeness of the site visiting time to a specific special day (e.g. Mother’s Day, Valentine's Day) in which the sessions are more likely to be finalized with transaction. The value of this attribute is determined by considering the dynamics of e-commerce such as the duration between the order date and delivery date. For example, for Valentina’s day, this value takes a nonzero value between February 2 and February 12, zero before and after this date unless it is close to another special day, and its maximum value of 1 on February 8. The dataset also includes operating system, browser, region, traffic type, visitor type as returning or new visitor, a Boolean value indicating whether the date of the visit is weekend, and month of the year.

Acknowledgements

Sakar, C.O., Polat, S.O., Katircioglu, M. et al. Neural Comput & Applic (2018).

Inspiration

Education is the most powerful weapon which you can use to change the world. 😃

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

🇬🇧 United Kingdom English Introduction The GiGL Spaces to Visit dataset provides locations and boundaries for open space sites in Greater London that are available to the public as destinations for leisure, activities and community engagement. It includes green corridors that provide opportunities for walking and cycling. The dataset has been created by Greenspace Information for Greater London CIC (GiGL). As London’s Environmental Records Centre, GiGL mobilises, curates and shares data that underpin our knowledge of London’s natural environment. We provide impartial evidence to support informed discussion and decision making in policy and practice. GiGL maps under licence from the Greater London Authority. Description This dataset is a sub-set of the GiGL Open Space dataset, the most comprehensive dataset available of open spaces in London. Sites are selected for inclusion in Spaces to Visit based on their public accessibility and likelihood that people would be interested in visiting. The dataset is a mapped Geographic Information System (GIS) polygon dataset where one polygon (or multi-polygon) represents one space. As well as site boundaries, the dataset includes information about a site’s name, size and type (e.g. park, playing field etc.). GiGL developed the Spaces to Visit dataset to support anyone who is interested in London’s open spaces - including community groups, web and app developers, policy makers and researchers - with an open licence data source. More detailed and extensive data are available under GiGL data use licences for GIGL partners, researchers and students. Information services are also available for ecological consultants, biological recorders and community volunteers – please see www.gigl.org.uk for more information. Please note that access and opening times are subject to change (particularly at the current time) so if you are planning to visit a site check on the local authority or site website that it is open. The dataset is updated on a quarterly basis. If you have questions about this dataset please contact GiGL’s GIS and Data Officer. Data sources The boundaries and information in this dataset, are a combination of data collected during the London Survey Method habitat and open space survey programme (1986 – 2008) and information provided to GiGL from other sources since. These sources include London borough surveys, land use datasets, volunteer surveys, feedback from the public, park friends’ groups, and updates made as part of GiGL’s on-going data validation and verification process. Due to data availability, some areas are more up-to-date than others. We are continually working on updating and improving this dataset. If you have any additional information or corrections for sites included in the Spaces to Visit dataset please contact GiGL’s GIS and Data Officer. NOTE: The dataset contains OS data © Crown copyright and database rights 2025. The site boundaries are based on Ordnance Survey mapping, and the data are published under Ordnance Survey's 'presumption to publish'. When using these data please acknowledge GiGL and Ordnance Survey as the source of the information using the following citation: ‘Dataset created by Greenspace Information for Greater London CIC (GiGL), 2025 – Contains Ordnance Survey and public sector information licensed under the Open Government Licence v3.0 ’

London Borough level tourism trip estimates (thousands). The ‘top-down’ nature of the Local Area Tourism Impact (LATI) model (starting with London data) means it is best suited to disaggregate expenditure. However, tourism trips were also disaggregated for comparative purposes using the estimated proportions of spending by overseas, domestic and day visitors in the boroughs. Since the trip estimates are derived from data on trips to London they do not account for trips to different boroughs by visitors whilst in London. Indicative borough level day visitor/tourist estimates for 2007 were derived from the LDA’s own experimental London level day visitor estimates. As such the borough level day visitor estimates should be treated with caution and the 2007 day visitor estimates are not comparable with those from previous years. They are intended only to give a best estimate of the scale of day visitor tourism in each borough from the currently available data. Further tourism data for UK regions covering trends in visits, nights, and spend to London by visitors from overseas is available on the Visit Britain website. Analyse data by age, purpose, duration, and quarter. This dataset is no longer updated.

People Counts This data set is sourced from Dundee City Council’s Public Space Camera Surveillance System. It shows a count of people in 8 specified areas across Dundee. The data set shows a snapshot of people within these areas every Monday, Wednesday and Saturday during the period 1pm-2pm.This data is experimental and subject to further refinement. Please note that due the nature of CCTV cameras at times data may not be collected as specified above. Therefore, caution should be exercised when analysing data and drawing conclusions for this data set.CCTV datasets contain information on object detections taken from a selection of the CCTV cameras throughout Dundee City. CCTV images are translated into object counts, objects counted include ‘person’, ‘car’, ‘bicycle’, ‘bus’, ‘motorcycle', 'truck, ‘pickup truck 'and ‘van’. The data is generated and owned by Dundee City Council. Copyright © Dundee City Council 2022. This dataset is available for use under the Open Government Licence.Background information about the Dundee CCTV cameras including a map showing the location of the cameras is available on the Dundee City Council website and can be accessed using the following link:https://www.dundeecity.gov.uk/service-area/city-development/sustainable-transport-and-roads/dundees-public-space-camera-surveillance-system

[1] The Progress by Population Group analysis is a component of the Healthy People 2020 (HP2020) Final Review. The analysis included subsets of the 1,111 measurable HP2020 objectives that have data available for any of six broad population characteristics: sex, race and ethnicity, educational attainment, family income, disability status, and geographic location. Progress toward meeting HP2020 targets is presented for up to 24 population groups within these characteristics, based on objective data aggregated across HP2020 topic areas. The Progress by Population Group data are also available at the individual objective level in the downloadable data set. [2] The final value was generally based on data available on the HP2020 website as of January 2020. For objectives that are continuing into HP2030, more recent data will be included on the HP2030 website as it becomes available: https://health.gov/healthypeople. [3] For more information on the HP2020 methodology for measuring progress toward target attainment and the elimination of health disparities, see: Healthy People Statistical Notes, no 27; available from: https://www.cdc.gov/nchs/data/statnt/statnt27.pdf. [4] Status for objectives included in the HP2020 Progress by Population Group analysis was determined using the baseline, final, and target value. The progress status categories used in HP2020 were: a. Target met or exceeded—One of the following applies: (i) At baseline, the target was not met or exceeded, and the most recent value was equal to or exceeded the target (the percentage of targeted change achieved was equal to or greater than 100%); (ii) The baseline and most recent values were equal to or exceeded the target (the percentage of targeted change achieved was not assessed). b. Improved—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved 10% or more of the targeted change. c. Little or no detectable change—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was not statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved less than 10% of the targeted change; (iii) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was not statistically significant; (iv) Movement was away from the baseline and target, standard errors were not available, and the objective had moved less than 10% relative to the baseline; (v) No change was observed between the baseline and the final data point. d. Got worse—One of the following applies: (i) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was statistically significant; (ii) Movement was away from the baseline and target, standard errors were not available, and the objective had moved 10% or more relative to the baseline. NOTE: Measurable objectives had baseline data. SOURCE: National Center for Health Statistics, Healthy People 2020 Progress by Population Group database.

​This collection consists of total number of signatures to 1769 petitions over time (hourly resolution) along with petition metadata (title, category, time of creation), directly crawled from the website. Please see 'Related resources' section below for related data collections. This project aims to develop methodologies to study online political behaviour including use of the Internet to generate new data and experiments; to collect and analyse data on internet-mediated interactions at both individual and organisational levels; and to use this data to re-examine and where necessary develop political science knowledge and theory in light of widespread use of the Internet First, the project will re-examine the logic of collective action, assessing the impact of reduced communication and coordination costs; the changing nature of leadership; and the effects of different information environments on propensity to participate in political mobilisation. This part of the research will involve conducting laboratory and field experiments into online behaviour. Second, the research will develop the Digital-era Governance model for newer 'Web 2.0' applications and other technological developments such as cloud computing. The research will re-examine the nature of citizen-government interactions in this changing environment, examining the impact of Internet-based mediation on information exchange, organisational forms in government and citizen participation in policy-making. This part of the research will involve a comparison of government's online presence in eight countries, using webmetric techniques, and in-depth qualitative analysis of governance models, using elite interviewing and documentary analysis. Using a webscraping approach, the US White House petition website was accessed daily with an automated script to record the overall signatures to date on each active petition.