Dataset Overview

This dataset provides a comprehensive overview of internet usage across countries as of 2024. It includes data on the percentage of the population using the internet, sourced from multiple organizations such as the World Bank (WB), International Telecommunication Union (ITU), and the CIA. The dataset covers all United Nations member states, excluding North Korea, and provides insights into internet penetration rates, user counts, and trends over recent years. The data is derived from household surveys and internet subscription statistics, offering a reliable snapshot of global digital connectivity.

Data Science Applications

This dataset can be used in various data science applications, including: - Digital Divide Analysis: Evaluate disparities in internet access between developed and developing nations. - Trend Analysis: Study the growth of internet penetration over time across different regions. - Policy Recommendations: Assist policymakers in identifying underserved areas and strategizing for improved connectivity. - Market Research: Help businesses identify potential markets for digital products or services. - Correlation Studies: Analyze relationships between internet penetration and socioeconomic indicators like GDP, education levels, or urbanization.

Column Descriptors

The dataset contains the following columns: 1. Location: Country or region name. 2. Rate (WB): Percentage of the population using the internet (World Bank data). 3. Year (WB): Year corresponding to the World Bank data. 4. Rate (ITU): Percentage of the population using the internet (ITU data). 5. Year (ITU): Year corresponding to the ITU data. 6. Users (CIA): Estimated number of internet users in absolute terms (CIA data). 7. Year (CIA): Year corresponding to the CIA data. 8. Notes: Additional notes or observations about specific entries.

Ethically Mined Data

The data has been sourced from publicly available and reputable organizations such as the World Bank, ITU, and CIA. These sources ensure transparency and ethical collection methods through household surveys and official statistics. The dataset excludes North Korea due to limited reliable information on its internet usage.

Acknowledgements

This dataset is based on information compiled from: - World Bank - International Telecommunication Union - CIA World Factbook - Wikipedia's "List of countries by number of Internet users" page

Special thanks to these organizations for providing open access to this valuable information, enabling deeper insights into global digital connectivity trends.

Citations: [1] https://en.wikipedia.org/wiki/List_of_countries_by_number_of_Internet_users [2] https://en.wikipedia.org/wiki/List_of_countries_by_number_of_Internet_users

At the height of the coronavirus pandemic, on the last day of March 2020, Wikipedia in all languages broke a record for most traffic in a single day. Since the breakout of the Covid-19 pandemic at the start of January, tens if not hundreds of millions of people have come to Wikipedia to read - and in some cases also contribute - knowledge, information and data about the virus to an ever-growing pool of articles. Our study focuses on the scientific backbone behind the content people across the world read: which sources informed Wikipedia’s coronavirus content, and how was the scientific research on this field represented on Wikipedia. Using citation as readout we try to map how COVID-19 related research was used in Wikipedia and analyse what happened to it before and during the pandemic. Understanding how scientific and medical information was integrated into Wikipedia, and what were the different sources that informed the Covid-19 content, is key to understanding the digital knowledge echosphere during the pandemic. To delimitate the corpus of Wikipedia articles containing Digital Object Identifier (DOI), we applied two different strategies. First we scraped every Wikipedia pages form the COVID-19 Wikipedia project (about 3000 pages) and we filtered them to keep only page containing DOI citations. For our second strategy, we made a search with EuroPMC on Covid-19, SARS-CoV2, SARS-nCoV19 (30’000 sci papers, reviews and preprints) and a selection on scientific papers form 2019 onwards that we compared to the Wikipedia extracted citations from the english Wikipedia dump of May 2020 (2’000’000 DOIs). This search led to 231 Wikipedia articles containing at least one citation of the EuroPMC search or part of the wikipedia COVID-19 project pages containing DOIs. Next, from our 231 Wikipedia articles corpus we extracted DOIs, PMIDs, ISBNs, websites and URLs using a set of regular expressions. Subsequently, we computed several statistics for each wikipedia article and we retrive Atmetics, CrossRef and EuroPMC infromations for each DOI. Finally, our method allowed to produce tables of citations annotated and extracted infromations in each wikipadia articles such as books, websites, newspapers.Files used as input and extracted information on Wikipedia's COVID-19 sources are presented in this archive.See the WikiCitationHistoRy Github repository for the R codes, and other bash/python scripts utilities related to this project.

The Enterprise Wiki Software market is experiencing robust growth, driven by the increasing need for efficient knowledge management and collaboration within organizations of all sizes. The market, valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated market value of $8 billion by 2033. This expansion is fueled by several key factors. Firstly, the rise of remote work and hybrid work models necessitates improved internal communication and knowledge sharing, making enterprise wiki software a crucial tool for maintaining productivity and organizational alignment. Secondly, the increasing adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, further boosting market growth. Furthermore, the integration of advanced features like AI-powered search, version control, and robust security measures enhances the overall value proposition for businesses. While initial implementation costs and the need for comprehensive training can act as restraints, the long-term benefits in terms of improved employee productivity, reduced operational costs, and enhanced knowledge accessibility are compelling organizations to overcome these challenges. The market segmentation reveals a significant demand from both large enterprises and SMEs, with cloud-based solutions gaining traction due to their flexibility and affordability. North America currently holds the largest market share, followed by Europe and Asia Pacific. However, emerging economies in Asia Pacific are poised for significant growth in the coming years due to increasing digital adoption and the expansion of businesses in this region. The competitive landscape is dynamic, with established players like Atlassian and Zoho competing with emerging niche players offering specialized features. Success in this market depends on delivering user-friendly interfaces, robust security features, seamless integration with existing enterprise systems, and a strong focus on customer support and ongoing product development. The market is expected to witness further consolidation as companies strive for market leadership through strategic partnerships, acquisitions, and product innovation.

3D data workflow RDM Administration Analytics Enabling complex analysis of large scale digital collections Develop a DataVault Filling the digital preservation gap Collaboration for Research Enhancement by Active Metadata Use semantic desktop to capture contextual research data Software re-use, repurposing and reproducibility Unlocking the UK’s thesis data through persistent identifiers Using Alfresco for management of research data An Intelligent Data Cleaning Software Tool for Research Data Giving researchers credit for their data Cloud Work Bench Open Source Database-as-a-Service with Data Publishing Pushing Database Wiki out of the nest DAF Case Bank Extending the Organisational Profile Document (OPD) to cover RDM Sound Matters: a framework for use and re-use of sound Standards MetaProject Distributed Knowledge Sharing Platform for RDM A consortial approach to building and integrated RDM system - "small and specialist" Project pitches for the following ideas:

ObjectiveThe recent spreading of Zika virus represents an emerging global health threat. As such, it is attracting public interest worldwide, generating a great amount of related Internet searches and social media interactions. The aim of this research was to understand Zika-related digital behavior throughout the epidemic spreading and to assess its consistence with real-world epidemiological data, using a behavioral informatics and analytics approach.MethodsIn this study, the global web-interest and reaction to the recently occurred outbreaks of the Zika Virus were analyzed in terms of tweets and Google Trends (GT), Google News, YouTube, and Wikipedia search queries. These data streams were mined from 1st January 2004 to 31st October 2016, with a focus on the period November 2015—October 2016. This analysis was complemented with the use of epidemiological data. Spearman’s correlation was performed to correlate all Zika-related data. Moreover, a multivariate regression was performed using Zika-related search queries as a dependent variable, and epidemiological data, number of inhabitants in 2015 and Human Development Index as predictor variables.ResultsOverall 3,864,395 tweets, 284,903 accesses to Wikipedia pages dedicated to the Zika virus were analyzed during the study period. All web-data sources showed that the main spike of researches and interactions occurred in February 2016 with a second peak in August 2016. All novel data streams-related activities increased markedly during the epidemic period with respect to pre-epidemic period when no web activity was detected. Correlations between data from all these web platforms resulted very high and statistically significant. The countries in which web searches were particularly concentrated are mainly from Central and South Americas. The majority of queries concerned the symptoms of the Zika virus, its vector of transmission, and its possible effect to babies, including microcephaly. No statistically significant correlation was found between novel data streams and global real-world epidemiological data. At country level, a correlation between the digital interest towards the Zika virus and Zika incidence rate or microcephaly cases has been detected.ConclusionsAn increasing public interest and reaction to the current Zika virus outbreak was documented by all web-data sources and a similar pattern of web reactions has been detected. The public opinion seems to be particularly worried by the alert of teratogenicity of the Zika virus. Stakeholders and health authorities could usefully exploited these internet tools for collecting the concerns of public opinion and reply to them, disseminating key information.