40 datasets found
  1. i

    Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and...

    • ieee-dataport.org
    Updated Oct 21, 2024
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    Mohamad Amar Irsyad Mohd Aminuddin (2024). Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and Mobile Webpages [Dataset]. https://ieee-dataport.org/documents/website-fingerprinting-dataset-browsing-network-traffic-desktop-and-mobile-webpages
    Explore at:
    Dataset updated
    Oct 21, 2024
    Authors
    Mohamad Amar Irsyad Mohd Aminuddin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.The webpage URL is selected by using the first 100 website based on: https://dataforseo.com/free-seo-stats/top-1000-websites.Each webpage URL is visited 90 times for each deskop and mobile browsing mode.

  2. YouTube Dataset on Mobile Streaming for Internet Traffic Modeling, Network...

    • figshare.com
    txt
    Updated Apr 14, 2022
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    Frank Loh; Florian Wamser; Fabian Poignée; Stefan Geißler; Tobias Hoßfeld (2022). YouTube Dataset on Mobile Streaming for Internet Traffic Modeling, Network Management, and Streaming Analysis [Dataset]. http://doi.org/10.6084/m9.figshare.19096823.v2
    Explore at:
    txtAvailable download formats
    Dataset updated
    Apr 14, 2022
    Dataset provided by
    figshare
    Authors
    Frank Loh; Florian Wamser; Fabian Poignée; Stefan Geißler; Tobias Hoßfeld
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    YouTube
    Description

    Streaming is by far the predominant type of traffic in communication networks. With thispublic dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3G/4G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases.

  3. Mobile internet users worldwide 2020-2029

    • statista.com
    Updated Feb 5, 2025
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    Statista Research Department (2025). Mobile internet users worldwide 2020-2029 [Dataset]. https://www.statista.com/topics/779/mobile-internet/
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.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).Find more key insights for the number of smartphone users in countries like Australia & Oceania and Asia.

  4. Mobile internet penetration in Europe 2024, by country

    • statista.com
    Updated Feb 5, 2025
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    Statista Research Department (2025). Mobile internet penetration in Europe 2024, by country [Dataset]. https://www.statista.com/topics/779/mobile-internet/
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    Switzerland is leading the ranking by population share with mobile internet access, recording 95.06 percent. Following closely behind is Ukraine with 95.06 percent, while Moldova is trailing the ranking with 46.83 percent, resulting in a difference of 48.23 percentage points to the ranking leader, Switzerland. The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection. 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).

  5. Mobile internet usage reach in North America 2020-2029

    • statista.com
    Updated Feb 5, 2025
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    Statista Research Department (2025). Mobile internet usage reach in North America 2020-2029 [Dataset]. https://www.statista.com/topics/779/mobile-internet/
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The population share with mobile internet access in North America was forecast to increase between 2024 and 2029 by in total 2.9 percentage points. This overall increase does not happen continuously, notably not in 2028 and 2029. The mobile internet penetration is estimated to amount to 84.21 percent in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.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).Find more key insights for the population share with mobile internet access in countries like Caribbean and Europe.

  6. R

    Indian Traffic Sign Dataset

    • universe.roboflow.com
    zip
    Updated Sep 11, 2023
    + more versions
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    DataCluster Labs (2023). Indian Traffic Sign Dataset [Dataset]. https://universe.roboflow.com/datacluster-labs-agryi/indian-traffic-sign-vvx9y
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    zipAvailable download formats
    Dataset updated
    Sep 11, 2023
    Dataset authored and provided by
    DataCluster Labs
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Traffic Signals Bounding Boxes
    Description

    Indian Traffic Sign Image Dataset

    Datasets for Indian traffic signs

    About Dataset

    **This dataset is collected by Datacluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: s*ales@datacluster.ai* **

    This dataset is an extremely challenging set of over 2000+ original Indian Traffic Sign images captured and crowdsourced from over 400+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at DC Labs.

    Dataset Features 1. Dataset size : 2000+ 2. Captured by : Over 400+ crowdsource contributors 3. Resolution : 100% of images HD and above (1920x1080 and above) 4. Location : Captured with 400+ cities accross India 5. Diversity : Various lighting conditions like day, night, varied distances, view points etc. 6. Device used : Captured using mobile phones in 2020-2021 7. Usage : Traffic sign detection, Self-driving systems, traffic detection, sign detection, etc.

    Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

    The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

  7. d

    Omnichannel Consumer Journeys | 1st Party | 3B+ events verified, US...

    • datarade.ai
    .csv, .parquet
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    MFour, Omnichannel Consumer Journeys | 1st Party | 3B+ events verified, US consumers | Path to purchase across app, web and point of interest locations [Dataset]. https://datarade.ai/data-products/omnichannel-consumer-journeys-1st-party-3b-events-verifi-mfour
    Explore at:
    .csv, .parquetAvailable download formats
    Dataset authored and provided by
    MFour
    Area covered
    United States of America
    Description

    This dataset encompasses mobile app usage, web clickstream and location visitation behavior, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). The only omnichannel meter at scale representing iOS and Android platforms.

    Includes ties to consumer demographics.

    In-app audio, media and social ad exposure data included. Can be commissioned to build other in-app and account level visibility.

  8. Number of internet users worldwide 2014-2029

    • statista.com
    Updated Apr 11, 2025
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    Statista Research Department (2025). Number of internet users worldwide 2014-2029 [Dataset]. https://www.statista.com/topics/1145/internet-usage-worldwide/
    Explore at:
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    World
    Description

    The global number of internet users in was forecast to continuously increase between 2024 and 2029 by in total 1.3 billion users (+23.66 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 7 billion users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.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).Find more key insights for the number of internet users in countries like the Americas and Asia.

  9. Z

    Data from: Energy-Saving Strategies for Mobile Web Apps and their...

    • data.niaid.nih.gov
    • explore.openaire.eu
    • +1more
    Updated Mar 13, 2023
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    Benedikt Dornauer (2023). Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Research - Dataset [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7698282
    Explore at:
    Dataset updated
    Mar 13, 2023
    Dataset provided by
    Benedikt Dornauer
    Michael Felderer
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In 2022, over half of the web traffic was accessed through mobile devices. By reducing the energy consumption of mobile web apps, we can not only extend the battery life of our devices, but also make a significant contribution to energy conservation efforts. For example, if we could save only 5% of the energy used by web apps, we estimate that it would be enough to shut down one of the nuclear reactors in Fukushima. This paper presents a comprehensive overview of energy-saving experiments and related approaches for mobile web apps, relevant for researchers and practitioners. To achieve this objective, we conducted a systematic literature review and identified 44 primary studies for inclusion. Through the mapping and analysis of scientific papers, this work contributes: (1) an overview of the energy-draining aspects of mobile web apps, (2) a comprehensive description of the methodology used for the energy-saving experiments, and (3) a categorization and synthesis of various energy-saving approaches.

  10. B

    ITU World Telecommunication/ICT Indicators database

    • borealisdata.ca
    • dataone.org
    Updated Apr 13, 2022
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    Union ational Telecommunication Union (ITU) (2022). ITU World Telecommunication/ICT Indicators database [Dataset]. http://doi.org/10.5683/SP3/ESWWF6
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 13, 2022
    Dataset provided by
    Borealis
    Authors
    Union ational Telecommunication Union (ITU)
    License

    https://borealisdata.ca/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.5683/SP3/ESWWF6https://borealisdata.ca/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.5683/SP3/ESWWF6

    Time period covered
    1960
    Area covered
    International
    Description

    The World Telecommunication/ICT Indicators Database contains time series data for the years 1960, 1965, 1970 and annually from 1975 to 2020 for more than 180 telecommunication/ICT statistics covering fixed-telephone networks, mobile-cellular telephone subscriptions, quality of service, Internet (including fixed- and mobile-broadband subscription data), traffic, staff, prices, revenue, investment and statistics on ICT access and use by households and individuals. Selected demographic, macroeconomic and broadcasting statistics are also included. Data are available for over 200 economies. However, it should be noted that since ITU relies primarily on official economy data, availability of data for the different indicators and years varies. Notes explaining data exceptions are also included. The data are collected from an annual questionnaire sent to official economy contacts, usually the regulatory authority or the ministry in charge of telecommunication and ICT. Additional data are obtained from reports provided by telecommunication ministries, regulators and operators and from ITU staff reports. In some cases, estimates are made by ITU staff; these are noted in the database.

  11. Mobile broadband connections per 100 inhabitants in the United States...

    • statista.com
    Updated Nov 19, 2024
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    Statista Research Department (2024). Mobile broadband connections per 100 inhabitants in the United States 2014-2029 [Dataset]. https://www.statista.com/topics/3124/mobile-internet-usage-in-the-united-states/
    Explore at:
    Dataset updated
    Nov 19, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    The number of mobile broadband connections per 100 inhabitants in the United States was forecast to continuously increase between 2024 and 2029 by in total 21.1 connections (+11.49 percent). After the fifteenth consecutive increasing year, the mobile broadband penetration is estimated to reach 204.76 connections and therefore a new peak in 2029. Notably, the number of mobile broadband connections per 100 inhabitants of was continuously increasing over the past years.Mobile broadband connections include cellular connections with a download speed of at least 256 kbit/s (without satellite or fixed-wireless connections). Cellular Internet-of-Things (IoT) or machine-to-machine (M2M) connections are excluded. 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).Find more key insights for the number of mobile broadband connections per 100 inhabitants in countries like Canada and Mexico.

  12. How to choose the right product for your client?

    • kaggle.com
    Updated Mar 23, 2020
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    Julia Beyers (2020). How to choose the right product for your client? [Dataset]. https://www.kaggle.com/juliabeyers/how-to-choose-the-right-product-for-your-client/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 23, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Julia Beyers
    Description

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F4686357%2F186cf4f6172ca2c696819b7b09931bd3%2Fimage3.jpg?generation=1584955857130173&alt=media" alt="">

    The presence of business in the digital space is a must now. Indeed, there’s hardly any company, be it a small startup or an international corporation, that wouldn’t be available online. For this, the company may use one of two options — to develop an app or a website, or both.

    In the case of a limited budget, business owners often have to make a choice. Thus, considering that mobile traffic bypassed the desktop’s in 2016 and continues to grow, it becomes obvious that the business should become accessible and convenient for smartphone users. But what is better a responsive website or a mobile application?

    Entrepreneurs often turn to development companies to ask this question. Lacking sufficient knowledge, they hope to get answers to their questions from people with experience in this field. So, we decided to compile a guide that will give you clear and understandable information.

    Mobile app

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F4686357%2F0541557795519f24d812f78dfb51867e%2Fimage4.png?generation=1584955894277647&alt=media" alt="">

    Let's look at the stats. It will help you understand why a mobile app may be the obvious choice for your client.

    In 2019, smartphone users installed about 204 billion(!) applications on their devices. On average, this is more than 26 applications per inhabitant of the planet Earth. And if this is not enough evidence, here’s one more point. The expected revenue of mobile applications will be $189 billion in 2020.

    It sounds impressive, but this does not mean that a mobile application is something indispensable for every business. Not at all. Let's go through the pros and cons of a mobile application and try to understand when it is needed.

    Pros

    • A new level of interaction. Mobile applications are a more convenient method of interaction. They load and process content faster. One more useful feature is notifications. Perhaps, applications are the best way to inform users about new updates, promotions, and other news (who will read long letters in the mail?).
    • Personalized targeting. Mobile applications are ideal for products or services that need to be used on an ongoing basis. The options like creating accounts, entering profile information, etc., make applications more personalized than websites. All this allows the business to target their audience more accurately without wasting money.
    • Offline usage. That’s another major advantage. Applications can provide users with access to content without an internet connection.

    Cons

    • Development costs. In order to reach the maximum audience with a mobile app, it is necessary to cover two main operating systems — iOS and Android. Development for each OS can be too expensive for small business owners and they will have to make difficult choices. The way out of this situation is cross-platform development. Why? Because there’s no need to guess which platform targets prefer using — iOS or Android. Instead, you create just one app that runs seamlessly on both platforms.

    • Maintenance. The application is a technical product that needs constant support. Upgrades should be carried out in a timely manner. Often, users need to personally update applications by downloading a new version, which is annoying. Regular bug-fixing for various devices (smartphones, tablets) and different operating systems might be a real problem. Plus, any update should be confirmed by the store where the application is placed.

    • Suitable for businesses that provide interactive and personalized content (refers to all lifestyle and healthcare solutions), require regular app usage (for instance, to-do lists), rely on visual interaction and so on. For games, like Angry Birds, creating an app is also a wise choice.

    Website

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F4686357%2Fd4f5bf1fdd0d0e65fae38c7251f56f13%2Fimage1.jpg?generation=1584955919738648&alt=media" alt="">

    In order to be convenient for users of mobile devices, a website should be responsive. We want to make an emphasis on this since it is critically important. Most of the traffic on the Internet comes from mobile devices, so your website should be adaptable, or in other words, mobile-friendly. If a mobile user needs to zoom in all the necessary elements and text to see something, they will immediately quit your website.

    On the other hand, a responsive website has the following benefits.

    Pros

    • Maintenance. Maintaining a website is less costly. When compared to applications where the user mu...
  13. f

    Data from: Revealing QoE of Web Users from Encrypted Network Traffic

    • figshare.com
    zip
    Updated Jun 16, 2020
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    Alexis Huet; Antoine Saverimoutou; Zied Ben Houidi; Hao Shi; Shengming Cai; Jinchun Xu; Bertrand Mathieu; Dario Rossi (2020). Revealing QoE of Web Users from Encrypted Network Traffic [Dataset]. http://doi.org/10.6084/m9.figshare.12459293.v1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 16, 2020
    Dataset provided by
    figshare
    Authors
    Alexis Huet; Antoine Saverimoutou; Zied Ben Houidi; Hao Shi; Shengming Cai; Jinchun Xu; Bertrand Mathieu; Dario Rossi
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    We present a dataset targeting a large set of popular pages (Alexa top-500), from probes from several ISPs networks, browsers software (Chrome, Firefox) and viewport combinations, for over 200,000 experiments realized in 2019.We purposely collect two distinct sets with two different tools, namely Web Page Test (WPT) and Web View (WV), varying a number of relevant parameters and conditions, for a total of 200K+ web sessions, roughly equally split among WV and WPT. Our dataset comprises variations in terms of geographical coverage, scale, diversity and representativeness (location, targets, protocol, browser, viewports, metrics).For Web Page Test, we used the online service www.webpagetest.org at different locations worldwide (Europe, Asia, USA) and private WPT instances in three locations in China (Beijing, Shanghai, Dongguan). The list of target URLs comprised the main pages and five random subpages from Alexa top-500 worldwide and China. We varied network conditions : native connections and 4G, FIOS, 3GFast, DSL, and custom shaping/loss conditions. The other elements in the configuration were fixed: Chrome browser on desktop with a fixed screen resolution, HTTP/2 protocol and IPv4.For Web View, we collected experiments from three machines located in France. We selected two versions of two browser families (Chrome 75/77, Firefox 63/68), two screen sizes (1920x1080, 1440x900), and employ different browser configurations (one half of the experiments activate the AdBlock plugin) from two different access technologies (fiber and ADSL). From a protocol standpoint, we used both IPv4 and IPv6, with HTTP/2 and QUIC, and performed repeated experiments with cached objects/DNS. Given the settings diversity, we restricted the number of websites to about 50 among the Alexa top-500 websites, to ensure statistical relevance of the collected samples for each page.The two archives IFIPNetworking2020_WebViewOrange.zip and IFIPNetworking2020_Webpagetest.zip correspond respectively to the Web View experiments and to the Web Page Test experiments.Each archive contains three files:- config.csv: Description of parameters and conditions for each run,- metrics.csv: Value of different metrics collected by the browser,- progressionCurves.csv: Progression curves of the bytes progress as seen by the network, from 0 to 10 seconds by steps of 100 milliseconds,- listUrl folder: Indexes the sets of urls.Regarding config.csv, the columns are: - index: Index for this set of conditions, - location: Location of the machine, - listUrl: List of urls, located in the folder listUrl - browserUsed: Internet browser and version - terminal: Desktop or Mobile - collectionEnvironment: Identification of the collection environment - networkConditionsTrafficShaping (WPT only): Whether native condition or traffic shaping (4G, FIOS, 3GFast, DSL, or custom Emulator conditions) - networkConditionsBandwidth (WPT only): Bandwidth of the network - networkConditionsDelay (WPT only): Delay in the network - networkConditions (WV only): network conditions - ipMode (WV only): requested L3 protocol, - requestedProtocol (WV only): requested L7 protocol - adBlocker (WV only): Whether adBlocker is used or not - winSize (WV only): Window sizeRegarding metrics.csv, the columns are: - id: Unique identification of an experiment (consisting of an index 'set of conditions' and an index 'current page') - DOM Content Loaded Event End (ms): DOM time, - First Paint (ms) (WV only): First paint time, - Load Event End (ms): Page Load Time from W3C, - RUM Speed Index (ms) (WV only): RUM Speed Index, - Speed Index (ms) (WPT only): Speed Index, - Time for Full Visual Rendering (ms) (WV only): Time for Full Visual Rendering - Visible portion (%) (WV only): Visible portion, - Time to First Byte (ms) (WPT only): Time to First Byte, - Visually Complete (ms) (WPT only): Visually Complete used to compute the Speed Index, - aatf: aatf using ATF-chrome-plugin - bi_aatf: bi_aatf using ATF-chrome-plugin - bi_plt: bi_plt using ATF-chrome-plugin - dom: dom using ATF-chrome-plugin - ii_aatf: ii_aatf using ATF-chrome-plugin - ii_plt: ii_plt using ATF-chrome-plugin - last_css: last_css using ATF-chrome-plugin - last_img: last_img using ATF-chrome-plugin - last_js: last_js using ATF-chrome-plugin - nb_ress_css: nb_ress_css using ATF-chrome-plugin - nb_ress_img: nb_ress_img using ATF-chrome-plugin - nb_ress_js: nb_ress_js using ATF-chrome-plugin - num_origins: num_origins using ATF-chrome-plugin - num_ressources: num_ressources using ATF-chrome-plugin - oi_aatf: oi_aatf using ATF-chrome-plugin - oi_plt: oi_plt using ATF-chrome-plugin - plt: plt using ATF-chrome-pluginRegarding progressionCurves.csv, the columns are: - id: Unique identification of an experiment (consisting of an index 'set of conditions' and an index 'current page') - url: Url of the current page. SUBPAGE stands for a path. - run: Current run (linked with index of the config for WPT) - filename: Filename of the pcap - fullname: Fullname of the pcap - har_size: Size of the HAR for this experiment, - pagedata_size: Size of the page data report - pcap_size: Size of the pcap - App Byte Index (ms): Application Byte Index as computed from the har file (in the browser) - bytesIn_APP: Total bytes in as seen in the browser, - bytesIn_NET: Total bytes in as seen in the network, - X_BI_net: Network Byte Index computed from the pcap file (in the network) - X_bin_0_for_B_completion to X_bin_99_for_B_completion: X_bin_k_for_B_completion is the bytes progress reached after k*100 millisecondsIf you use these datasets in your research, you can reference to the appropriate paper:@inproceedings{qoeNetworking2020, title={Revealing QoE of Web Users from Encrypted Network Traffic}, author={Huet, Alexis and Saverimoutou, Antoine and Ben Houidi, Zied and Shi, Hao and Cai, Shengming and Xu, Jinchun and Mathieu, Bertrand and Rossi, Dario}, booktitle={2020 IFIP Networking Conference (IFIP Networking)}, year={2020}, organization={IEEE}}

  14. O

    Parking — Occupancy forecasting

    • data.qld.gov.au
    • researchdata.edu.au
    html
    Updated Jul 30, 2025
    + more versions
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    Brisbane City Council (2025). Parking — Occupancy forecasting [Dataset]. https://www.data.qld.gov.au/dataset/parking-occupancy-forecasting
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Jul 30, 2025
    Dataset authored and provided by
    Brisbane City Council
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

    The Brisbane City Council parking occupancy forecasting data is provided to be accessed by third party web or app developers to develop tools to provide Brisbane residents and visitors with likely parking availability within a paid parking area.

    The parking occupancy forecasting data is compiled using advanced analytics and machine learning to estimate paid parking availability. The solution uses parking occupancy survey data, parking meter transaction data and other traffic and environmental data.

    This dataset is linked to the open data called Parking — Meter locations. The field called MOBILE_ZONE is used to link the datasets. MOBILE_ZONE is a seven-digit mobile payment zone number that may include one or many parking meter numbers.

    Additional information on parking meters can be found on the Brisbane City Council website.

    The Brisbane City Council parking occupancy forecasting data includes parking data for all of Council’s parking meters. The data attributes used in this resource and their descriptions can be found in the Parking — Occupancy forecasting — metadata — CSV resource in this dataset.

    The Data and resources section of this dataset contains further information for this dataset.

  15. Attitudes towards the internet in Mexico 2025

    • statista.com
    Updated Apr 11, 2025
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    Umair Bashir (2025). Attitudes towards the internet in Mexico 2025 [Dataset]. https://www.statista.com/topics/1145/internet-usage-worldwide/
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    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Umair Bashir
    Description

    When asked about "Attitudes towards the internet", most Mexican respondents pick "It is important to me to have mobile internet access in any place" as an answer. 56 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

  16. g

    The major statistical data of natural referencing | gimi9.com

    • gimi9.com
    Updated Nov 30, 2024
    + more versions
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    (2024). The major statistical data of natural referencing | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_65f594ba5cf5f141524928b6/
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    Dataset updated
    Nov 30, 2024
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This dataset gathers the most crucial SEO statistics for the year, providing an overview of the dominant trends and best practices in the field of search engine optimization. Aimed at digital marketing professionals, site owners, and SEO analysts, this collection of information serves as a guide to navigate the evolving SEO landscape with confidence and accuracy. Mode of Data Production: The statistics have been carefully selected and compiled from a variety of credible and recognized sources in the SEO industry, including research reports, web traffic data analytics, and consumer and marketing professional surveys. Each statistic was checked for reliability and relevance to current trends. Categories Included: User search behaviour: Statistics on the evolution of search modes, including voice and mobile search. Mobile Optimisation: Data on the importance of site optimization for mobile devices. Importance of Backlinks: Insights on the role of backlinks in SEO ranking and the need to prioritize quality. Content quality: Statistics highlighting the importance of relevant and engaging content for SEO. Search engine algorithms: Information on the impact of algorithm updates on SEO strategies. Usefulness of the Data: This dataset is designed to help users quickly understand current SEO dynamics and apply that knowledge in optimizing their digital marketing strategies. It provides a solid foundation for benchmarking, strategic planning, and informed decision-making in the field of SEO. Update and Accessibility: To ensure relevance and timeliness, the dataset will be regularly updated with new information and emerging trends in the SEO world.

  17. Attitudes towards the internet in China 2025

    • statista.com
    Updated Apr 11, 2025
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    Umair Bashir (2025). Attitudes towards the internet in China 2025 [Dataset]. https://www.statista.com/topics/1145/internet-usage-worldwide/
    Explore at:
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Umair Bashir
    Description

    When asked about "Attitudes towards the internet", most Chinese respondents pick "It is important to me to have mobile internet access in any place" as an answer. 50 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

  18. Attitudes towards the internet in Japan 2025

    • statista.com
    Updated Apr 11, 2025
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    Umair Bashir (2025). Attitudes towards the internet in Japan 2025 [Dataset]. https://www.statista.com/topics/1145/internet-usage-worldwide/
    Explore at:
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Umair Bashir
    Description

    When asked about "Attitudes towards the internet", most Japanese respondents pick "I'm concerned that my data is being misused on the internet" as an answer. 35 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

  19. a

    Public Traffic Restrictons Mobile Application

    • egishub-phoenix.hub.arcgis.com
    Updated Nov 29, 2018
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    City of Phoenix (2018). Public Traffic Restrictons Mobile Application [Dataset]. https://egishub-phoenix.hub.arcgis.com/datasets/public-traffic-restrictons-mobile-application/about
    Explore at:
    Dataset updated
    Nov 29, 2018
    Dataset authored and provided by
    City of Phoenix
    Description

    Web Application (Mobile Use) for Public Traffic Restriction and Emergency Closure for public consumption

  20. Attitudes towards the internet in Australia 2025

    • statista.com
    Updated Apr 11, 2025
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    Umair Bashir (2025). Attitudes towards the internet in Australia 2025 [Dataset]. https://www.statista.com/topics/1145/internet-usage-worldwide/
    Explore at:
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Umair Bashir
    Description

    When asked about "Attitudes towards the internet", most Australian respondents pick "It is important to me to have mobile internet access in any place" as an answer. 55 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

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Mohamad Amar Irsyad Mohd Aminuddin (2024). Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and Mobile Webpages [Dataset]. https://ieee-dataport.org/documents/website-fingerprinting-dataset-browsing-network-traffic-desktop-and-mobile-webpages

Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and Mobile Webpages

Explore at:
Dataset updated
Oct 21, 2024
Authors
Mohamad Amar Irsyad Mohd Aminuddin
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.The webpage URL is selected by using the first 100 website based on: https://dataforseo.com/free-seo-stats/top-1000-websites.Each webpage URL is visited 90 times for each deskop and mobile browsing mode.

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