4 datasets found
  1. f

    A Personalized Activity-based Spatiotemporal Risk Mapping Approach to...

    • figshare.com
    tiff
    Updated Mar 18, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang (2021). A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic [Dataset]. http://doi.org/10.6084/m9.figshare.13517105.v1
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Mar 18, 2021
    Dataset provided by
    figshare
    Authors
    Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang
    License

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

    Description

    The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.

  2. c

    ckanext-js-tweaks

    • catalog.civicdataecosystem.org
    Updated Jan 22, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). ckanext-js-tweaks [Dataset]. https://catalog.civicdataecosystem.org/dataset/ckanext-js-tweaks
    Explore at:
    Dataset updated
    Jan 22, 2025
    Description

    The js-tweaks extension for CKAN offers a collection of JavaScript scripts, macros, and helpers aimed at streamlining common tasks and user interactions within a CKAN instance. It primarily focuses on enriching the user interface through simple modifications that can improve the overall usability of the platform. By providing readily available tools to implement features such as tooltips, this extension facilitates a more interactive and informative environment for CKAN users. Key Features: Tooltip Implementation: Allows for the rapid addition of basic tooltips to elements on a CKAN page by simply adding the data-tooltip="text" attribute. Bootstrap Tooltip Compatibility: Supports the use of Bootstrap's tooltip functionality for more advanced tooltip implementations and customization using standard Bootstrap attributes (data-toggle="tooltip" data-placement="top" title="Tooltip on top"). Customizable UI: Provides a foundation for further UI enhancements through the inclusion of JavaScript scripts and macros, which is meant to allow for targeted tweaks to match specific user needs or preferences. Simplified Routing: The goal is to make daily routing easier. Technical Integration: The js-tweaks extension is enabled by adding js-tweaks to the ckan.plugins setting in the CKAN configuration file (/etc/ckan/default/ckan.ini by default). After modifying the configuration, restarting CKAN instance is necessary to apply the configurations to enable the modifications offered by the extension. Benefits & Impact: Implementing the js-tweaks extension enables CKAN administrators to quickly implement enhancements to the user interface and routing within the overall platform, such as by adding tooltips or building on the JS, improving user experience without extensive coding or modification to the core CKAN system. While the provided documentation is limited, it aims to reduce complexity and make CKAN interfaces intuitive.

  3. Tweets during Nintendo E3 2018 Conference

    • kaggle.com
    Updated Jun 14, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Xavier (2018). Tweets during Nintendo E3 2018 Conference [Dataset]. https://www.kaggle.com/datasets/xvivancos/tweets-during-nintendo-e3-2018-conference/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 14, 2018
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Xavier
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    Data set containing Tweets captured during the Nintendo E3 2018 Conference.

    Content

    All Twitter APIs that return Tweets provide that data encoded using JavaScript Object Notation (JSON). JSON is based on key-value pairs, with named attributes and associated values. The JSON file include the following objects and attributes:

    • Tweet - Tweets are the basic atomic building block of all things Twitter. The Tweet object has a long list of ‘root-level’ attributes, including fundamental attributes such as id, created_at, and text. Tweet child objects include user, entities, and extended_entities. Tweets that are geo-tagged will have a place child object.

      • User - Contains public Twitter account metadata and describes the author of the Tweet with attributes as name, description, followers_count, friends_count, etc.

      • Entities - Provide metadata and additional contextual information about content posted on Twitter. The entities section provides arrays of common things included in Tweets: hashtags, user mentions, links, stock tickers (symbols), Twitter polls, and attached media.

      • Extended Entities - All Tweets with attached photos, videos and animated GIFs will include an extended_entities JSON object.

      • Places - Tweets can be associated with a location, generating a Tweet that has been ‘geo-tagged.’

    More information here.

    Acknowledgements

    I used the filterStream() function to open a connection to Twitter's Streaming API, using the keywords #NintendoE3 and #NintendoDirect. The capture started on Tuesday, June 12th 04:00 am UCT and finished on Tuesday, June 12th 05:00 am UCT.

    Inspiration

    • Time analysis
    • Try text mining!
    • Cross-language differences in Twitter
    • Use this data to produce a sentiment analysis
    • Twitter geolocation
    • Network analysis: graph theory, metrics and properties of the network, community detection, network visualization, etc.
  4. f

    The description of the attributes from the DependentVariable class in...

    • figshare.com
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Deepansh J. Srivastava; Thomas Vosegaard; Dominique Massiot; Philip J. Grandinetti (2023). The description of the attributes from the DependentVariable class in version 1.0 of the CSD model. [Dataset]. http://doi.org/10.1371/journal.pone.0225953.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Deepansh J. Srivastava; Thomas Vosegaard; Dominique Massiot; Philip J. Grandinetti
    License

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

    Description

    The description of the attributes from the DependentVariable class in version 1.0 of the CSD model.

  5. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang (2021). A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic [Dataset]. http://doi.org/10.6084/m9.figshare.13517105.v1

A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic

Explore at:
tiffAvailable download formats
Dataset updated
Mar 18, 2021
Dataset provided by
figshare
Authors
Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang
License

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

Description

The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.

Search
Clear search
Close search
Google apps
Main menu