6 datasets found
  1. A Personalized Activity-based Spatiotemporal Risk Mapping Approach to...

    • figshare.com
    tiff
    Updated Mar 18, 2021
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    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
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    tiffAvailable download formats
    Dataset updated
    Mar 18, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    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. kartikmining

    • zenodo.org
    • data-staging.niaid.nih.gov
    txt, zip
    Updated Jan 21, 2020
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    Kartik Bajaj; Karthik Pattabiraman; Ali Mesbah; Kartik Bajaj; Karthik Pattabiraman; Ali Mesbah (2020). kartikmining [Dataset]. http://doi.org/10.5281/zenodo.495499
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    zip, txtAvailable download formats
    Dataset updated
    Jan 21, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Kartik Bajaj; Karthik Pattabiraman; Ali Mesbah; Kartik Bajaj; Karthik Pattabiraman; Ali Mesbah
    License

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

    Description

    Overview of Data

    This dataset is a data dump containing data from June 2008 to March 2013. Note that Stack Overflow originated only in June 2008. Therefore, this dump includes all the questions and answers on Stack Overflow until March 2013.

    Stack Overflow provides data dumps of all user generated data, including questions asked with the list of answers, the accepted answer per question, up/down votes, favourite counts, post score, comments, and anonymized user reputation. Stack Overflow allows users to tag discussions and has a reputation-based mechanism to rank users based on their active participation and contributions.

    Attribute Information

    Attribute info the datasets are in xml format including questions and answers for the following topics:

    * CSS
    * CSS-mobile
    * HTML5
    * HTML5-mobile
    * JavaScript
    * Javascript-mobile

  3. m

    Dataset of Malicious and Benign Webpages

    • data.mendeley.com
    Updated May 1, 2020
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    AK Singh (2020). Dataset of Malicious and Benign Webpages [Dataset]. http://doi.org/10.17632/gdx3pkwp47.1
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    Dataset updated
    May 1, 2020
    Authors
    AK Singh
    License

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

    Description

    The dataset contains extracted attributes from websites that can be used for Classification of webpages as malicious or benign. The dataset also includes raw page content including JavaScript code that can be used as unstructured data in Deep Learning or for extracting further attributes. The data has been collected by crawling the Internet using MalCrawler [1]. The labels have been verified using the Google Safe Browsing API [2]. Attributes have been selected based on their relevance [3]. The details of dataset attributes is as given below: 'url' - The URL of the webpage. 'ip_add' - IP Address of the webpage. 'geo_loc' - The geographic location where the webpage is hosted. 'url_len' - The length of URL. 'js_len' - Length of JavaScript code on the webpage. 'js_obf_len - Length of obfuscated JavaScript code. 'tld' - The Top Level Domain of the webpage. 'who_is' - Whether the WHO IS domain information is compete or not. 'https' - Whether the site uses https or http. 'content' - The raw webpage content including JavaScript code. 'label' - The class label for benign or malicious webpage.

    Python code for extraction of the above listed dataset attributes is attached. The Visualisation of this dataset and it python code is also attached. This visualisation can be seen online on Kaggle [5].

  4. f

    Mapping of CSD model attribute values to JSON serialized values.

    • figshare.com
    xls
    Updated May 31, 2023
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    Deepansh J. Srivastava; Thomas Vosegaard; Dominique Massiot; Philip J. Grandinetti (2023). Mapping of CSD model attribute values to JSON serialized values. [Dataset]. http://doi.org/10.1371/journal.pone.0225953.t006
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    xlsAvailable download formats
    Dataset updated
    May 31, 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

    Mapping of CSD model attribute values to JSON serialized values.

  5. The description of the attributes from the Dimension class in version 1.0 of...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 1, 2023
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    Deepansh J. Srivastava; Thomas Vosegaard; Dominique Massiot; Philip J. Grandinetti (2023). The description of the attributes from the Dimension class in version 1.0 of the CSD model. [Dataset]. http://doi.org/10.1371/journal.pone.0225953.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    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 Dimension class in version 1.0 of the CSD model.

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

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    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
    PLOShttp://plos.org/
    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.

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

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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
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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
Figsharehttp://figshare.com/
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.

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