Transportation Innovation Zones - Stakeholder Workshops Results
Datasets available for download
Info additionnelle
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| Dernière modification | mars 31, 2025, 12:47 (TU) |
| Créé le | octobre 4, 2024, 02:38 (TU) |
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Domain / Topic
Domain or topic of the dataset being cataloged.
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Transportation |
| Description
A description of the dataset.
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The City of Toronto hosted four online workshops in mid-September 2020 to gather feedback and recommendations from stakeholders on a proposed Transportation Innovation Zone (TIZ) program. The workshops had a total of 93 participants representing a wide range of organization types and interests. The workshops were hosted on the City's Webex Meetings web conferencing platform, and made use of the GroupMap.com online tool for collaborative idea rating on participant generated statements (ideas) in the form of questions and suggestions. This dataset is the export of results from these four GroupMap sessions. For more details on how the workshop was carried out and who participated, please see the TIZ Stakeholder Workshops Summary Reports under "Consultation" toronto.ca/tiz. |
| Mots-clés
Keywords/tags categorizing the dataset.
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Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
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.json - application/json, .xml, .xpdl, .xsl - application/xml, .csv - text/csv |
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Dataset Size
Dataset size in megabytes.
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Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
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Published Date
Published date of the dataset.
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2020-11-18 |
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Time Period Data Span (start date)
Start date of the data in the dataset.
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Time Period Data Span (end date)
End date of time data in the dataset.
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GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
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| chatgpt_summary | The dataset titled "Transportation Innovation Zones - Stakeholder Workshops Results" falls under the domain of Transportation. It is tagged with keywords such as Housing Potential, Innovation, Transportation, and survey. The dataset is available in various formats including JSON, XML, and CSV. It was published on November 18, 2020, and the location of the dataset is provided. The owner of the dataset is Transportation Services, specifically Jason Diceman, who can be contacted at Jason.diceman@toronto.ca. The dataset is published by the City of Toronto Open Data organization. The dataset provides the results of four online workshops hosted by the City of Toronto in mid-September 2020. These workshops aimed to gather feedback and recommendations on a proposed Transportation Innovation Zone (TIZ) program. The workshops had 93 participants representing a wide range of organization types and interests. The dataset is licensed under the Open Government Licence – Toronto. The resources available in the dataset include 'TIZ Workshops GroupMap Results (September 2020) - data', 'TIZ Workshops GroupMap Results (September 2020) - data.csv', 'TIZ Workshops GroupMap Results (September 2020) - data.xml', and 'TIZ Workshops GroupMap Results (September 2020) - data.json'. The metadata for the dataset was created on October 4, 2024, and last modified on March 18, 2025. |
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Access category
Type of access granted for the dataset (open, closed, service, etc).
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| Licence
License used to access the dataset.
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Open Government Licence – Toronto |
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Limits on use
Limits on use of data.
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Location
Location of the dataset.
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https://open.toronto.ca/dataset/transportation-innovation-zones-stakeholder-workshops-results |
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Data Service
Data service for accessing a dataset.
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Owner
Owner of the dataset.
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Transportation Services, Jason.diceman@toronto.ca |
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Contact Point
Who to contact regarding access?
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Contact Point Email
The email to contact regarding access?
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Publisher
Publisher of the dataset.
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Publisher Email
Email of the publisher.
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Jason.diceman@toronto.ca |
| Producteur
Author of the dataset.
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Jason.diceman@toronto.ca |
| Courriel de l'auteur
Email of the author.
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Jason.diceman@toronto.ca |
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Accessed At
Date the data and metadata was accessed.
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Identifier
Unique identifier for the dataset.
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Langue
Language(s) of the dataset
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Link to dataset description
A URL to an external document describing the dataset.
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Persistent Identifier
Data is identified by a persistent identifier.
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N/A |
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Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
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N/A |
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Contains data about individuals
Does the data hold data about individuals?
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N/A |
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Contains data about identifiable individuals
Does the data hold identifiable data about individual?
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N/A |
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Contains Indigenous Data
Does the data hold data about Indigenous communities?
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N/A |
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Source
Source of the dataset.
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https://www.toronto.ca/tiz |
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Version notes
Version notes about the dataset.
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Is version of another dataset
Link to dataset that it is a version of.
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Other versions
Link to datasets that are versions of it.
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Provenance Text
Provenance Text of the data.
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Provenance URL
Provenance URL of the data.
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Temporal resolution
Describes how granular the date/time data in the dataset is.
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GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
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GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
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Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
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Community Permission
Community permission (who gave permission).
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The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
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Number of data rows
If tabular dataset, total number of rows.
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Number of data columns
If tabular dataset, total number of unique columns.
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Number of data cells
If tabular dataset, total number of cells with data.
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Number of data relations
If RDF dataset, total number of triples.
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Number of entities
If RDF dataset, total number of entities.
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Number of data properties
If RDF dataset, total number of unique properties used by the triples.
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Data quality
Describes the quality of the data in the dataset.
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Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.
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