Portrait of the dissemination of high-value municipal datasets

Data Québec's municipal partners began work in 2018 in order to determine the datasets most likely to be used by citizens. Building on the work of other Canadian jurisdictions, six criteria have been established to assess the value of data. Based on these criteria, high-value datasets were targeted. It is therefore starting in 2019 that the municipal partners of Data Quebec use this list of high-value datasets to prioritize their open data dissemination work. Also since 2017, [partners have been regularly setting standards] (https://www.donneesquebec.ca/fr/normes-etablies/) for data dissemination. Therefore, future work is planned in order to establish new standards for these high-value data. This portrait shows the progress of the dissemination and standardization of these datasets as well as their availability by municipality. High-value criteria: * Target socio-economic and environmental issues * Offer better service delivery * Encourage innovation and sustainable economic growth * Increase government transparency and accountability as well as information flow * Meet strong community demand * Meet strong community demand * Data quality

Datasets available for download

Additional Info

Field Value
Last Updated October 22, 2024, 15:51 (UTC)
Created October 1, 2024, 07:34 (UTC)
Domain / Topic
Domain or topic of the dataset being cataloged.
Society
Description
A description of the dataset.

Data Québec's municipal partners began work in 2018 in order to determine the datasets most likely to be used by citizens. Building on the work of other Canadian jurisdictions, six criteria have been established to assess the value of data. Based on these criteria, high-value datasets were targeted. It is therefore starting in 2019 that the municipal partners of Data Quebec use this list of high-value datasets to prioritize their open data dissemination work. Also since 2017, [partners have been regularly setting standards] (https://www.donneesquebec.ca/fr/normes-etablies/) for data dissemination. Therefore, future work is planned in order to establish new standards for these high-value data. This portrait shows the progress of the dissemination and standardization of these datasets as well as their availability by municipality. High-value criteria: * Target socio-economic and environmental issues * Offer better service delivery * Encourage innovation and sustainable economic growth * Increase government transparency and accountability as well as information flow * Meet strong community demand * Meet strong community demand * Data quality

Tags
Keywords/tags categorizing the dataset.
Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
Dataset Size
Dataset size in megabytes.
Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
Published Date
Published date of the dataset.
2019-05-24
Time Period Data Span (start date)
Start date of the data in the dataset.
Time Period Data Span (end date)
End date of time data in the dataset.
GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
Field Value
Access category
Type of access granted for the dataset (open, closed, service, etc).
License
License used to access the dataset.
Creative Commons 4.0 Attribution (CC-BY) licence – Quebec
Limits on use
Limits on use of data.
Location
Location of the dataset.
Data Service
Data service for accessing a dataset.
Owner
Owner of the dataset.
Government and Municipalities of Québec | Gouvernement et municipalités du Québec
Contact Point
Who to contact regarding access?
Ministère de la Cybersécurité et du Numérique
Contact Point Email
The email to contact regarding access?
Publisher
Publisher of the dataset.
Publisher Email
Email of the publisher.
pilote@donneesquebec.ca
Author
Author of the dataset.
Author Email
Email of the author.
Accessed At
Date the data and metadata was accessed.
Field Value
Identifier
Unique identifier for the dataset.
Language
Language(s) of the dataset
Link to dataset description
A URL to an external document describing the dataset.
Persistent Identifier
Data is identified by a persistent identifier.
Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
Contains data about individuals
Does the data hold data about individuals?
Contains data about identifiable individuals
Does the data hold identifiable data about individual?
Contains Indigenous Data
Does the data hold data about Indigenous communities?
Field Value
Source
Source of the dataset.
https://open.canada.ca/data/en/dataset/20ed36e5-85fb-4409-b272-b1fa1d8c92b3
Version notes
Version notes about the dataset.
Is version of another dataset
Link to dataset that it is a version of.
Other versions
Link to datasets that are versions of it.
Provenance Text
Provenance Text of the data.
Provenance URL
Provenance URL of the data.
Temporal resolution
Describes how granular the date/time data in the dataset is.
GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
Field Value
Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
Community Permission
Community permission (who gave permission).
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
Field Value
Number of data rows
If tabular dataset, total number of rows.
Number of data columns
If tabular dataset, total number of unique columns.
Number of data cells
If tabular dataset, total number of cells with data.
Number of data relations
If RDF dataset, total number of triples.
Number of entities
If RDF dataset, total number of entities.
Number of data properties
If RDF dataset, total number of unique properties used by the triples.
Data quality
Describes the quality of the data in the dataset.
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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