Early Years Forecast SDA12 2011 2031
Early years child population forecasts (0-12 years) are available by 2012 Service Delivery Area (SDA) from 2011 to 2031.
Early years child population forecasts (0-12 years) are available by 2012 Service Delivery Area (SDA). An updated version of these forecasts is available in the Early Years Forecast SDA 2017, 2016-2041 dataset. SDAs are a geography created in 2009 for service providers. SDAs were updated in 2012 to incorporate data from the 2011 Census. Peel has 77 SDAs. Early years population forecasts are consistent with the Regional Official Plan, sub-municipal data, and the Provincial Growth Plan.The forecasts are based on demographic analysis and knowledge of where growth and development can be accommodated within the Region.
The forecasts were provided at 5 year intervals on Census years (2011, 2016, 2021, etc.). Intermediate years were calculated using interpolation.
Datasets available for download
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Early Year Forecasts 2011Table
Layer 0 via ArcGIS REST API
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Early Year Forecasts 2011 (Explore)HTML
Explore Early Year Forecasts 2011 on ArcGIS Hub
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FeatureServerURL
Additional resource from ArcGIS Hub
Additional Info
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| Last Updated | March 24, 2026, 20:52 (UTC) |
| Created | March 24, 2026, 20:52 (UTC) |
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Domain / Topic
Domain or topic of the dataset being cataloged.
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Title
Title for the Dataset.
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Early Years Forecast SDA12 2011 2031 |
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Description
A description of the dataset.
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Early years child population forecasts (0-12 years) are available by 2012 Service Delivery Area (SDA) from 2011 to 2031. Early years child population forecasts (0-12 years) are available by 2012 Service Delivery Area (SDA). An updated version of these forecasts is available in the Early Years Forecast SDA 2017, 2016-2041 dataset. SDAs are a geography created in 2009 for service providers. SDAs were updated in 2012 to incorporate data from the 2011 Census. Peel has 77 SDAs. Early years population forecasts are consistent with the Regional Official Plan, sub-municipal data, and the Provincial Growth Plan.The forecasts are based on demographic analysis and knowledge of where growth and development can be accommodated within the Region. The forecasts were provided at 5 year intervals on Census years (2011, 2016, 2021, etc.). Intermediate years were calculated using interpolation. |
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Tags / Keywords
Keywords/tags categorizing the dataset.
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Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
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Dataset Size
Dataset size in megabytes.
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136.0 |
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Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
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da0afa7dfa124846a9d6e486443c1152 |
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Published Date
Published date of the dataset.
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2019-11-26 |
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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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Access category
Type of access granted for the dataset (open, closed, service, etc).
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public |
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License
License used to access the dataset.
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Open Data Licence for The Regional Municipality of Peel (Version 1.0) |
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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://data.peelregion.ca/datasets/RegionofPeel::early-years-forecast-sda12-2011-2031 |
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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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[email protected]_RegionofPeel |
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Contact Point
Who to contact regarding access?
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Regional Municipality of Peel |
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Contact Point Email
The email to contact regarding access?
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http://www.peelregion.ca/ |
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Publisher
Publisher of the dataset.
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Regional Municipality of Peel |
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Publisher Email
Email of the publisher.
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Author
Author of the dataset.
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[email protected]_RegionofPeel |
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Author Email
Email of the author.
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Accessed At
Date the data and metadata was accessed.
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2020-08-12 |
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Identifier
Unique identifier for the dataset.
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da0afa7dfa124846a9d6e486443c1152 |
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Language
Language(s) of the dataset
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English |
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Link to dataset description
A URL to an external document describing the dataset.
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https://data.peelregion.ca/datasets/RegionofPeel::early-years-forecast-sda12-2011-2031 |
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Persistent Identifier
Data is identified by a persistent identifier.
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Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
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Contains data about individuals
Does the data hold data about individuals?
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Contains data about identifiable individuals
Does the data hold identifiable data about individual?
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Contains Indigenous Data
Does the data hold data about Indigenous communities?
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Portal Type
Platform type of the source portal.
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Version
Version of the datatset
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None |
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Source
Source of the dataset.
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None |
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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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Region of Peel - Human Services |
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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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400 |
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Number of data columns
If tabular dataset, total number of unique columns.
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24 |
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Number of data cells
If tabular dataset, total number of cells with data.
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9600 |
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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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