Data tables for Cost-Effective Energy Pathways Study final report
This dataset contains the data tables for the final report of the Cost-Effective Energy Pathways Study for Ontario ("Study"). This report is available in English and posted at: Cost Effective Energy Pathways Study for Ontario The Ministry of Energy and Mines commissioned ESMIA Consultants, working with Dunsky Energy + Climate Advisors, to conduct an independent whole-economy energy modelling study, using an open competitive procurement. The goal of the Study was to analyze how Ontario’s energy sector could be impacted by electrification and changing consumer energy demand. Work on the Study occurred from December 2022 to September 2024. The Study takes a holistic view of Ontario’s economy to assess cost-effective scenarios to meet energy needs across all sectors up to 2050. The Study represents independent advice for the government’s consideration. It may not reflect government perspectives or directions on Ontario's energy transition. The Study does not provide policy advice, reflect regional differences, or fully capture the energy system's technical, behavioural, or market complexities. See the final report for details on the modelling approach and some of the associated key considerations and caveats.
Datasets available for download
Additional Info
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| Last Updated | October 20, 2025, 02:25 (UTC) |
| Created | October 20, 2025, 02:25 (UTC) |
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Domain / Topic
Domain or topic of the dataset being cataloged.
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Economy |
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Title
Title for the Dataset.
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Data tables for Cost-Effective Energy Pathways Study final report |
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Description
A description of the dataset.
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This dataset contains the data tables for the final report of the Cost-Effective Energy Pathways Study for Ontario ("Study"). This report is available in English and posted at: Cost Effective Energy Pathways Study for Ontario The Ministry of Energy and Mines commissioned ESMIA Consultants, working with Dunsky Energy + Climate Advisors, to conduct an independent whole-economy energy modelling study, using an open competitive procurement. The goal of the Study was to analyze how Ontario’s energy sector could be impacted by electrification and changing consumer energy demand. Work on the Study occurred from December 2022 to September 2024. The Study takes a holistic view of Ontario’s economy to assess cost-effective scenarios to meet energy needs across all sectors up to 2050. The Study represents independent advice for the government’s consideration. It may not reflect government perspectives or directions on Ontario's energy transition. The Study does not provide policy advice, reflect regional differences, or fully capture the energy system's technical, behavioural, or market complexities. See the final report for details on the modelling approach and some of the associated key considerations and caveats. |
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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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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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2025-06-12 |
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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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License
License used to access the dataset.
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Open Government Licence – Ontario |
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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.canada.ca/data/en/dataset/2b395d98-2571-4742-9587-c7addcce04bc |
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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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Government of Ontario | Gouvernement de l'Ontario |
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Contact Point
Who to contact regarding access?
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Energy, Northern Development and Mines |
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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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Author
Author of the dataset.
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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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Identifier
Unique identifier for the dataset.
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Language
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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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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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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