2022 Saskatoon Point-in-Time Homelessness Count

Making sure that “everyone counts” in Point-in-Time (PIT) Homelessness Counts is a key resource to address homelessness and support efforts to ensure that all Saskatoon residents have access to safe, affordable, and appropriate housing. Indigenous people continue to be impacted disproportionately and many households face high levels of precariousness and risk of homelessness—a reality that the COVID-19 pandemic has made starkly visible. Despite housing as a human right being recognized by international covenant and the 2019 National Housing Strategy Act, the health crisis has combined with such shadow epidemics as isolation, technology deficits, and food insecurity to aggravate vulnerabilities and leave many with nowhere safe to go and the heightened visibility of street homelessness. PIT Homelessness Counts gather data to help understand factors in homelessness, to give a human face to the statistics, and to help design and implement effective program and policy investments and interventions. The fifth Saskatoon PIT Homelessness Count—and second as part of Employment and Social Development Canada (ESDC)’s Reaching Home national coordinated PIT Count— including an indoor and outdoor enumeration, streets needs assessment, and public perception survey, was held in Saskatoon on April 28, 2022.

Datasets available for download

Additional Info

Field Value
Last Updated April 18, 2024, 16:56 (UTC)
Created February 15, 2024, 00:40 (UTC)
Domain / Topic
Domain or topic of the dataset being cataloged.
Published Date
Published date of the dataset.
Time Span (start date)
Start date of the data in the dataset.
Time Span (end date)
End date of time data in the dataset.
GeoSpatial Area Span
A spatial region or named place the dataset covers.
Field Value
Unique identifier for the dataset.
Access category
Type of access granted for the dataset (open, closed, etc).
Location of the dataset.
Data Service
Data service for accessing a dataset.
Owner of the dataset.
The Canadian Observatory on Homelessness
Contact Point
Who to contact regarding access.
Publisher of the dataset.
The Homeless Hub
Publisher Email
Email of the publisher
Author of the dataset.
Machiweyi Kunzekweguta, Isobel M. Findlay, Michael Kowalchuk, and Anh Pham
Accessed At
Date the data and metadata was accessed.
Field Value
Link to dataset description
A URL to an external document describing the dataset.
Language(s) of the dataset
Persistent Identifier
Data is identified by a persistent identifier.
Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
Format (CSV, XLS, TXT, PDF, etc)
Format of the dataset.
.pdf - application/pdf
Source of the dataset.
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
Contains Individual Data
Does the data hold individualized data?
Contains Identifiable Data
Does the data hold identifiable individual data?
Contains Indigenous Data
Does the data hold data about Indigenous communities?
Limits on use
Limits on use of data.
Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
Field Value
Data complies with a community standard (RDA-R1.3-01D)
This indicator requires that data complies with community standards. (FAIR ID = RDA-R1.3-01D).
Data uses knowledge representation expressed in standardised format (RDA-I1-01D)
The indicator serves to determine that an appropriate standard is used to express knowledge, in particular the data model and format (FAIR ID = RDA-I1-01D).
Data uses machine-understandable knowledge representation (RDA-I1-02D)
This indicator focuses on the machine-understandability aspect of the data. This means that data should be readable and thus interoperable for machines without any requirements such as specific translators or mappings (FAIR ID = RDA-I1-02D).
Data uses FAIR-compliant vocabularies (RDA-I2-01D)
The indicator requires the controlled vocabulary used for the data to conform to the FAIR principles, and at least be documented and resolvable using globally unique and persistent identifiers. The documentation needs to be easily findable and accessible (FAIR ID = RDA-I2-01D).
Data includes references to other data (RDA-I3-01D )
This indicator is about the way data is connected to other data, for example linking to previous or related research data that provides additional context to the data (FAIR ID = RDA-I3-01D).
Data is accessible through an access protocol that supports authentication and authorisation (RDA-A1.2-01D)
The indicator requires that if the data or local environment indicates a degree of additional protection then the access protocol must support authentication and authorisation of people and/or machines? (FARI ID = RDA-A1.2-01D)
Data can be accessed manually (RDA-A1-02D)
Data can be accessed manually (i.e., with human intervention, FAIR ID = RDA-A1-02D).
Data identifier resolves to a digital object (RDA-A1-03D)
Data identifier resolves to a digital object (FAIR ID = RDA-A1-03D)
Data is accessible through a standardised protocol (RDA-A1-04D)
The indicator refers to automated interactions between machines to access digital objects (FAIR ID = RDA-A1-04D).
Data can be accessed automatically (RDA-A1-05D)
Data can be accessed automatically (i.e. by a computer program, FAIR ID = RDA-A1-05D)
Data is accessible through a free access protocol (RDA-A1.1-01D)
The indicator requires that the protocol can be used free of charge which facilitates unfettered access (FAIR ID = RDA-A1.1-01D).
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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