Great Lakes Sediment Archive Database (1960-1975)
The Great Lakes Sediment Database (also known as the National Water Research Institute (NWRI) Sediment Archive) is an archive of data on the sediments of the Great Lakes, their connecting channels, and the St. Lawrence River which was collected by NWRI and in cooperation with other agencies between 1960 and 1975. It is housed in Environment and Climate Change Canada's Canada Centre for Inland Waters in Burlington, Ontario. The data has been subdivided into two groups according to location and purpose:
1.Great Lakes Basin Sediment Data: physical and geochemical data for sediment samples and cores collected lakewide in lakes Ontario, Erie, St. Clair, Huron (including Georgian Bay), Michigan and Superior between 1960 and 1975 by R.L. Thomas, A.L.W. Kemp and C.F.M. Lewis of NWRI. The data includes descriptions of sediment and core properties, grain-size statistics and sediment geochemistry;
- Nearshore Sediments Data: physical data for samples and cores, bathymetry, and sediment thickness collected in the Canadian nearshore zone of lakes Ontario, Erie, St. Clair, Huron and Georgian Bay between 1960 and 1975. The data includes descriptions of sediment and core properties, grain-size statistics, sediment patterns and x-radiographs of sediment cores. Underwater photographs are also available for Lake Huron and Georgian Bay.
The database was prepared to preserve historic and current sediment data and make it available for research, remediation, lake and shoreline management, habitat studies and engineering projects. Because the basin and nearshore surveys were the first systematic and detailed surveys of both zones, their data should also be useful for studies of trends in physical properties, sediment transport, and contamination or trophic levels. The sediment-sample archive serves the same purpose by making historic samples available for analysis of changes in composition or geotechnical properties.
Supplemental Information
The database was produced by Dr. Norm Rukavina, formerly of NWRI, as an archive of his own sediment data and that of some of his colleagues and associates. Marilyn Dunnett was responsible for the editing of the data and its quality control, and Chris Prokopec for the organization of the database, its metadata description, and the preparation of ArcView maps.
Supporting Projects: Great Lakes Action Plan (GLAP)
Datasets available for download
Additional Info
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| Last Updated | October 20, 2025, 03:07 (UTC) |
| Created | October 20, 2025, 03:07 (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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Great Lakes Sediment Archive Database (1960-1975) |
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Description
A description of the dataset.
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The Great Lakes Sediment Database (also known as the National Water Research Institute (NWRI) Sediment Archive) is an archive of data on the sediments of the Great Lakes, their connecting channels, and the St. Lawrence River which was collected by NWRI and in cooperation with other agencies between 1960 and 1975. It is housed in Environment and Climate Change Canada's Canada Centre for Inland Waters in Burlington, Ontario. The data has been subdivided into two groups according to location and purpose: 1.Great Lakes Basin Sediment Data: physical and geochemical data for sediment samples and cores collected lakewide in lakes Ontario, Erie, St. Clair, Huron (including Georgian Bay), Michigan and Superior between 1960 and 1975 by R.L. Thomas, A.L.W. Kemp and C.F.M. Lewis of NWRI. The data includes descriptions of sediment and core properties, grain-size statistics and sediment geochemistry;
The database was prepared to preserve historic and current sediment data and make it available for research, remediation, lake and shoreline management, habitat studies and engineering projects. Because the basin and nearshore surveys were the first systematic and detailed surveys of both zones, their data should also be useful for studies of trends in physical properties, sediment transport, and contamination or trophic levels. The sediment-sample archive serves the same purpose by making historic samples available for analysis of changes in composition or geotechnical properties. Supplemental Information The database was produced by Dr. Norm Rukavina, formerly of NWRI, as an archive of his own sediment data and that of some of his colleagues and associates. Marilyn Dunnett was responsible for the editing of the data and its quality control, and Chris Prokopec for the organization of the database, its metadata description, and the preparation of ArcView maps. Supporting Projects: Great Lakes Action Plan (GLAP) |
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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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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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2016-08-04 |
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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 - Canada |
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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/67393512-584f-442b-ae9c-52be0f2aede1 |
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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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Environment and Climate Change Canada | Environnement et Changement climatique Canada |
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Contact Point
Who to contact regarding access?
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Government of Canada; Environment and Climate Change Canada, [email protected] |
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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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[email protected] |
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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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