Search

Search Results

Western University Dataverse Logo
Borealis
Taylor, Zack; Lucas, Jack; Hewitt, Christopher Macdonald 2022-09-30 The Unified Infrastructure for Canadian Census Research, or UNI·CEN, is a comprehensive database of historical and contemporary Canadian aggregate Census data, digital boundary files, and ancillary material, all provided in modern data formats. The goal of the project is to liberate Canadian Census data so that it can be easily used by academic researchers, students, and the public. <br><br> The documentation describes the processes used to digitize historical Federal Electoral District Boundaries. <br><br> Citation: Taylor, Zack and Christopher Macdonald Hewitt. 2022. "UNI·CEN Documentation Report 5: Federal Electoral District Digitization Project.” London, Canada: Network for Economic and Social Trends, Western University.
Western University Dataverse Logo
Borealis
Taylor, Zachary; Hewitt, Christopher Macdonald 2022-09-21 The <strong>Unified Infrastructure for Canadian Census Research</strong>, or UNI·CEN, is a comprehensive database of historical and contemporary Canadian aggregate Census data, digital boundary files, and ancillary material, all provided in modern data formats. The goal of the project is to liberate Canadian Census data so that it can be easily used by academic researchers, students, and the public. <br><br> The documentation describes the processes used to digitize the 1951, 1956, 1961, and 1966 Census Tract boundaries and associated datasets. <br><br> <strong>Citation:</strong> Taylor, Zack and Christopher Macdonald Hewitt. 2022. "UNI·CEN Documentation Report 4: Early Postwar Census Tract Digitization Project.” London, Canada: Network for Economic and Social Trends, Western University. https://ir.lib.uwo.ca/nest_observatory_docs/1 <br><br> <strong>Available at:</strong> https://ir.lib.uwo.ca/nest_observatory_docs/1
Western University Dataverse Logo
Borealis
Taylor, Zachary; Lucas, Jack; Kirby, J.P.; Hewitt, Christopher Macdonald 2023-03-27 Replication Data for Taylor, Zack, Jack Lucas, J.P. Kirby, and Christopher Macdonald Hewitt. 2023. “Canada’s Federal Electoral Districts, 1867–2021: New Digital Boundary Files and a Comparative Investigation of District Compactness.” Canadian Journal of Political Science.
Western University Dataverse Logo
Borealis
Taylor, Zachary; Hewitt, Christopher Macdonald 2022-09-21 The <strong>Unified Infrastructure for Canadian Census Research</strong>, or UNI·CEN, is a comprehensive database of historical and contemporary Canadian aggregate Census data, digital boundary files, and ancillary material, all provided in modern data formats. The goal of the project is to liberate Canadian Census data so that it can be easily used by academic researchers, students, and the public. <br><br> The <strong>UNI·CEN Digital Boundary Files</strong> series contains versions of all publicly available digital boundary files with shorelines harmonized, at five levels of Census geography. This documentation report describes the procedures used to create the files, as well as data sources and available file formats. <br><br> <strong>Citation:</strong> Taylor, Zack and Christopher Macdonald Hewitt. 2022. "UNI·CEN Documentation Report 3: Digital Boundary Files.” London, Canada: Network for Economic and Social Trends, Western University. https://ir.lib.uwo.ca/nest_observatory_docs/2 <br><br> <strong>Available at:</strong> https://ir.lib.uwo.ca/nest_observatory_docs/2
Western University Dataverse Logo
Borealis
Taylor, Zachary; Hewitt, Christopher Macdonald 2022-07-27 Early Postwar Canadian Census Data Creation Project Files. Contains digitized census tract boundary files and associated tabular data, with codebooks, for Census years 1951, 1956, 1961, and 1966.

Map search instructions

1.Turn on the map filter by clicking the “Limit by map area” toggle.
2.Move the map to display your area of interest. Holding the shift key and clicking to draw a box allows for zooming in on a specific area. Search results change as the map moves.
3.Access a record by clicking on an item in the search results or by clicking on a location pin and the linked record title.
Note: Clusters are intended to provide a visual preview of data location. Because there is a maximum of 50 records displayed on the map, they may not be a completely accurate reflection of the total number of search results.