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LIVING DATA PROJECT STORIES

Water health and data rescue for Canada's Watershed Reports

7/31/2025

 
Data Rescue Intern: David Zilkey

​In January 2025, I had the opportunity to complete a data rescue internship with Water Rangers as part of the Living Data Project. Water Rangers is a non-profit organization whose goal is to empower communities to protect and steward their local waterways. They do this in several ways, including the production of educational materials and water testing kits designed for use by citizen scientists.
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Figure 1: Interactive Watershed Reports map from www.watershedreports.ca. Users can click on their watershed to explore its report and zoom in to individual subwatersheds.

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Long-term vegetation and soil data from Banff & Jasper Forests

7/31/2025

 
Data Rescue intern: Mobina Gholamhosseini

During Fall 2023 to Winter 2024, I had the opportunity to take part in a data rescue internship through the Canadian Institute of Ecology and Evolution’s Living Data Project (LDP), supported by an NSERC CREATE. As a graduate student at the Université de Montréal, I was thrilled to contribute to the accessibility of valuable ecological data. The focus of the internship was on a valuable dataset originally collected in 1967–68 from 63 lodgepole pine-dominated forest stands in Banff and Jasper National Parks (Alberta, Canada). These data — on soils, trees, and understory vegetation — represent an important snapshot of forest conditions from over 50 years ago, collected during the MSc thesis work of Roger Hnatiuk.
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New Brunswick Historical Maps Digitization

7/31/2025

 
Data Rescue Intern: Yiduo “Harry” Zhang 
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​The 1957-1958 New Brunswick topographic map series carries valuable data of historical land cover, land use, and landscape feature locations throughout the province that are only available on paper. Many of these paper maps currently in possession of the Canadian Forest Service also contain handwritten annotations about historical field sample sites cumulated through decades of work done by various researchers from the agency. With its provincial scope and a resolution of 1:50,000 scale, this historical dataset could prove invaluable for studies of species distribution and habitat change. However, in order to effectively utilize, store, and distribute this spatial dataset, it first needs to be digitized. 
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Caption: Screenshot of the georeferenced maps
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Coastal Giant Salamanders in the Chilliwack River Valley

7/31/2025

 
Data Rescue Intern: Sasindu Gunawardana

In the summer of 2024, I had the opportunity to work as a data rescue intern with the Living Data Project. During my internship, I worked on a crucial dataset belonging to Dr. John Richardson from UBC, which documents a long-term (1994–2001) mark-recapture study of Coastal Giant Salamanders in 12 small streams in the Chilliwack River Valley, British Columbia.
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Marine radar counts of Marbled Murrelets

7/31/2025

 
Data Rescue Intern: Sarah Ravoth

In winter 2024, I was an intern with Environment and Climate Change Canada through the LDP program, working with a long-term seabird dataset. Specifically, I worked with data collected on marbled murrelets, a small seabird found in the North Pacific. Marbled murrelets spend most of their time foraging at sea and breed in old-growth forests along the coast; they are listed as Threatened under the Canadian Species at Risk Act primarily due to loss of old growth nesting habitat.
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Survey boat with radar station anchored at Power River catchment entrance.

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Rescuing four-decade-old benthic invertebrate data from the Turkey Lakes Watershed in Ontario

7/31/2025

 
Data Rescue Intern: Diana Bertuol Garcia

From December 2024 to February 2025, I worked as a Data Rescue Intern with the Department in Fisheries and Ocean (DFO) from Ontario. Since the 1980s, the DFO office in Sault Ste. Marie, Ontario has collected samples of lakes and streams sediments to characterize benthic communities across Ontario water bodies and to assess the magnitude of temporal and spatial variability in species composition across seasons, years, depths and different lakes. Much of the work has been concentrated in the Turkey Lakes Watershed (TLW), as part of the whole-ecosystem monitoring project on the effect of acid rain on terrestrial and aquatic ecosystems. Many sub-projects related to benthic communities have been conducted throughout the years, and the consistency of data collection and methods was dependent on the duration of each sub-project and funding available. Moreover, most of the data had been collected in the 1980s, and thus most people involved in data collection had already left the organization. As a result, the data was scattered across Excel files and lots of PDF files of scanned old documents without documentation or explanatory documents. Hence, my goal for the internship was to organize these files into a cohesive and well-documented relational dataset that could be readily uploaded to the government open data portal.
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Photos courtesy of Fisheries and Oceans Canada in Sault Ste. Marie, ON

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St. Denis National Wildlife - hackathon

7/31/2025

 
Data Rescue Intern: Faraz Khan

My LDP internship was focused on rescuing bird survey data collected by Environment and Climate Change Canada (ECCC) from the 1980s to the 1990s in the St. Denis National Wildlife Area, in Saskatchewan. The St Denis National Wildlife area is in a region known as the Prairie Pothole Region, a system of wetlands which spans the north central portion of the North American Great Plains. This complex of wetlands is ecologically important, and acts as a harbour for many species of plants and animals. St. Denis has been under study since the 1960s, where researchers collected various metrics such as water quality, toxicology, wildlife counts, hydrological data, and meteorological information. Though St Denis has been under continued study for approximately 60 years, there has been little progress made in collating a cohesive dataset. A large amount of data involving the same metrics have been collected by different researchers across different time frames. As such, it is a worthwhile effort to collect these disparate datasets from St. Denis to form a continuous set of data.
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