The following dataset contains a list of all publicly funded universities and the Nova Scotia Community College (NSCC) campuses across the Province including mailing addresses and geographic coordinates.

This dataset provides information which is currently displayed on the Residential Care Programs Map. The intent of the [Residential Care Programs Map](https://moh.apps.gov.bc.ca/alrc/) is to provide an online resource to assist families searching for all types of care under the Residential Care Regulation, including long term care, community living, hospice, acquired brain injury, mental health, substance use and child and youth residential care. Information is listed by care type, licensee, name of facility, address, city and maximum capacity. This dataset includes both publicly subsidized and private paid facilities. New licensed residential care facilities are added as they become operational. The dataset is updated biweekly.

All island polygons. Islands may overlap as there are islands within islands (e.g., a lake on an island contains an island). GNIS_NAME_1 contains the most atomic name for the island. For example, there are 3797 "Haida Gwaii" islands. If the island has not been named as part of a more specific group or with an individual name, "Haida Gwaii" is the GNIS_NAME_1 value. GNIS_NAME_2 and GNIS_NAME_3 values are null. If the island has a more specific name, "Haida Gwaii" moves to GNIS_NAME_2, and the more atomic name, such as "Moresby Island" is the GNIS_NAME_1. If the island has an individual name, belongs to a group, and is part of Haida Gwaii, the same logic of naming from most to least specific applies. For example, GNIS_NAME_1 = "George Island", GNIS_NAME_2 = "Copper Islands", GNIS_NAME_3 = "Haida Gwaii".

This geospatial data depicts potential development areas (PDAs) recommended by the Committee for the Regional Assessment of Offshore Wind Development in Nova Scotia. The Committee for the Regional Assessment of Offshore Wind Development in Nova Scotia (Committee) provides federal and provincial Ministers with information, knowledge, and analysis regarding future offshore wind (OSW) development in Nova Scotia. Its work is intended to inform and improve future planning, licencing, permitting, and impact assessment processes. Under the Terms of Reference, the Committee submitted an interim report to Ministers on March 23, 2024. This report included the preliminary identification of recommended areas for potential future development areas (PFDAs) for offshore wind. Based on work completed since the interim report, the Committee issued its final report on January 23, 2025, which included refined development areas, the Potential Development Areas (PDAs). These PDAs are based on technical feasibility (using available information) and have the least impact on other offshore users. It should be noted that the PDAs are recommendations only and do not reflect official offshore wind energy areas.

In place since fall 1994, the sentinel fisheries program is the result of a collaboration between Fisheries and Oceans Canada (DFO) and Quebec and Newfoundland commercial fishermen's associations. Under this program, contracts are awarded by tender to fishermen’s associations to carry out fishing activities according to scientific protocols developed by DFO. The main objective of this survey is to collect data that will be used to calculate abundance indices for the northern Gulf of St. Lawrence Atlantic cod stock. Description of fixed gears survey The fixed gear sentinel fisheries of the northern Gulf of St. Lawrence are conducted in the sub-division 3Pn and the divisions 4R, 4S of the Northwest Atlantic Fisheries Organization (NAFO) using fixed gillnets or longlines (other fishing gears were also used at the start of the program). Fishing activities with nets must have a mesh size of 5 ½ inches (140mm) and are limited to a maximum of 6 to 20 nets depending on the region and capture and the target immersion time is between 19 to 24 hours. Longline fishing activities, for its part, must be carried out with traditional J #16 or C #12 hooks. The maximum number of hooks varies from 500 to 1000, depending on the catch, and the target immersion time is 4 to 6 hours. Data are collected by observers at sea or by technicians. Data For each fishing activity, the total catch is sorted and weighed by species. For each species other than Atlantic cod, the number of individuals caught is noted. Atlantic cod are then measured at the fork (cm). Other biological data such as weight (total, gonad, liver and stomach), age, sex and maturity can then be collected on a subsample of cod. The biological data are divided into 4 files: a “Metadata” file containing set information, a “Catches” file containing catches per set for fish taxa, a “Carbio” file containing biological and morphometric measurements per individual, a “Freql” file containing the length frequency of fish. The data collected as part of this program is available below. It is important to note, however, that 1) only traits deemed successful have been retained; 2) historical data may contain inaccuracies; 3) the most recent survey is not available for validation purposes.

Vaccinium is a group of small fruit-bearing shrubs that includes the blueberries, cranberries, and lingonberries which are among the few major crops grown in Canada that are truly native to Canada. Dataset Type: Occurrence Specimen Type: Preserved specimens

The Canadian indexes of social resilience and vulnerability were created to provide area-based information on resilience and vulnerability to natural hazards and disasters across Canada. Specifically, the Canadian Index of Social Resilience (CISR) aims to reflect a community’s ability to respond to and recover from natural hazards. In contrast, the Canadian Index of Social Vulnerability (CISV) aims to reflect the social vulnerability of an area based on factors that have the potential to amplify the impact of disasters on populations. Before the CISR and CISV were built, indicator frameworks were developed for social resilience and social vulnerability, respectively. Indicators were selected because of their demonstrated association with social resilience or social vulnerability. The selection was informed by the theoretical and research literature, existing indexes, availability of relevant data and engagement with subject-matter experts. The CISR and the CISV were created using data from Dissemination areas (DAs) across the country. The selected indicators were included in a principal component analysis, which is a statistical technique that allows a large number of indicators to be collapsed into a smaller number of interpretable components. Based on the results of the principal component analysis, DA-level scores were calculated for each index. Higher CISR scores correspond to DAs that are more resilient and higher CISV scores correspond to DAs that are more vulnerable. These indexes can be used to better understand areas which may experience the largest disproportional social impacts from natural hazards.

The Agri-Environmental Spatial Data (AESD) product from the Census of Agriculture provides a large selection of farm-level variables from the Census of Agriculture and uses alternative data sources to improve the spatial distribution of the production activities. Therefore, the AESD database offers clients the possibility to better analyze the impact of agriculture activities on the environment and produce key indicators, or for any applications where accurate location of activities matters. Variables are offered using two types of physical boundaries: by Soil Landscape of Canada polygons and by Sub-sub-drainage areas (watersheds). The focus of the redistribution of the data is on the field crops and land use variables, but the database includes all census variables related to crops, livestock and management practices. This frame can also be used to extract Census of Agriculture data by custom geographic areas. Also, users interested in this version of the Census of Agriculture database using administrative types of regions can request it. In both cases, please contact Statistics Canada. This file was produced by Statistics Canada, Agriculture Division, Remote Sensing and Geospatial Analysis section, 2022, Ottawa.

This dataset was designed for Environment and Climate Change Canada's (ECCC) National Environmental Emergencies Center (NEEC) for oil spill preparedness and response. The polygons from this layer come from the coastal ecosystems geodatabase as part of the Mapping of coastal ecosystems of the Estuary and Gulf of St. Lawrence project. This layer represents semi-vegetated (25-75%) and vegetated (75-100%) zones of which marsh vegetation is the dominant. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure. The mapping of coastal ecosystems was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project (https: //ldgizc.uqar.ca/Web/projets/projet-resilience-cotiere) funded by the MELCC; and by the Fisheries and Oceans Canada team, as part of its Integrated marine response planning (IMRP) component of the Oceans Protection Plan (OPP), with the objective of updating the Marine Oil Spill Preparedness and Response Regime of Canada. The master geodatabase of coastal ecosystems is hosted and distributed by UQAR on their SIGEC-Web mapping platform: https://ldgizc.uqar.ca/Web/sigecweb The characterization of marshes was mainly carried out using photo-interpretation of RVBI aerial photos acquired by DFO (2015-2020) and oblique photos taken by helicopter acquired by UQAR in 2017. This dataset also includes the information from validation stations visited by UQAR (2018-2020), used to validate and refine the photo-interpretation.