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Legislative text, court decisions, regulatory filings, patents, government contracts, election data
9,340 datasets
Six land cover classes track vegetation recovery from energy exploration disturbances across a 2006-2007 timeframe. The Alberta Energy Regulator created this dataset using Landsat multispectral imagery and land use classification data. It covers a specific pilot area spanning multiple townships in Alberta.
Maria Font's dataset contains crystallographic models and map files for three protein structures from sulfate-reducing bacteria, with PDB codes 2RC0, 9RC2, and 9RBZ. The 4.6 GB archive also includes all AlphaFold models and associated data presented in the study. It was last updated on April 17, 2026.
2026-updated spatial data outlines planning requirements for activity centres in Perth and Peel. The policy, authored by the Western Australian Department of Planning, Lands and Heritage, integrates land use, public transport, and urban design criteria to coordinate development.
Historic districts in San Francisco are mapped by the San Francisco Planning Department. The dataset includes districts listed in Articles 10 and 11 of the San Francisco Planning Code and those listed or eligible for listing in the California and National Registers of Historic Places. It syncs nightly with the Planning Department's database and is updated several times a year when new districts are approved or listed.
Field interview data collected by the New Orleans Police Department (NOPD) from individuals stopped for questioning and complainants. The dataset is provided by the City of New Orleans and was last updated on March 22, 2026. The data is available in multiple formats including CSV, JSON, RDF, and XML.
Annual Vegetation Recovery Classification Results of the Play-Based Regulation Pilot Study Area is a geospatial dataset classifying vegetation recovery into six land cover classes. It was produced by the Alberta Energy Regulator using Landsat imagery from 2010 and 2011. The data assesses surface change from energy exploration within a defined pilot area in Alberta.
Vegetation recovery data classifies land into six recovery types for an Alberta energy regulation pilot area. The Alberta Energy Regulator produced this dataset using Landsat imagery from 2011 and 2012. It assesses surface change related to energy exploration activities.
Six vegetation recovery classes—shrub land, grassland, agricultural areas, coniferous, broadleaf, and mixed forest—were derived from Landsat multispectral imagery for 2012 and 2013. The dataset was produced by the Alberta Energy Regulator in 2014 to assess surface change within the Play-Based Regulation pilot area. It covers a region extending from Township 52 to 70, including towns like Edson and Whitecourt.
Annual Land Disturbance Classification Results of the Play-Based Regulation Pilot Study Area provides a 9-class categorization of vegetation loss and recovery from anthropogenic disturbances. The Alberta Energy Regulator created this dataset using 2012-2013 Landsat imagery and 2013 land cover data. It serves as baseline data for planning and monitoring surface infrastructure impacts in the pilot area.
2009-2010 Landsat imagery was used to classify vegetation loss from anthropogenic disturbances in a specific Alberta pilot region. The Alberta Energy Regulator created this dataset in 2014 to assess surface change from energy exploration, forestry, and agriculture. It contains vegetation loss data categorized into 9 distinct classes.
Thirteen distinct land cover classes, including coniferous forest, water bodies, and developed areas, are mapped across a 2005 Landsat image of Alberta. The Alberta Energy Regulator created this dataset to establish a baseline for assessing surface impacts from energy exploration. It covers a specific pilot area extending from Township 52 to 70, encompassing several towns.
Annual Vegetation Recovery Classification Results from the Alberta Energy Regulator's Play-Based Regulation pilot study area. The dataset classifies vegetation recovery into six land cover classes using Landsat multispectral imagery from 2005 and 2006. It was created by the Government of Alberta to assess surface change from energy exploration.
Alberta, Canada's Play-Based Regulation pilot area is covered by this land-use and land-cover classification dataset derived from 2010 Landsat imagery. It contains 13 distinct classes, including various forest types, developed areas, water bodies, and agricultural land. The dataset was created by the Alberta Energy Regulator to serve as baseline data for assessing surface change related to energy exploration.
Environment Agency records detail breaches of Environmental Permitting Regulations (2010) for waste and installation permits from 2014 onward. The dataset may exclude records on grounds of National Security or Commercial Confidentiality. A briefing accompanies the data, which is copyrighted by the Environment Agency in 2025.
Fisheries and Oceans Canada's Quebec region maintains a commercial catches sampling program for stock assessment in the Estuary and Gulf of St. Lawrence. The program provides biological data on 24 commercially exploited fish and invertebrate species, collected at wharf or at sea. Data collection began in 1976 and offers relatively large spatio-temporal coverage.
FY27–FY32 data underpinning a policy analysis of India's crude oil supply security. The dataset was created by author Adesh Mishra and is hosted by Harvard Dataverse. It was last updated on June 9, 2026.
OD0037 Value And Number Of Procurement Contracts from 2009 provides the total value of procurement contracts entered into by the Province of Prince Edward Island. The dataset is published by the Government of Prince Edward Island on the open_canada platform. It was last updated on 2026-04-17.
Mexico's expert survey on federal judicial elections conducted by FLACSO México in 2025. The dataset likely contains responses from experts on judicial elections and includes a specific module on populism. It was authored by Nicolas Loza and updated in May 2026.
Mexico's expert survey on federal judicial elections at the state level, conducted in 2025. Nicolas Loza from FLACSO México's Electoral Judicial Integrity project authored the dataset, which includes a module on populism. The dataset was last updated in May 2026.
PoFBench is a test-only benchmark designed to measure performance of policy-based custom filters in LLM-powered systems. It contains harmful content for AI filter evaluation, including biased expressions, crime-related scenarios, and jailbreak attempts. The dataset was created by SamsungSDS-Research and was last updated on 2026-05-06.