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Offline RL trajectories, game data, robot demonstrations, RLHF, multi-agent interaction
11,150 datasets
City of Hobart provides an interactive geospatial tool for determining eligibility for local business support grants. The map allows users to search by address or current location to verify if a property is within the Hobart Local Government Area. This dataset is maintained by the City of Hobart Open Data team and is intended to streamline the application process for business assistance.
Australian Ocean Data Network hosts data from an experiment testing artificial selection for coral larval heat tolerance to support large-scale restoration. The study phenotyped and bred Acropora spathulata colonies, subjected their larvae to three thermal stress treatments (27°C, 33°C, 35°C), and deployed survivors in a field seeding experiment. The dataset likely contains results on larval mortality, genetic bottleneck effects, and recruit performance under field conditions.
2017 data from a project to define and monitor aesthetic values for the Great Barrier Reef World Heritage Area. The project, conducted by CSIRO under the NESP TWQ program, aimed to identify indicators for measuring natural beauty and aesthetic importance. Outcomes were intended to support the Reef 2050 Long-Term Sustainability Plan and improve management decisions.
The New South Wales Government's Major Evacuation Centre Guideline outlines key requirements and principles for managing evacuations. The document, Version 1.0 from June 2014, was prepared under the EMPLAN and Evacuation Management Guideline. It takes an all-hazards approach to ensure NSW is ready to deal with major emergencies and natural disasters.
The Evacuation Management Guideline is a policy document prepared under the EMPLAN framework by the NSW Government. It outlines key requirements, principles, authorities, and mechanisms for conducting evacuations under formal emergency management arrangements. The document takes an all-hazards approach and was last updated on 2026-06-26.
Natural England's 2022 dataset identifies areas for new ponds to benefit Great Crested Newt populations. It classifies land into 'Core' and 'Fringe' areas based on predicted newt presence and pond density, scoring habitat suitability using features like grassland density and proximity to woodland. The data excludes urban areas, roads, and flood zones, and is derived from multiple environmental and land cover sources.
This dataset identifies areas where new ponds would benefit Great Crested Newt populations in South and East Yorkshire. It classifies areas as 'Core' with a pond density of 2+ ponds per 1km square and 'Fringe' with a density of 1 pond, based on predicted newt presence and proximity. The data, created by Natural England and other UK agencies, scores habitat suitability based on features like pH, grassland density, and land classification, with attribution statements dating from 2007 to 2021.
A 2020 geospatial dataset from Natural England identifying areas in Somerset where new ponds would benefit Great Crested Newt populations. It classifies core and fringe areas based on predicted newt presence and pond density, scoring habitat suitability using grassland, woodland, arable, and soil type features. The data excludes urban areas, roads, rivers, and flood zones, and is based on land cover and soils data from multiple sources including Ordnance Survey and the Centre for Ecology & Hydrology.
Natural England's 2022 dataset identifies areas in Shropshire where new ponds would benefit Great Crested Newt populations. It classifies land into Core and Fringe areas based on pond density and predicted newt presence, scoring habitat suitability using features like grassland density and distance to woodland. The data is derived from multiple sources including land cover maps, Ordnance Survey data, and ecological surveys.
Natural England's 2021 dataset identifies priority areas for pond creation to benefit Great Crested Newt populations in North and West Yorkshire. It scores habitat suitability based on features like elevation, woodland density, soil drainage, and proximity to urban areas. The data is derived from multiple sources including Ordnance Survey, the Centre for Ecology & Hydrology, and the Freshwater Habitats Trust.
A 2022 dataset from Natural England identifying areas in Essex where new ponds would benefit Great Crested Newt populations. It classifies areas as 'Core' or 'Fringe' based on pond density and predicted newt presence, scoring habitat suitability using features like grassland, woodland, and distance from rivers. The data is derived from multiple sources including land cover maps, soil data, and local authority records.
Strategic Opportunity Areas for Great Crested Newt conservation in Cumbria identify locations where new ponds would benefit populations. The dataset scores habitat suitability based on seven positive features like grassland density and six negative features like urban density, with areas classified as 'Core' or 'Fringe'. Natural England produced this dataset in 2021, incorporating data from Ordnance Survey, the Centre for Ecology & Hydrology, and local authorities.
Department of Opportunities and Social Development Office locations across Nova Scotia include Civic Address, City, Postal Code, Name of Office, Phone, Fax, Hours, and Website. The data is provided by the Government of Nova Scotia and was last updated on 2026-07-15. It is available in multiple formats including XML, CSV, HTML, and RSS under the OGL-CA-2.0 license.
Spatial Services (DCS) provides a geospatial dataset depicting regulated river water sources as defined in gazetted Water Sharing Plans under the NSW Water Management Act 2000. The data represents an aggregation from In Force Sharing Plans for regulated systems. The dataset was initially published and last updated on 28/08/2024.
Wolf Island in the Galapagos Islands provides the location for four coral records (WLF03, WLF04, WLF05, WLF10) containing trace element and growth data. The dataset includes monthly-resolution trace metal (Sr/Ca, Mg/Ca, Ba/Ca) and skeletal density data, plus annual metrics for extension and calcification rates. It was contributed by Emma V. Reed of the University of Arizona, with some data previously published in a 2018 study.
Monthly inundated fraction data over China from 2000 to 2015, derived from the GIEMS-2 satellite product. The dataset was released by researchers from Peking University to support a study on the trade-off between forestation and wetland conservation. It provides a 0.5º × 0.5º spatial resolution view of surface water dynamics over a 16-year period.
A collection of raw and aggregated data from a study analyzing bibliographic references, mentions, and quotations in academic articles. The dataset is based on a sample of 729 articles from 147 journals across 27 thematic areas, containing 34,140 bibliographic references, 53,461 mentions, and 1,639 quotations. It was created by Erika Alves dos Santos at the Universidade de São Paulo as part of a doctoral thesis on FRBRizing bibliographic reference structures.
A 2023 revision of Australia's continental-scale seabed map, representing decades of data collection and analysis. The dataset is compiled from 1582 individual surveys using multibeam echosounders, LiDAR, and other sources, and covers an area from 92°E to 172°E and 8°S to 60°S. It provides a three-dimensional picture of the seafloor and is produced by the Australian Ocean Data Network.
Monthly nutrient and chlorophyll a distributions were measured for two years as part of the Port Phillip Bay Environmental Study. Reported data focus on nutrient variation in northern Port Phillip Bay during a high runoff period in September 1993 and a low runoff period in January 1995. The data were collected by the Australian Ocean Data Network using a continuous profiling technique aboard a ship, resolving features over scales of about 200 meters.
A cryo-electron microscopy structure of the Adeno-associated virus 2 (AAV2) complexed with its receptor (AAVR) at 2.8 Å resolution. The data was produced by researchers from Tsinghua University to characterize the precise recognition interface between the viral capsid and the receptor's PKD2 domain. The structure reveals interacting residues, and mutagenesis studies confirm their role in binding and viral infectivity.