Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
942
datasets available to search
ShareScore release 0.9.0
Dataset results
942 results for “Scenarios”
Figure 2 in Environmental niche modelling of the Chinese pond mussel invasion in Europe under climate change scenarios
Figure 2. Response curves of the environmental variables selected for prediction of S. woodiana distribution under the recent climate scenario. Each curve (green line) shows how the logistic prediction changes as each environmental variable is varied. The orange dashed line crosses the maximum value of the variable.
Experiments for 'Scenario-Based Verification of Uncertain Parametric MDPs'
<p>This artifact accompanies the 2022 article in the International Journal on Software Tools for Technology Transfer (STTT) with the same title. The artifact contains a docker container, which can be unzipped and then loaded with:</p> <pre><code>docker load -i upMDPs_STTT.tar</code></pre> <p>Please refer to the README in the ZIP file for more information, or to the Git repository on <a href="https://gitlab.science.ru.nl/tbadings/sttt-scenario">https://gitlab.science.ru.nl/tbadings/sttt-scenario</a>.</p> <p>The Python source code from which the Docker container is created is available in the <code>upMDPs_STTT_source.zip</code> file. This zip file contains the exact content of the Git repository above (accessed on August 20, 2024).</p>
Future forest flux (e.g., GPP, NPP, NEP) simulated by the optimized InTEC model under four SSP-RCP scenarios
Open the record for dataset details and reuse information.
A Potential Method for Identifying Milk Adulteration and Pb(II) Contamination Scenarios Using Principal Component Analysis from Smartphone Photographs
<p>Early Research Data</p>
Exploring Human and Artificial Attention Mechanisms in Driving Scenarios
Open the record for dataset details and reuse information.
Data from: Heritable variation and lack of tradeoffs suggest adaptive capacity in Acropora cervicornis despite negative synergism under climate change scenarios
<p>Knowledge of multi-stressor interactions and the potential for trade-offs among tolerance traits is essential for developing intervention strategies for the conservation and restoration of reef ecosystems in a changing climate. Thermal extremes and acidification are two major co-occurring stresses predicted to limit the recovery of vital Caribbean reef-building corals. Here we conducted an aquaria-based experiment to quantify the effects of increased water temperatures and pCO2 individually and in concert on 12 genotypes of the endangered branching coral, Acropora cervicornis, currently being reared and outplanted for large-scale coral restoration. Quantification of 11 host, symbiont, and holobiont traits throughout the 2-month long experiment showed several synergistic negative effects, where the combined stress treatment often caused greater reduction in physiological function than the individual stressors alone. However, we found significant genetic variation for most traits and positive trait correlations among treatments indicating an apparent lack of tradeoffs, suggesting that adaptive evolution will not be constrained. Our results suggest that it may be possible to incorporate climate-resistant coral genotypes into restoration and selective breeding programs, potentially accelerating adaptation. </p>
Challenges of students and residents of human medicine in the first four months of the fight against the Covid-19 pandemic – Implications for future waves and scenarios
<p><strong>Introduction:</strong> In the fight against the Covid-19 pandemic, medical students and residents are expected to adapt and contribute in a healthcare environment characterized by ever-changing measures and policies. The aim of this narrative review is to provide a summary of the literature that addresses the challenges of students and residents of human medicine in the first four months of the fight against the Covid-19 pandemic in order to identify gaps and find implications areas for improvement within the current situation and for potential future scenarios. <br> <strong>Methods:</strong> We performed a systematic literature search and content analysis (CA) of articles available in English language that address the challenges of students and residents of human medicine in the first four months of the fight against the Covid-19 pandemic.<br> <strong>Results:</strong> We retrieved 82 articles from a wide range of journals, professional backgrounds and countries. CA identified five recurring subgroup topics: «faculty preparation», «uncertaintiesy and mental health», «clinical knowledge», «rights and obligations» and «(self-) support and supply». Within these subgroups the main concerns of «(re)deployment», «interruption of training and career», «safety issues», «transmission of disease», and «restricted social interaction» were identified as potential stressors that hold a risk for fatigue, loss of morale and burnout.<br> <strong>Discussion:</strong> Students and residents are willing and able to participate in the fight against Covid-19 when provided with appropriate deployment to areas of need, thorough supervision, legal guidance, Personal Protective Equipment (PPE)safety measures and, clinical necessary knowledge, thorough supervision, social integration and mental health support. Preceding interviews to decide on reasonable voluntary deployment, the use of new technology and frequent feedback communication with faculties, educators and policymakers can further help with a successful and sustainable integration of students and residents in the fight against the pandemic.Faculties and policymakers should be in close contact with the youngest in training and be cognizant of their concerns and intrinsic creativity on the scenario. The use of new technology for interaction and knowledge provision, preceding interviews to decide on reasonable voluntary deployment and the provision of mental health support seem important measures to aid students and residents in the fight against the current pandemic.<br> <strong>Conclusion:</strong> It is critical that faculties, educators and policymakers have a better thorough understanding of the needs and concerns of medical trainees during this pandemic times. Leaders should facilitate close communication with students and residents, value their intrinsic creativeness and regularly evaluate their needs in regards to deployment, knowledge aspects, safety measures, legal concerns and overall well-being.</p>
Projected shifts in deadwood bryophytes in Sweden, data used for species distribution modelling and for climate and forest scenario analysis
<p>Climate change and habitat loss are main threats to forest biodiversity. We fitted ensembles of single species distribution models for 23 deadwood-living bryophyte species in Sweden, based on species records from the Swedish Lifewatch website. This data set comprises the species and environmental data used for species distribution modelling, and coefficients of the fitted single species distribution models (GLM, Poisson point-process, MaxEnt).</p> <p>Based on the fitted species distribution models, we conducted simulations of future species distributions given realistic climate and forest projection scenarios at the national scale of Sweden. The data used for the scenario analysis are stored here.</p>
Figure 3 from: Watts CHS, Hendrich L, Balke M (2016) A new interstitial species of diving beetle from tropical northern Australia provides a scenario for the transition of epigean to stygobitic life (Coleoptera, Dytiscidae, Copelatinae). Subterranean Biology 19: 23-29. https://doi.org/10.3897/subtbiol.19.9513
Figure 3 - Right lateral aspect of head of Exocelina species: Exocelina ferruginea (A), E. saltusholmesensis sp. n. (B), Exocelina abdita (C).
Figure 1 from: Watts CHS, Hendrich L, Balke M (2016) A new interstitial species of diving beetle from tropical northern Australia provides a scenario for the transition of epigean to stygobitic life (Coleoptera, Dytiscidae, Copelatinae). Subterranean Biology 19: 23-29. https://doi.org/10.3897/subtbiol.19.9513
Figure 1 - Habitus of Exocelina species: Exocelina ferruginea (A), Exocelina punctipennis (B), Exocelina saltusholmesensis sp. n. (C).
Determinants of energy futures - a scenario discovery method applied to cost and carbon emission futures for South American electricity infrastructure
<p>Scenario discovery SAMBA data files:</p> <p>1) The folder SAMBA_324_datafiles.zip contains all 324 data files for the OSeMOSYS run.<br> Each of these files has a code on top referring to the combination that it represents.<br> The key to the levers is in the Excel file "Metafile". There the naming convention of technologies as well as corresponding combination for scenario are also available.<br> 2) The Access database Scenario_discovery_database.mbd contans results from the 324 runs.<br> The key to the scenarios are in the Excel file "Metafile" tab "Scenario_key".<br> 3) The file OSeMOSYS_SAMBA_161130.txt is the version OSeMOSYS that was used to run all scenarios.<br> 4) The PRIM analysis is available on the GitHub repository: https://github.com/NMoksnes/Scenario_discovery</p>
Future climate under CMIP6 solar activity scenarios
<p>This dataset is used for the paper: Future climate under CMIP6 solar activity scenarios</p>
CCG India Scenarios
<p>Six Clic-SAND files for the analysis of targets set by the Indian government at COP-26. </p>
Tropical rainforest resilience under CMIP6-SSP scenarios
<div> <div> <p>Contains the analysis for the preprint 'Multi-fold increase in rainforests tipping risk beyond 1.5-2⁰C warming' (https://doi.org/10.31223/X5NH1V).</p> </div> </div> <div>Dataset archived at https://zenodo.org/records/7706640. </div>
AMTraC-19 (v8.0) Dataset: Systematic Comparison of the COVID-19 Pandemic Scenarios
<p>Paper describing scenarios which generated this dataset:</p> <p>Q. D. Nguyen, S. L. Chang, C. M. Jamerlan, M. Prokopenko, <a href="https://doi.org/10.1186/s12963-023-00318-6">Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions</a>, <em>Population Health Metrics</em>, 21, 17, 2023.</p> <p>The AMTraC-19 source code (v8.0) is released on Zenodo: <a href="https://doi.org/10.5281/zenodo.8067944">https://doi.org/10.5281/zenodo.8067944</a></p> <p> </p>
Updated SSP scenarios
<p>Updated SSP scenarios and DICE results presented in Koch and Leimbach's (2022) paper: "SSP economic growth projections: major changes of key drivers in integrated assessment modelling"</p>
Health health impact assessment relevant output calculated from scenarios involving different levels of Near Term Climate Forcer mitigation
<p>This dataset contains output data from the health impact assessment using air pollutant concentrations from AerChemMIP model experiments in different Future Scenarios that involve the mitigation of Near-Term Climate Forcers, Climate and Land-use. The model experiments were conducted by UKESM1, a model contributing to CMIP6, and was run over the period 2015 to 2100 to investigate the effect of anthropogenic emissions on near-term climate forcers. The atmosphere only CMIP6 configuration of UKESM1 was used to run this set of experiments. Model simulations were conducted at a global resolution of 1.875° x 1.25°. These concentrations were then used to assess the impact of different mitigation pathways on the air pollution health burden. In addition, output is also provided from sensitivty scenarios that explore the impact that the total population count, age structure of the population and baseline mortality rates have on the calculated air pollution health burden.</p> <p>Outputs provided in the dataset include 10 year means of the global and regional total population count data, population weighted pollutant concentrations (both annual mean PM<sub>2.5</sub> and seasonal maximum ozone concentrations), total adult human health mortality (including the upper and lower 95% confidence intervals) in response to exposure to PM<sub>2.5</sub> and O<sub>3</sub> for different sensitivity scenarios.</p> <p>The second file (GEMM-5COD) represents the same set of calculations and data but using a different set of mortality outcomes (5 specific causes of disease) for PM2.5 exposure instead of non-accidential mortality (non-communicable disease) and all lower respiratory infections (GEMM NCD+LRI) in the original set of calculations.Further details can be found in the accompanying publication that uses the data.</p>
Scenario Data: Hourly Demand and Supply per Region (NSWPH regions, weather years 2011-2019)
<p>TBD</p>
Anthropogenic pressure index on biomes (APIB): scenarios for Brazil 2050
<p>Anthropogenic transformations in the terrestrial biosphere have become increasingly significant and concerning. Whether through agriculture, silviculture, industrialization, and/or urbanization, these disturbances alter fundamental biogeochemical cycles and contribute to the addition or removal of genetically distinct species and populations from or to habitats in most terrestrial ecosystems, thus compromising the sustainability of ecological processes and the provision of ecosystem goods and services. In the short term, the primary threats to biodiversity arising from human activities include habitat loss and fragmentation. According to global assessments, the number of species at risk of extinction has increased, and the size of species populations has decreased.</p><p>Understanding the future of land use and land cover changes in Brazil and their impact on ecosystems is essential for the future of climate and biodiversity. Therefore, an Anthropogenic Pressure Index on Biomes (APIB) was developed to establish the level and distribution of anthropogenic pressure on biodiversity in Brazilian territories. This allowed for the analysis of the dynamics of anthropogenic pressure on biodiversity based on future scenarios of land use and land cover change and the identification of regions that are internally homogeneous and heterogeneous regarding the dynamics of this pressure in different scenarios.</p><p>For the development of APIB, the following spatially explicit factors related to anthropogenic pressure on biomes were considered: a) land use and land cover (forest vegetation, grassland vegetation, planted pasture, agriculture, mosaic of occupation, and forestry); b) rivers; c) protected areas; d) agricultural establishments; e) highways; and f) hydroelectric projects. Three scenarios of land use and land cover change were considered: a) the sustainable development scenario (SSP1), combined with a strict climate policy (RCP 1.9); b) the intermediate road development scenario (SSP2 and RCP 4.5); and c) the scenario of high inequality, which associates SSP3 with RCP 7.0.</p><p> </p><p><strong>Data</strong></p><p>Anthropogenic Pressure Index on Biomes (APIB) value.</p><p> </p><p><strong>Spatial resolution</strong></p><p>The data is available at a spatial resolution of 0.083º x 0.083º (~100 km²) and covers the entire Brazilian territory.</p><p> </p><p><strong>Temporal resolution </strong></p><p>Period of observed data: 2000 and 2014</p><p>Scenario Period: 2050</p><p> </p><p><strong>Coordinate reference system</strong> </p><p>Geographic Coordinate System with Datum SIRGAS 2000 (EPSG:5880)</p><p> </p><p><strong>Data format</strong></p><p>Data is provided as Shapefile.</p><p> </p><p><strong>Dataset usage</strong> </p><p>It is free to use, but please make sure to cite the repository and our paper properly if you use this dataset.</p><p>F. G. S. Bezerra, <i>et al.</i>, Spatio-temporal analysis of dynamics and future scenarios of anthropic pressure on biomes in Brazil. <i>Ecol Indic</i> <strong>137</strong> (2022). https://doi.org/10.1016/j.ecolind.2022.108749</p><p> </p><p><strong>Publication & further information</strong></p><p>For additional scenario information, please contact Francisco Gilney Silva Bezerra (franciscogilney@gmail.com).</p><p> </p><p><strong>Acknowledgments</strong></p><p>The authors would like to thank the São Paulo Research Foundation (FAPESP, project number 2017/22269-2 and Nexus Project) for their support in the development of this study.</p>
Effects of Scenario-based Education Initiative and OSCE for Recognition and Management of Delirium
ClinicalTrials.gov study NCT05623475. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.