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zenodo44/100

Codes and dataset of the publication "Effectiveness of Sentinel-1 and Sentinel-2 for Flood Detection Assessment in Europe"

The folder contains the codes, input and output of the analysis carried out for supporting the publication of the paper: Tarpanelli A., Mondini A., Camici S.:Effectiveness of Sentinel-1 and Sentinel-2 for Flood Detection Assessment in Europe, Natural Hazards and Earth System Sciences, https://doi.org/10.5194/nhess-2022-63, 2022.   The codes should be run in order A1-A7 to generate all the figures of the paper. For details please send an email to: angelica.tarpanelli@irpi.cnr.it

opencc-by-4.0Jul 2022View details →

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The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - B. Data for 2020 - 2026 - Covid scenario

opencc-by-4.0Nov 2021View details →

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Complete datasets and code for "Hungry or angry? Experimental evidence for the effects of food availability on two measures of stress in developing wild raptor nestlings"

Abstract Food shortage challenges the development of nestlings; yet, to cope with this stressor, nestlings can induce stress responses to adjust metabolism or behaviour. Food shortage also enhances the antagonism between siblings, but it remains unclear whether the stress response induced by food shortage operates via the individual nutritional state or via the social environment experienced. In addition, the understanding of these processes is hindered by the fact that effects of food availability often co-vary with other environmental factors. We used a food supplementation experiment to test the effect of food availability on two complementary stress measures, feather corticosterone (CORTf) and Heterophil/Lymphocyte-ratio (H/L) in developing red kite (Milvus milvus) nestlings, a species with competitive brood hierarchy. By statistically controlling for the effect of food supplementation on the nestlings’ body condition, we disentangled the effects of food and ambient temperature on nestlings during development. Experimental food supplementation increased body condition, and both CORTf and H/L were reduced in nestlings of high body condition. Additionally, CORTf decreased with age in non-supplemented nestlings. H/L decreased with age in all nestlings and was lower in supplemented last-hatched nestlings compared to non-supplemented ones. Ambient temperature showed a negative effect on H/L. Our results indicate that food shortage increases the nestlings’ stress levels through both, a reduced food intake affecting nutritional state and the nestlings’ social environment. Thus, food availability in conjunction with ambient temperature shape between- and within nest differences in stress load, which may have carry-over effects on behaviour and performance in further life-history stages.

opencc-by-4.0Aug 2022View details →

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The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - A. Code and data for 2016-2019

The SPIN covid19 RMRIO dataset is a time series of MRIO tables covering years from 2016-2026 on a yearly basis. The dataset covers 163 sectors in 155 countries. This repository includes data for years from 2016 to 2019 (hist scenario) and the corresponding labels. Data for years 2020 to 2026 are stored in the corresponding repositories: <ul> <li>covid: <a href="https://doi.org/10.5281/zenodo.5713825">10.5281/zenodo.5713825</a></li> <li>counterfactual: <a href="https://doi.org/10.5281/zenodo.5713839">10.5281/zenodo.5713839</a></li> </ul> Tables are generated using the <a href="https://github.com/TBeaufils/SPIN">SPIN method</a>, based on the <a href="https://doi.org/10.5281/ZENODO.3993659">RMRIO tables</a> for the year 2015, GDP, imports and exports data from the <a href="https://data.imf.org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b">International Financial Statistics</a> (IFS) and the World Economic Outlooks (WEO) of <a href="https://www.imf.org/en/Publications/WEO/weo-database/2019/October">October 2019</a> and <a href="https://www.imf.org/en/Publications/WEO/weo-database/2021/April">April 2021</a>. From 2020 to 2026, the dataset includes two diverging scenarios. The covid scenario is in line with April 2021 WEO's data and includes the macroeconomic effects of Covid 19. The counterfactual scenario is in line with October 2019 WEO's data and simulates the global economy without Covid 19. Tables from 2016 to 2019 are labelled as hist. The Projections folder includes the generated tables for years from 2016 to 2019 (hist scenario) and the corresponding labels. The Sources folder contains the data records from the IFS and WEO databases. The Method data contains the data files used to generate the tables with the SPIN method and the following Python scripts: <ul> <li>SPIN_covid19_MRIO_files_preparation.py generates the data files from the source data.</li> <li>SPIN_covid19_RMRIO runs.py is the command to run the SPIN method and generate the dataset.</li> <li>figures.py is a script to produce figures reflecting the consistency of the projected tables and the evolution of macroeconomic figures in the 2016-2026 period for a selection of countries.</li> </ul> All tables are labelled in 2015 US$ and valued in basic prices.

opencc-by-4.0Nov 2021View details →

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The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - C. Data for 2020 - 2026 - Counterfactual scenario

opencc-by-4.0Nov 2021View details →

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Survey on the Effects of COVID-19 on the Wellbeing of Mexico City Households (ENCOVID- 19 CDMX – JULY 2020)

Amid the COVID-19 outbreak, the ENCOVID-19 CDMX provides information on the well-being of Mexico City households in four main domains: labor, income, mental health, and food insecurity. It offers timely information to understand the social consequences of the pandemic and the lockdown measures. It is a cross-sectional telephone survey that, in addition to the four main domains and a set of COVID-19 related questions, includes key indicators to capture the impact of the pandemic on issues like education, social programs, and crime. This is the first dataset of the project, corresponding to July 2020, collected four months after the lockdown began in Mexico. Data collection was performed between the 8th and the 17th of July.

opencc-by-4.0Aug 2022View details →

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EGFxSet: Electric guitar tones processed through real effects of distortion, modulation, delay and reverb

EGFxSet (Electric Guitar Effects dataset) features recordings for all clean tones in a 22-fret Stratocaster, recorded with 5 different pickup configurations, also processed through 12 popular guitar effects. Our dataset was recorded in real hardware, making it relevant for music information retrieval tasks on real music. We also include annotations for parameter settings of the effects we used. More details can be found in <a href="http://egfxset.github.io">egfxset.github.io</a> The dataset can also be accessed with <a href="https://mirdata.readthedocs.io/en/stable/source/mirdata.html#module-mirdata.datasets.egfxset">mirdata</a> Effects and parameters included: <table> <tbody> <tr> <td>Effect</td> <td>Model</td> <td>Effect Type</td> <td>Knob Names</td> <td>Knob Type</td> <td>Setting</td> </tr> <tr> <td>blues driver</td> <td>Boss BD-2 Blues Driver</td> <td>distortion</td> <td>['level', 'tone', 'gain']</td> <td>['volume','eq','effect amount']</td> <td>[0.5,0.5,1.0]</td> </tr> <tr> <td>tube screamer</td> <td>Ibanez Mini Tube Screamer</td> <td>distortion</td> <td>['tone', 'overdrive', 'level']</td> <td>['eq','effect amount','volume']</td> <td>[0.5,1.0,0.5]</td> </tr> <tr> <td>distortion</td> <td>Pro Co Sound RAT2 Distortion</td> <td>distortion</td> <td>['distortion', 'filter', 'volume']</td> <td>['effect amount','eq','volume']</td> <td>[1.0, 0.5,1.0]</td> </tr> <tr> <td>chorus</td> <td>Boss CE-3 Chorus</td> <td>modulation</td> <td>['rate', 'depth', 'stereo mode']</td> <td>['rate','effect amount','selector']</td> <td>['120 bpm', 1.0, False]</td> </tr> <tr> <td>flanger</td> <td>Mooer E-Lady</td> <td>modulation</td> <td>['color', 'type', 'range', 'rate']</td> <td>['eq','selector','effect amount','rate']</td> <td>[0.5, 'normal', 1.0, '120 bpm']</td> </tr> <tr> <td>phaser</td> <td>MXR Phase 45</td> <td>modulation</td> <td>['speed']</td> <td>['rate']</td> <td>['120 bpm']</td> </tr> <tr> <td>tape echo</td> <td>Line 6 DL4 Delay</td> <td>delay</td> <td>['effect selector', 'delay time', 'repeats', 'tweak (bass)', 'tweez (treble)', 'mix']</td> <td>['selector', 'rate', 'effect decay', 'eq', 'eq', 'effect amount']</td> <td>['tape echo', '120 bpm', 0.6, 0.5, 0.5, 0.5]</td> </tr> <tr> <td>digital delay</td> <td>Line 6 DL4 Delay</td> <td>delay</td> <td>['effect selector', 'delay time', 'repeats', 'tweak (bass)', 'tweez (treble)', 'mix']</td> <td>['selector', 'rate', 'effect decay', 'eq', 'eq', 'effect amount']</td> <td>['digital delay', '120 bpm', 0.6, 0.5, 0.5, 0.5]</td> </tr> <tr> <td>sweep echo</td> <td>Line 6 DL4 Delay</td> <td>delay</td> <td>['effect selector', 'delay time', 'repeats', 'tweak (sweep speed)', 'tweez (sweep depth)', 'mix']</td> <td>['selector', 'rate', 'effect decay', 'rate', 'effect amount', 'effect amount']</td> <td>['sweep echo', '120 bpm', 0.6, '120 bpm',1.0,0.5]</td> </tr> <tr> <td>plate reverb</td> <td>Orange CR-60 Combo Amplifier</td> <td>reverb</td> <td>['volume', 'bass', 'treble', 'type', 'reverb', 'master volume', 'clean']</td> <td>['volume','eq','eq','selector','effect amount', 'volume', 'selector']</td> <td>[0.5, 0.5, 0.5, 'plate', 1.0, 0.2, True]</td> </tr> <tr> <td>hall reverb</td> <td>Orange CR-60 Combo Amplifier</td> <td>reverb</td> <td>['volume', 'bass', 'treble', 'type', 'reverb', 'master volume', 'clean']</td> <td>['volume','eq','eq','selector','effect amount', 'volume', 'selector']</td> <td>[0.5, 0.5, 0.5, 'hall', 1.0, 0.2, True]</td> </tr> <tr> <td>spring reverb</td> <td>Orange CR-60 Combo Amplifier</td> <td>reverb</td> <td>['volume', 'bass', 'treble', 'type', 'reverb', 'master volume', 'clean']</td> <td>['volume','eq','eq','selector','effect amount', 'volume', 'selector']</td> <td>[0.5, 0.5, 0.5, 'spring', 1.0, 0.2, True]</td> </tr> </tbody> </table> Please cite these papers if using EGFxSet: Pedroza HE, Abreu W, Corey R, Roman IR. "Leveraging real electric guitar tones and effects to improve robustness in guitar tablature transcription modeling." In 27th International Conference on Digital Audio Effects (DAFx), 2024. Pedroza, Hegel, Gerardo Meza, and Iran R. Roman. "EGFxSet: Electric guitar tones processed through real effects of distortion, modulation, delay and reverb." ISMIR Late Breaking Demo, 2022.

opencc-by-4.0Sep 2022View details →

zenodo44/100

Cascading effects augment the direct impact of CO2 on phytoplankton growth in a biogeochemical model, links to model results

This dataset provides the output of eight model simulations with the global ocean biogeochemical model FESOM-REcoM necessary to reproduce the findings of Seifert et al. (2022). In addition to information on the mesh, the dataset contains 1) 5-year means of global phytoplankton biomass, chlorophyll, net primary production, growth rates, limitations, calcification, grazing rates, calcite concentrations, zooplankton biomass, export fluxes as well as CO2(aq), HCO3- and nutrient concentrations, and 2) a time series of global and North Atlantic coccolithophore biomass, temperature, and CO2(aq) concentrations from 1958 to 2018. File names refer to the Figures and Tables in the paper where the respective data are used. See “readme” for detailed information on the dataset and separate files.

opencc-by-4.0Jun 2022View details →

zenodo44/100

Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Machine Breakdown Event

Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> an announcement of a machine breakdown event was simulated on Friday at 6:00, describing that machine MAQ119 could breakdown at any moment, detected using a predictive maintenance system. Accordingly, the proposed scheduler imposed a machine available frames constraint, during its event, of 0 usable frames, thus removing the machine from production. The proposed genetic algorithm was executed for 1 hour at period 769 (Friday at 7:00) until the remainder of the schedule’s time window. Also, the predefined optimization weights were 1 for total cost and 0 for machine occupancy deviation.   File Description: <ul> <li>Input_JSON_Machine_Breakdown_Optimization - JSON input data for the machine breakdown event</li> <li>Output_JSON_Machine_Breakdown_Optimization - JSON output data for the machine breakdown event</li> <li>Output_Statistics_Machine_Breakdown_Optimization - Excel output machine breakdown event statistics</li> </ul>

opencc-by-4.0Sep 2022View details →

zenodo44/100

Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Maintenance Optimization

Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> a maintenance optimization scenario was formulated to validate the scheduler's ability to schedule tasks as well as maintenance activities while also minimizing the total costs. Accordingly, it was considered an optimization weight of 1 for the total cost and 0 for machine occupancy deviation, as well as a 2-hour execution time for the genetic algorithm. Each maintenance activity, for every machine, has a duration of 6 hours and 10 minutes, with a labor cost of 3,22 EUR/hour during the stipulated maintenance hours and a monetary penalty, that doubles the cost (i.e., 6.44 EUR/hour) if done out of maintenance hours.   File Description: <ul> <li>Input_JSON_Maintenance_Optimization - JSON input data for the maintenance optimization</li> <li>Output_JSON_Maintenance_Optimization - JSON output data for the maintenance optimization</li> <li>Output_Statistics_Maintenance_Optimization - Excel output maintenance optimization statistics</li> </ul>

opencc-by-4.0Sep 2022View details →

zenodo44/100

Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Total Cost and Machine Occupancy Deviation Optimization

Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> a total cost and machine occupancy deviation optimization scenario was formulated that aims to demonstrate how the proposed scheduler is able to balance tasks between machines while also reducing overall costs. For this scenario, it was considered an optimization weight of 0.5 for both the total costs and machine occupancy deviation objectives and the genetic algorithm was executed for 2 hours.   File Description: <ul> <li>Input_JSON_Total_Cost_Machine_Occupancy_Deviation_Optimization - JSON input data for the total cost and machine occupancy deviation optimization</li> <li>Output_JSON_Total_Cost_Machine_Occupancy_Deviation_Optimization - JSON output data for the total cost and machine occupancy deviation optimization</li> <li>Output_Statistics_Total_Cost_Machine_Occupancy_Deviation_Optimization - Excel output total cost and machine occupancy deviation optimization statistics</li> </ul>

opencc-by-4.0Sep 2022View details →

zenodo44/100

Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Energy Cost Optimization with Energy Selling

Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> an energy cost optimization considering the presence of an energy buyer is proposed to validate the scheduler’s ability to maximize profits while also minimizing energy costs. The scenario considers an added sales value corresponding to 50% of the buying. For this scenario, the genetic algorithm was executed for 2 hours, with 1 and 0 for the optimization weights total cost and machine occupancy deviation, respectively.   File Description: <ul> <li>Input_JSON_Energy_Cost_Energy_Selling_Optimization - JSON input data for the energy cost optimization with energy selling</li> <li>Output_JSON_Energy_Cost_Energy_Selling_Optimization - JSON output data for the energy cost optimization with energy selling</li> <li>Output_Statistics_Energy_Cost_Energy_Selling_Optimization - Excel output energy cost optimization with energy selling statistics</li> </ul>

opencc-by-4.0Sep 2022View details →

zenodo44/100

Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Joint Optimization of Production and Maintenance

Using the previous datasets at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>>,  <<a href="https://zenodo.org/record/7055698">https://zenodo.org/record/7055698</a>>, <<a href="https://zenodo.org/record/7055580">https://zenodo.org/record/7055580</a>>, and <<a href="https://zenodo.org/record/7055573">https://zenodo.org/record/7055573</a>>  a joint optimization of production and maintenance scenario was formulated which aims at combining all the features from the cited scenarios. For energy selling, it was considered an added sales value corresponding to 50% of the buying. Regarding maintenance activities, it was simulated an announcement of a maintenance activity for MAQ118 from Monday at 07:00 (i.e., period 1) to Monday at 17:00 (i.e., period 120), and another for MAQ120 which can be done at any time. These maintenance activities take 6 hours and 10 minutes to complete and have an associated labor cost of 3,22 EUR/hour in maintenance hours, and a double cost penalty (i.e., 6.44 EUR/hour) if done out of maintenance hours. The scenario was executed in 2 hours, with the corresponding optimization weights of 0.8 and 0.2 for the total cost and machine occupancy deviation, respectively.   File Description: <ul> <li>Input_JSON_Joint_Optimization_Production_Maintenance - JSON input data for the joint optimization of production and maintenance</li> <li>Output_JSON_Joint_Optimization_Production_Maintenance - JSON output data for the joint optimization of production and maintenance</li> <li>Output_Statistics_Joint_Optimization_Production_Maintenance - Excel output joint optimization of production and maintenance statistics</li> </ul>

opencc-by-4.0Sep 2022View details →

zenodo44/100

Data and code accompanying: A quantitative synthesis of and predictive framework for studying winter warming effects in reptiles

This data and code were used to generate the publication "A quantitative synthesis of and predictive framework for studying winter warming effects in reptiles", doi: 10.1007/s00442-022-05251-3 Please direct any queries or requests to use these datasets/code to: k.macleod@bangor.ac.uk Two datasets are presented in separate excel files: one contains meta-analytical data from experimental studies on winter warming effects on reptiles, and the other contains the same type of data from observational studies on the same. R code for analysis is in an R file; this should be openable in any text editing application. Manuscript abstract below: Increases in temperature related to global warming have important implications for organismal fitness. For ectotherms inhabiting temperate regions, ‘winter warming’ is likely to be a key source of the thermal variation experienced in future years. Studies focusing on the active season predict largely positive responses to warming in the reptiles; however, overlooking potentially deleterious consequences of warming during the inactive season could lead to biased assessments of climate change vulnerability. Here, we review the overwinter ecology of reptiles, and test specific predictions about the effects of warming winters, by performing a meta-analysis of all studies testing winter warming effects on reptile traits to date. We collated information from observational studies measuring responses to natural variation in temperature in more than one winter season, and experimental studies which manipulated ambient temperature during the winter season. Available evidence supports that most reptiles will advance phenologies with rising winter temperatures, which could positively affect fitness by prolonging the active season although effects of these shifts are poorly understood. Conversely, evidence for shifts in survivorship and body condition in response to warming winters was equivocal, with disruptions to biological rhythms potentially leading to unforeseen fitness ramifications. Our results suggest that the effects of warming winters on reptile species are likely to be important but highlight the need for more data and greater integration of experimental and observational approaches. To improve future understanding, we recap major knowledge gaps in the published literature of winter warming effects in reptiles and outline a framework for future research.

opencc-by-4.0Sep 2022View details →

zenodo44/100

Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation

Satellite measurements of backscattered UV radiation are sensitive to the presence of UV-absorbing aerosols in the atmosphere. These measurements are commonly used for determining the concentration of atmospheric trace gases such as O3, SO2, and H2CO. The theoretical results in this dataset describe the effects of UV-absorbing mineral dust and carbonaceous smoke aerosols on these backscatter satellite measurements between 300-400 nm. The information provided is independent of any specific trace gas retrieval algorithm and does not require detailed a priori knowledge of aerosol and surface properties. The results are derived from the analysis of the radiative transfer model simulations performed with the optical property data used in the Ozone Monitoring Instrument (OMI) UV aerosol retrieval algorithm, OMAERUV. Results from this algorithm have been validated with Aerosol Robotic Network (AERONET) observations (Jethva & Torres, 2011; Torres et al., 2018). This dataset is associated with the following publication: Jethva, H., Haffner, D., Bhartia, P. K., & Torres, O. (2022). Estimating Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation, Earth Space Sci., Accepted.

opencc-by-4.0Sep 2022View details →

zenodo44/100

Experimental data of "Mesoscopic Klein-Schwinger effect in graphene"

Current-to-voltage characteristics of the devices studied in the main and supplementary text of the article "Mesoscopic Klein-Schwinger effect in graphene" by A. Schmitt et al. Dimensions of devices are provided in the article

opencc-by-4.0Sep 2022View details →

zenodo44/100

Code/data to accompany publication "Using cloud radar to investigate the effect of rainfall on migratory insect flight"

Code/data to accompany publication "Using cloud radar to investigate the effect of rainfall on migratory insect flight". The cloud radar data files contains all the data used in the publication "Using cloud radar to investigate the effect of rainfall on migratory insect flight" by Charlotte E. Wainwright, Sabrina N. Volponi, Phillip M. Stepanian, Don R. Reynolds, and David H. Richter, published in Methods in Ecology and Evolution in 2022. The MATLAB code implements the method described in the paper on the data files included.

opencc-by-4.0Sep 2022View details →

zenodo44/100

Dataset: Analytical Physical Model for Electrolyte Gated Organic Field Effect Transistors in the Helmholtz Approximation

Data corresponding to the figures of the manuscript "Analytical Physical Model for Electrolyte Gated Organic Field Effect Transistors in the Helmholtz Approximation" by Larissa Huetter, Adrica Kyndiah and Gabriel Gomila

opencc-by-4.0Sep 2022View details →

zenodo44/100

Effect of different system parameters on the design of the EU DEMO vacuum vessel pressure suppression system (dataset)

Set of design maps for the EU DEMO VVPSS, for each: <ul> <li>VVPSS size</li> <li>Number of VVPSS connections</li> <li>Initial VVPSS temperature</li> </ul> reporting peak and equilibrium pressure in the VV following an in-vessel LOCA initiated by a double-ended guillotine break of the largest feeding pipe. Model details reported in publication A. Froio and I. Moscato, Effect of different system parameters on the design of the EU DEMO vacuum vessel pressure suppression system, submitted to Fusion Engineering and Design. The README.txt file has been written according to the Dubline Core Standard for Metadata (https://www.dublincore.org/).

opencc-by-4.0Oct 2022View details →

zenodo44/100

Processed model output of the climate simulation in the study: The effects of diachronous surface uplift of the European Alps on regional climate and the isotopic composition of precipitation (δ18Op) [Boateng et al.]

The geodynamic evolution of the Alps suggests that the Alps did not rise monotonically due to the different post-collisional processes such as slab break-off. However, understanding such subsurface dynamics would require adequate knowledge about its surface uplift history. Stable isotope paleoaltimetry methods are widely used to infer past surface elevation using geologic archives. However, its accurate interpretation relies on attributing the extracted isotopic signal from proxies to surface uplift despite other influences such as climate. To resolve this issue, topographic sensitivity experiments across the Alps are used to investigate the impacts of the diachronous surface uplift on regional climate and δ18Op. The Atmospheric General Circulation Model ECHAM5 with water isotope tracking capabilities (ECHAM5-wiso) is used to simulate the climate with varied topographic scenarios. We present the processed (long-term means) model output of the relevant climate variables (i.e δ18Op, near-surface temperature, precipitation amount, near-surface meridional and zonal winds, mean sea level pressure, and elevation) in response to the changes in topography. The file names are representative of the topographic scenarios used for the simulations. For example, the file “W2E1.nc” is the model output produced by a topographic scenario in which the topography across the west-central Alps was set to 200% of its modern height, and the Eastern Alps were kept at 100%. The “CTL.nc” file contains model output from the control simulation that uses present-day topography. The datasets for instance can be used to select far-field sampling points for the δ-δ paleoaltimetry method that are not significantly affected by the topographic changes.

opencc-by-4.0Oct 2022View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record