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zenodo36/100

Data repository for study "Understanding agricultural market dynamics in times of crisis: the dynamic agent-based model Agrimate"

<p>Data for the study "Understanding agricultural market dynamics in times of crisis: the dynamic agent-based model Agrimate".</p> <p><strong>hindcasting_analysis</strong></p> <ul> <li>figures of the hindcasting exercise in the main text</li> <li>raw_data <ul> <li>&nbsp;&nbsp; raw model output data for <ul> <li>baseline scenario --&nbsp;<em>agrimate_baseline=2007-2009_extra_regions=(Egypt=EGY)_regions=AgrimateEU28_start=2000-01-01.nc</em></li> <li>production failure scenario --&nbsp;&nbsp;<em>agrimate_baseline=2007-2009_extra_regions=(Egypt=EGY)_production_anomalies=FAOsince-2005_regions=AgrimateEU28_start=2000-01-01.nc</em></li> <li>production failure and export restriction scenario --&nbsp;<em>agrimate_baseline=2007-2009_export_restrictions=2007-2011_extra_regions=(Egypt=EGY)_production_anomalies=FAOsince-2005_regions=AgrimateEU28_start=2000-01-01.nc</em></li> </ul> </li> </ul> </li> </ul> <p><strong>multibreadbasket_analysis</strong></p> <ul> <li>figures of the multibreadbasket analysis in the main text</li> <li>raw_data <ul> <li>&nbsp;&nbsp; raw model output data for <ul> <li>simulations under historical climatic conditions with &lt;number&gt; as an identifier&nbsp; -- <em>agrimate_his-&lt;number&gt;.nc</em></li> <li>simulations under +2&deg;C projection with &lt;number&gt; as an identifier&nbsp; -- <em>agrimate_2p0-&lt;number&gt;.nc</em></li> </ul> </li> </ul> </li> <li>processed_data <ul> <li>processed output data to easier/faster plot</li> </ul> </li> </ul> <p><strong>sensitivity_analysis</strong></p> <ul> <li>raw data and graphics as in&nbsp;<strong>main_output</strong> for different model parameters as given in Table F.1</li> </ul> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Feb 2024View details →
zenodo36/100

The Repository for the Manuscript "Temperature and Precipitation Dominate Seasonal Variations in Seismic Velocity and Attenuation in Deserts"

<p><strong><span>Overview</span></strong></p> <p><span>This dataset contains the essential code and data for calculating the Horizontal-to-Vertical Spectral Ratio (HVSR), analyzing vehicle-generated seismic events, retrieving Q-values, and comparing them with meteorological data. It also includes waveform data from 20 seismic events.</span></p> <p><span>The seismic data originate from a temporary broadband seismic array deployed in the Tarim Basin, from July 2017 to October 2019 (Zuo et al., 2022). This dataset focuses on three seismic stations: T12, T52, and T23. Stations T12 and T23 recorded data from July 2017 to October 2019, while station T52 recorded from November 2018 to October 2019.</span></p> <p><span>&nbsp;</span></p> <p><strong><span>Code</span></strong></p> <p><span>The dataset includes Python scripts for calculating HVSR and retrieving Q-values. The HVSR calculation follows Li et al., (2023), while forward modeling is based on Antonio Garc&iacute;a-Jerez et al., (2016).</span></p> <p><span>The codes for Q-value estimation are stored in &lsquo;Retrieving Q-value&rsquo; folder. The Q-value estimation process, demonstrated for station T12 in Jupyter Notebook, involves extracting single vehicle signals from continuous data, time-frequency spectrogram calculations, two-dimensional correlation coefficient of their time-frequency amplitude calculations, using hierarchical clustering algorithm to classify vehicle signals, vehicle speed estimation, and performing Q-value inversion.</span></p> <p><span>&nbsp;</span></p> <p><strong><span>Dataset </span></strong></p> <p><span>HVSR variations over time for three stations are calculated from continuous seismic recordings and are stored in the <em>&lsquo;HVSR&rsquo;</em> folder under each station directory. </span></p> <p><span>Time-frequency spectrograms for Q-value estimation are stored in the <em>&lsquo;Spectrogram&rsquo;</em> folder, with filenames indicating the record time of each vehicle signal. The Q-value is inverted using these signals, and for stability, we stacked every 100 individual results, which are stored in the 'Q-values' folder under the corresponding station name folder. Due to interference from wind and other sources, Q-value inversion using vehicle signals was unreliable for T23, so Q-values are only provided for T12 and T52.</span></p> <p><span>Meteorological data (temperature and soil water content) are stored in the <em>&lsquo;temperature&rsquo;</em> and <em>&lsquo;soil water content&rsquo;</em> folders under each station directory.</span></p> <p><span>Seismic event waveforms for 20 selected strong earthquakes are stored in the <em>&lsquo;events&rsquo;</em> folder, with filenames indicating the start and end times of the events.</span></p> <p><span>&nbsp;</span></p>

opencc-by-4.0Sep 2024View details →
zenodo36/100

Capsaicinoid repository

<p>Untargeted-metabolomics of 40 different chili varieties, large-scale etraction and purified capsaicinoids. Included is a capsaicinoid spectral library, all mzmine, GNPS and SIRIUS outputs. Corrospoinding paper's DOI will be added once generated. Updated version also contains all NMR files as well.</p>

opencc-by-4.0Oct 2024View details →
zenodo36/100

Data repository for "Lockdown impact on age-specific contact patterns and behaviours, France, April 2020"

<p>Aggregated contact matrices associated with the publication&nbsp;&quot;Lockdown impact on age-specific contact patterns and behaviours, France, April 2020&quot; .&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Nov 2021View details →
zenodo36/100

Code repository that supports the research presented in the paper "The gender gap in higher STEM studies: a Systematic Literature Review"

<p>Resources for the Systematic Literature Review (SLR) carries out as part of PhD thesis about the gender gap in STEM studies in higher education by Sonia Verdugo-Castro and supervised by Alicia Garc&iacute;a-Holgado and M&ordf; Cruz S&aacute;nchez G&oacute;mez.</p> <p>The SLR covers papers in WoS and Scopus from 2015 to 2021.</p> <p>All the papers retrieved and the different steps in the SLR selection process are contained and documented in:</p> <ul> <li><a href="https://docs.google.com/spreadsheets/d/1ldml-Mg-oguX9gXayllojBRtZ1kjdD4WRSqYwf1yZ0o/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1ldml-Mg-oguX9gXayllojBRtZ1kjdD4WRSqYwf1yZ0o/edit?usp=sharing</a></li> </ul>

openother-openDec 2021View details →
zenodo36/100

Materials for Design Open Repository. Polymer Derived Ceramics

<p>The current dataset is composed of a collection of Polymer Derived Ceramics (PDCs). It&nbsp;contains the number of chemical elements (NoE), PDC composition, used precursor, Pyrolysis temperature <em>T</em><sub>p</sub>, Pyrolysis time <em>t</em><sub>p</sub>, gas atmosphere, a set of columns containing the chemical elements and their corresponding fraction, and the references.&nbsp;This dataset was developed in the framework of the European project ACHIEF for the discovery&nbsp;of novel materials to be used in industrial processes.</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Data repository - Integrating Degrowth and Efficiency Perspectives to Enable an Emission-neutral Food System

<p>Data repository: Integrating Degrowth and Efficiency Perspectives to Enable an Emission-neutral Food System&nbsp;<br> <br> Benjamin Leon Bodirsky, David Meng-Chuen Chen, Isabelle Weindl, Bjoern Soergel, Felicitas&nbsp;<br> Beier, Edna J. Molina Bacca, Franziska Gaupp, Alexander Popp, Hermann Lotze-Campen. In review.</p> <p>Folder structure:&nbsp;</p> <p>1. Figures: Contains .Rmd notebook for figure production, as well as source data (from model inputs and outputs)</p> <p>2. Magpie_start_script: Contains start script degrowth.R for replication of model runs. See readme.txt for precise instructions.</p> <p>3. Scenario_outputs. Entire output folders of model scenario runs.</p>

opencc-by-4.0Sep 2021View details →
zenodo36/100

Data repository - Substitution of ruminant meat with microbial protein in forward-looking global land-use scenarios towards 2050

<p>This repository contains model-based scenario results&nbsp;of a study on substituting ruminant meat with microbial protein in human diets by 2050.&nbsp;The scenario data has been generated with the global multi-regional open-source land-use modelling framework MAgPIE 4.3.4:<br> https://github.com/magpiemodel/magpie/releases/tag/v4.3.4<br> https://zenodo.org/record/4730378</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Supplementary Repository S1

<p>SQL queries and query results that were used to estimate the precision of MAIA jobs on <a href="https://biigle.de">biigle.de</a>.</p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Supplementary Repository S5

<p><a href="https://ifealid.cebitec.uni-bielefeld.de">IFeaLiD</a> feature maps of the images <code>05602019-04-0606-57-09.JPG</code> and <code>02472019-04-0606-09-35.JPG</code> of the <a href="https://doi.org/10.1594/PANGAEA.935884">SO268/2_100-1 dataset</a>.</p> <p>The original images are licensed under CC BY 4.0 (<a href="https://creativecommons.org/licenses/by/4.0">https://creativecommons.org/licenses/by/4.0</a>).</p> <p>The &quot;untrained&quot; feature maps were produced with a single forward pass through ResNet101 initialized with weights trained on COCO. The &quot;trained&quot; feature maps were produces with a forward pass through ResNet101 initialized with COCO and trained for 30 epochs on 12,224 expert annotations in the <a href="https://doi.org/10.1594/PANGAEA.935891">SO268/2_160-1</a> and <a href="https://doi.org/10.1594/PANGAEA.935892">SO268/2_164-1</a> datasets.</p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

An evidence-based study on issue labeling in Github-based repositories (Supplementary material)

<p>The open-source software community has grown in size and importance over the years. As a consequence, the number of project contributors has increased considerably. The capability of open-source project repositories to accommodate issue reports is essential. An issue report encompasses a large set of data that describes the necessary changes a software should handle. As developers need detailed information to reproduce and find them, incomplete information is a severe problem that may influence triage and defect detection leading to delays in project maintenance. Issue trackers commonly use the labeling method to add extra details to issues. Knowing the importance of labels, this dissertation focus on investigating the usage, creation, and similarities in the context of the issue lifecycle in both maintenance and evolution in the repository issue trackers of the largest and most popular code hosting platform, Github. In addition, it analyzes the number of labeled and unlabeled issues in the repository and the connection between the issues&#39; components, with an analysis focused on the lifecycle. The results indicate a significant correlation between repositories with many issues and the creation of labels, but not all repositories use them. 64.58% of the repositories insert new labels as the project evolves. 73.14% repositories applied on issues the Github standard labels. We also found an influence of primary issue fields such as title, description, and comments in most issue labels, impacting the creation and labeling issues. These numbers show that issue labeling is of prominent relevance for project maintenance and evolution. It provides developers with an easy and convenient way to inform about an incoming issue reported by systems users.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Data repository of Predictors of Social Response to COVID-19 among Health Care Workers Caring for Individuals with Confirmed COVID-19 in Jordan

<p>The outbreak of COVID-19 forced public health authorities around the world to call for national emergency plans. Public responses, in form of social discrimination and stigmatizing behaviors, are increasingly being observed against confirmed individuals with confirmed COVID-19 and healthcare workers (HCWs) caring for those individuals. Hence, this study aimed to investigate the perception of social discrimination and coping strategies, and explore predictors of social discrimination and coping toward COVID-19 among HCWs and individuals with confirmed COVID-19. This study used a cross-sectional descriptive-comparative design to collect data using a convenience sample of 105 individuals with confirmed COVID-19 and 109 HCWs using a web-based survey format. In this study, individuals confirmed with COVID-19 reported a high level of social discrimination compared with HCWs (t = 2.62, <em>p</em> &lt; .01). While HCWs reported high level of coping with COVID-19 compared with individuals with COVID-19 (t = -3.91, <em>p</em> &lt; .001). Educational level, age, monthly income, and taking over-the-counter medication were predictors of social discrimination and coping with COVID-19 among HCWs and individuals confirmed with COVID-19. In conclusion, the findings showed individuals with confirmed COVID-19 were more likely to face social discrimination and HCWs perform better coping with COVID-19 than individuals with confirmed COVID-19.</p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Data repository for "Climate change increases the severity and duration of soil water stress in the temperate forest of eastern North America"

<p>Dataset provided for publication in Frontiers in Forests and Global Change : &quot;Climate change increases the severity and duration of soil water stress in the temperate forest of eastern North America&quot;.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

High-Throughput Screening of Tribological Properties of Monolayer Films using Molecular Dynamics and Machine Learning: Supplemental Repository

<p>Supplemental repository for the &quot;High-Throughput Screening of Tribological Properties of Monolayer Films using Molecular Dynamics and Machine Learning&quot; article. Contains calculated tribological properties of dual-monolayer systems from Molecular Dynamics (MD) simulation and Machine Learning (ML).</p>

opencc-by-4.0Oct 2021View details →
zenodo36/100

Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore technologies reveals platform-specific error patterns (repository for Genome Research paper, 2022)

<p>Simulated ONT and PacBio RNA-Seq data for &quot;Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore technologies reveals platform-specific error patterns&quot; paper (Mikheenko et al., Genome Research, 2022). All&nbsp;details can be found in the Methods section of the paper.</p> <p><strong>PacBio.simulated_uniform_coverage.fasta.gz</strong>&nbsp;and <strong>ONT.simulated_uniform_coverage.fasta.gz&nbsp;files</strong> were used in&nbsp;Supplemental Note &ldquo;Benchmarking of the read-to-isoform assignment algorithm&rdquo;.</p> <p><strong>ONT.simulated_real_expression.fasta.gz</strong>&nbsp;file and all GTF files were used in the Section &quot;Splice site correction improves transcript discovery precision&quot;.&nbsp;<strong>mouse.gencode.M26.spatial.15percent.reduced.gtf</strong>&nbsp;was used as the annotation file for all tools.&nbsp;<strong>mouse.gencode.M26.spatial.15percent.expressed.gtf </strong>contains the set of all expressed isoforms.&nbsp;<strong>mouse.gencode.M26.spatial.15percent.expressed_kept.gtf</strong> contains those&nbsp;of the&nbsp;isoforms that are in presented in the annotation file (&quot;known&quot; transcripts),&nbsp;<strong>mouse.gencode.M26.spatial.15percent.reduced.gtf</strong> contains expressed isoforms that were removed from the annotation&nbsp;(&quot;novel&quot; transcripts).</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

TRINITY open access data repository data set 2 by Budapest University of Technology and Economics

<p>Horizon 2020 programme supports access to and reuse of research data generated by Horizon 2020 projects through the Open Research Data Pilot (ORDP). To support the validation of scientific results, the pilot focuses on providing access to data needed to validate the scientific results. There are several types of such data, e.g. machine learning data sets, models, measurements, statistical results of experiments, survey outcomes, etc.</p> <p>This deliverable summarizes the data that are expected to be collected in the course of the project and where and how they are stored. The aspect of providing open access to research data (as required by the European Commission&rsquo;s Open Research Data Pilot, <a href="https://www.openaire.eu/what-is-the-open-research-data-pilot">https://www.openaire.eu/what-is-the-open-research-data-pilot</a>) is addressed in Section 3. Finally, in Section 4 we describe the data sets that were or are expected to be generated within the TRINITY projects and made freely available.</p>

opencc-by-3.0Mar 2022View details →
zenodo36/100

TRINITY open access data repository by Budapest University of Technology and Economics

<p>Horizon 2020 programme supports access to and reuse of research data generated by Horizon 2020 projects through the Open Research Data Pilot (ORDP). To support the validation of scientific results, the pilot focuses on providing access to data needed to validate the scientific results. There are several types of such data, e.g. machine learning data sets, models, measurements, statistical results of experiments, survey outcomes, etc.</p> <p>This deliverable summarizes the data that are expected to be collected in the course of the project and where and how they are stored. The aspect of providing open access to research data (as required by the European Commission&rsquo;s Open Research Data Pilot, <a href="https://www.openaire.eu/what-is-the-open-research-data-pilot">https://www.openaire.eu/what-is-the-open-research-data-pilot</a>) is addressed in Section 3. Finally, in Section 4 we describe the data sets that were or are expected to be generated within the TRINITY projects and made freely available.</p>

opencc-by-3.0Mar 2022View details →
zenodo36/100

FAIR Island Community Zenodo Repository Metadata Assessment

<p>A FAIR assessment for the FAIR Island Community Zenodo Repository.&nbsp;</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

Open data repository, An et al., Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images

<p>Open data repository of journal article &quot;Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images&quot; by Jeehye An <em>et al.&nbsp;</em>At time of publication of this dataset, the manuscript is still under revision.</p> <p>This dataset contains mouse T2 weighted MRI data, and manually and automated segmented ischemic stroke lesion masks for developing and evaluating a deep learning-based automated lesion segmentation. All files are in NIFTI format.<br> &nbsp;</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

Repository for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"

<p>Repositories&nbsp;for&nbsp;&quot;Standardized classification of&nbsp;cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography&quot;</p> <p>Repository&nbsp;1: Digital subtraction angiographies of CVS patients for grading with pM1 values</p> <p>Repository&nbsp;2: Vessel values</p> <p>Repository 3: Clinical data of CVS patients</p>

opencc-by-4.0Feb 2022View details →

ScienceDex guides

Understand access before you commit

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