Skip to main content
Powered by ShareScore

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.

93

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

93 results for “Environmental Predictability”

Learn how ShareScore rates datasets ↗
zenodo28/100

An Interpretable 3D Multi-Hierarchical Molecular Hybrid Representation for Environmental, Health, and Safety Properties Prediction

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo28/100

Accompanying dataset for: "A Bayesian method for predicting background radiation at environmental monitoring stations"

<h3>Physical parameters included</h3> <ul> <li>Ten-minute-averaged ambient dose equivalent rates (nSv/h) observed by the Immission Monitors for Ring area (IMR stations) at the sites of the SCK CEN and the Doel NPP for selected periods in time</li> </ul> <h3>Geographic locations</h3> <ul> <li>Belgian Nuclear Research Centre (SCK CEN) in Mol, Belgium: 18 IMR stations</li> <li>Nuclear Power Plant in Doel, Belgium: 16 IMR stations</li> </ul> <h3>Periods</h3> <ul> <li>6 through 13 August 2022</li> <li>30 August through 1 September 2022</li> <li>10 through 12 September 2022</li> </ul> <h3>Description of data</h3> <p>The zipped folder contains three sub folders for the different periods of interest. Each sub folder contains 34 files. Files are either named IMR-D##.txt to indicate Doel-based or IMR-M##.txt to indicate SCK CEN-based stations. Exact locations (WGS84) are included in the headers. Time stamps (referred to as 'local_time' in the files) are given in Central European Summer Time (UTC+2), and the ambient dose equivalent rates (referred to as 'value' in the files) in nanosievert per hour (nSv/h).</p> <h3>Acknowledgements</h3> <p>The authors thank Fran&ccedil;ois Menneson from FANC-ACFN for providing access to the Telerad data.</p>

openJun 2024View details →
zenodo28/100

Accompanying software for: "A Bayesian method for predicting background radiation at environmental monitoring stations"

<h3>Introduction</h3> <p>This software accompanies: "A Bayesian Method for predicting background radiation at environmental monitoring stations". The software is written in Python and depends (besides on standard packages like numpy) on the PyMC package for Bayesian inference. A brief user manual is provided that will allow to install the necessary prerequisites in a conda environment, and describes how to perform the inferences that are described in the paper. This requires additionally downloading the dataset that we have also made available on this platform (<a href="https://doi.org/10.5281/zenodo.12581795" target="_blank" rel="noopener">10.5281/zenodo.12581795</a>).&nbsp;</p> <h3>Description of files</h3> <ul> <li><em>manual.pdf</em> describes how to install the necessary packages in conda, and how to perform inferences from the paper.</li> <li><em>main.py</em> is the main script, which contains the input parameters and calls the relevant functions.</li> <li><em>bayesian_inference.py</em> contains the beating heart of the software. Here, the Bayesian problems for calibration and predictions are set up and solved using the PyMC package.</li> <li><em>data_paper_interface.py&nbsp;</em>is only necessary when reproducing the data from the paper. It contains the different cases that were used in the paper, and can be used to parse data from the accompanying dataset.</li> </ul>

openJul 2024View details →
zenodo28/100

Mirrorplots for "Quantum chemistry based prediction of electron ionization mass spectra for environmental chemicals"

Open the record for dataset details and reuse information.

opencc-by-4.0Jul 2024View details →
dryad28/100

Data from: Predicting spatial patterns of Sindbis virus (SINV) infection risk in Finland using vector, host and environmental data

Open the record for dataset details and reuse information.

publicFeb 2021View details →
dryad28/100

Data from: Do glucocorticoids predict fitness? Linking environmental conditions, corticosterone and reproductive success in the blue tit, Cyanistes caeruleus

Open the record for dataset details and reuse information.

publicSep 2017View details →
dryad28/100

Data from: Modeling the effect of environmental temperatures, microhabitat, and behavioral thermoregulation on predicted activity patterns in a desert lizard across its thermally diverse distribution

Open the record for dataset details and reuse information.

publicJun 2021View details →
dryad28/100

Data from: Environmental transmission of a personality trait: foster parent exploration behaviour predicts offspring exploration behaviour in zebra finches

Open the record for dataset details and reuse information.

publicJun 2013View details →
zenodo24/100

Gene expression in rotifer diapausing eggs in response to divergent environmental predictability regimes

<p>This data set accompanies the manuscript &quot;Gene expression in rotifer diapausing eggs in response to divergent environmental predictability regimes&quot;. It consists of the fastq files from RNA sequencing of 12 samples of diapausing eggs from the rotifer <em>Brachionus plicatilis</em>. The reads have already been quality filtetered and trimmed. The 12 fastq files are gzipped and archived in trimmed.tar, where there is trimmed_md5sum.txt file to check for data integrity. There is also a &quot;metadata.txt&quot; describing the samples, and a short README.txt file.</p>

opencc-by-4.0Jul 2020View details →
ClinicalTrials.gov24/100

Predicting Migraine Attacks Based on Environmental and Behavioral Changes as Detected From the Smartphone

ClinicalTrials.gov study NCT03762902. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Physiological and Environmental Data in a Remote Setting to Predict Exacerbation Events in Patients With Chronic Obstructive Pulmonary Disease

ClinicalTrials.gov study NCT06118632. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
geo20/100

Gene co-expression networks drive and predict reproductive effects in Daphnia in response to environmental disturbances

GEO Series GSE102226. Daphnia pulex. 335 samples. Type: Expression profiling by array.

openGEO-OpenDec 2017View details →
dryad0/100

Data from: Environmental variation predicts patterns of phenotypic and genomic variation in an African tropical forest frog

<p>Central African rainforests are predicted to be disproportionately affected by future climate change. How species will cope with these changes is unclear, but rapid environmental changes will likely impose strong selection pressures. Here we examined environmental drivers of phenotypic and genomic variation in the central African puddle frog (<i>Phrynobatrachus auritus</i>) to identify areas of elevated environmentally-associated turnover where populations may have the greatest capacity to adapt. We also compared current and future climate models to pinpoint areas of high genomic vulnerability where allele frequencies will have to shift the most in order to keep pace with future climate change. Analyses of body size, relative leg length, and head shape suggest that seasonal aspects of temperature and precipitation significantly influence phenotypic variation, whereas geographic distance and precipitation seasonality are the most important drivers of SNP allele frequency variation. However, neither landscape barriers nor the effects of past Pleistocene refugia had any influence on genomic differentiation. Most phenotypic and genomic differentiation coincided with key ecological gradients across the forest-savanna ecotone, montane areas and a coastal to interior rainfall gradient. Areas of greatest vulnerability were found in the lower Sanaga basin and southeastern region of Cameroon. In contrast with past conservation efforts that have focused on hotspots of species richness or endemism, our findings highlight the importance of preserving environmentally heterogeneous landscapes to preserve putatively adaptive variation and ongoing evolutionary processes in the face of climate change.</p>

opencc-zeroDec 2018View 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