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.
1,188
datasets available to search
ShareScore release 0.9.0
Dataset results
1,188 results for “DELTA”
Figure 4a–e in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 4a–e. Character editor, explanations in the text.
Figure 3a–f in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 3a–f. Taxon editor, explanations in the text.
Figure 2a–g in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 2a–g. Dropdown menus of the DELTA Editor.
Graph of phase shift $\Delta P_0$ vs electron trapping efficiency parameter $\beta $
<p>Graph of phase shift $\Delta P_0$ vs electron trapping efficiency parameter $\beta $, taking rest of parameters as $\varepsilon =0.1$, $\phi _m=1$, $\alpha =3.5 $, $\mu =0.56$ and $\nu=0.44$. The upper curve for $q =0.25$ (red line), middle one for $q=0.5$ (green line) and lower one is $q= 0.75 $ (blue line).</p>
OpenEar color example from Visible Ear Simulator anatomy Delta
<p>This dataset is an example of the color data used in the non-drillable anatomy segments of the Visible Ear Simulator academic freeware.</p> <p>It contains UV maps for larger segments as well as 3D models including vertex colors.</p> <p>For a full description of the work related to this dataset, please refer to the published article in <em>Otology & Neurotology</em>.</p>
Data for "Impacts of ozone-vegetation interactions on ozone pollution episodes in North China and the Yangtze River Delta"
<p>Data for "Impacts of ozone-vegetation interactions on ozone pollution episodes in North China and the Yangtze River Delta"</p>
kefisher98/IP_EA_deltaSCF: Ionization Potential, Electron Affinity, and Delta SCF for Small Organic Molecules
<p>Ionization potential, electron affinity, and delta SCF for small organic molecules selected from the ANI-1 data set. Properties are calculated with 24 different density functional approximations as well as CCSD(T).</p>
Colville River Delta Sea Ice Model and Output Data Files
<p>In this study, we used a 1D Delft3D-FLOW model to simulate the temporal development of the Colville River Delta, AK during the most active Arctic seasons. Simulations focused on the deltaic clinoform (i.e., the cross-sectional view of a delta) and used a floating barge structure to mimic the effects of sea ice on surface waters. Delft3D simulations were coupled with modules written in MATLAB and outputs were process in MATLAB.</p><p>The dataset includes an example model run file (Delft3D-FLOW and MATLAB) and output of results from simulations used to assess Arctic delta development under sea ice. </p><p>Files include:</p><ol><li>Example Delft3D-FLOW model setup file, MATLAB run script, and ice files for a 1500-year simulation.</li><li>Processed MATLAB structures and metadata for model results<ol><li>Long-term Delta Developmental Outputs (1500-year simulations)<ol><li>Ice-free</li><li>Ice-affected</li><li>Ice-free with waves</li><li>Ice-affected with waves</li></ol></li><li>Varying Sea Ice Characteristics Outputs (500-year simulations)<ol><li>Ice matrix (six simulations)</li></ol></li><li>Future Arctic Delta Scenarios Outputs (450-year simulations) <ol><li>Scenario A</li><li>Scenario B</li></ol></li></ol></li></ol>
Enhanced performance of Pr_4Ni_3O_10+_\delta - Ce_0.75Gd_0.1Pr_0.15O_2-\delta composite electrode via particle size grading
<p>The zipped file consists of original data of impedance for electrodes measured at 625 degrees and pO2 of 0.21 atm, and the corresponding DRT result, as well as peak fitting results based on DRT results. A txt file of specification is prepared for illustration.</p>
Results and analysis script from a discrete choice experiment assessing public preferences for rewilding in the Oder Delta
<p>1. Rewilding is an emerging paradigm in restoration science, and is increasingly gaining popularity as a cost-effective ecosystem restoration option. A rewilding framework was recently proposed that contains three integral components: restoring trophic complexity, allowing for stochastic disturbances, and enhancing species' potential to disperse. However, as of yet, there has been limited quantitative analysis looking at public preference for rewilding and each of its elements.</p> <p>2. We used a discrete choice experiment approach to determine public preference for rewilding in the Oder Delta. The unique geographical context of the Oder Delta, spreading evenly across two countries, allowed us to analyze differences between the German (n = 1,005) and Polish (n = 1,066) samples.</p> <p>3. In both countries, we found respondents were willing to pay for rewilding interventions when compared against a status quo option. Notably, preferences were strongest for restoring trophic complexity through promoting the comeback of large mammals.</p> <p>4. In addition, we found respondents living locally to the study region had significantly different preferences than the nationwide samples, exhibiting negative willingness to pay for the restoration of natural flooding regimes and the presence of large predator species.</p>
Dataset for 'Can restoring water and sediment fluxes across a mega-dam cascade alleviate a sinking river delta?'
<p>Please cite this dataset and corresponding manuscript at <a href="https://doi.org/10.1126/sciadv.adn9731">10.1126/sciadv.adn9731</a> if data were used in any way.</p> <p>Correspondence to Prof Lu Xi Xi at geoluxx@nus.edu.sg</p>
Recherchebreen delta formation and glacier flow velocity data
<p>Data supporting our study on the rapid delta formation connected to glacier surge. The dataset contains positions of delta shoreline and centreline length (2020-2022) together with glacier flow velocity derived from Sentinel-1. Delta-related data produced by Jan Kavan, glacier velocity data by Adrian Luckman.</p> <p> </p> <p>This study is a contribution to the National Science Centre project ‘GLAVE’ (Award No. UMO-2020/38/E/ST10/00042).</p>
Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta: supporting data - high water levels
<p>This dataset contains modelled high water levels in the Guayas delta supporting the paper 'Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta' published in HESS 2024.</p> <p>The dataset is organised through two folders:</p> <ul> <li>mangroves: all data from the scenarios with mangroves included in the domain</li> <li>no_mangroves: all data from the scenarios without mangroves included in the domain</li> </ul> <p>Each folder is further divided along 6 subfolders:</p> <ul> <li>I: El Niño Ocean & river</li> <li>II: El Niño Ocean</li> <li>III: El Niño river</li> <li>IV: Neutral</li> <li>I_50per: 50 % increase in seaward El Niño anomalies</li> <li>I_150per: 150 % increase in seaward El Niño anomalies</li> </ul> <p>Each folder contains two files:</p> <ul> <li>vars.csv - each row represents a mesh node and there are three columns: <ul> <li>X: x value of the model mesh node [m]</li> <li>Y: y value of the model mesh node [m]</li> <li>HIGH_WATER: high water level [m]</li> </ul> </li> </ul>
Figure 2 in Description of new records of the family Digamasellidae (Acari: Mesostigmata) from Kızılırmak Delta, Samsun Province, Turkey*
Figure 2. Multidendrolaelaps putte (female): dorsal (A); ventral (B); tectum (C); chelicera (D).
Figure 1 in Description of new records of the family Digamasellidae (Acari: Mesostigmata) from Kızılırmak Delta, Samsun Province, Turkey*
Figure 1. Dendrolaelaps casualis (female): dorsal (A); ventral (B); tectum (C); chelicera (D).
Pole Reversals and Delta Q Dynamics: A MEFI-Based Multiscale Analysis
<p>This study examines the phenomena of geomagnetic pole reversals through the Modified Einstein</p> <p>Field Interaction (MEFI) framework. By exploring Delta Q stabilization, resonance deviations, and</p> <p>their global impacts, the study demonstrates MEFI's potential as a universal model. This journal</p> <p>entry provides visual evidence and simulations to highlight the quantum, geophysical, and societal</p> <p>effects of pole reversals, underscoring MEFI?s predictive power.</p>
Remote sensing of multitemporal functional lake-to-channel connectivity and implications for water movement through the Mackenzie River Delta, Canada
<p>Dataset representing functional lake-to-channel connectivity in the Mackenzie Delta, NWT, Canada between 1984 and 2022 (final.class_20230324.feather), developed using Landsat 5, 7, and 9 optical imagery. </p> <p>Data in folders corresponds to data processing steps in scripts: https://doi.org/10.5281/zenodo.14618991</p> <p>Associated with manuscript: Remote sensing of multitemporal functional lake-to-channel connectivity and implications for water movement through the Mackenzie River Delta, Canada in WRR: Dolan, W., Pavelsky, T. M., & Piliouras, A. (2024). Remote sensing of multitemporal functional lake‐to‐channel connectivity and implications for water movement through the Mackenzie River Delta, Canada. <em>Water Resources Research</em>, <em>60</em>(4), e2023WR036614. https://doi.org/10.1029/2023WR036614</p>
Molcular Dynamics Trajectories for Delta Opioid Receptor bound with C6-Quino
<p>Molecular Dynamics Data for publication at Nature Communications, doi.org/10.1038/s41467-025-57734-5.</p> <p>Balazs R. Varga1#, Sarah M. Bernhard1#, Amal El Daibani1#, Saheem Zaidi2#, Jordy H. Lam2, Jhoan Aguilar1, Kevin Appourchaux1, Antonina Nazarova2, Alexa Kouvelis1, Ryosuke Shinouchi3, Haylee R. Hammond3, Shainnel O. Eans3, Violetta Weinreb4, Elyssa B. Margolis5, Jonathan F. Fay6, Xi-Ping Huang4, Amynah Pradhan1, Vsevolod Katritch2*, Jay P. McLaughlin3*, Susruta Majumdar1* and Tao Che1*</p> <p>Structure-guided design of partial agonists at an opioid receptor</p> <p>This folder contains the PDB format file ("Topology") and the XTC format file (Trajectories). The timestep in this strided trajectory is 0.5 ns per frame. Periodic boundary condition (pbc) can be restored using VMD's standard pbc commands.</p> <p>Please cite us if you find this data useful!</p>
Molcular Dynamics Trajectories for Delta Opioid Receptor bound with C5-Quino
<p>Molecular Dynamics Data for publication at Nature Communications, doi.org/10.1038/s41467-025-57734-5.</p> <p>Balazs R. Varga1#, Sarah M. Bernhard1#, Amal El Daibani1#, Saheem Zaidi2#, Jordy H. Lam2, Jhoan Aguilar1, Kevin Appourchaux1, Antonina Nazarova2, Alexa Kouvelis1, Ryosuke Shinouchi3, Haylee R. Hammond3, Shainnel O. Eans3, Violetta Weinreb4, Elyssa B. Margolis5, Jonathan F. Fay6, Xi-Ping Huang4, Amynah Pradhan1, Vsevolod Katritch2*, Jay P. McLaughlin3*, Susruta Majumdar1* and Tao Che1*</p> <p>Structure-guided design of partial agonists at an opioid receptor</p> <p>This folder contains the PDB format file ("Topology") and the XTC format file (Trajectories). The timestep in this strided trajectory is 0.5 ns per frame. Periodic boundary condition (pbc) can be restored using VMD's standard pbc commands.</p> <p>Please cite us if you find this data useful!</p>
AMTraC-19 (v7.7d) Dataset: Simulating transmission scenarios of the Delta variant of SARS-CoV-2 in Australia
<p>A preprint paper describing scenarios which generated this dataset can be accessed here: https://arxiv.org/abs/2107.06617. Please cite this work when using the dataset:<br> S. L. Chang, C. Zachreson, O. M. Cliff, M. Prokopenko, Simulating transmission scenarios of the Delta variant of SARS-CoV-2 in Australia, arXiv: 2107.06617, 2021.</p> <p>Abstract. An outbreak of the Delta (B.1.617.2) variant of SARS-CoV-2 that began around mid-June 2021 in Sydney, Australia, quickly developed into a nation-wide epidemic. The ongoing epidemic is of major concern as the Delta variant is more infectious than previous variants that circulated in Australia in 2020. Using a re-calibrated agent-based model, we explored a feasible range of non-pharmaceutical interventions, including case isolation, home quarantine, school closures, and stay-at-home restrictions (i.e., "social distancing"). Our modelling indicated that the levels of reduced interactions in workplaces and across communities attained in Sydney and other parts of the nation were inadequate for controlling the outbreak. A counter-factual analysis suggested that if 70% of the population followed tight stay-at-home restrictions, then at least 45 days would have been needed for new daily cases to fall from their peak to below ten per day. Our model successfully predicted that, under a progressive vaccination rollout, if 40-50% of the Australian population follow stay-at-home restrictions, the incidence will peak by mid-October 2021. We also quantified an expected burden on the healthcare system and potential fatalities across Australia.</p> <p>The AMTraC-19 source code (v7.7d) is released on Zenodo: https://zenodo.org/record/5778218</p>
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.