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.
7,195
datasets available to search
ShareScore release 0.9.0
Dataset results
7,195 results for “SET”
A global data set of realized treelines sampled from Google Earth aerial images
<div> <span>We </span><span>sampled</span><span> Google Earth aerial images</span><span> to get a representative and globally distributed dataset of treeline locations</span><span>. </span><span>Google Earth images</span><span> are available to everyone, but may not be automatically downloaded and processed according to Google's license terms. Since we only wanted to detect tree individuals, we evaluated the aerial images manually by hand.</span> </div> <div> </div> <div> <span>Doing so, we scaled Google Earth's GUI interface to a buffer size of approximately 6000 m from a perspective of 100 m (+/- 20 m) above Earth's surface. Within this buffer zone, we took coordinates and elevation of the highest </span><span>realized </span><span>treeline locations. In some remote areas of Russia and Canada, individual trees were not identifiable due to insufficient image resolution. If this was the case, no treeline was sampled, unless we detected another visible treeline within the 6,000 m buffer and took this next highest treeline</span><span>. We did not ap</span><span>p</span><span>ly an automated image processing approach. </span><span>We calculated mass elevation effect as the distance to the nearest mountain chain limits. Continentality was assessed by the distance to the nearest coastline. Isolation was calculated by the nearest distance of a mountain chain to another mountain chain within a comparable elevational band. </span> </div>
Data set of ""Reconciling high-resolution strain rate of continental China from GNSS data with the spherical spline interpolation""
<p>Date data of ”Reconciling high-resolution strain rate of continental China from GNSS data with the spherical spline interpolation“</p> <p>"readme.txt" is the description of those zips. And Each zip also contains a "readme.txt", which is a description of the respective zip.</p>
set of SQS models of 128 atomic structure
<p>These are the SQS POSCARS of binary BCC models with diversified concentration of alloying element - appropriate for elastic constants calculations</p>
Data set and analysis for the preprint "Influences of local and global context on local orientation perception"
<p>This is the raw data and preprocessed one, with GNU Octave scripts for plots and analyses, for the preprint :</p> <p>https://www.authorea.com/users/596319/articles/629862-influences-of-local-and-global-context-on-local-orientation-perception</p> <p>see the readme file in the zip file for further information.</p>
A cost-effectiveness analysis of second-generation antihistamine 1 receptor blockers and Japanese kampo shoseiryuto for treatment of perennial allergic rhinitis in outpatient settings in Japan
<p><strong><span>Background: </span></strong><span>Perennial allergic rhinitis (PAR) is common in Japan. Second-generation antihistamines (SGAs) are used commonly </span><span>for its</span><span> treatment, but it remains unclear which SGA is the most cost-effective. Additionally, the pharmacoeconomics of Japanese kampo shoseiryuto, which has been traditionally prescribed to treat PAR in Japan, remain poorly understood.</span></p> <p><strong><span>Objectives: </span></strong><span>This study aimed to investigate the effectiveness of various SGAs and shoseiryuto for the treatment of PAR in Japanese outpatients, from the healthcare payer's perspective, using a base-case analysis.</span></p> <p><strong><span>Methods: </span></strong><span>The current study entailed identification of the most cost-effective of the six SGAs (</span><span>bepotastine 10 mg, cetirizine 10 mg, ebastine 10 mg, </span><span>epinastine 20</span><span> mg, loratadine 10 mg, and olopatadine 5 mg) and shoseiryuto, whose clinical effectiveness were evaluated using the overall improvement rate. </span><span>T</span><span>he time horizon</span><span> was 14 days. Costs were identified based on the Medical Fee Index in 2020.</span></p> <p><strong><span>Key findings: </span></strong><span>Overall, bepotastine 10 mg, cetirizine 10 mg, </span><span>ebastine </span><span>10 mg, and loratadine 10 mg were found to be cost-effective. Shoseiryuto was less cost-effective than ebastine 10 mg (dominated). Ebastine 10 mg was found to be the most cost-effective based on deterministic and probabilistic sensitivity analyses.</span></p> <p><strong><span>Conclusions: </span></strong><span>Ebastine 10 mg was found to be the most cost-effective treatment strategy for PAR among the agents evaluated in this study</span><span>. This insight might help </span><span>in creating an appropriate formulary for the treatment of PAR in hospitals and communities.</span></p>
Result for setting time
<p>Result for setting time</p>
A Cost-Utility Analysis of Oral Triptans for Migraine in an Adult Outpatient Setting in Japan
<p><strong><span>Objectives</span></strong><span><strong>. </strong>Pharmacoeconomic studies have not been performed frequently in Japan. This study attempted to clarify which oral triptans, including eletriptan, naratriptan, rizatriptan, sumatriptan, and zolmitrian, are cost-effective in treating migraine in an adult outpatient setting in Japan.</span></p> <p><strong><span>Methods</span></strong><span><strong>. </strong>A cost-utility analysis was conducted for healthcare payers. The population targeted was Japanese patients over the age of 18 who experienced migraines. A base-case model was prepared using probabilities from a network meta-analysis. Direct costs consisted of medical and drug costs (2017 version). Effectiveness was measured with the EQ-5D-3L questionnaire for adult patients with migraine. The duration of the study was 30 days.</span></p> <p><strong><span>Results</span></strong><span><strong>.</strong> The cost-utility analysis base-case scenario demonstrated that eletriptan, rizatriptan, and sumatriptan were cost-effective from the healthcare payers' perspective. Deterministic sensitivity analyses showed that the results were sensitive to the drug prices of three triptans. A probabilistic sensitivity analysis revealed that eletriptan, rizatriptan, and sumatriptan were acceptable because of their accessibility and the healthcare payer's willingness to pay for them (5,000,000 yen/quality-adjusted life-years) were 0.662, 0.172, and 0.075, respectively.</span></p> <p><strong><span>Conclusions</span><span>.</span> </strong><span>The results revealed that eletriptan, rizatriptan, and sumatriptan are cost-effective treat</span><span>ments</span><span> in Japan </span><span>for </span><span>migraine from a healthcare payer's perspective.</span></p>
DAta set. Fallen Journals
<p>Producción de las universidades españolas en el periodo 2018-2022, en las revistas expulsadas de Web of Science en 2023. Se incluye le listado de autores que tienen 6 o más trabajos.</p>
High-resolution quasi-idealized experiments for future and present-day based upon composites from a decades-long set of recurving landfalling (RCL) North Atlantic ET cases
<p>We present a high-resolution quasi-idealized experiment based upon composites from a decades-long set of recurving landfalling (RCL) North Atlantic extratropical transition (ET) cases. Following Jung and Lackmann (2021), we apply the track-based classification method of Colbert and Soden (2012) to the historical database (1979 to 2018) of North Atlantic RCL ET events; recurving landfalling tropical cyclones (TCs) are defined as those which cross 70°W north of 25°N or cross 65W north of 40N and threaten the U.S. East Coast. We use the Atlantic Hurricane Database (HURDAT2) best-track data (Landsea and Franklin 2013); the track-based classification procedure yields 37 RCL ET cases over the 40-year period. To minimize the spread of the selected ET cases in terms of time to complete transition, we apply a threshold of 36 h as in Jung and Lackmann (2021). As HURDAT2 only specifies when transition is complete but does not provide the timeline of the transition, we supplement it with the cyclone phase space (CPS) method of Hart (2003) to diagnose onset and completion times of ET; ET events are first identified by HURDAT2 and then we compute the CPS parameters to confirm the ET timeline for each event using the ERA5 reanalysis dataset (Hersbach et al. 2020). This filtering process yields 21 RCL ET cases. This dataset is initialized by randomized 15-case composites selected from the 21 RCL ET cases as in Jung and Lackmann (2021). This dataset was used to produce figures and tables in the manuscript of Jung and Lackmann (2023, in review). </p> <p>Due to storage limitations, the full dataset is much too large to be published (~ 500GB). Instead, a subset consisting of 3-hourly atmospheric temperature at 17 vertical levels, zonal and meridional wind at 17 vertical levels, 3 hourly accumulated precipitation, mean sea level pressure, 10-m zonal and meridional wind, sea surface temperature, and relative humidity at 17 vertical levels is presented. If you wish to access the full dataset, please contact one of the authors. </p>
Data set for "Spatially explicit ecological modeling improves empirical characterization of dispersal"
<p>Data set used and created in the simulations, analysis and figures of the associated paper.</p>
Data sets for "Bridgmanite grain size variation accounts for the mid-mantle viscosity jump" by H. Fei et al.
<p>The date sets contain the grain size data and EPMA data for the article "Bridgmanite grain size variation accounts for the mid-mantle viscosity jump" by H. Fei et al.</p>
PAML data set for integrins, tetraspanins, and ADAMs in the coral Acropora
<p>Data set for gamete composing integrins, tetraspanins, and ADAMs in the coral <em>Acropora digitifera</em>. The LC-MS/MS analyses of eggs or sperm of the coral <em>Acropora digitifera</em> were conducted. Identified integrins, tetraspanins, and ADAMs which are reported in their involvement in the fertilization of the coral <em>Acropora</em>. The data sets were used for analyses of molecular evolutionary analyses with codeml to select which genes encoding the proteins showed accelerated evolution during acquisition of species-specific fertilization. cDNA sequences of the identified proteins were used for collecting the orthologues of the <em>Acropora</em> spp using Orthoscope.</p>
FIGURE 4 in Where to set the bar? Recent descriptions inflate species number in South American toad-headed turtles (Mesoclemmys)
FIGURE 4. Comparison of the mean of the head width (HW), the carapace width (CW), and the plastron length (PL) relative to carapace length (CL) in four adults of Mesoclemmys jurutiensis and M. sabiniparaensis. The data was retrieved from table 4 in Cunha et al. (2021) and table 6 in Cunha et al. (2022). The percentile method was used to generate 95% confidence intervals around the mean (black circle) by bootstrapping 1000 times the observations (grey points). The means of the outgroups M. gibba (dotted horizontal line), M. raniceps (dashed horizontal line), and M. perplexa (dot-dashed horizontal line) were retrieved from table 7 in Cunha et al. (2022).
FIGURE 1 in Where to set the bar? Recent descriptions inflate species number in South American toad-headed turtles (Mesoclemmys)
FIGURE 1. (A) Maximum likelihood tree redrawn from Cunha et al. (2022); (B) maximum likelihood tree using a concatenated alignment (1261 bp; 675 bp COI, 586 bp 16S) combining sequences from Cunha et al. (2021, 2022); (C) topology of the corresponding clades redrawn from Thomson et al. (2021) derived from a Bayesian analysis of 15 nuclear loci. Taxa not represented in Cunha et al. (2021, 2022) are shown in grey. Nomenclature for genera follows TTWG (2021).
FIGURE 3. Maximum likelihood tree using a in Where to set the bar? Recent descriptions inflate species number in South American toad-headed turtles (Mesoclemmys)
FIGURE 3. Maximum likelihood tree using a COI alignment (675 bp) expanding the alignment from Cunha et al. (2021, 2022). Sequences used by Cunha et al. (2021, 2022) in bold. Codes preceding taxon names are GenBank accession numbers. Nomenclature for genera follows TTWG (2021).
FIGURE 2 in Where to set the bar? Recent descriptions inflate species number in South American toad-headed turtles (Mesoclemmys)
FIGURE 2. Maximum likelihood trees for the COI (675 bp) and 16S (586 bp) alignments corresponding to the datasets of Cunha et al. (2021, 2022). Codes preceding taxon names are GenBank accession numbers. Nomenclature for genera follows TTWG (2021).
IG. 6. Ordination diagram of PCA of the Patagonian bat assemblage for craniodental variables using A) data set not size-corrected; and B) data set size-corrected. Polygons include specimens from each species: H. macrotus (▲), H. magellanicus (), H. montanus (▲), L. varius (■), M. chiloensis (●), and T. brasiliensis (£). Vectors show the strengh of correlation of each variable with the plane of PC1 and PC2. See text for abbreviations in Ecomorphological diversity in the Patagonian assemblage of bats from Argentina
IG. 6. Ordination diagram of PCA of the Patagonian bat assemblage for craniodental variables using A) data set not size-corrected; and B) data set size-corrected. Polygons include specimens from each species: H. macrotus (▲), H. magellanicus (), H. montanus (▲), L. varius (■), M. chiloensis (●), and T. brasiliensis (£). Vectors show the strengh of correlation of each variable with the plane of PC1 and PC2. See text for abbreviations
Data set for 'All-microwave Lamb shift engineering for a fixed frequency multi-level superconducting qubit'
<p>Solurce data for the paper 'All-microwave Lamb shift engineering for a fixed frequency multi-level superconducting qubit' (https://www.nature.com/articles/s42005-024-01841-0).</p>
Test Data set
<p>Test data set for flow field</p>
Underwater caves sonar data set
<p>Data set collected with an autonomous underwater vehicle testbed in the unstructured environment of an underwater cave complex. The vehicle is equipped with two mechanically scanned imaging sonar sensors to simultaneously map the caves horizontal and vertical surfaces, a Doppler velocity log, two inertial measurement units, a depth sensor, and a vertically mounted camera imaging the sea floor for ground truth validation at specific points. The testbed collected the data in July 2013, guided by a human diver, to sidestep autonomous navigation in a complex environment. For ease of use, the original robot operating system bag files are provided together with a version combining imagery and human-readable text files for processing on other environments.</p> <p>This dataset was described in:<br> Mallios A, Vidal E, Campos R, Carreras M. Underwater caves sonar data set. The International Journal of Robotics Research. 2017;36(12):1247-1251. doi:10.1177/0278364917732838</p> <p>Web: <a href="https://cirs.udg.edu/caves-dataset/">https://cirs.udg.edu/caves-dataset/</a></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.