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747 results for “Open Data”
Data related to: Open-system evolution of a crustal-scale magma column, Klamath Mountains, California
<p>Granitic magmas commonly display evidence for some level of interaction with and/or origins from crustal rocks. There is fundamental debate in the community as to the processes that control the origins of these magmas and the potential for their contamination as they pass through the crust. One approach to addressing these issues involves a combination of detailed field mapping combined with geochemical analysis of bulk-rock samples and their constituent minerals. In particular, resolution of debates about magma origin(s) and contamination processes rely on U-Pb ages of zircon combined with isotopic data gathered from bulk-rock samples and from minerals such as zircon.</p> <p>The data presented here consist of U-Pb, Hf, and oxygen isotope analyses of zircon crystals separated from a major plutonic complex in northern California: the Wooley Creek batholith and Slinkard pluton. In addition, data are presented for samples of the metamorphic rocks that host these intrusions and for xenoliths of these host rocks engulfed by the intrusions. These data are discussed in the above-mentioned manuscript. Generation of the data was supported by National Science Foundation grants EAR-0838342 to C. Barnes and A. Yoshinobu, EAR-0838546 to K. Chamberlain, and EAR-1524336 to J. Valley. The WiscSIMS isotope facility (oxygen isotope data) was supported by NSF grant EAR-1658823 and the University of Wisconsin-Madison.</p> <p>Figure 1 illustrates the locations of plutonic samples analyzed.</p> <p>Table 1 presents sample locations and rock types.</p> <p>Tables 2–5 present U-Pb ages and Hf isotope data determined by laser-ablation inductively coupled plasma mass spectrometry at the University of California-Santa Barbara.</p> <p>Tables 6A–6E present U-Pb ages determined by SHRIMP-RG (sensitive high resolution ion microprobe-reverse geometry) at Stanford University.</p> <p>Table 7 presents oxygen isotope (zircon) data determined by SIMS (secondary ion mass spectrometry at the University of Wisconsin-Madison.</p>
Sato and Ise (submitted) Open Data
<p>______________________________________________________<br>Sato and Ise (2021) Open Data<br>Author: Hisashi SATO (JAMSTEC) hsatoscb_(at)_gmail.com<br>Date: 22 Feb 2022<br>URLs:<br>https://ebcrpa.jamstec.go.jp/~hsato/Sato_and_Ise_2020</p> <p>Corresponding publication: <br>H. Sato and T. Ise (2021) Predicting global terrestrial biomes with the LeNet convolutional neural network. Geoscientific Model Development 2022 Vol. 15 Issue 7 Pages 3121-3132. DOI: 10.5194/gmd-15-3121-2022<br>______________________________________________________<br>1. Folder "1.VCDs"<br>It contains Visualized Climate Environments (VCEs) for training and testing the Convolutional-Neural-Network (CNN) model. Names of compressed files (*.tar.gz) correspond to experiments. Each compressed file contains 4 to 16 folders.<br>Naming rule of folders:<br>The strings "CRU," "NCEP," "HadGEM," and "Miroc" stand for that the files are made from CRU_TS4.0, NCEP/NCAR reanalysis, Had2GEM-ESM, and Miroc-ESM climate datasets, respectively. The strings "AMeans" and "MMeans", respectively, stand for the annual-mean and monthly-mean climates, which are represented by VCEs in the compressed file.<br>The string "EachYear" means that the compressed files contains VCEs of each year climate from 1971 to 1980, otherwise the compressed files contains VCEs of averaged climate over 10 years. The strings "hist", "RCP26", and "RCP85" mean that the compressed files contain VCEs of climate averaged over 1971-1980, 2091-2100@RCP2.6, and 2091-2100@RCP8.5, respectively.<br>MainSimulation_training.tar.gz<br>VCEs for training the CNN model for the main simulation and dependency test of climatic datasets for training and reconstructing performances.<br>MainSimulation.tar.gz<br>VCEs for testing the CNN model for the main simulation.<br>CombinationSelection_Amean.tar.gz<br>VCEs for an experiment to find optimal combination of climatic variables (annual means) represented by the VCEs. In the VCE of the RGB color tile, up to three climate variables can be represented by RGB channels. To find the optimal combination of climatic variables, we systematically evaluated the model performance of 14 combinations of climatic variable experiments for annual means. It's result is presented in the Table S3.<br>Extracting this compressed fire results in "CRU", "NCEP", "HadGEM", and "Miroc" folders. Each folder contains 14 subfolders named with sequential numbers, which corresponds to model numbers in the Table S3.<br>CombinationSelection_Mmean.tar.gz<br>Same as the CombinationSelection_Amean.tar.gz except made with monthly mean climates, and related information is available in the Table S4.<br>ScalerSelection.tar.gz<br>VCEs for evaluating the influences of different transformations of climatic variables on the resulting accuracy. It's result is presented in the Table S5.<br>Extracting this compressed fire results in "CRU", "NCEP", "HadGEM", and "Miroc" folders. Each folder contains 4 subfolders named with sequential numbers. "Scaler1" stands for log transformed, "Scaler2" stands for no transformed (linear), "Scaler3" stands for Sigmoid(gain=5) transformed, "Scaler4" stands for Sigmoid(gain=10) transformed.<br>ColorAssignExperiment.tar.gz<br>VCEs for evaluate the influences of assignment patterns of air temperature and precipitation to RGB color channels of the VCE. It's result is presented in the Table S6. Extracting this compressed fire results in "CRU", "NCEP", "HadGEM", and "Miroc" folders. Each folder contains 6 subfolders named with sequential numbers, which indicates model number in the Table S6.<br>AverageExtentExperiment.tar.gz<br>VCEs for sensitivity test, where training and test accuracies are compared among models that are trained by monthly climate averaged over three different periods: 10 years (1971-1980; Control), 20 years (1961-1980), and 30 years (1951-1980).<br>Individual VCE shows climatic condition of each half degree grid cell. According to the ISLSCP2 data, VCEs are classified by their their potential vegetation type of the grid. Number of deepest folder names correspond vegetation code of the ISLSCP2.<br>Following is the vegetation code.<br> 01: Tropical Evergreen Forest/Woodland<br> 02: Tropical Deciduous Forest/Woodland<br> 03: Temperate Broadleaf Evergreen Forest/ Woodland<br> 04: Temperate Needleleaf Evergreen Forest/Woodland<br> 05: Temperate Deciduous Forest/Woodland<br> 06: Boreal Evergreen Forest/Woodland<br> 07: Boreal Deciduous Forest/Woodland<br> 08: Evergreen/Deciduous Mixed Forest<br> 09: Savanna<br> 10: Grassland/Steppe<br> 11: Dense Shrubland<br> 12: Open Shrubland<br> 13: Tundra<br> 14: Desert<br> 15: Polar Desert/Rock/Ice<br>The naming rule for VCEs of 10 years average climate is following:<br>Latitude number + "_" + Longitude number + ".png"<br>The naming rule for VCEs of each year's climate is following:<br>Latitude number + "_" + Longitude number + "_" + Year of climate + ".png"<br>Here, latitude number ranges from 001 to 360, starting from north-latitude-90 to southward with half degree interval. The longitude number ranges from 001 to 720, starting from west-longitude-180 to eastward with half degree interval. <br>On top of this subfolder, there is PicList.zip, which is a compressed file of PicList.txt. This text file is required to classify VCEs with the trained model.<br>_____________________________________________<br>2. Folder "2.Result"<br>It contains copies of the image classification results on the Digits screen. <br>Subfolder names correspond to experiment names. Each subfolder contains sub sub-folders "DigitsOutput," "ConfusionMatrix," and "ReconstructedBiomeMap." Naming rules for files are basically same as those of VCEs.<br>_____________________________________________<br>3. Folder "3.LearningCurves"<br>It contains screen capture of Digits output, showing learning curve of CNN models. CRU climate data. This folder contains 5 subfolders. Naming rules of these subfolders are same as those of VCEs.<br>_____________________________________________<br>4. Folder "5.FigureMaterials" <br>It contains data and codes (in R) for drawing the figures in the manuscript."<br>_____________________________________________________________</p>
Barley recombination open data
<p>Data concerning the publication "Genomic prediction of the recombination rate variation in barley – A route to highly recombinogenic genotypes".</p> <p> </p>
Surveying Open Data Practices: Final datasets
<p>Final datasets from the two rounds of dissemination of the survey on Open Data Practices conducted during the Surveying Open Data Practices project 2020 - 2021. First round of dissemination was in English, French and Portuguese to researchers in Uganda, Ethiopia, Burkina Faso, Senegal, Botswana, Malawi, Mozambique and Zimbabwe. The second round of dissemination was in English to Botswanan researchers in collaboration with the Botswana Academy of Sciences. </p>
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island
Dataset for How open is innovation research?–An empirical analysis of data sharing among innovation scholars
<p>This dataset comprises responses from 241 innovation researchers on their personal data sharing behavior as well as their perceptions of and attitudes towards open research data. This dataset is the supplementary material to Barczak et al. (2021) (<a href="https://doi.org/10.1080/13662716.2021.1967727" target="_blank" rel="noopener">https://doi.org/10.1080/13662716.2021.1967727</a>).</p>
Supplements and raw data for article to be published in Open Linguistics
<p>Supplements A, B and C of article (docx and pdf versions) :</p> <p>Emmanuel Cartier, Alexander Onysko*, Esme Winter-Froemel, Eline Zenner, Gisle Andersen, Béryl Hilberink-Schulpen, Ulrike Nederstigt, Elizabeth Peterson, and Frank van Meurs (2022). Linguistic repercussions of COVID-19:A corpus study on four languages, Open Linguistics 2022; 8:1-16.</p> <p>A supporting web exploration interface is available here : <a href="https://tal.lipn.univ-paris13.fr/neoveille/html/covid19_project/html/data_exploration.php">Link to web interface</a></p> <p>Raw data for the supplements and the web interface are here :</p> <p><a href="https://zenodo.org/api/files/d633542e-cdbc-4f4b-a43b-5bf7895b8a7c/raw_data_virus_names.tar.gz">raw_data_virus_names.tar.gz</a> : the raw data of the virus names (with a file for all languages, and a file per language).</p> <p><a href="https://zenodo.org/api/files/d633542e-cdbc-4f4b-a43b-5bf7895b8a7c/raw_data_virus_associated_words.tar.gz">raw_data_virus_associated_words.tar.gz</a> : the raw data of the virus names associated words (with a file for all languages, and a file per language).</p>
Code & Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"
<p>This entry contains code and data that was used in the publication: "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals" submitted in Publications journal.</p> <p>*It was version 2 when we added Fig_3_Tab2_Defining_science_disciplines_plus_plot.R script to version 1.</p> <p>*It was version 3 because we added script that calculates median and mean values of the stringency levels to version 2 data.</p> <p>*Latest version is version 4: we added supplementary data.</p> <p>#IDEA:</p> <p>This project was about analyzing policies of two thousand journals within the framework of eight TOP standards: <br> data citation, transparency of data, material, code and design and analysis, replication, plan and study pre-registration, <br> and two effective interventions: “Registered reports” and “Open science badges”. </p> <p># MATERIALS & METHODS<br> We downloaded the TOP Factor (v33, 2022-08-29 3:12 PM) metric from the https://osf.io/kgnva/files/osfstorage/5e13502257341901c3805317 <br> website and analyzed its content with an in-house R script (in this repo):<br> 1) SCRIPT: fig1_Analyzing_journals_policies_and_TOP_guidelines.R<br> 2) SCRIPT: Figure2a_b_TOP_impl_journal_statistist_0_1_piechart_barplot.R<br> In order to get statistics about implementation of the TOP guidelines across discipline-specific journals, <br> we extracted information about journal’s disciplines from the Scopus content database. <br> We downloaded SCOPUS content coverage from the https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030 (existJuly2022.xlsx)<br> and used the first Sheet.<br> We identified match between those 2 tables: <br> 3) SCRIPT: Rscript_overlapping_TOP_dataframe_and_SCOPUS_db.R<br> And resulted in Overlap_SCOPUS_TOP.rds file<br> And performed visualization and statistics:<br> 4) SCRIPT: Fig_3_Tab2_Defining_science_disciplines_plus_plot.R</p> <p> </p> <p>#RESULTS Submitted to Publications 30.9.2022.</p> <p>Reviewed 2.11.2022.</p> <p>Latest version: 25.11.2022.</p>
Data accompanying "Calibrated microphone array recordings reveal that a gleaning bat emits low-intensity echolocation calls even in open-space habitat"
<p>Introduction to the dataset: </p> <p>In this manuscript, we analyse recordings of brown long-eared bats in the wild collected with a 4-microphone array, which we use to measure the distance between the bat and the microphone.<br> The distance is then used to correct the recordings for distance-dependent frequency and amplitude attenuation.<br> To ensure that our measurements and corrections are correct, we fully calibrated the microphone array and analysis set-up. <br> The calibration includes a comparison between real distances and calculated distances between a loudspeaker and the microphone array as well as comparisons between the real amplitude and the calculated amplitude of the loudspeaker.<br> To obtain the original amplitude of the calibration recording, we calibrated the loudspeaker as well</p> <p>In this folder, we provide the original bat recordings as well as the datasheet with all analysed call measurements, and the original data from the microphone calibration.</p> <p>DATA & FILE OVERVIEW</p> <p>Folder list: <br> - Bat data: folder containing the original Plecotus recordings and raw call parameters<br> - Calibration data : folder containing the array calibration raw data, as well as codes and recordings necessary to calibrate the loudspeaker. <br> </p>
Open data for "Programmable frequency-bin quantum states in a nano-engineered silicon device"
<p>The folder includes includes the raw data that were used for generation of all Figures in the paper "Programmable frequency-bin quantum states in a nano-engineered silicon device".</p>
Data set for phase-field simulation of epitaxial crystal growth in open fractures with lateral flow
<p>The numerical data in this repository consists of the simulation data of epitaxial crystal growth in open fractures with lateral flow. The simulations were performed using the software package named "Pace3D".</p> <p>The simulation data shows the grain structure, the concentration field and the fluid flow velocity in stream direction (if present) at intermediate stages. It was converted from the Pace3D output data format to VTK data format. The VTK files can be visualized using open source software packages like Paraview. For visualization the data has to be decompressed (e.g. with gzip, 7zip).</p>
Data set open access of Palm Oil Supply Chain
<p>This data set including interview recorded as the qualitative data, picture, draft article, and interview transcript. This is open access data.</p>
RESILOC Semantic Layer Open Data
<p>Ontologies implemented for the RESILOC project.</p>
Central European Grid Frequency data in Open-ENF .fredb format
<p>This file contains the Central European Wide Area Grid frequency for each second betwen 31st Dec 2009 23:00 UTC and 31st Dec 2020 23:00</p>
Deciphering the structural dynamics in molten salt-promoted MgO-based CO2 sorbents and their role in the CO2 uptake. Open data access
<p><strong>Open data for publication "Deciphering the structural dynamics in molten salt-promoted MgO-based CO<sub>2</sub> sorbents and their role in the CO<sub>2</sub> uptake" </strong></p>
Open data for "3D integration enables ultra-low-noise isolator-free lasers in Si photonics"
<p>Open data for "3D integration enables ultra-low-noise isolator-free lasers in Si photonics"</p>
Data for: Butterfly eyespots exhibit unique patterns of open chromatin
<p>How the precise spatial regulation of genes is correlated with spatial variation in chromatin accessibilities is not yet clear. Previous studies that analysed chromatin from homogenates of whole-body parts of insects found little variation in chromatin accessibility across those parts, but single-cell studies of <em>Drosophila </em>brains showed extensive spatial variation in chromatin accessibility across that organ. In this work we studied the chromatin accessibility of butterfly wing tissue fated to differentiate distinct colors and patterns in pupal wings of <em>Bicyclus anynana</em>. We observed that three dissected wing regions showed unique chromatin accessibilities. Open chromatin regions specific to eyespot color patterns were highly enriched for binding motifs recognized by Suppressor of Hairless (Su(H)), Krüppel (Kr), Buttonhead (Btd) and Nubbin (Nub) transcription factors. Genes in the vicinity of the eyespot-specific open chromatin regions included those involved in wound healing and SMAD signal transduction pathways, previously proposed to be involved in eyespot development. We conclude that eyespot and non-eyespot bits of tissue taken from the same wing have distinct patterns of chromatin accessibility, possibly driven by the eyespot-restricted expression of potential pioneer factors, such as Kr.</p>
NOAA Open Data Dissemination: Petabyte scale Earth System Data in the Cloud
<p>NOAA Open Data Dissemination (NODD) makes NOAA environmental data publicly and freely available on Amazon Web Services (AWS), Microsoft Azure (Azure), and Google Cloud Platform (GCP). These data can be accessed by anyone with an internet connection and span key datasets across the Earth system including satellite imagery, radar, weather models and observations, ocean databases, and climate data records. NODD works closely with NOAA stakeholders to make these data available consistently and performantly, often with near-real-time latency. Since its inception, NODD has grown to provide public access to more than 24PB of NOAA data and can support billions of requests and petabytes of access daily. NODD growth is driven by use; stake- holders routinely access more than 5PB of NODD data every month. NODD continues to grow to support open petabyte-scale Earth system data science in the cloud by investing in onboarding additional NOAA data, performant data formats, and streaming data platforms. Here, we document how this pro- gram works with a focus on data provenance, discuss the key datasets available through NODD, show how these data are being used, and highlight ways these data can be accessed with the goal of accelerating use of NOAA resources in the cloud.</p>
Geochemical data for: Intense overpressurization at basaltic open-conduit volcanoes as inferred by geochemical signals: The case of the Mt. Etna December 2018 eruption
<p>The reported dataset is annexed to the article "Intense overpressurization at basaltic open-conduit volcanoes as inferred by geochemical signals: the case of the Mt Etna December 2018 eruption". It consists of five types of parameters: soil CO<sub>2</sub> flux from Mt Etna flanks, CO<sub>2</sub>/SO<sub>2</sub> molar ratio of the volcano plume, SO<sub>2</sub> and HCl fluxes by volcano plume, and He isotope ratio in some peripheral gas emissions, all of them recorded in the period 2017–2019. The data come from continuous monitoring networks installed on Mt Etna and from discrete samplings carried out at specific sites, all the monitoring facilities being supported by the INGV-Civil Defence joint surveillance program.</p>
Open Data for publication Influence of the Time Scale on the Reaction Mechanism of CO Oxidation over a Au/TiO2 Catalyst
<p>The file contains the origianl raw data for publication:</p> <p>Influence of the Time Scale on the Reaction Mechanism of CO Oxidation over a Au/TiO2 Catalyst, Angewandte Chemie, 2023</p> <p>The data contains the IR spectra of the CO2 signal, the IR spectra at different temepratures (modulation experiments) and the IR spectra for different modulation periods at 50 deg C (modulation experiments), as described in the publication.</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.