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22,922 results for “collections as data”
Analysis of gaps in rapeseed (Brassica napus L.) collections in European genebanks - supplementary data
<p>Species distribution modelling (or ecological niche modelling) was used to predict the effects of climate change on the future distribution of the wild relatives of Brassica napus L. in Europe and countries bordering the Mediterranean Sea. Modelling procedures followed the methods described by Aguirre-Gutierrez et al. 2017 (10.1111/ddi.12573) and van Treuren et al. 2017+2020 (10.1016/j.biocon.2017.10.003; 10.1016/j.gecco.2020.e01054).</p>
Digitized geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy) collected from public sources.
<p>The database is a supplementary material of:</p><p>Livani, M., Petracchini, L., Benetatos, C., Marzano, F., Billi, A., Carminati, E., Doglioni, C., Petricca, P., Maffucci, R., Codegone, G., Rocca, V., Antoncecchi, I. (2023). Subsurface geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy). Earth System Science Data Discussions, 15, n. 9, 4261-4293, doi: 10.5194/essd-15-4261-2023</p><p> </p><p>This database comprises subsurface geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy). We realized the database by collecting, revising, and digitizing data, originally in raster format, from public sources. These data have been then used to reconstruct the overall subsurface 3D architecture and to extract the physical properties of the subsurface geological units.</p><p>The data have a common geographical system: WGS 84/UTM zone 32N; EPSG: 32632.</p><p>The database contains borehole information from 160 deep wells (i.e., wellhead coordinates, rotary table elevation, measured depth, true depth, total depth and deviation survey) and digitized Spontaneous Potential, Gamma Ray, and Sonic logs. Five horizons were digitized from 61 geological cross-sections and from 10 isobath maps that roughly correspond to the boundaries of units showing different lithological properties and with different mechanical properties. The horizons are, from the oldest to the youngest: the top of the magnetic basement, the top of the carbonate succession, the base of the Pliocene, the base of the Calabrian and the base of recent continental deposits. In addition, the gridded surfaces of the 3D geological model are available.</p><p>We organized the database into two groups: "primitive data" and "derived data".</p><p>Primitive data are the result of the digitization of public data. The database of the primitive data is formed by the main horizons reported in the geological cross-sections, the isobaths of the main geological surfaces, the well locations, comprised their trajectory along depth, lithological and stratigraphical information, and geophysical logs from composite well logs. Well data include specific sets of well logs aimed to geological/mechanical characterization of the geological units (e.g., Spontaneous Potential log, Resistivity log, Gamma Ray log, and Sonic log).</p><p>Derived data consist of two datasets: i) the primitive isobaths maps and geological cross-sections data that have been filtered and verified after a data accuracy analysis performed to unravel discrepancies in the interpretation of the subsurface geological horizons; ii) a set of regional surfaces of the main geological units of the Po Plain subsurface. These surfaces were generated by interpolating the filtered primitive data and without considering the fault occurrence/displacements.</p><p>Primitive and derived data are provided in delimited text file format organized according to the data type (i.e., well, geological cross-section, map and gridded surface). The format and the organization of data are explained in the related "readme" file presents within each data folder.</p><p>Our database represents a collection of the main published works regarding the Po Plain. Detailed studies related to specific sectors of the Po Plain might not be present in our database.</p><p>Further details about the data processing and organization are given in the related manuscript.</p><p> </p>
Data for: Considerations for fitting occupancy models to data from eBird and similar volunteer-collected data
<p>An occupancy model makes use of data that are structured as sets of repeated visits to each of many sites, in order estimate the actual probability of occupancy (i.e., proportion of occupied sites) after correcting for imperfect detection using the information contained in the sets of repeated observations. We explore the conditions under which preexisting, volunteer-collected data from the citizen science project eBird can be used for fitting occupancy models. The data archived here are used to explore two ways in which the single-visit records could be used in occupancy models. First, we use empirical data contained within this archive to assess the potential for space-for-time substitution: aggregating single-visit records from different locations within a region into pseudo-repeat visits. The archived data are used to illustrate that the locations chosen for data collection by observers were not always representative of the habitat in the surrounding area, which would lead to biased estimates of occupancy probabilities when using space-for-time substitution. Second, create a large set of simulated data (output from the simulations contained in this archive) that we used to explore the utility of including data from single-visit records to supplement sets of repeated-visit data.</p>
Spatial Data collection for study spatial transition dynamic of Rohingya settlement in Bangladesh: 1st version
<p>Full open access article can be found in: <a href="https://doi.org/10.1016/j.landusepol.2023.106874">https://doi.org/10.1016/j.landusepol.2023.106874</a></p> <p> </p> <p><strong>Full Changelog</strong>: <a href="https://github.com/ssujit/SpatialTransitionDynamic/commits/version">https://github.com/ssujit/SpatialTransitionDynamic/commits/version</a></p>
GPR data collected near the Chepeta Weather Station and the DUST-1 sampler, Uinta Mountains, Utah
Ground penetrating radar data collected on September 9, 2021 in the Uinta Mountains at the Chepeta Remote Automated Weather Station (RAWS) and the DUST-1 passive dust sampler. Data were collected with a GSSI SIR-4000 control unit and a 350HS antenna connected to an Emlid Reach RS2 GPS receiver. Data files have been distance normalized and field-applied range gains have been removed before being exported in .sgy format. Files were also exported in .kml format for viewing the transect locations in Google Earth. Two long transects (780 feet each) were collected. The "West" transect passed to the west of the Chepta RAWS; the "East" transect passed to the east. The transects started at different points along the northern lip of the summit upland and came together at a common point at their southern ends. Marks were made in the data file every 60 feet while surveying; these marks were used to distance normalize the results. The system collected 334 scans/second with 512 samples/scan while surveying. Two 30-foot perpendicular transects were also surveyed (north to south, and west to east) with their intersection adjacent to a soil pit excavated to a depth of 92 cm. The location of the soil pit was noted in each transect with a mark near 16 feet. Data were used to evaluate spatial variations in the thickness of regolith overlying the bedrock beneath this gently sloping summit flat.
CONTRAST-IT corpus: Spanish data collection
<p><strong>This data collection served to create the </strong><a href="http://philhist-contrast-it-noske.philhist.unibas.ch/cnt/run.cgi/first_form"><strong>CONTRAST-IT</strong></a><strong> corpus.</strong> </p> <p><strong>CONTRAST-IT </strong>is a medium-size multilingual corpus (including ca. 1.5 million words) based on a comparable collection of articles published in online daily newspapers. The articles are written in five languages: Italian (from Italy), French (from France), <strong>Spanish</strong> (from Spain), English (from the UK), and German (from Germany).</p> <p>This <strong>Spanish dataset</strong> includes 300'000 words drawn from 476 articles. All the texts collected are authentic, full-length electronic journalistic articles, chosen based on their high representativeness of contemporary <strong>Spanish</strong> newspaper language. The articles were published in 2011 and 2012 in two electronic daily newspapers (elpais.com and elmundo.es).</p> <p>The corpus and data collection were used in two Swiss National Science Foundation Projects:</p> <ul> <li><a href="https://data.snf.ch/grants/grant/133716">Italian Constituent Order in a Contrastive Perspective (ICOCP) (snf.ch)</a></li> <li><a href="https://data.snf.ch/grants/grant/159273">Italian Sentence Adverbs in a Contrastive Perspective (ISAaC) (snf.ch)</a></li> </ul> <p>For details on the corpus and data collection, see:</p> <ul> <li>De Cesare, A.-M<em>.</em> 2019. CONTRAST-IT e COMPARE-IT. Due nuovi corpora per l’italiano contemporaneo. <em>CHIMERA. Romance Corpora and Linguistic studies</em> 6: 43-74. <a href="https://revistas.uam.es/chimera/article/view/11430">https://revistas.uam.es/chimera/article/view/11430</a></li> </ul> <p><a href="https://contrast-it.philhist.unibas.ch/en/corpora/contrast-it-corpus/">CONTRAST-IT. Corpus | contrast_it: italiano in prospettiva contrastiva / Italian in a contrastive perspective (unibas.ch)</a></p>
CONTRAST-IT corpus: French data collection
<p><strong>This data collection served to create the </strong><a href="http://philhist-contrast-it-noske.philhist.unibas.ch/cnt/run.cgi/first_form"><strong>CONTRAST-IT</strong></a><strong> corpus.</strong> </p> <p><strong>CONTRAST-IT </strong>is a medium-size multilingual corpus (including ca. 1.5 million words) based on a comparable collection of articles published in online daily newspapers. The articles are written in five languages: Italian (from Italy), <strong>French</strong> (from France), Spanish (from Spain), English (from the UK), and German (from Germany).</p> <p>This <strong>French dataset</strong> includes 300'000 words drawn from 520 articles. All the texts collected are authentic, full-length electronic journalistic articles, chosen based on their high representativeness of contemporary <strong>French</strong> newspaper language. The articles were published in 2011 and 2012 in two electronic daily newspapers (lemonde.fr and lefigaro.fr).</p> <p>The corpus and data collection were used in two Swiss National Science Foundation Projects:</p> <ul> <li><a href="https://data.snf.ch/grants/grant/133716">Italian Constituent Order in a Contrastive Perspective (ICOCP) (snf.ch)</a></li> <li><a href="https://data.snf.ch/grants/grant/159273">Italian Sentence Adverbs in a Contrastive Perspective (ISAaC) (snf.ch)</a></li> </ul> <p>For details on the corpus and data collection, see:</p> <ul> <li>De Cesare, A.-M<em>.</em> 2019. CONTRAST-IT e COMPARE-IT. Due nuovi corpora per l’italiano contemporaneo. <em>CHIMERA. Romance Corpora and Linguistic studies</em> 6: 43-74. <a href="https://revistas.uam.es/chimera/article/view/11430">https://revistas.uam.es/chimera/article/view/11430</a></li> </ul> <p><a href="https://contrast-it.philhist.unibas.ch/en/corpora/contrast-it-corpus/">CONTRAST-IT. Corpus | contrast_it: italiano in prospettiva contrastiva / Italian in a contrastive perspective (unibas.ch)</a></p>
CONTRAST-IT corpus: Italian data collection
<p>This data collection served to create<strong> </strong>the <a href="http://philhist-contrast-it-noske.philhist.unibas.ch/cnt/run.cgi/first_form"><strong>CONTRAST-IT</strong></a><strong> corpus.</strong> </p> <p><strong>CONTRAST-IT </strong>is a medium-size multilingual corpus (including ca. 1.5 million words) based on a comparable collection of articles published in online daily newspapers. The articles are written in five languages: Italian (from Italy), French (from France), Spanish (from Spain), English (from the UK), and German (from Germany).</p> <p>This <strong>Italian dataset</strong> includes 300'000 words drawn from 531 articles. All the texts collected are authentic, full-length electronic journalistic articles, chosen based on their high representativeness of contemporary Italian newspaper language. The articles were published in 2011 and 2012 in three electronic daily newspapers (repubblica.it, lastampa.it, corriere.it).</p> <p>The corpus and data collection were used in two Swiss National Science Foundation Projects:</p> <ul> <li><a href="https://data.snf.ch/grants/grant/133716">Italian Constituent Order in a Contrastive Perspective (ICOCP) (snf.ch)</a></li> <li><a href="https://data.snf.ch/grants/grant/159273">Italian Sentence Adverbs in a Contrastive Perspective (ISAaC) (snf.ch)</a></li> </ul> <p>For details on the corpus and data collection, see:</p> <ul> <li>De Cesare, A.-M<em>.</em> 2019. CONTRAST-IT e COMPARE-IT. Due nuovi corpora per l’italiano contemporaneo. <em>CHIMERA. Romance Corpora and Linguistic studies</em> 6: 43-74. <a href="https://revistas.uam.es/chimera/article/view/11430">https://revistas.uam.es/chimera/article/view/11430</a></li> <li><a href="https://contrast-it.philhist.unibas.ch/en/corpora/contrast-it-corpus/">CONTRAST-IT. Corpus | contrast_it: italiano in prospettiva contrastiva / Italian in a contrastive perspective (unibas.ch)</a></li> </ul>
EmoKey Moments Muse EEG Dataset (EKM-ED): A Comprehensive Collection of Muse S EEG Data and Key Emotional Moments
<p><strong>EmoKey Moments Muse EEG Dataset (EKM-ED): A Comprehensive Collection of Muse S EEG Data and Key Emotional Moments</strong></p> <p> </p> <p><strong>Dataset Description:</strong></p> <p>The EmoKey Moments EEG Dataset (EKM-ED) is an intricately curated dataset amassed from 47 participants, detailing EEG responses as they engage with emotion-eliciting video clips. Covering a spectrum of emotions, this dataset holds immense value for those diving deep into human cognitive responses, psychological research, and emotion-based analyses.</p> <p><strong>Dataset Highlights:</strong></p> <ol> <li><strong>Precise Timestamps</strong>: Capturing the exact millisecond of EEG data acquisition, ensuring unparalleled granularity.</li> <li><strong>Brainwave Metrics</strong>: Illuminating the variety of cognitive states through the prism of Delta, Theta, Alpha, Beta, and Gamma waves.</li> <li><strong>Motion Data</strong>: Encompassing the device's movement in three dimensions for enhanced contextuality.</li> <li><strong>Auxiliary Indicators</strong>: Key elements like the device's positioning, battery metrics, and user-specific actions are meticulously logged.</li> <li><strong>Consent and Ethics</strong>: The dataset respects and upholds privacy and ethical standards. Every participant provided informed consent. This endeavor has received the green light from the Ethics Committee at the University of Granada, documented under the reference: 2100/CEIH/2021.</li> </ol> <p>A pivotal component of this dataset is its focus on "key moments" within the selected video clips, honing in on periods anticipated to evoke heightened emotional responses.</p> <p><strong>Curated Video Clips within Dataset:</strong></p> Film Emotion Duration (seconds) The Lover Baseline 43 American History X Anger 106 Cry Freedom Sadness 166 Alive Happiness 310 Scream Fear 395 <p>The cornerstone of EKM-ED is its innovative emphasis on these key moments, bringing to light the correlation between distinct cinematic events and specific EEG responses.</p> <p><strong>Key Emotional Moments in Dataset:</strong></p> Film Emotion Key moment timestamps (seconds) American History X Anger 36, 57, 68 Cry Freedom Sadness 112, 132, 154 Alive Happiness 227, 270, 289 Scream Fear 23, 42, 79, 226, 279, 299, 334 <p>Citation:<br> Gilman, T. L., et al. (2017). A film set for the elicitation of emotion in research. Behavior Research Methods, 49(6).<br> <a href="https://doi.org/10.3758/s13428-016-0842-x">Link to the study</a></p> <p>With its unparalleled depth and focus, the EmoKey Moments EEG Dataset aims to advance research in fields such as neuroscience, psychology, and affective computing, providing a comprehensive platform for understanding and analyzing human emotions through EEG data.<br> <br> <br> </p> <p>———————————————————————————————————<br> FOLDER STRUCTURE DESCRIPTION<br> ———————————————————————————————————</p> <p>- questionnaires: all there response questionnaires (Spanish); raw and preprocessed<br> Including SAM<br> |<br> ——preprocessed: Ficha_Evaluacion_Participante_SAM_Refactored.csv: the SAM responses for every film clip</p> <p><br> - key_moments: the key moment timestamps for every emotion’s clip</p> <p>- muse_wearable_data: XXXX<br> |<br> |—raw<br> |——1: ID = 1 of subject<br> |————muse: EEG data of Muse device<br> |—————————ANGER_XXX.csv : leg data of the anger elicitation<br> |—————————FEAR_XXX.csv : leg data of the fear elicitation<br> |—————————HAPPINESS_XXX.csv : leg data of the happiness elicitation<br> |—————————SADNESS_XXX.csv : leg data of the sadness elicitation<br> |————order: film elicitation order of play: For example: HAPPINESS,SADNESS,ANGER,FEAR<br> …<br> |<br> |—preprocessed<br> |——unclean-signals: without removing EEG artifacts, noise, etc.<br> |————muse: EEG data of Muse device<br> |—————————0.0078125: data downsampled to 128 Hz from 256Hz recorded<br> |——clean-signals: removed EEG artifacts, noise, etc.<br> |————muse: EEG data of Muse device<br> |—————————0.0078125: data downsampled to 128 Hz from 256Hz recorded<br> <br> <br> <em>The ethical consent for this dataset was provided by La Comisión de Ética en Investigación de la Universidad de Granada, as documented in the approval titled: 'DETECCIÓN AUTOMÁTICA DE LAS EMOCIONES BÁSICAS Y SU INFLUENCIA EN LA TOMA DE DECISIONES MEDIANTE WEARABLES Y MACHINE LEARNING' registered under 2100/CEIH/2021.</em></p>
Supplementary data accompanying HOCOMOCO v12 collection of transcription factor binding motifs
<p><strong>*** SUMMARY ***</strong></p><p>This dataset contains supplementary data accompanying HOCOMOCO v12 collection</p><p>of DNA binding motifs for human and mouse transcription factors, https://hocomoco.autosome.org</p><p> </p><p>The contents include:</p><p>- the complete initial set of motifs discovered from ChIP-Seq and HT-SELEX data;</p><p>- the curated subset of motifs associated with distinct motif subtypes that were used in benchmarking;</p><p>- the benchmarking results and the resulting final motif collections, including motif logos;</p><p>- accompanying metadata.</p><p> </p><p>Please refer to the README and the HOCOMOCO website for further details.</p><p> </p>
Study to Collect Safety and ECG Data on Brolucizumab 6 mg Intravitreal Treatment in Patients With Wet AMD
ClinicalTrials.gov study NCT03954626. IPD Sharing: YES. Countries: 2. Publications: 1.
Pregnancy Registry to Collect Long-Term Safety Data From Women Treated With HyQvia
ClinicalTrials.gov study NCT02556775. IPD Sharing: YES. Countries: 5. Publications: 1.
Simulation, robot codes and figure data from collective phototactic robotectonics
Open the record for dataset details and reuse information.
Data for: Coordination of care is facilitated by delayed feeding and collective arrivals in the long-tailed tit
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Data collected for: The contrasted impacts of grasshoppers on soil microbial activities in function of ecosystem productivity and herbivore diet
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Data from: Emergence of splits and collective turns in pigeon flocks under predation
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Data from: Integrating deep learning derived morphological traits and molecular data for total-evidence phylogenetics: lessons from digitized collections
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SWIFT data collected in the Southern California Bight by SWIFT drifters as part of the ONR Langmuir Circulation Departmental Research Initiative (LC-DRI)
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Data from: Quantification of collective behaviour via causality analysis
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Data for: From individual behaviors to collective outcomes: fruiting body formation in Dictyostelium as a group-level phenotype
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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.