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2,984 results for “Raw data”
Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2020-01-01 to 2020-12-31 [RAW]
<p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2020. </p> <p>Phenocam "hartheim2" shows the view from the main tower at 8.4 m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosyste Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p>
Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2021-01-01 to 2021-12-31 [RAW]
<div> <p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2021. </p> <p>Phenocam "hartheim2" shows the view from the main tower at 7m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosystem Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p> </div>
Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2022-01-01 to 2022-12-31 [RAW]
<div> <p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2022. </p> <p>Phenocam "hartheim2" shows the view from the main tower at at 8.4 m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosystem Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p> <p> </p> </div>
Raw data of individuals with Down syndromre, individuals with Williams syndrome, healthy children and adults in a visual learning task, a conditional learning task and a transitive inference task.
<p>Raw data of 17 individuals with Down syndrome (8 girls/women; average age: 17.8 years; range: 7.2-30.8 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.</p> <p>Raw data of 27 individuals with Williams syndrome (16 girls/women; average age: 23.7; range: 9.4-43.8 at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.</p> <p>Raw data of 71<strong> </strong>healthy children (31 girls; average age: 6.42 years; range: 2.95-11.64 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.</p> <p>Raw data of 22 healthy adults (11 femaleswomen; average age: 26.05 years; range: 20.32-29.76 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.</p>
Raw Data for Mapping Repositories and their Institutional Open Science Policies in Asia
<p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In Asia, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in Asian countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in Asia' at <a href="https://doi.org/10.5281/zenodo.12566244">https://doi.org/10.5281/zenodo.12566244</a></p>
Mass spectrometry raw data for "Proteomics reveals substantial differences between in vitro matured abattoir-derived and in vivo matured oocytes in cattle"
<p><em><span>In vitro</span></em><span> production (IVP) of bovine embryos still has its limitations such as low blastocyst rate and lower embryo quality, resulting in lower pregnancy rates following the transfer of IVP embryos compared to <em>in vivo</em> produced embryos. </span><span>Given these differences in developmental competence, RNA sequencing and microarray technology have been applied to describe the differences in transcriptional activity between <em>in vitro</em> and <em>in vivo</em> produced embryos. All but one of these studies solely utilized oocytes obtained from slaughterhouse material for the <em>in vitro</em> production of embryos, thereby introducing the possibility, that differences between IVP and <em>in vivo</em> embryos are in part attributable to differing sources of oocytes. The aim of the present study was therefore to compare the proteome of oocytes retrieved from slaughterhouse material, with and without a period of <em>in vitro</em> maturation and <em>in vivo</em> matured oocytes obtained from donor cattle following superovulation. <span>For each group the protein pattern of four biological replicates containing ten oocytes each were analyzed via SWATH<sup>TM</sup>-MS.</span></span></p>
Survey questions and raw data for the study in the paper "Educational Technology for Tutors – What are Useful Tools and Information?"
<p>The data include the questions data set, the answers dataset and the codebook for the questions conducted with soscisurvey (https://www.soscisurvey.de/de/index). The survey itself can be imported in soscisurvey (via the XML data) and reused.</p> <p>The answers are unedited.</p>
Raw Data of Pilot Plant Runs for CONSENS Project (Case Study 1)
<p>In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and <em>o</em>-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum. </p> <p>The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17.</p> <p>In the following the contents of the files are explained.</p> <p><strong>NIR_data_AQ15_raw.zip: </strong>Contains Bruker binary files (0-Files) of NIR spectrometer at AQ15 (Location is located subsequently to NMR spectrometer)</p> <p><strong>NMR_spectra_raw.zip: </strong>Contains Spinsolve files (Binarys of FID and Spectrum, DX-Files) of NMR spectrometer. The use of DX-files files is not recommended.</p> <p><strong>PCS_data_csv.zip</strong>: Contains csv-files of the process control system (PCS) including data of mass flow controlers (*_Bilanz.csv), filling level (*_FillLe.csv), pressures (*_pres), temperatures (*_Temp), position of valves (*_Valves). Relevant labels are: BP13 = LiHMDS storage tank, BP12 = aniline storage tank, BP12 = <em>o</em>-FNB storage tank, CM003 and CM004 = tubular reactors, T0041 and T005 = Temperature at reactor exits, P009 and P003 = Pressure at reactor inlets, P006 = Pressure at reactor exits.</p> <p><strong>housing_data_NMR.csv</strong>: Contrains data of NMR enclosure of all four days. Each columns from left to right represent timestamps, bypass pressure (bar), bypass temperature (°C), Gasalarm (logical), bypass actual flowrate (g min<sup>-1</sup>), bypass flowrate setpoint (g min<sup>-1</sup>), bypass density (kg m<sup>3</sup>)</p> <p><strong>matlab_variables_explanation.xlsx</strong>: Explanation of variables used in matlab structure "data_validation_run".</p> <p><strong>data_validation_run.mat</strong>: Matlab structure containing most relevant process data including NMR results, NIR results, housing data of NMR, and process control system data.</p>
Raw multibeam bathymetry data collected around the Candlemas Islands, part of the South Sandwich Islands chain in the Southern Ocean on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the Candlemas Islands, part of the South Sandwich Islands chain in the Southern Ocean in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>lineYYYYDDmonHHMMSS.ssv, data file, ASCII</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw multibeam bathymetry data collected around Siple Island in Marie Byrd Land, Antarctica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected Siple Island in Marie Byrd Land, Antarctica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>lineYYYYDDmonHHMMSS.ssv, data file, ASCII</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw multibeam bathymetry data collected around Scott Island in the Southern Ocean on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around Scott Island in the Southern Ocean in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p> <p> </p>
Raw multibeam bathymetry data collected around the sub-Antarctic Prince Edward Islands on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the sub-Antarctic Prince Edward Islands in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>*.txt, ancillary file, ASCII</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw multibeam bathymetry data collected in the wider polynya area around the Mertz glacier, East Antarctica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected in the wider polynya area around the Mertz glacier, East Antarctica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/l</p>
Raw multibeam bathymetry data collected around the Mertz glacier, East Antarcica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the Mertz glacier, East Antarcica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw multibeam bathymetry data collected around the Balleny Islands, Antarctica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the Balleny Islands, Antarctica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw data for manuscript A. Dey et. al., ACS Nano 2023, 17, 16, 16080–16088.
<p><strong>Scan_00165.zip</strong>: This compressed file contains the raw X-ray data collected at beamline P06 at PETRA III, DESY, relevant for the manuscript. From this dataset that includes Bragg diffraction and X-ray fluorescence data from the indium Kα, gallium Kα, and arsenic Kα lines, all figures containing X-ray data in the manuscript were created. For viewing, use, e.g., <a href="https://ncnr.nist.gov/ncnrdata/view/nexus-hdf-viewer.html">https://ncnr.nist.gov/ncnrdata/view/nexus-hdf-viewer.html</a>.</p> <p><strong>W795_29a.tif</strong>: This data file is the raw SEM image from which the high magnification cut-out in the manuscript figure was taken. The SEM image was collected at an acceleration voltage of 15 kV using a trough-lens detector in secondary electron imaging mode. The field of view is 2.12 µm. For viewing, use any standard image viewer.</p> <p><strong>W795_InGaAsQDs.0_00023.spm</strong>: This data file is the raw AFM image from which after processing the AFM figures and AFM height information given in the manuscript were obtained. The image size is 200 nm × 200 nm, and was obtained at a scanning speed of 1 Hz with a resolution of 512 × 512 pixels. For viewing, install, e.g., <a href="http://gwyddion.net/download.php">http://gwyddion.net/download.php</a>.</p>
Raw Data for Mapping Repositories and their Institutional Open Science Policies in the Middle East and North Africa (MENA)
<div> <p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In the Middle East and North Africa (MENA) region, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in MENA countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in MENA' at <a href="https://doi.org/10.5281/zenodo.11370031">https://doi.org/10.5281/zenodo.11370031</a></p> </div>
Raw data for Infrastructure and Awareness Landscape Analysis in Latin America
<p>Persistent Identifiers (PIDs), such as Digital Object Identifiers (DOIs), are foundational to connecting and enhancing the visibility of Latin American research within a global framework. Although the region is rich in diverse and impactful research, many repositories remain only partially integrated into international registries and aggregators, limiting their discoverability and reach. The adoption of PIDs across repositories in Latin America varies widely, underscoring the need for increased awareness about the role of open PIDs in advancing research accessibility and visibility.</p> <p>This dataset offers a comprehensive overview of the current landscape of repositories, publishing systems, and Open Science policies across Latin America, shedding light on the institutional and national efforts that support an open and inclusive research infrastructure. It highlights the importance of collaboration among researchers, institutions, funders, librarians, and government agencies in fostering Open Science practices and encouraging strategic PID adoption. By expanding these open practices and strengthening PID adoption, Latin American research can achieve greater integration and impact within the global research ecosystem.</p> <p>You can read the full report titled "Infrastructure and Awareness Landscape Analysis in Latin America" at <a href="https://doi.org/10.5281/zenodo.14010858" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14010858</a> </p>
MRI raw data for: A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry
<p>MRI raw data from three different magnetic field strength (1.5 T, 3 T, 7T; 7T data are in separate datasets) for the publication 'A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry', in which a phantom was presented that allows for an experimental evaluation of QSM reconstruction algorithms. The phantom contains susceptibility producing particles with dia- and paramagnetic properties embedded in an MRI visible medium (gelatin and agarose gel) and is suitable to assess the performance of algorithms that attempt to separate isotropic dia- and paramagnetic susceptibility at the sub-voxel level. The dataset additionally contains raw data for a phantom that only contains diamagnetic and paramagnetic particles, respectively, for magnetic field strengths of 1.5 T and 3 T (additional 7 T data are provided in separate datasets).</p>
Raw data for the article "Effective perspiration is essential to uphold the stability of zero-gap MEA-based cathodes used in CO2 electrolysers"
<p>Raw data for the article "Effective perspiration is essential to uphold the stability of zero-gap MEA-based CO2 electrolysers", published in Journal of Materials Chemistry A 2023 11:5083–5094, doi: <a href="https://doi.org/10.1039/D2TA06965B">10.1039/D2TA06965B</a></p> <p>Folder names describe the type of data content.</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.