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306 results for “data archive”

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zenodo36/100

Samoan Passage Moored Profiler Data Archive

<p>Samoan Passage Moored Profiler Data Archive. Please note that the copy here on zenodo contains only the GitHub repository, data are stored elsewhere.</p> <p>Head to <a href="https://github.com/gunnarvoet/sp-data-archive-mp">https://github.com/gunnarvoet/sp-data-archive-mp</a> for instructions on how to clone the full dataset or download data files manually at <a href="https://osf.io/7b8fn/">https://osf.io/7b8fn/</a>.</p>

opencc-zeroOct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 9 April 2010

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 9 April 2010</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 14 January 2016

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 14 January 2016</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 2 August 2017

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 2 August 2017.</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 26 August 2014

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 26 August 2014</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 30 January 2018.

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 30 January 2018.</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 31 August 2016

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 31 August 2016</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 15 July 2016

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 15 July 2016</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 11 August 2011

<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 11 August 2011</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Samoan Passage CTD/LADCP Data Archive

<p>Samoan Passage CTD/LADCP Data Archive. Please note that the copy here on zenodo contains only the GitHub repository, data are stored elsewhere.</p> <p>Head to <a href="https://github.com/gunnarvoet/sp-data-archive-ctd">https://github.com/gunnarvoet/sp-data-archive-ctd</a> for instructions on how to clone the full dataset or download data files manually at <a href="https://osf.io/up5j4/">https://osf.io/up5j4/</a>.</p>

opencc-zeroOct 2022View details →
zenodo36/100

Data Archive from the MX3D Bridge in Amsterdam

<h1><strong>Data Archive from the MX3D Bridge in Amsterdam</strong></h1> <p>This DOI refers to the data collected from the <a href="https://www.thefabricator.com/thefabricator/article/additive/testing-the-worlds-first-3d-printed-metal-bridge">3d-printed bridge from MX3D in Amsterdam</a> from ~June 2021 &ndash; 6th July 2023. Contained within this DOI is a set of metadata that outlines the specifics of the sensors that were used to collect the data.</p> <h2><strong>Breakdown of (zipped) directory structure</strong></h2> <ol> <li> <p><strong>"Calibration_Info" Folder</strong>: This directory includes the manufacturer's sensor datasheets and houses two subdirectories:</p> <ul> <li>"CXTA01-T" and "CXL04GP3-R-AL", each containing calibration factor files specific to inclinometers and accelerometers, respectively.</li> </ul> </li> <li> <p><strong>"26102020 MX3D Bridge Sensor System" Spreadsheet (.xlsx)</strong>: This spreadsheet enumerates the sensors, cataloging critical details such as measurement direction, location, and associated data modules.</p> </li> <li> <p><strong>"Sensor Layout" PDF (.pdf)</strong>: A document depicting the layout of sensors on the MX3D bridge, with "North" and "South" annotations pertaining to the bridge's orientation in Amsterdam.</p> </li> <li> <p><strong>"Sensor Layout with Surroundings" PDF (.pdf)</strong>: An enhanced version of the Sensor Layout document, this PDF includes additional annotations regarding the surrounding bars to provide context to the sensor locations.</p> </li> </ol>

opencc-by-4.0Feb 2024View details →
zenodo36/100

Data archive for: Chain forming diatoms use different strategies to avoid diffusion limited N assimilation

<p>Data archive for: &ldquo;Chain forming diatoms use different strategies to avoid diffusion limited N assimilation&rdquo; published in <em><strong>Limnology and Oceanography (L&amp;O), <a href="https://doi.org/10.1002/lno.12677">https://doi.org/10.1002/lno.12677</a></strong></em>.</p> <p>&nbsp;</p> <p>Dataset of single cell assimilation of DIC and NO<sub>3</sub><sup>-</sup> by <em>Skeletonema marinoi</em> in the exponential and stationary growth phase captured using secondary ion mass spectrometry (SIMS) and stable isotopic tracers. The data set contains the data used in the study and the outliers excluded from further analysis.</p> <p>&nbsp;</p> <p>Two strains (Strain 1 and Strain 2) were incubated during either the exponential or stationary growth phase over 24h with <sup>15</sup>N enriched NO<sub>3</sub><sup>-</sup> and <sup>13</sup>C enriched DIC. The cell specific DIC and NO<sub>3</sub><sup>-</sup> assimilation was measured using SIMS.</p> <p>See the main manuscript for a extensive experimental setup and more details.</p> <p><strong>Each file is uploaded as both a .CSV and .XLSX, so that you can choose which you prefer.</strong></p> <p>&nbsp;</p> <p><strong>Row description:</strong></p> <p>Each row represents one <em>Skeletonema marinoi cell</em>.</p> <p><strong>Column description: </strong></p> <p><em>Single.cell:</em> if the cell was a solitary cell (y) or not (n)</p> <p><em>End.cell:</em> if the cell was located at the end of a chain (y) or not (n)</p> <p><em>Chain_position:</em> a number assigned to identify every cell in a chain starting with 1 at one end of the chain</p> <p><em>Chain_length_numeric:</em> the total number of cells in the chain</p> <p><em>Chain_length_max_6: </em>the total number of cell in the chain, all numbers larger than 6 are pooled together and labelled &gt;6</p> <p><em>Two_chain:</em> if the cell was in a chain consisting of only 2 cells (y) or not (n)</p> <p><em>Cell_information:</em> whether the cell was a solitary cell (Single cell), found in a two cell chain (Two cell chain), found at the end of a chain longer than 2 cell (End cell), or in the middle of a chain longer than 3 cells (Middle cell).</p> <p><em>Chain:</em> a identifying number assigned to differentiate the different chains</p> <p><em>C_fmol_per_cell_day:</em> DIC assimilated in fmol cell<sup>-1</sup> day<sup>-1</sup></p> <p><em>N_fmol_per_cell_day:</em> NO<sub>3</sub><sup>-</sup> assimilated in fmol cell<sup>-1</sup> day<sup>-1</sup></p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Archive of the microtremor data used in Cho and Nakazawa 2024

<p>This archive includes microtremor data and the analysis results used in "Shallow microtremor survey using miniature and small arrays: Strategy for efficient and feasible dense survey" by Ikuo Cho and Tsutomu Nakazawa (2024, Earth and Space Science).&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo36/100

Data archive for paper "Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city"

<p><strong>Overview</strong></p> <p>This is the data archive for paper "<a href="https://www.nature.com/articles/s41467-024-49836-3" target="_blank" rel="noopener">Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city</a>". It contains the paper's data archive with model outputs (see <code>notebooks</code> folder) and the Singularity image for (optionally) re-running experiments.</p> <p>For the standalone models to model air conditioners and heat pumps please refer to <a href="https://github.com/dmey/minimal-dx">MinimalDX</a>.</p> <p><strong>Prerequisites</strong></p> <ul> <li>Linux with Bash shell.</li> <li><a>Git</a> version &gt;= 2.</li> <li><a href="https://sylabs.io/">Singularity</a> version &gt;= 3.</li> <li><a href="https://en.wikipedia.org/wiki/Portable_Batch_System">Portable Batch System</a>*.</li> <li><a href="https://en.wikipedia.org/wiki/Intel_Fortran_Compiler">Intel Fortran Compiler</a> [<em>Required for MesoNH simulations</em>].</li> <li>A compatible version of the MPI library implementation version 3 [<em>Required for MesoNH simulations</em>].</li> </ul> <p>Please note that most steps require <a href="https://sylabs.io/">Singularity</a>. If you are looking for information on how to install or use Singularity, please refer to the <a href="https://sylabs.io/docs">Singularity documentation</a>. Please note that depending on your specific system settings and resource availability, you may need to modify PBS parameters at the top of submit scripts stored in the hpc directory.</p> <p><strong>Simulations</strong></p> <p><em><strong>Offline</strong></em></p> <ol> <li>Build Surfex with <code>qsub hpc/surfex_build.pbs</code>.</li> <li>Run scenarios with the following commands: <pre><code> qsub -v case_name=fincap hpc/surfex_run.pbs qsub -v case_name=fincap_extended_autosize hpc/surfex_run.pbs qsub -v case_name=minidx_cop=2.5 hpc/surfex_run.pbs qsub -v case_name=minidx_cop=3.0 hpc/surfex_run.pbs qsub -v case_name=minidx_cop=3.5 hpc/surfex_run.pbs qsub -v case_name=minidx_cop=4.0 hpc/surfex_run.pbs<br> qsub -v case_name=minidx_cop=4.5 hpc/surfex_run.pbs </code></pre> </li> </ol> <p><em><strong>Online</strong></em></p> <p>To run MesoNH simulations, follow the three steps outlined below in the same order. Note: Depending on your system and configuration, submit scripts may require change.</p> <ol> <li>Build MesoNH with <code>qsub hpc/build_mnh_intel.pbs</code>.</li> <li>Run the preprocessing step with <code>qsub hpc/submit_mnh_prep.pbs</code>.</li> <li>Finally run MesoNH cases with the following commands for <code>fincap</code> and <code>minidx</code> simulations respectively: <pre><code> hpc/submit_mnh.sh fincap 20050120 12 1 toulouse hpc/submit_mnh.sh minidx 20050120 12 1 toulouse </code></pre> </li> <li>Post-process the results with <code>qsub hpc/submit_mnh_post.pbs</code></li> </ol> <p><strong>Analyses</strong></p> <pre><code>qsub hpc/postprocess_results.pbs # Plots in notebooks/ </code></pre>

openother-atMar 2024View details →
dryad36/100

Key habitat for male Strix nebulosa (Great Gray Owls) varies across the diurnal cycle and reflects sex-specific role, data archive

<p>We used GPS tracking and remotely-sensed environmental data to evaluate whether breeding-season habitat selection by adult male <em>Strix nebulosa </em>(Great Gray Owls) (n = 19) varied across diurnal periods (dawn, day, dusk, and night). To address knowledge gaps related to nocturnal habitat, we also evaluated finer-scale, microhabitat selection by male owls at night. Here, we include both the remotely-sensed habitat data and on-the-ground microhabitat data associated with owl locations.  Generally, <em>S. nebulosa </em>are associated with mature forests for nesting and meadows for foraging. Yet, in our study, owls avoided herbaceous wetlands during the day but strongly selected them at dawn, dusk, and at night, indicating context-dependent habitat selection. Moreover, owls avoided dry meadows at all times of the day, suggesting that wet rather than xeric meadows are important for foraging. Owls also preferred nighttime microhabitats that facilitated foraging, such as those with presence of primary prey and open understories dominated by graminoids and forbs. During the daytime, owls preferred higher canopy cover and areas with increased soil moisture, which likely provided suitable roosting habitat. Understanding of habitat preferences across sexes, activity periods, and other contexts can improve the identification and conservation of critical habitat for wildlife.</p>

opencc-zeroJul 2024View details →
zenodo36/100

padpadpadpad/Padfield_2018_ELE_metab_size_struc: Archive of analysis and raw data for Padfield et al (2018) ELE

<p>This is an archived version of the data and analysis to go along with the paper:</p> <p>Padfield et al. (2018) Linking phytoplankton community metabolism to the individual size distribution. Ecology Letters. <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/ele.13082">https://doi.org/10.1111/ele.13082</a>.</p>

openother-openMay 2018View details →
zenodo36/100

samfranks/eu_meadow_birds: Public archive of data and code for paper publication

<p>Public archive of data and code for paper publication Franks <em>et al</em>. (2018). Evaluating the effectiveness of conservation measures for European grassland-breeding waders. <em>Ecology and Evolution</em></p>

openother-openSep 2018View details →
zenodo36/100

Illustrative Darwin core archive to output data from a citizen science platform to a collection management system

<p>Illustrative DwC archive to send data back to a collection management system from a citizen sciences platform. This illustrative archive displays the specimens used for the trans-institutional and trans-platform pilot project held in the frame of ICEDIG.</p> <p>Further description of its content in the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>

opencc-by-4.0Feb 2019View details →
zenodo36/100

Empairex 1: Optical properties data archive

<p>This spreadsheet contains all the numerical data used to make the figures in the manuscript &quot;Chemical composition, optical properties and radiative forcing efficiency of nascent particulate matter emitted by an aircraft turbofan burning conventional and alternative fuels&quot; and in the corresponding supplementary information.&nbsp;</p>

opencc-by-4.0Dec 2018View details →
zenodo36/100

German Gas Feed-in/-out Data Archive

<p>Provided data includes the following data files:</p> <p>- 2015 German gas feed-out [TWh/a Hs] per NUTS3 region.</p> <p>- 2015 German gas feed-in timeseries [GWh/h Hs] per sector.</p> <p>- 2015 German gas feed-out&nbsp;timeseries [GWh/h Hs] per sector.</p> <p>- 2050 German gas feed-in timeseries [GWh/h Hs] per sector for the Energiewende scenario.</p> <p>- 2050 German gas feed-out&nbsp;timeseries [GWh/h Hs] per sector for the Energiewende scenario.</p> <p>- 2050 German gas feed-in timeseries [GWh/h Hs] per sector for the Reference scenario.</p> <p>- 2050 German gas feed-out&nbsp;timeseries [GWh/h Hs] per sector for the Reference scenario.</p>

opencc-by-4.0Apr 2019View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record