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6,782 results for “project”
Data and code for the manuscript titled "Persistence of SARS-CoV-2 immunity, Omicron's footprints, and projections of epidemic resurgences in South African population cohorts"
<p>Data and code for the manuscript titled “Persistence of SARS-CoV-2 immunity, Omicron’s footprints, and projections of epidemic resurgences in South African population cohorts”</p>
500-yr Projections of Thwaites Glacier, Antarctica, with MALI, including glacial isostatic adjustment: no elastic displacement
<p>This archive contains a subset of results reproducing the material presented in the manuscript "Stabilizing effect of bedrock uplift on retreat of Thwaites Glacier, Antarctica, at centennial timescales" by Cameron Book, et al. This archive only includes results for the simulations with elastic displacement in the GIA model disabled. These results are briefly discussed in the first paragraph of section 'Factors controlling feedbacks between glacier retreat and bedrock uplift'. The main results from the manuscript are in a separate archive. Questions should be directed to Matt Hoffman (mhoffman@lanl.gov).</p> <p>This archive contains the following directories:</p> <p>|-- N1_no_elastic<br> |-- N2_no_elastic<br> |-- N3_no_elastic<br> `-- N4_no_elastic</p> <p>The individual runs have the following corresponence to the manuscript, but<br> with the elastic displacement disabled:<br> N1=TYP<br> N2=BEST2<br> N3=VLV-THIN<br> N4=VLV</p> <p>Within each run directory, are the following model output files:<br> globalStats.nc: MALI global, scalar time-series<br> output_*.nc: MALI spatial output fields, separated by century</p>
Subspecies and Distribution. P. b. bougainville Quoy & Gaimard, 1824 — Bernier I and Dorre I, in Shark Bay, Western Australia. Nominate race reintroduced to Heirisson Prong and Faure I (Shark Bay) and to the Arid Recovery Project area in South Australia. in Peramelidae
Subspecies and Distribution. P. b. bougainville Quoy & Gaimard, 1824 — Bernier I and Dorre I, in Shark Bay, Western Australia. Nominate race reintroduced to Heirisson Prong and Faure I (Shark Bay) and to the Arid Recovery Project area in South Australia.
GSDGM files generated by human connectome project s500 rs-fMRI (CONN atlas 132 ROIs) data
<p>Group Surrogate Data Generating Model (GSDGM) dataset generated by human connectome project s500 rs-fMRI (CONN atlas 132 ROIs) data.</p>
Web scraping and API projects from "Online Data Collection and Management" (Spring 2022)
<p>As part of "Online Data Collection and Management" (taught at Tilburg University, Spring 2022), students collected publicly available datasets for use in academic research projects. With this repository, I am sharing (a) the documentation of these data sets, and (b) the associated source code that led to the collection of the data. The repository also contains the collected datasets.</p> <p>The data consists of the following projects:</p> <ul> <li>Autoscout (electric cars vs gasoline cars in the Dutch market)</li> <li>Mediamarkt (e-commerce)</li> <li>Steam API</li> <li>Twitch (chat capture)</li> <li>Zalando (e-commerce)</li> </ul> <p>Course website: https://odcm.hannesdatta.com. Archived at https://doi.org/10.5281/zenodo.6641811 (check for more recent versions if available).</p>
AGP data for the project "Over-optimism in unsupervised microbiome analysis"
<p>Datasets from the American Gut Project (AGP) that were used by Ullmann et al. for the research project "Over-optimism in unsupervised microbiome analyis".</p> <p>The datasets were published by McDonald et al.:</p> <p>McDonald D, Hyde E, Debelius JW, Morton JT, Gonzalez A, Ackermann G,<br> et al. American gut: an open platform for citizen science microbiome research.<br> Msystems. 2018;3(3). DOI: <a href="https://doi.org/10.1128/mSystems.00031-18">https://doi.org/10.1128/mSystems.00031-18</a></p> <p>We accessed the files otu_table__BODY_HABITAT_UBERON_feces_json.biom and metadata__BODY_HABITAT_UBERON_feces__.txt at ftp://ftp.microbio.me/AmericanGut/ag-2017-12-04.</p> <p>The phyloseq object ag.genus.rds results from these files after preprocessing. (For the preprocessing code, see our Github repository.) </p>
Ingleborough Soundscapes Project - Pilot Study Data from Colt Park Wood
<p>The audio recordings contained within the ‘Ingleborough Soundscape Project’ folders are free to download and may be copied, shared, modified, or commercialised, provided that the following written citation,<strong> Pheasant. R. J., (2021). Ingleborough Soundscape Project</strong> acknowledges the origin of the data.</p>
H2020 project CLAIM collected database
<p>Data collected from various sources during CLAIM project. Datasets (13 *.csv files) from Mediterranean Sea and Baltic Sea: micro- and macro-plastic, beach litter, seabed litter, CLAIM filtering device etc.</p>
JEMMA Callgraphs Projects
<p>JEMMA Callgraphs Projects</p> <p>> file: jemma_projects_callgraphs.zip<br> > size: 404.7 MB (compressed) ~7 GB (decompressed)<br> > num items: 49,991 csv files <br> > csv columns: caller_project_id, caller_class_id, caller_method_id, call_direction, callee_project_id, callee_class_id, callee_method_id,</p>
On the Discoverability of npm Vulnerabilities in Node.js Projects
<p>This package contains the material used in the manuscript.</p> <p>For more information on how to understand the package structure, please read the README.md.</p> <p> </p>
Earthquake Archaeological Effects documented in the Cusco area in 2019 (RISC project)
<p>In 2019, the RISC project led to the implementation of an unprecedented archaeoseismological survey in the Cusco area, Peru. The main objective was to identify and map the earthquake-induced damage on the stone architecture of famous Inca archaeological sites. This spreadsheet summarizes all the observations. Each row corresponds to an Earthquake Archaeological Effect (EAE). For each strain structure, the columns contain information relative to the geographical and architectural contexts, the measurements and the level of confidence. The data were extracted from the RISC database, which supported the fieldwork. For more details about the design and structure of the RISC database please read:</p> <p>Combey et al. (2021) Monumental Inca remains and past seismic disasters: A relational database to support archaeoseismological investigations and cultural heritage preservation in the Andes, Journal of South American Earth Sciences, Volume 111, 103447,<br>https://doi.org/10.1016/j.jsames.2021.103447.</p> <p>The file is in support of the paper published in Quaternary International in 2022: <span><span><a href="https://doi.org/10.1016/j.quaint.2022.07.003"><span>https://doi.org/10.1016/j.quaint.2022.07.003</span></a></span></span></p>
Distribution. NE Egypt (coastal region of Sinai), S Israel (Negev Desert), and Palestine. Descriptive notes. Head-body 130-170 mm, tail 120-180 mm, ear 17-22 mm, hindfoot 30-41 mm; weight 125-275 g. A medium-sized jird, Buxton's Jird has tail of about same length as head-body length and partially hairy soles of hindfeet. Bicolored tail ends with well-developed pencil of black hairs. Dorsal pelage is reddish sandy, diffusely speckled with black hairs, and ventral is white. Enlarged tympanic bullae project over back of skull and represent c.35-37% ofskull length. Karyotype 2n = 46. in Muridae
Distribution. NE Egypt (coastal region of Sinai), S Israel (Negev Desert), and Palestine. Descriptive notes. Head-body 130-170 mm, tail 120-180 mm, ear 17-22 mm, hindfoot 30-41 mm; weight 125-275 g. A medium-sized jird, Buxton's Jird has tail of about same length as head-body length and partially hairy soles of hindfeet. Bicolored tail ends with well-developed pencil of black hairs. Dorsal pelage is reddish sandy, diffusely speckled with black hairs, and ventral is white. Enlarged tympanic bullae project over back of skull and represent c.35-37% ofskull length. Karyotype 2n = 46.
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-06]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier and NGC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com/</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu/</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p> <p> </p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-03]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier and NGC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com/</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu/</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p> <p> </p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-05]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier and NGC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com/</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu/</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p> <p> </p>
NPL DigAC project data
<p>Data from NPL for the DigAC project. This is the raw data used in the published paper for the project.</p>
Human and Organizational Factors and their Influence on Turnover in Global Software Development Projects
<p><strong>LIST OF PAPERS - Human and Organizational Factors and their Influence on Turnover in Global Software Development Projects</strong></p> <p> </p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-04]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier and NGC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com/</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu/</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p> <p> </p>
Supplementary Data for the Project Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome
<p><strong>Supplementary Tables for the Project "Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome"</strong></p> <p>Supplementary Table 1. List of 18 genome-sequenced human gut bacteria with metabolic characteristics that were used for community assembly.</p> <p>Supplementary Table 2. Diet composition.</p> <p>Supplementary Table 3. Species relative abundance.</p> <p>Supplementary Table 4. Gene abundance and expression changes.</p> <p>Supplementary Table 5. Gene pathway enrichment results.</p> <p>Supplementary Table 6. Metabolomics data.</p> <p>Supplementary Table 7. Metabolite fold changes, clustering and model parameters.</p> <p>Supplementary Table 8. Description of the intestinal flux model.</p> <p>Supplementary Table 9. Enzymatic paths between substrates and products.</p> <p>Supplementary Table 10. Pearson's correlation coefficients between potential substrates and products, and metagenomics and metatranscriptomic measurements.</p>
E3SM simulations to assess the projected changes in tropical cyclone activity during active and inactive North Atlantic hurricane seasons
<p>This dataset compiles the results of high resolutions E3SM experiments performed to assess the projected changes in the North Atlantic tropical cyclone activity in a warming climate. The results of these experiments are currently in revision under the title "<strong>Future Changes in Active and Inactive Atlantic Hurricane Seasons in the Energy Exascale Earth System Model</strong>" </p> <p>The file tracks_teca.zip compiles the TC tracks detected in the experiments, using the Toolkit for Extreme Climate Analysis (TECA), available at https://teca.readthedocs.io/en/latest/applications.html#teca-tc-stats</p> <p>GPI_LaNinaAMMp.zip and GPI_ElNinoAMMn.zip includes the genesis potential index and its components for each of the experiments.</p> <p>For further information, please contact the author at anasena@iastate.edu</p> <p>Acknowledgements:</p> <p><strong>This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. E3SM simulations were performed using BER Earth System Modeling program’s Compy computing cluster located at Pacific Northwest National Laboratory. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Earth and Environmental Systems Modeling (EESM) Program, under Early Career Research Program Award Number DE‐SC0021109.</strong></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.