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17,036
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Dataset results
17,036 results for “Nature”
Level A Pan Europe Natural river discharge, E-HYPE 3.0
Simulated river discharge at each subbasin from E-HYPEv3.0 in m3/s. Daily data for 1961 to 2001 as time-series. Dam regulation and irrigation are NOT simulated in the natural runs. However, dams will still function as lakes with some amount of attenuation. Original data source: See information about the E-HYPE setup. Tools for repurposing: HYPE. Temporal resolution: Daily. Spatial resolution: 215 km2. Unit: m3/s. Data format: Zipped text file. On the first row there is a brief description and the rest of the file contains one row per time step, with the sub basin id as each column header on the second row. The first item on each line is the time step using the format YYYY-MM-DD, so 1961-01-01 for the first of January 1961. The dataset, Subbasin(EHYPEv3pt0).zip (shapefile with subbasin polygons) can be linked with the data.
Human auditory ecology : Extending hearing research to the perception of natural soundscapes by humans in rapidly-changing environments
<p>The audiomaterial corresponding to boreal, tropical and temperate forests, desert, savannah, sub-alpine meadow, and the construction site in New York is copyrighted (license from Wild Sanctuary) and cannot be used without explicit agreement of Bernie Krause. Additional audiomaterial (urban park and street traffic in Paris, France; fast street traffic in Marseille, France; English and French speech material) may only be used with the explicit agreement of the following authors: Jérôme Sueur and Sylvain Haupert (Museum National d'Histoire Naturelle in Paris, France); Sabine Meunier (LMA/CNRS in Marseille, France); Franck Ramus (CNRS in Paris, France) (see Figure legends).</p>
IODP Expedition 391 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
IODP Expedition 397T Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
Dataset for publication "Efficient magnetic switching in a correlated spin glass", Nature Communications volume 14, Article number: 6127 (2023).
<p>Dataset for publication "Efficient magnetic switching in a correlated spin glass", Nature Communications volume 14, Article number: 6127 (2023), DOI 10.1038/s41467-023-41718-4, include images, data used for generate that images, input files, converged potential files used for the calculations on SPR-KKR package 8.6. and raw data files.</p>
IODP Expedition 383 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
PISM model output data from Garbe et al. (Nature, 2020) publication
<p>This dataset contains the <a href="https://www.pism.io">PISM</a> model output data of the Antarctic Ice Sheet hysteresis simulations published and discussed in</p><p><a href="https://doi.org/10.1038/s41586-020-2727-5">Garbe, J., Albrecht, T., Levermann, A., Donges, J. F., and Winkelmann, R. The hysteresis of the Antarctic Ice Sheet. <i>Nature</i><strong> 585</strong>(7826), 2020.</a></p><p>A detailed description of the individual file contents is given in `README.txt` below. The corresponding PISM model code used for these simulations is archived <a href="https://doi.org/10.5281/zenodo.3956431">here</a>.</p><p>In case of questions, feel free to contact me at <a href="mailto:julius.garbe@pik-potsdam.de">julius.garbe@pik-potsdam.de</a>.</p>
Weekly county-level pollution data for China from Zhang, Carleton, Lin, and Zhou (accepted, Nature Sustainability), "Estimating the role of air quality improvements in the decline of suicide rates in China"
<p>This dataset contains weekly, county-level air pollution data for 2,839 counties from 2013 to early 2018. These data are used and described in Zhang, Carleton, Lin, and Zhou (accepted, <em>Nature Sustainability</em>), "Estimating the role of air quality improvements in the decline of suicide rates in China". When the paper is published a link to the manuscript will be added here. </p> <p>The manuscript Methods section details data construction. In summary, these county-level observations are obtained from monitoring stations maintained by the China National Environmental Monitoring Center (CNEMC), which is affiliated with the Ministry of Ecology and Environment of China. CNEMC began publishing hourly air pollution data in 2013, including the Air Quality Index, PM2.5, PM10, ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide. We average hourly data to the station-day level and use inverse-distance weighting with a radius of 200km to convert data from station to the county level. We average across days to generate county-level weekly values. Any missing station-hour observations in the raw data are omitted in this spatial and temporal aggregation. Our main analysis relies on PM2.5, but all pollutants are released here.</p>
The evolution and future of research on Nature-based Solutions to address societal challenges
<p>This dataset comprises the bibliographic text files used to analyse the Nature-based Solutions research landscape as presented in:</p> <ul> <li>Dunlop, T., Khojasteh, D., Cohen-Shacham, E., Glamore, W., Haghani, M., van den Bosch, M., Rizzi, D., Greve, P., Felder, S. The Evolution and Future of Research on Nature-based Solutions to Address Societal Challenges. <em>Communications Earth & Environment</em>. 2024.</li> </ul> <p>Excel spreadsheets containing data for the Global Water Security Index (Gain et al., 2016) presented in Figure 2 and the data required to reproduce Figures 1 and 2 in the paper above are also shared.</p>
Integrated global assessment of the natural forest carbon potential (tifs)
<p>Since we have large data files for the maps used in the paper 'Integrated global assessment of the natural forest carbon potential', we have uploaded the maps separately here. After downloading the maps, you can place them in the path: Data/BiomassMergedMaps. Then, the code for making figures will be replicable.</p> <p>This is version 1.1, which includes the addition of the 'readMe.txt' and the soil carbon potential map, and corrections to each model's maps in TGB for both full and net potential.</p>
global interpreted planted forest, natural forests validation samples
<p>This dataset provided the global validation dataset including planted forest, natural forest, and non-forest in 2015. This dataset was visually interpreted using the high spatial resolution (<1 m) images from Google Earth, and combining the spatial distribution of planted forets, and forest gain map.</p> <p>1 denotes planted forest, 2 denotes the natural forest, and 3 denotes the nonforest.</p> <p>Detailed information about how the global validation dataset was visually interpreted can be seen in the following reference:</p> <p>Xu, H., He, B., Guo, L., Yan, X., Zeng, Y., Yuan, W., et al. (2024). Global forest plantations mapping and biomass carbon estimation. Journal of Geophysical Research: Biogeosciences, 129, e2023JG007441.</p>
IODP Expedition 378 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
Supplemental Files for Schlegel et al., Nature (2024)
<p>This repository contains supplemental files for the paper "<strong>Whole-brain annotation and multi-connectome cell typing of Drosophila</strong>" - Schlegel <em>et al.</em>, Nature (2024).</p> <ul> <li><em>nblast_flywire_all_right_aba_comp.feather</em> contains all-by-all NBLAST score for all FlyWire neurons where neurons from the left hemisphere have been mirrored to the right</li> <li><em>nblast_flywire_hemibrain_min_comp.feather</em> <em> </em>contains NBLAST scores for FlyWire versus "hemibrain" neurons</li> <li><em>nblast_flywirre_mirrored_hemibrain_comp.feather</em> contains NBLAST scores for FlyWire versus "hemibrain" neurons where all FlyWire neurons have been mirrored</li> <li><em>sk_lod_783_healed_ds2.parquet</em> contains skeletons in SWC format for all FlyWire neurons (generated from lod 1 meshes and 2X downsampled, coordinates are in nanometres); the raw data can be read with e.g. the Python <a href="https://pypi.org/project/pyarrow/"><em>pyarrow</em></a> package (see <a href="https://arrow.apache.org/docs/python/parquet.html">documentation</a> for examples). Alternatively, you can use the <a href="https://github.com/navis-org/navis"><em>navis</em></a> Python package to read the contents into neuron objects (see <a href="https://navis-org.github.io/navis/reference/navis/#navis.read_parquet">navis.read_parquet).</a></li> </ul> <p>Additional notes:</p> <ul> <li>all root IDs refer to the 783 release of FlyWire</li> <li>for NBLAST files: <ul> <li>columns/indices for FlyWire neurons are given as "{root_id},{supervoxel_id}", where the supervoxel ID represents an anchor that can be used to map this neuron to different materialization versions</li> <li>scores were compressed by rounding to the 4th decimal and clipping values below 0</li> </ul> </li> </ul> <p>For neuron annotations and further details please see <a href="https://github.com/flyconnectome/flywire_annotations">https://github.com/flyconnectome/flywire_annotations</a>. </p> <p>The proofreading and FlyWire resource are described in our companion paper (Dorkenwald <em>et al.</em>, Nature, 2024).</p>
IODP Expedition 367 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons
<p>We present here the raw data and scripts to reproduce the results presented in the preprint "Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons" available on BioRxiv. Before using the scripts and associated data, we recommend reading the "readme" word document also available, which details the information available in the different data sheets. </p> <p>Preprint abstract : </p> <p>Coastal lagoons are transitional ecosystems that host a unique diversity of species and support many ecosystem services. Owing to their position at the interface between land and sea, they are also subject to increasing human impacts, which alter their ecological functioning. Because coastal lagoons are naturally highly variable in their environmental conditions, disentangling the effects of anthropogenic disturbances like eutrophication from those of natural variability is a challenging, yet necessary issue to address. Here, we analyze a dataset composed of macrobenthic invertebrate abundances and environmental variables (hydro-morphology, water, sediment and macrophytes) gathered across 29 Mediterranean coastal lagoons located in France, to characterize the main drivers of community composition and structure. Using correlograms, linear models and variance partitioning, we found that lagoon hydro-morphology (connection to the sea and lagoon surface), which affects the level of environmental variability (salinity and temperature), as well as lagoon-scale benthic habitat diversity (using macrophyte morphotypes) seemed to regulate macrofauna distribution, while eutrophication and associated stressors like low dissolved oxygen, acted upon the existing communities, mainly by reducing species richness and diversity. Furthermore, M-AMBI, a multivariate index composed of species richness, Shannon diversity and AMBI (AZTI's Marine Biotic Index) and currently used to evaluate the ecological state of French coastal lagoons, was more sensitive to eutrophication (18%) than to natural variability (9%), with nonetheless 49% of its variability explained jointly by both. To improve the robustness of benthic indicators like M-AMBI and increase the effectiveness of lagoon benthic habitat management, we call for a revision of the ecological groups at the base of the AMBI index and of the current lagoon typology which could be inspired by the lagoon-sea connection levels used in this study. </p>
Effects of Periodic Normal Stress Oscillations on Frictional Properties of Simulated Natural Fault Gouges under In Situ P-T Conditions
<p>Files named by in a format of "Uxxx_xx_xxMPa_xxC" refer to the original mechanical data recorded during experiment.</p> <p>The compressed package includes the files to perform numerical modeling, modeling results and the experimental data for comparison. To replicate the numerical modeling, readers can open the COMSOL project file (".mph" file) using COMSOL software (version >5.4) then input the parameters for the boundary conditions, such as the temperature, load-point velocity, oscillation amplitude and frequency. </p>
Systematic review data on the role of urban planning in the context of sustainability transformations and human-nature connections
<p>This data publication belongs to the following research paper:<br>Harms, P., Hofer, M. & Artmann, M. Planning cities with nature for sustainability transformations — a systematic review. Urban Transform 6, 9 (2024). <br>https://doi.org/10.1186/s42854-024-00066-2 </p> <p>We conducted a systematic literature review according to the PRISMA Statement 2020 (Page et al. 2021). The list shows the steps performed and the names of the corresponding datasets available here:</p> <p>Step A - Identification of Records<br>A_01_PRISMA-protocoll.pdf<br>A_02_searchstring.txt<br>A_03_recordsidentified.ris</p> <p>Step B - Screening of Records<br>B_01_recordsscreened-title-keywords.ris<br>B_02_recordsscreened-abstract.ris<br>B_03_recordsscreened-fulltext.ris<br>B_04_studiesincluded.ris<br>B_05_screeningdecisions-overview.xlsx</p> <p>Step C - Qualitative Analysis<br>C_01_codingscheme.xlsx</p> <p> </p>
Dataset of "Introduction to neuromorphic functions of memristors: The inductive nature of synapse potentiation"
<p>This dataset supports the article "Introduction to Neuromorphic Functions of Memristors: The Inductive Nature of Synapse Potentiation," published in the Journal of Applied Physics.</p> <p>Raw data for the article "Introduction to neuromorphic functions of memristors: The inductive nature of synapse potentiation". For further details see the Readme.txt file.</p>
A Catalog of Natural Channelrhodopsins
<p>This repository is an appendix to the publication <a href="https://doi.org/10.1016/j.cub.2020.09.056">[Rozenberg20](10.1016/j.cub.2020.09.056)</a>, "Lateral Gene Transfer of Anion-Conducting Channelrhodopsins between Green Algae and Giant Viruses", that is intended to keep the list of the channelrhodopsins (ChRs) presented there as a constantly updated resource that includes updates to the old records, addition of novel unpublished entries, entries from newly published experiments and corrections to the previously published sets.</p> <p>Most of the credit belongs to the projects that generated and assembled the data that ultimately contained the ChRs (especially, <a href="https://doi.org/10.1371/journal.pbio.1001889">[MMETSP_Keeling14](10.1371/journal.pbio.1001889)</a> and <a href="https://doi.org/10.1038/s41586-019-1693-2">[1KP_initiative19](10.1038/s41586-019-1693-2)</a>) and to the experimentalists who took the challenge of characterizing them. The catalog currently focuses mostly but not exclusively on proteins from cultured organisms.</p> <p>Although the format might eventually change, the current version of the catalog is composed of two xlsx spreadsheets:</p> <ul> <li>Channelrhodopsins_Original_List.xlsx that represents the original ChR list with additional metadata, but without changes to the sequences and additions and without changing the classification of the ChRs. This file will remain unchanged throughout releases. It contains the following fields: <ul> <li>ID - integer index</li> <li>Sequence name - unique name of the sequence</li> <li>Is outgroup (not ChR) - flag indicating whether the sequence is not a ChR (a small number of rhodopsins inherited from <a href="https://dx.doi.org/10.1038%2Fnmeth.2836">[Klapoetke14](10.1038/nmeth.2836)</a> belonged to different families)</li> <li>Symbol - gene symbol, short alias</li> <li>Species - source species/strain</li> <li>Taxonomic group - taxonomic affiliation of the species</li> <li>ChR group - clade name, if empty indicates clades unknown back then</li> <li>Bioproject - NCBI bioproject for the sequence</li> <li>Sequence source - initiative/database/publication the gene nucleotide sequence was part of</li> <li>Activity - activity confirmed for the exact sequence (potentially, a shorter version or in rare cases an allelic variant thereof). In the original list, selectivity (cation/anion) was indicted for all ChRs with demonstrated channel activity even if selectivity could not be or was not assessed experimentally.</li> <li>Reference - publication(s) where the activity was demonstrated</li> <li>Full-length 98%-identity clustering: <ul> <li>Representative - representative sequence for the cluster with an identity of 98%</li> <li>Cluster - cluster number</li> <li>Identity - identity % to the reference</li> </ul> </li> <li>Rhodopsin-domain 100%-identity clustering: <ul> <li>Representative - representative sequence for the cluster with an identity of 100% after the 98%-identity clusters were aligned and trimmed to include only the rhodopsin domain</li> <li>Cluster - cluster number</li> </ul> </li> <li>Sequence - full protein sequence for the entry (this might be the complete sequence of the gene, partial sequence of the gene that was not recovered entirely in the assembly or sequence of a specific construct used for expression)</li> <li>Is partial sequence - flag indicating whether the rhodopsin domain is truncated</li> <li>Has indels - flag indicating whether the rhodopsin domain contains indels (unspliced introns in transcripts, gene annotation artifacts)</li> <li>Sequence completeness comment - comments about the nature of the indels</li> </ul> </li> <li>Channelrhodopsins_Updated_List.xlsx includes amended ChR sequences, manually added entries and novel expressed or otherwise published proteins. In this release all of the sequences with complete rhodopsin domains are assigned to a family (some families have only provisional names). The spreadsheet is structured differently from the first one and focuses more on the unique complete sequences by separating genes from constructs that are derived from them. The redundancy of the dataset was further reduced by combining identical sequences. Highly similar sequences are treated mostly separately. In some cases they have been downgraded to allelic or splice variants, but this is not yet consistent. There are now three sheets: <ul> <li>full_channelrhodopsins - full ChR sequences</li> <li>fragmented_channelrhodopsins - ChR sequences with incomplete rhodopsin domains</li> <li>not_channelrhodopsins - additional proteins that have been mentioned in ChR datasets that are not from the ChR family</li> </ul> </li> <li>The sheets have the following fields: <ul> <li>ID - integer index corresponding to the record (new records have IDs >875).</li> <li>Sequence name - this is the chosen sequence name for the longest version of the sequence</li> <li>Version - sequence version. Sequences get updated and increment their versions in the following cases: <ul> <li>the correct start codon was identified</li> <li>a full sequence for the gene was found in an alternative database</li> <li>a full sequence for the gene has been obtained or corrected from the raw data</li> <li>gene annotation artifacts have been corrected manually based for the genomic sequence</li> <li>unspliced introns were found and removed</li> </ul> </li> <li>Reviewed - a somewhat arbitrary flag indicating whether the complete sequence has been manually reviewed</li> <li>Constructs - NCBI protein accessions of constructs overlapping with the gene indicating the overlapping region. Note that construct are allowed to overlap multiple full-length genes even from nominally different species.</li> <li>Symbol - short gene alias</li> <li>Species - species from which the longest representative sequence belongs</li> <li>Taxonomic group</li> <li>ChR group - ChR affiliation based on phylogeny</li> <li>ChR supergroup - ChR supergroup (A: ACRs and green algal CCRs, B: "bacteriorhodopsin-like" CCRs, D: the clade of dinoflagellate and related colpodellid ChRs)</li> <li>Bioproject - bioproject accession(s) for the data from which the sequence is derived</li> <li>Sequence source - one or multiple sources for the sequence, preference is given to earlier released publications</li> <li>Source type - the kind of source(s) (e.g. genome/transcriptome) the sequence comes from</li> <li>First mention - reference for the source where the gene was first indicated as a ChR. Notice that with highly similar sequences this is sometimes tricky.</li> <li>Currents - channeling activity. This differentiates between confirmed and unconfirmed selectivities: square brackets specify the likely but unconfirmed selectivity</li> <li>Cation selectivity - further details on selectivity of cation ChRs</li> <li>Currents reference</li> <li>Absorption maximum, nm</li> <li>Action maximum, nm</li> <li>Spectra references</li> <li>Spectra comment</li> <li>Representative sequence from [Rozenberg20] - representative highly similar sequence (this is inherited from the from the original file: full-length 98% clustering > rhodopsin domain 100% clustering)</li> <li>Sequence - the amino acid sequence</li> <li>Superseded identical sequences - identical sequences included in the same record (with species/strain indicated if different)</li> <li>Splice variants - putative minor splice variants from the same species/strain</li> <li>Allelic variants - putative minor allelic variations from the same species/strain</li> <li>Superseded included sequences - shorter sequences included in the record</li> <li>Superseded incorrect sequences - other sequences that are different due to artifacts</li> <li>Version comments - brief version history</li> <li>Other comments</li> </ul> </li> </ul> <p>Starting from version 2.0, the repository also contains:</p> <ul> <li>Channelrhodopsins_Alphafold3_structures.zip - raw alphafold3 structures of all of the complete ChRs with retinal.</li> </ul> <p>This is work in progress, use with care. If a formal citation is needed, please cite <a href="https://doi.org/10.1016/j.cub.2020.09.056">[Rozenberg20](10.1016/j.cub.2020.09.056)</a>, "Lateral Gene Transfer of Anion-Conducting Channelrhodopsins between Green Algae and Giant Viruses" and <a href="https://www.science.org/doi/10.1126/sciadv.add7729">[Vierock22](10.1126/sciadv.add7729)</a>, "WiChR, a highly potassium selective channelrhodopsin for low-light one- and two-photon inhibition of excitable cells". For the most recent phylogeny of ChRs see <a href="https://doi.org/10.7554/eLife.90100.1">[Oppermann23](10.7554/eLife.90100.1)</a>, "Robust optogenetic inhibition with red-light-sensitive anion-conducting channelrhodopsins", and <a href="https://github.com/BejaLab/ACRs">https://github.com/BejaLab/ACRs</a>.</p>
The generic nature of the condensed state of proteins | Talk - I PhasAGE International Conference
<p>The <strong>I PhasAGE international conference</strong> brought together members of the PhasAGE consortium as well as outstanding international speakers showcasing high impact achievements in the field of liquid-liquid phase separation in aging and late-onset diseases.</p> <p>For details on conference program please see: https://phasage.eu/phasage-conference-1/ </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.