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13,499 results for “researcher”
Caribou-Poker Creeks Research Watershed: Input data for calculating stream metabolism from 2021-2022
This dataset contains the input data needed for calculating stream metabolism using the 'streamMetabolizer' R package (i.e., dissolved oxygen, oxygen at 100% saturation, depth, water temperature, light, and discharge) for four sites in the Caribou-Poker Creeks Research Watershed (CPCRW). Data are reported at 15-minute intervals from May to September in 2021 and 2022.
Caribou-Poker Creeks Research Watershed: Dissolved organic carbon and microbial respiration measurements from biodegradable dissolved organic carbon incubations, summer 2021
This dataset contains dissolved organic carbon (DOC) and microbial respiration measurements taken during lab incubations of water collected from the Caribou-Poker Creeks Research Watershed (CPCRW), with the goal of quantifying the proportion of biodegradable dissolved organic carbon (BDOC) and microbial utilization of DOC. Incubations were conducted in June, July, and August 2021 using water from six stream sites throughout the CPCRW. Incubation experiments were designed to measure responses to carbon and nutrient additions as well as different temperatures.
Caribou-Poker Creeks Research Watershed: Stream chemistry from summers of 2021-2022
This dataset contains stream chemistry data collected at six sites throughout the Caribou-Poker Creeks Research Watershed (CPCRW) from May-September 2021 and 2022. The dataset includes concentrations of dissolved organic carbon (DOC), nitrate (NO3), soluble reactive phosphorus (SRP), and SUVA254 (absorbance at 254nm normalized by DOC concentration) from weekly grab samples as well as daily samples collected by autosamplers. Note that only weekly samples were collected from the NEONdn site, and SRP was only analyzed on weekly samples.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR), Gradient, and Watershed: Dissolved Organic Carbon 2007-2022
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data set includes weekly thaw depth measurements collected from winter warming, summer warming, and control treatment plots at CiPEHR. Additional measurements from on-plot gas flux wells, water table monitoring wells, and off-plot locations are also reported. Note that the experimental warming portion of this experiment concluded in 2022. These data are a continuation of measurements taken at previously warmed plots but plots were not actively manipulated after 2022. At the Gradient Thaw Site, in this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): soil organic carbon stocks and radiocarbon measurements, 2009 & 2022
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data set includes measurements of soil organic carbon stocks and radiocarbon (14C) values that are normalized to account for the effects of subsidence and ground collapse. SOC and 14C values were normalized using an equivalent ash approach described in Plaza et al. (2019) Nat Clim Change and Lathrop et al. (2025) Global Change Biology.
Physical Hydrologic Data for the National Audubon Society's 16 Research Sites in coastal mangrove transition zone of southern Florida, March 1986 - ongoing
Temperature, salinity and depth were continuously collected using Hydrolab/Hach sensors within the coastal mangrove transition zone at 16 sites from southern Biscayne Bay to Cape Sable. Data were collected at 12 sites within the coastal mangrove zone of Everglades National Park, incorporating the Cape Sable, Taylor River and Panhandle region. Data were collected at 4 sites within the coastal mangrove zone of southern Biscayne Bay, incorporating the Manatee Bay, Barnes Sound, and Card Sound regions. Rainfall, pH, and dissolved oxygen were collected at a number of these sites with varying periods of record.
Continuous soil temperature measurements at 10 cm depth from 3 month-long deployments in summer and winter within the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) site in 2017 and 2018
To understand the influence of marsh elevation and flooding on soil temperature in Spartina alterniflora marsh, we measured soil temperature at 10 cm depth along two transects that spanned a marsh edge to interior gradient. We then associated those measurements with elevation, creek water height and vegetation characteristics. Soil temperature was logged every 15 min with a Hobo Onset Tidbit Pendant Temperature probe in Spartina alterniflora-dominated marsh near the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) eddy covariance flux tower. Measurements were collected along two transects of approximately 250 m in length from 18 plots (transect 1) or 20 plots (transect 2) and over 3 sample deployments of approximately 1 month in length: 27 Jul – 31 Aug 2017 (transect 1), 8 Jan – 13 Feb 2018 (transect 1) and 23 Aug – 18 Sep 2018 (transect 2). Plot elevations along each transect were measured with a Trimble R6 RTK after probes were installed in the marsh. Creek water heights were estimated with the pressure transducer associated with the GCE-LTER eddy covariance flux tower data. Spartina alterniflora height forms were measured for each sample station during August as the mean of all stem heights within 0.25 m quadrants centered over each soil probe location. While these data are 24 hr soil temperature measurements, during all three deployments, we found that daily mean soil temperature was negatively correlated with marsh elevation on the marsh platform during low tide conditions, which represented the majority of the observations.
Biomass accumulation in trees and downed wood at Bartlett Experimental Forest, Hubbard Brook Experimental Forest, the Bowl Natural Research Area, and the White Mountain National Forest, NH, USA
Standing trees and downed wood were inventoried in all of the chronosequence stands in the White Mountains, New Hampshire to characterize biomass. Live and standing dead trees were inventoried in the chronosequence stands in 1994, 2004, 2012, and 2021. Coarse (≥ 7.6 cm diameter) and fine woody debris (3.0 – 7.6 cm) were inventoried at the same stands in 2004 and 2020. Twigs (FWD < 3.0 cm) were inventoried in 2004 and 2020. The Bowl and Mt. Pond old-growth sites were inventoried (standing trees and downed wood) in 2021.
GIS68 GIS Coverages of Konza Prairie Research Experiments in 2020
These data show locations for some experiments at Konza Prairie including: Chronic Addition of Nitrogen Gradient Experiment (ChANGE), Ghost Fire, Shrub Rainfall Manipulation Plots (ShRaMPs), sampling locations for ingrowth cores collected as part of the ShRaMPs experiment, Climate Extremes Experiment, Drought-Net, the Experimental Streams Experiment, the Nutrient Network Experiment, Phosphorous Plots experiment, the Vert-Invert experiment, and restoration areas.GIS680 defines the locations where the ChANGE experiment occurs on Konza Prairie. These data are to be used in conjunction with the NGE01 dataset.GIS681 defines the locations where the Ghost Fire experiment occurs on Konza Prairie. These data are to be used in conjunction with the GFE01.GIS682 defines locations where the ShRaMPs shelters occur on Konza Prairie.GIS683 defines locations where ingrowth cores were installed as part of the ShRaMPs experiment.GIS684 defines the locations where the Climate Extremes experiment occurs on Konza Prairie. These data are to be used in conjunction with the CEE01 dataset.GIS685 defines the locations where the Drought-Net experiment occurs on Konza Prairie.GIS686 defines the site where the Experimental Streams experiments occur on Konza Prairie.GIS687 defines the locations where the Nutrient Network experiment occurs on Konza Prairie. These data are to be used in conjunction with the NUT01 dataset.GIS688 defines the locations where the Phosphorous Plots experiment occurs on Konza Prairie. These data are to be used in conjunction with the PPL01 dataset.GIS689 defines the locations where the Vert-Invert experiment occurs on Konza Prairie. These data are to be used in conjunction with the VIR01 dataset.GIS690 contains locations of restoration areas. These data are to be used in conjunction with the HRE01, SPR01, and PRP01 datasets. These data are available to download as zipped shapefiles (.zip), and compressed Google Earth KML layers (.kmz).
GIS60 GIS Coverages Defining Other Konza Sample and Research Areas (1982-present)
These data show locations of samples and research areas at Konza that do not fit under our standard classifications. GIS 600 contains the locations of the Hulbert plots on Konza Prairie. GIS605 contains locations for rainfall shelters, ramps, experimental streams, restoration plots, the weather station, grasshopper cages, the climate extremes project. Currently no associated LTER datasets exist for these locations. GIS 610 provides a record of the historic Konza gridded location system. Older datasets may reference these locations with a column letter and row number. GIS615 contains the location for the Clean Air Status and Trends Network (CASTNET) site on Konza Prairie. For more information, visit the following link: http://www.epa.gov/castnet/javaweb/site_pages/KNZ184.html. GIS620 contains the location for the USGS gauging station. These data may be used in conjunction with the Stream Discharge for Kings Creek Measured at USGS Gauging Station (ASD01) dataset. For more information, visit the following link: http://waterdata.usgs.gov/nwis/nwisman/?site_no=06879650. GIS630) and GIS635 contain the location and treatment information for two bison grant grazing experiments. Currently, no associated LTER datasets exist for these data. These data are available to download as zipped shapefiles (.zip), compressed Google Earth KML layers (.kmz).
Zooplankton and micronekton abundance using an Isaacs-Kidd Midwater trawl on Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2023
During Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, acoustic backscattering layers were identified using multifrequency echosounders and were targeted for collection of zooplankton and micronekton using an Isaacs-Kidd Midwater Trawl. On each cruise, trawling was conducted at at least three stations, including the one at the shelfbreak front, one inshore of the front, and one offshore of the front. The catches from the trawls were preserved on ship and later identified to the lowest possible taxonomic level using a dissecting microscope. Each identified taxon was counted to provide net total abundance by taxon. Trawling was initiated in spring 2023 and is ongoing.
Small Mammal Mark-Recapture Population Dynamics at Core Research Sites at the Sevilleta National Wildlife Refuge, New Mexico (1989-present)
This file contains mark/recapture trapping data collected from 1989-present on permanently established web trapping arrays at sites on the Sevilleta National Wildlife Refuge in central New Mexico.. The trapping sites are representative of Chihuahuan Desert Grassland, Chihuahuan Desert Shrubland, Pinyon-Juniper Woodland, Juniper Savanna, Plains-Mesa Sand Scrub and Blue Grama Grassland. Not all sites have been trapped for the entire period: goatdraw (1992-2008), blue grama (2002-2004) rsgrass (1989-1998), rslarrea (1989-2009), two2 (1989-1998), savanna (1999-2002). Only 2 sites have been continuously been sampled since 1989 (5pgrass and 5plarrea). At each site 3 trapping webs are sampled for 3 consecutive nights in spring and fall. Each trapping web consists of 145 rebar stakes numbered from 1-145. There are 148 traps deployed on each web: 12 along each of 12 spokes radiating out from a central point (stake #145) plus 4 traps placed at the center of each web. The wide format facilitates community composition and species diversity analyses. Wide format has been reshaped so that the count data for each species are presented in a unique column. Data are summarized for each trapping web X trapping bout to present the mean number of animals per trap per night of the trapping bout. Wide format fills zeros for species that were not captured on a web during a given trapping bout. Long format facilitates filtering the dataset to a particular small mammal species of interest, but this format requires the addition of zeros to be functional for accurate data analysis requiring counts of animals.
Research data supporting for "The embedded research librarian: a project partner"
<p>This dataset contains the data that supports the following paper: Féret, R. and Cros, M., 2019. The embedded research librarian: a project partner. <em>LIBER Quarterly</em>, 29(1), pp.1–20. DOI: <a href="https://dx.doi.org/10.18352/lq.10304">10.18352/lq.10304</a></p> <p>The dataset contains 3 files related to the bibliographic metadata of the publications of the 7 H2020 projects supported by the University Library of Lille and a general file providing the data for the table, figure 2 and 3 and for the data on H2020 projects coordinators:</p> <ul> <li>figures: this file contains the information related to the projects supported by the Library, including the data presented in the figure 2 (tab 1), the figure 3 (tab 2), the table 1 (tab 3) and the data on 2020 project coordinators (tab 4).</li> <li>wos_publications : the data extracted from the Web of Science for 106 publications (.txt, UTF-8, Windows), searched on the base of the 7 H2020 projects Cordis number.</li> <li>refined_wos_publications : the same data after having been transformed into a .xlsx format in the tool OpenRefine.</li> <li>processed_publications : contains the main bibliographic data (authors, article title, source title, DOI, date of publication) and their open status.</li> </ul> <p><strong>Abstract of the paper</strong><br> This paper presents new services developed by the Lille University Library for European and National research project coordinators. This is a specific audience that libraries are not used to target, with a widely recognised institutional status and academic background. Supporting them in their coordination activities is an opportunity to gain a new role for libraries, which starts from the design of research at the submission stage and lasts several years after, during the project lifetime. These services help coordinators to meet their funders’ expectations on open access and research data management. It is also a way to develop new collaborations with research units and some university services, such as the Grant Office. The Lille University Library has already supported the writing of forty grant proposals since 2017, including about thirty since early 2019. The Library currently follows twelve projects on open access, research data management or both. This second figure is likely to increase in 2020 due to the number of projects supported at submission stage since the beginning of 2019. The paper describes our set of services and the lessons we learned from our approach.</p>
Impact of urban and shipping emissions on NASA-Unified Weather Research and Forecasting model results
<p>This dataset supports Huang et al. (2019, JGR-Atmospheres): "Impact of aerosols from urban and shipping emission sources on terrestrial carbon uptake and evapotranspiration: a case study in East Asia". The file named "NUWRFout.tar.gz" contains NUWRF base and sensitivity simulation results on 31 May 2016. The file named "LIS_soil_LAI.zip" contains model grid information, soil conditions and leaf area index (LAI) at NUWRF initialization times in late May 2016.</p>
Research Data Supporting "Understanding Structural and Electronic Properties of Bismuth Trihalides and Related Compounds"
<p>Research Data Supporting "Understanding Structural and Electronic Properties of Bismuth Trihalides and Related Compounds"</p> <p>DOI: 10.1021/acs.inorgchem.9b03214</p>
MiRoR5 - P2- Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
<p>Anonymised data of respondents to an open-ended online survey on their experience with collective intelligence</p>
MiRoR7-P1- Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design
<p>dataset referring to </p> <p><strong>Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design</strong></p> <p> </p> <p> </p> <p>Lorenzo Bertizzolo<sup>1</sup>, Patrick M Bossuyt<sup>2</sup>, Ignacio Atal<sup>1, 5</sup>, Philippe Ravaud<sup>1, 3-6</sup>, Agnès Dechartres<sup>7</sup></p> <p> </p> <p><sup>1</sup> INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of therapeutic evaluation of chronic diseases Team (METHODS), Paris, F-75004 France; Paris Descartes University, Sorbonne Paris Cité, France.</p> <p><sup>2</sup> Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Netherlands.</p> <p><sup>3</sup> Centre d’Épidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP (Assistance Publique des Hôpitaux de Paris), Paris, France.</p> <p><sup>4</sup> Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.</p> <p><sup>5</sup> Cochrane France, Paris, France</p> <p><sup>6</sup> Columbia University, Mailman School of Public Health, Department of Epidemiology, New York, USA</p> <p><sup>7</sup> Sorbonne Université, INSERM, Institut Pierre Louis de Santé Publique, Département Biostatistique, Santé Publique et Information Médicale, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière – Charles Foix, Paris, France</p>
The Research Software Alliance (ReSA) and the community landscape
<p>The Research Software Alliance (ReSA)’s mission is to bring research software communities together to collaborate on the advancement of research software. ReSA has formed taskforces and one of them revolves around a <strong>software landscape analysis</strong> aiming to answer the question "How can we identify the different communities and topics of interest for the research software community (e.g., preservation, RSEs, citation, productivity, sustainability)?"</p> <p>Here we include text describing the work of the taskforce to date (see <a href="https://zenodo.org/api/files/5a1e0c32-cbf7-4b9a-9c02-139b2ce66e85/2020-03-11-ReSA-landscape.md?versionId=ffedcfe9-33f4-4aba-9d6b-9975fc1c548d">2020-03-11-ReSA-landscape.md</a>), as well as plans for the future, and an invitation to readers to contribute to the ReSA list of research software communities. We are a;sp including the current version of the list in a CSV file (see <a href="https://zenodo.org/api/files/5a1e0c32-cbf7-4b9a-9c02-139b2ce66e85/2020-03-11-ReSA-landscape.csv?versionId=be4bbcdd-79a8-4444-a764-98bf0d548922">2020-03-11-ReSA-landscape.csv </a>), and we welcome contributions on the live spreadsheet that can be found via this <a href="https://docs.google.com/spreadsheets/d/15JHqOxR4HIKHYe821IPvbxIuXP1zMjXKGEIJwB-GPqE/edit#gid=0">link</a>.</p>
From A to Z: Projective coordinates leakage in the wild: research data and tooling
<p>Description</p> <p>This dataset and software tool are for reproducing the research results related to CVE-2020-10932 and CVE-2020-11735, resulting from the article "From A to Z: Projective coordinates leakage in the wild" (to appear at CHES 2020). The data was used to carry out the attack in Section 6 of the article.</p> <p>Data format</p> <p>txt files</p> <p>The <code>[int].txt</code> files contain an encoded page-fault trace prefixed by <code>trace:</code>.</p> <p>A trace represents the sequence of tracked memory pages that were executed during the generation of an ECDSA signature. The trace is encoded using ASCII characters for better visualization.</p> <p>The encoding follows this table:</p> <pre><code class="language-markdown">| Functions | Symbol | Page offset | | ---------------------- |:------:|:-------:| | _gcry_ecc_ecdsa_sign | T | 0xa1000 | | _gcry_mpi_invm | . | 0xcf000 | | _gcry_mpi_set | S | 0xd5000 | | _gcry_mpi_add | A | 0xcd000 | | _gcry_mpih_sub_n | - | 0xd8000 | | _gcry_mpih_rshift | - | 0xd8000 |</code></pre> <p><code>_gcry_ecc_ecdsa_sign</code> is the highest level function tracked in the attack. This allows to differentiate different calls to the <code>_gcry_mpi_invm</code> function which contains an insecure version of a Binary Extended Euclidean Algorithm (BEEA).</p> <p>Using these pages it is possible to locate the execution of <code>_gcry_mpi_invm</code> corresponding to the computation of <code>Z mod p</code> during projective to affine coordinates conversion (see <code>preprocess_trace</code> function).</p> <p>It can be seen, that <code>_gcry_mpih_sub_n</code> and <code>_gcry_mpih_rshift</code> shares a page. However, they can be differentiated using mainly the caller memory page. This sharing, instead of being a drawback, allows a straightforward recovery of BEEA execution flow (see <code>extract_Zi</code> and <code>extract_Xi</code> functions in <code>recover_z.py</code>).</p> <p>dat files</p> <p>The format of the <code>[int].dat</code> files is as follows.</p> <ul> <li><code># X [hex]</code>: Ground truth projective output of scalar multiplication, before affine conversion</li> <li><code># Y [hex]</code>: Ground truth projective output of scalar multiplication, before affine conversion</li> <li><code># Z [hex]</code>: Ground truth projective output of scalar multiplication, before affine conversion</li> <li><code># curve_name [str]</code>: The curve (P256)</li> <li><code># h [hex]</code>: Hash of the message to be signed</li> <li><code># k [hex]</code>: Ground truth ECDSA nonce</li> <li><code># q [hex]</code>: Curve order</li> <li><code># r [hex]</code>: First component of the ECDSA signature</li> <li><code># s [hex]</code>: Second component of the ECDSA signature</li> <li><code># x [hex]</code>: Ground truth ECDSA private key</li> <li><code># y [hex] [hex]</code>: Public key coordinates</li> <li><code># leak_pad [int],[int],[int]</code>: Leakage recovered during backtracking. Example: <code>0,4,15 => 0 = k % 2**4 = k & 15</code></li> </ul> <p>Tooling</p> <p>The <code>recover_z.py</code> script</p> <ul> <li>Loads a trace.</li> <li>Recovers the corresponding Z coordinate from the trace data.</li> <li>verifies the recovered Z matches the ground truth Z.</li> </ul> <p>Example</p> <p>Unpack the data:</p> <pre><code>tar xf traces.tar.gz</code></pre> <p>Run the tooling on trace index 123:</p> <pre><code>$ python2 recover_z.py 123 INFO:recovered Z:65b9b7006bc7b030218bef1b6e569f9f7acaee059b53d669388c6b860f67e213 INFO: real Z:65b9b7006bc7b030218bef1b6e569f9f7acaee059b53d669388c6b860f67e213</code></pre> <p>The output demonstrates the recovered Z coordinate is correct, i.e. matches the ground truth.</p> <p>Credits</p> <p>Authors</p> <ul> <li>Alejandro Cabrera Aldaya (Tampere University, Tampere, Finland)</li> <li>Cesar Pereida García (Tampere University, Tampere, Finland)</li> <li>Billy Bob Brumley (Tampere University, Tampere, Finland)</li> </ul> <p>Funding</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 804476).</p> <p>License</p> <p>This project is distributed under MIT license.</p> <p> </p>
Data relating to Clyne et al. Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study
<p>Data relating to the study reported in the paper "Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study".</p>
ScienceDex guides
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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.