Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
7,195
datasets available to search
ShareScore release 0.9.0
Dataset results
7,195 results for “SET”
Similarity data set used to test Synchronous Growth Changes (SGC) on dendrochronological data using tree-ring series from the ITRDB
<p>Dataset used to test the SGC, SSGC and AGC in:</p> <div> <div>Visser, RM. 2021 On the similarity of tree-ring patterns: Assessing the influence of semi-synchronous growth changes on the Gleichläufigkeitskoeffizient for big tree-ring data sets. <em>Archaeometry</em> 63(1): 204–215. DOI: <a href="https://doi.org/10.1111/arcm.12600">https://doi.org/10.1111/arcm.12600</a>.</div> </div> <p>The dataset contains the database used in this study</p> <ul> <li><em>itrdb_structure.sql</em> described the structure of the database (PostgreSQL/PostGIS)</li> <li>Tables <ul> <li><em>GC_??_tbl</em> are tables with ?? denoting the continent (see below) containg the comparisons between tree-ring series and the growth changes <ul> <li>The following columns are present: <ul> <li>ID1 and ID2: These are the ID's of the series compared.</li> <li>SGC: Synchronous Growth Changes</li> <li>SSGC: Semi Synchronous Growth Changes</li> <li>Overlap: the number of tree-rings compared</li> </ul> </li> <li>Data files with values in each table. The continents are as defined in the ITRDB (https://www.ncei.noaa.gov/access/paleo-search/?dataTypeId=18) <ul> <li>GC_af_tbl_202005 (Africa)</li> <li>GC_as_tbl_202005 (Asia)</li> <li>GC_au_tbl_202005 (Australia)</li> <li>GC_ca_tbl_202005 (Canada)</li> <li>GC_eu_tbl_202005 (Europe)</li> <li>GC_mx_tbl_202005 (Mexico)</li> <li>GC_sa_tbl_202005 (South America)</li> <li>GC_us_tbl_202005 (North America)</li> </ul> </li> </ul> </li> <li><em>headers</em>: <ul> <li>The following columns are present: <ul> <li>continent: two letter code of the continent (ITRDB)</li> <li>filename: orginal filename as deposited in the ITRDB</li> <li>line_nr: line number of the header</li> <li>header_text: text of the header related to the line number</li> </ul> </li> <li>Datafile: headers_201905222007.csv</li> </ul> </li> <li><em>names</em>: <ul> <li>The following columns are present: <ul> <li>filename: orginal filename as deposited in the ITRDB</li> <li>name_orig: orginal name of the tree-ring series as deposited in the ITRDB</li> <li>name_new: the IDs of the tree-ring series were replaced with a two‐letter code for the continent (AF, AS, AU, CA, EU, SA, US) and a sequence code to prevent duplicate IDs. These are used as ID1 and ID2 in the tables <em>GC_??_tbl</em></li> </ul> </li> <li>Datafile: names_201905240643.csv</li> </ul> </li> </ul> </li> <li>file: <em>geo_location_201906250635.csv</em> <ul> <li>Contains the locations related to each site in the database</li> <li>The following columns: <ul> <li>filename: orginal filename as deposited in the ITRDB</li> <li>continent: two letter code of the continent (ITRDB)</li> <li>lat: latitude</li> <li>long: longitude</li> <li>geom_point: WGS84 coordinates expressed as well-known text (WKT)</li> </ul> </li> </ul> </li> </ul> <p>For the related code, see also: </p> <p>Ronald Visser. (2022). Code and data related to semi-synchronous growth changes and the similarity of tree-ring patterns (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7157738</p> <p>Or: https://github.com/RonaldVisser/SGC</p>
Water will find its way: transport through narrow tunnels in hydrolases (Hal protein with different MD simulation settings)
<h1>Hal_2fs.zip</h1> <h2><em>"Water will find a way: transport through narrow tunnels in hydrolases (Hal_2fs protein variant)"</em></h2> <p>The input files and results used for the paper <em>"Water will find a way: transport through narrow tunnels in hydrolases"</em> are separated in the different folders depending the stage they belong to.</p> <h3>Folders</h3> <p>1. <em>01_Simulations.tar.gz</em>: All the files used to get the data employing Molecular Dynamics simulations. <br>2. <em>02_Caver.tar.gz</em>: Caver config used together with the <em>"Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations"</em> method (https://doi.org/10.1016/j.mex.2022.101968), and after re-clustering as described in the methods section of the paper.<br> 3. <em>03_Aquaduct.tar.gz</em>: Aquaduct results for all the MD trajectories.<br> 4. <em>04_TransportTools.tar.gz</em>: TransportTools results (https://doi.org/10.1093/bioinformatics/btab872).<br> 5. <em>05_WaterAnalysis.tar.gz</em>: The results from the exact matching analysis were parsed to perform H-bond analysis. Here are the PDBs where the <em>minimum sphere event</em> is present. Also the txt files with the results from the H-bond analysis are here.</p> <h3>Files</h3> <p> 1. <em>01_build_database.py</em>: Python3 script to parse the results from the exact matching analysis from TransportTools into a dictionary of transport events. For more detailed information read the script documentation.<br> 2. <em>Hal_2fs.dat</em>: Parsed database of transport events for Hal system. Command used: <br><em>python3 01_build_database.py -c 04_TransportTools/Hal_2fs.ini -o Hal_2fs.dat</em></p> <p> </p> <h1>Hal_300K.zip</h1> <h2><em>"Water will find a way: transport through narrow tunnels in hydrolases (Hal_300K protein variant)"</em></h2> <p>The input files and results used for the paper <em>"Water will find a way: transport through narrow tunnels in hydrolases"</em> are separated in the different folders depending the stage they belong to.</p> <h3>Folders</h3> <p>1. <em>01_Simulations.tar.gz</em>: All the files used to get the data employing Molecular Dynamics simulations. <br>2. <em>02_Caver.tar.gz</em>: Caver config used together with the <em>"Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations"</em> method (https://doi.org/10.1016/j.mex.2022.101968), and after re-clustering as described in the methods section of the paper.<br> 3. <em>03_Aquaduct.tar.gz</em>: Aquaduct results for all the MD trajectories.<br> 4. <em>04_TransportTools.tar.gz</em>: TransportTools results (https://doi.org/10.1093/bioinformatics/btab872).<br> 5. <em>05_WaterAnalysis.tar.gz</em>: The results from the exact matching analysis were parsed to perform H-bond analysis. Here are the PDBs where the <em>minimum sphere event</em> is present. Also the txt files with the results from the H-bond analysis are here.</p> <h3>Files</h3> <p> 1. <em>01_build_database.py</em>: Python3 script to parse the results from the exact matching analysis from TransportTools into a dictionary of transport events. For more detailed information read the script documentation.<br> 2. <em>Hal_300K.dat:</em> Parsed database of transport events for Hal system. Command used:<br><em>python3 01_build_database.py -c 04_TransportTools/Hal_300K.ini -o Hal_300K.dat</em></p> <p> </p> <h1>Hal_TIP3P.zip</h1> <h2><em>"Water will find a way: transport through narrow tunnels in hydrolases (TIP3P protein variant)"</em></h2> <p>The input files and results used for the paper <em>"Water will find a way: transport through narrow tunnels in hydrolases"</em> are separated in the different folders depending the stage they belong to.</p> <h3>Folders</h3> <p>1. <em>01_Simulations.tar.gz</em>: All the files used to get the data employing Molecular Dynamics simulations. <br>2. <em>02_Caver.tar.gz</em>: Caver config used together with the <em>"Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations"</em> method (https://doi.org/10.1016/j.mex.2022.101968), and after re-clustering as described in the methods section of the paper.<br> 3. <em>03_Aquaduct.tar.gz</em>: Aquaduct results for all the MD trajectories.<br> 4. <em>04_TransportTools.tar.gz</em>: TransportTools results (https://doi.org/10.1093/bioinformatics/btab872).<br> 5. <em>05_WaterAnalysis.tar.gz</em>: The results from the exact matching analysis were parsed to perform H-bond analysis. Here are the PDBs where the <em>minimum sphere event</em> is present. Also the txt files with the results from the H-bond analysis are here.</p> <h3>Files</h3> <p> 1. <em>01_build_database.py</em>: Python3 script to parse the results from the exact matching analysis from TransportTools into a dictionary of transport events. For more detailed information read the script documentation.</p> <p> 2. <em>Hal_TIP3P.dat</em>: Parsed database of transport events for Hal system. Command used:<br><em>python3 01_build_database.py -c 04_TransportTools/Hal_TIP3P.ini -o Hal_TIP3P.dat</em></p>
A re-analysis of an existing Drosophila melanogaster dataset reveals a new set of genes involved in post-mating response
<p>The figures and tables presented here are part of a manuscript submitted for publication by Chloe J. Bennett and Rodolfo Aramayo entitled:</p> <p><strong>"A re-Analysis of an existing <em>Drosophila melanogaster</em> dataset reveals a new set of genes involved in post-mating response"</strong></p> <p><strong>Abstract</strong></p> <p>RNA sequencing (RNA-seq) is a commonly used method to identify changes in gene expression between two conditions. The analysis of RNA-seq output is complicated, with the possibility of getting different results from the same raw data. We developed and deployed four parallel pipelines to reanalyze an existing dataset of two female Drosophila melanogaster tissue types before and after mating. The Drosophila post-mating response (PMR) is a well-characterized suite of changes that occur after mating, accompanied by a flux in gene expression. In comparing our study with the previous analysis of this dataset, we find our results to be more stringent, though we do identify a number of significant genes not found before. We also found variation among our own separate experiments, with gene-to-transcript isoform number and index building playing important roles in outcome. Finally, we identified a set of genes found by our pipeline that were not identified by the previous study and proposed potential roles for these genes in post-mating biology. Together, this work presents a critique of current RNA-seq analysis techniques and proposes multiple workflow adjustments that can increase the sensitivity, specificity, and stringency of differential gene expression studies.</p>
Data Sets "Proteinoids--Polyaniline Interaction with Stimulated Neurons on Living and Plastic Surfaces"
<p>Data sets for the paper Proteinoids--Polyaniline Interaction with Stimulated Neurons on Living and Plastic Surfaces.</p>
FIGURE 12 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 12. Scanning electron micrographs of associated near complete lower right dentition (M67678) of the omomyid Microchoerus erinaceus from bed TB33, How Ledge Limestone, SW Headon Hill, showing crowns with group 4 etching and post-voiding scavenging bite and gnaw marks. A, H, J, P4; B, G, P3; C, F, canine; D, E, I, I1; K, M3; L, M2. Views are: buccal (A-D), mesial (E, I), lingual (F-H), and occlusal (J-L). C shows gnaw marks on the ventral edge of the root of the canine; I shows an enlarged ventral portion of the root of I1 (E shows the whole tooth), with a bite mark on the side and parallel gnaw marks on the medioventral edge. The horizontal crease on the buccal enamel wall of P3 (B) is a developmental pathology. Scale bar equals 0.5 mm for I, 1 mm for the rest.
FIGURE 10 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 10. Dimensions of the long (L) and short (W) axes in millimetres of the seven oval puncture marks on fossil theridomyid bones from bed TB33, How Ledge Limestone, compared with the means with one standard deviation of those on fossil theridomyid bones from bed O3, Osborne Member (from Vasileiadou et al., 2009), of those made by jackals (Canis aureus) on modern ungulate bones (from Dominguez-Rodrigo and Piqueras, 2003) and of those made by leopards (Panthera pardus) on fossil bones of mammals of 4.5-104 kg weight (from Pickering et al., 2004). 1, M67679; 2, M62154.
FIGURE 9 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 9. Scanning electron micrographs of teeth of the carnivoran Paramiacis sp. and puncture marks on theridomyid bones from bed TB33, How Ledge Limestone, SW Headon Hill. A, two puncture marks on distal right tibia (M67679) of Thalerimys fordi; B, enlarged detail of A, the large puncture mark (a) and small puncture mark (b) labelled; C, puncture mark on?Thalerimys distal metapodial (M62154); D, right M1 (carnassial) (M67697) of Paramiacis sp., in occlusal view; E, left P3 (M67697) of Paramiacis sp.; F, puncture mark on?Thalerimys proximal metapodial (M62171); G, enlarged detail of F; H, puncture mark on?Thalerimys phalanx 2 (M62253); I, enlarged detail of H. Scale bars equal 1 mm for A-F, H and 0.2 mm for G and I.
FIGURE 7 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 7. Scanning electron micrographs of teeth and bones of Nyctitheriidae and teeth of Omomyidae, Apatemyidae and Amphilemuridae from bed TB33, How Ledge Limestone, SW Headon Hill, showing damage. A, right dentary with M2 (M67692) of Cheilonyctia lawsoni, showing etching group 5 and rounded breakage anteriorly, sharp breakage posteriorly; B, right I2 (M67693) of C. lawsoni, showing dentine exposure of etching group 5; C, distal left humerus (M67694) of Nyctitheriidae, showing sharp spiral irregular breakage; D, right M1/2 (M62126) of Vectipithex smithorum, showing almost total loss of enamel, of etching group 5; E, right M1 (M67695) of Heterohyus nanus, showing etching group 4; F, left P2 (M61711) of Gesneropithex latidens, showing etching group 2; G, enlarged detail of F. Arrows highlight areas of maximum etching on A-B, E and the only remaining enamel on D. Scale bars equal 1 mm for A and C, 0.5 mm for D-F, 0.25 mm for G and 0.2 mm for B.
FIGURE 6 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 6. Scanning electron micrographs of teeth and bones of Herpetotheriidae from bed TB33, How Ledge Limestone, SW Headon Hill, showing damage. A, right M3 (M67688) of Amphiperatherium species B, in etching group 1; B, enlarged detail of A; C, right M2 (M67689) of Amphiperatherium species A, in etching group 2; D, left M4 (M67690) of Amphiperatherium species A, in etching group 4; E, right calcaneum (M67691) of Herpetotheriidae, showing etching on the sustentaculum edge and tuber tip; F, left upper incisor (M67680) of Herpetotheriidae, showing two puncture marks on its root; G, enlarged detail of F. Arrows highlight areas of maximum etching on C-E. Scale bars equal 0.3 mm for A, C-E, 0.1 mm for B, G.
FIGURE 4 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 4. Scanning electron micrographs of teeth and bones of Theridomyidae and teeth of Pseudosciuridae, from bed TB33, How Ledge Limestone, SW Headon Hill, showing damage. A-C, Thalerimys fordi; D-F,?Thalerimys; G, Treposciurus mutabilis; H-I, Tarnomys quercyi vectisensis. A, Right M1/2 (M67681) in etching group 2; B, left M1/2 (M67682) in etching group 3; C, right M1/2 (M67683) in etching group 4; D, proximal radius (M61425), showing etching on the epiphysis and parallel grooves perpendicular to the long axis; E, proximal metapodial (M61438) with multiple fine parallel grooves perpendicular to the long axis on both edges; F, enlarged detail of E; G, left M1/2 (M61749) in etching group 2; H, right M1/2 (M61753) in etching group 2; I, right M3 (M61754) in etching group 4. Arrows highlight areas of maximum etching on A-C, G-I. Scale equals 0.5 mm for A-D, F-I, 1 mm for E.
FIGURE 5 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 5. Scanning electron micrographs of teeth and bones of Gliridae from bed TB33, How Ledge Limestone, SW Headon Hill, showing damage. A, right M (M67699) of Bransatoglis bahloi in etching group 5 (arrows); B-C, right P4 3 (M67684) of Glamys priscus, showing very fine irregular grooves on the root (B is enlarged detail); D, left lower incisor (M67685) of Gliridae, showing splitting from weathering stage 1; E, proximal phalanx 1 (M67686) of Gliridae, showing rounded breakage and grooves perpendicular to the long axis (arrows); F, proximal metatarsal III (M67687) of Gliridae, showing spiral rounded fracture; G, proximal left femur (M61428) of Gliridae, showing etching (arrows) and spiral breakage without rounding. Scale bars equal 0.2 mm for A, C-E, 0.5 mm for F-G, 0.1 mm for B.
FIGURE 2 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 2. Percentages of the minimum numbers of individuals (MNI) of each family of micromammals from bed TB33, How Ledge Limestone, SW Headon Hill. See Table 1 for numerical data.
FIGURE 11 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 11. Scanning electron micrographs of teeth of the pantolestid Cryptopithecus major (A-B) and tooth and bones of the carnivoran Paramiacis sp. (C-F) from bed TB33, How Ledge Limestone, SW Headon Hill, showing damage. A, left DP4 (M61688) in etching group 5, arrows indicating the only islets of enamel left on the crown; B, lower right premolar (M62331) in etching group 5, devoid of all enamel, the dentine core also penetrated by etching; C, left M2 (M67697) in etching group 2, broken with fracture edges rounded; D, phalanx 2 shaft (M67697), showing distal etching and rounded proximal fracture edge (arrowed); E-F, phalanx 1 (M67697) broken into a distal articulatory part (E) and the shaft and proximal articulation (F), with rounded fracture edges (arrowed), but closely fitting broken surfaces. Scale bars equal 0.5 mm for A-B, 0.3 mm for C-D and 1 mm for E-F.
FIGURE 1 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 1. Geological context of the site studied. A, General field photograph of the upper part of the Totland Bay Member, including the How Ledge Limestone, and overlying Colwell Bay Member, SW Headon Hill, Isle of Wight. B; detailed photograph of bed TB30-34, with scale divisions measuring 10 cm; C, location map of coastal Hampshire and the western half of the Isle of Wight, with period level geology and sites mentioned in the text; D, Lithic log of the How Ledge Limestone and adjacent beds. Bed numbers are from Hooker (2021).
FIGURE 3 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 3. Percentages of etched bones and teeth (left Y axis and left two X axis plots) and breakage types of elongate bones (right Y axis and right three X axis plots) for the four best represented micromammalian families in bed TB33, How Ledge Limestone. Fresh bones are those broken while still fresh, showing irregular spiral breakage. Rounded indicates bones with rounded (etched) broken edges. Dry indicates bones with broken edges perpendicular to their long axes. See Tables 5-7 for numerical data.
FIGURE 8 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 8. Percentages of teeth of the theridomyid Thalerimys fordi and the three other best represented families in each etching group (Vasileiadou et al., 2007a), numbered on X axes, from bed TB33, How Ledge Limestone, and bed O3, Osborne Member. The teeth of T. fordi and Gliridae are restricted to the cheek teeth. N = total number of etched teeth in each taxon for each bed.
FIGURE 13 in Taphonomy of an Eocene micromammal assemblage in a lake-margin depositional setting elucidates an ancient food web
FIGURE 13. Trophic relationships between predators and prey derived from damage patterns of bones and teeth of the best represented micromammals in bed TB33, How Ledge Limestone, SW Headon Hill. The two hypothetical owls and the crocodilian are drawn at smaller scales than the rest.
SemTab 2024: Semantic Web Challenge on Tabular Data to Knowledge Graph Matching Data Sets - WikidataTables2024R1 and WikidataTables2024R2
<p>Data Sets from the ISWC 2024 Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, Round 1, Wikidata Tables. Links to other datasets can be found on the challenge website: https://sem-tab-challenge.github.io/2024/ as well as the proceedings of the challenge published on CEUR.</p> <p>For details about the challenge, see: http://www.cs.ox.ac.uk/isg/challenges/sem-tab/</p> <p>For 2024 edition, see: https://sem-tab-challenge.github.io/2024/</p> <p>Note on License: This data includes data from the following sources. Refer to each source for license details:<br>- Wikidata https://www.wikidata.org/</p> <p>THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</p>
Data set for BA and BQ samples
<p><span>Collection of data for the manuscript entitled</span></p> <p><span>Carbonized apples and quinces stillage for electromagnetic shielding</span></p> <p><span>Data for BA and BQ is a collection of data - file is manuscript, file type .pdf</span></p> <p><span>FTPO_TGA_BA.txt – thermogravimetric data of carbon-based nanomaterial produced from biomass apple, file type .txt</span></p> <p><span>VINCA_Raman_BA.txt – Raman spectra data of BA, file type .txt</span></p> <p><span>FTPO_TGA_BQ.txt - thermogravimetric data of carbon-based nanomaterial produced from biomass quince, file type .txt</span></p> <p><span>UniOldenburg_VNA_BA.txt – Vector network analysis of shielding efficiency BA, file type .txt</span></p> <p><span>UniOldenburg_VNA_BQ.txt – Vector network analysis of shielding efficiency BQ, file type .txt</span></p> <p><span>VINCA_Raman_BQ.txt – Raman spectra data of BQ, file type .txt</span></p> <p> </p>
Hydraulic geometry and whitewater coverage for a steep proglacial stream -- data sets and scripts
<p>Data sets and scripts used in the analyses for the following article:</p> <p>Dufficy, A.L., Eaton, B.C. and Moore, R.D. <span>Quantifying hydraulic geometry and whitewater coverage for steep proglacial streams to support stream temperature modelling. <em>Hydrological Processes</em>, DOI: 10.1002/hyp.70003.<br></span></p> <p><span>The number in the file names for the R scripts indicates the order in which the scripts should be run.</span></p> <p><span>The study was funded by the Natural Sciences and Engineering Research Council of Canada and the Faculty of Arts, University of British Columbia.</span></p> <p> </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.