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Datasets of Vascular Networks Extracted from Retinal Images of Hypertensive Retinopathy and Glaucoma Patients
<p>This dataset contains high resolution images of blood vessels extracted from Digital Retinal Images for Optic Nerve Segmentation Database (DRIONS-DB). It contains 110 blood vessels of individuals of which 23.1% are patients with chronic glaucoma while the remaining 76.9% are hypertensive retinopathy patients. </p>
The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews (data repository)
<p>These are the data we generated in our evaluation of the graphical user interface.</p> <p>Please see our publication on Wellcome Open Research for information about the evaluations.</p>
Deprecated - VAMDC extraction with query token = mecasda:86283556-1a6a-4fd3-b513-de792c32edd4:get
<p>Deprecated because the file upload was corrupted.</p> <p>This is a dataset extracted from http://vamdc.icb.cnrs.fr/mecasda-12.07/tap/ VAMDC node.</p> <p>Query originating this dataset: query=select species;</p> <p>Data source version: 1</p> <p>Data format: XSAMS 12.07</p> <p>Query uuid in VAMDC query store: 9ca8e9a9-b6d7-4f5e-a510-13cb8bf4b759</p>
Deprecated - VAMDC extraction with query token = starkb:3dec15c4-fc5b-4679-aa6a-3244d77436eb:head
<p>Deprecated because the file upload was corrupted.</p> <p>This is a dataset extracted from http://stark-b.obspm.fr/12.07/vamdc/tap/ VAMDC node.</p> <p>Query originating this dataset: query=select * where ( atomsymbol = 'li' and ioncharge = 0 );</p> <p>Data source version: 2017-06-23</p> <p>Data format: XSAMS 12.07</p> <p>Query uuid in VAMDC query store: 17053a9a-e56e-451b-9bd2-8e0cddda0d5d</p>
CATCH-EyoU Processes in Youth's Construction of Active EU Citizenship Cross-national Wave 1 Questionnaires Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia - EXTRACT
<p>The dataset was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538 <a href="http://www.catcheyou.eu/">http://www.catcheyou.eu/</a>. </p> <p>The data set consists of:</p> <ul> <li>1 data file saved in .sav format</li> </ul> <p>“CATCH-EyoU Processes in Youth’s Construction of Active EU Citizenship Cross-national Wave 1 Questionnaires Italy, Sweden, Germany, Greece, Portugal, Czech Republic, UK, and Estonia - EXTRACT.sav”</p> <ul> <li>1 README file</li> </ul> <p>The file was generated through IBM SPSS software. Discrete missing values: 88, 99. The .sav file (SPSS) can be processed using “R” (library “foreign”): <a href="https://cran.r-project.orgv/">https://cran.r-project.org</a></p> <p>This dataset relates to following paper: </p> <p>Ekaterina Enchikova, Tiago Neves, Sam Mejias, Veronika Kalmus, Elvira Cicognani, Pedro Ferreira (2019) Civic and Political Participation of European Youth: fair measurement in different cultural and social contexts. Frontiers in Education.</p> <p>Data Set Contact Person: Ekaterina Enchikova [UP-CIIE]; mail: enchicova@gmail.com </p> <p>Data Set License: this data set is distributed under a Creative Commons Attribution (CC-BY) <a href="http://creativecommons.org/licenses">http://creativecommons.org/licenses</a></p> <p> </p>
VAMDC extraction with identifier = 1ae3bd31-9182-44d2-84bf-2212b88ab7d6
<div>This is a dataset extracted from http://vald.astro.uu.se/atoms-12.07/tap/ VAMDC node.</div><div>Query originating this dataset: query=select species; </div><div> Data source version: 2018-04-04</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 1ae3bd31-9182-44d2-84bf-2212b88ab7d6</div>
Dataset of confocal microscopy stacks from plant samples - ImageJ SurfCut: a user-friendly, high-throughput pipeline for extracting cell contours from 3D confocal stacks
<p>This data set contains confocal stacks from <em>Arabidopsis thaliana </em><em>35S::GFP-MBD</em> light grown hypocotyl as well as propidium iodide stained cotyledon pavement cells and shoot apical meristem. This is the test dataset for the Fiji macro SurfCut (https://github.com/sverger/SurfCut; 10.5281/zenodo.2635737)</p> <p> </p> <p><strong>Material and methods:</strong></p> <p>Plant material and growth conditions</p> <p><em>Arabidopsis thaliana </em>wild type Col-0 and the microtubule reporter line <em>GFP-MBD</em> (WS-4, (Marc et al. 1998) were used. Seeds were cold treated for 48 hr to synchronize germination. Plants were then grown in a phytotron at 20°C, in a 16 hr light/8 hr dark cycle on solid Murashige and Skoog medium (MS medium, Duchefa, Haarlem, the Netherlands) with 0.8% agar, 1% sucrose, and no vitamin.</p> <p> </p> <p>Confocal microscopy</p> <p>Cell contour staining in the case of PC_PI_Col0_(1-8).tif and SAM_PI_Col-0.tif was performed by staining the cell wall with Propidium Iodide (PI). Plants were immersed in 0.2 mg/ml propidium iodide (PI, Sigma-Aldrich) for 10 min and washed with water prior to imaging. For imaging, samples were either placed on a solid agar medium and immersed in water, or placed between glass slide and coverslip separated by 400 μm spacers to prevent tissue crushing. Images were acquired using a Leica TCS SP8 confocal microscope, equipped with a water immersion objective (HCX IRAPO L 25x/0.95 W). PI excitation was performed using a 552 nm solid-state laser and fluorescence was detected at 600–650 nm. GFP excitation was performed using a 488 nm solid-state laser and fluorescence was detected at 495–535 nm. Stacks of 1024x1024 pixels (pixel size of 0.363 x 0.363 micron) optical section were generated with a Z interval of 0.5 μm.</p> <p> </p> <p><strong>File list:</strong></p> <p>Light grown hypocotyl, <em>GFP-MBD</em> reporter line:</p> <p>- Hypocotyl_GFP-MBD.tif</p> <p>Cotyledon’s pavement cells, PI staining:</p> <p>- PC_PI_Col0_1.tif</p> <p>- PC_PI_Col0_2.tif</p> <p>- PC_PI_Col0_3.tif</p> <p>- PC_PI_Col0_4.tif</p> <p>- PC_PI_Col0_5.tif</p> <p>- PC_PI_Col0_6.tif</p> <p>- PC_PI_Col0_7.tif</p> <p>- PC_PI_Col0_8.tif</p> <p>Shoot apical meristem, PI staining:</p> <p>- SAM_PI_Col-0.tif</p> <p> </p> <p><strong>Reference:</strong></p> <p>Marc, Jan, Cheryl L. Granger, Jennifer Brincat, Deborah D. Fisher, Teh-hui Kao, Andrew G. McCubbin, and Richard J. Cyr. 1998. “A GFP–MAP4 Reporter Gene for Visualizing Cortical Microtubule Rearrangements in Living Epidermal Cells.” <em>The Plant Cell</em> 10 (11): 1927–39. https://doi.org/10.1105/tpc.10.11.1927.</p>
Extracted Illustrations of the Berlin State Library's Digitized Collections (part 4 of 4)
<p><strong>This is part 4 of 4. The following dataset contains a reference the other ZIP files: </strong></p> <pre>https://doi.org/10.5281/zenodo.2598101</pre> <p>The dataset consists of various illustrations extracted from 26,233 historical books and other media offered in the Berlin State Library's Digitized Collections. The media objects are older than 1920.</p> <p>Version 1.0 contains of 594,890 extracted illustrations in total.</p> <p>The extraction of illustrations is driven by the coordinates given by the ABBYY FineReader OCR engine (in ALTO XML) . The extracted illustrations have not been resized but compressed and saved in JPEG format.</p> <p>Pre-trained models in order to separate color scales, hand-written signatures, library stamps or the like from interesting content are available under: <a href="https://github.com/elektrobohemian/imi-unicorns">https://github.com/elektrobohemian/imi-unicorns</a>.</p> <p>The extracts for each media object are stored in separated sub-folders and tar files named after the PPN (a unique ID used in the library) to facilitate further processing. Additional metadata can be obtained with help of the PPN as described here: <a href="https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md">https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md</a> .</p> <p>The dataset is published as a set of ZIP files, each fitting on a Blu Ray disc. <strong>After decompression, the contents will consume ca. 166 GB.</strong></p> <p><strong>This is part 4 of 4. The following dataset contains a reference the other ZIP files: </strong></p> <pre>https://doi.org/10.5281/zenodo.2598101</pre>
Extracted Illustrations of the Berlin State Library's Digitized Collections (part 3 of 4)
<p><strong>This is part 3 of 4. The following dataset contains a reference the other ZIP files: </strong></p> <pre>https://doi.org/10.5281/zenodo.2598101</pre> <p>The dataset consists of various illustrations extracted from 26,233 historical books and other media offered in the Berlin State Library's Digitized Collections. The media objects are older than 1920.</p> <p>Version 1.0 contains of 594,890 extracted illustrations in total.</p> <p>The extraction of illustrations is driven by the coordinates given by the ABBYY FineReader OCR engine (in ALTO XML) . The extracted illustrations have not been resized but compressed and saved in JPEG format.</p> <p>Pre-trained models in order to separate color scales, hand-written signatures, library stamps or the like from interesting content are available under: <a href="https://github.com/elektrobohemian/imi-unicorns">https://github.com/elektrobohemian/imi-unicorns</a>.</p> <p>The extracts for each media object are stored in separated sub-folders and tar files named after the PPN (a unique ID used in the library) to facilitate further processing. Additional metadata can be obtained with help of the PPN as described here: <a href="https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md">https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md</a> .</p> <p>The dataset is published as a set of ZIP files, each fitting on a Blu Ray disc. <strong>After decompression, the contents will consume ca. 166 GB.</strong></p> <p><strong>This is part 3 of 4. The following dataset contains a reference the other ZIP files: </strong></p> <pre>https://doi.org/10.5281/zenodo.2598101</pre>
Extracted Illustrations of the Berlin State Library's Digitized Collections (part 2 of 4)
<p><strong>This is part 2 of 4. The following dataset contains a reference the other ZIP files: </strong></p> <pre>https://doi.org/10.5281/zenodo.2598101</pre> <p>The dataset consists of various illustrations extracted from 26,233 historical books and other media offered in the Berlin State Library's Digitized Collections. The media objects are older than 1920.</p> <p>Version 1.0 contains of 594,890 extracted illustrations in total.</p> <p>The extraction of illustrations is driven by the coordinates given by the ABBYY FineReader OCR engine (in ALTO XML) . The extracted illustrations have not been resized but compressed and saved in JPEG format.</p> <p>Pre-trained models in order to separate color scales, hand-written signatures, library stamps or the like from interesting content are available under: <a href="https://github.com/elektrobohemian/imi-unicorns">https://github.com/elektrobohemian/imi-unicorns</a>.</p> <p>The extracts for each media object are stored in separated sub-folders and tar files named after the PPN (a unique ID used in the library) to facilitate further processing. Additional metadata can be obtained with help of the PPN as described here: <a href="https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md">https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md</a> .</p> <p>The dataset is published as a set of ZIP files, each fitting on a Blu Ray disc. <strong>After decompression, the contents will consume ca. 166 GB.</strong></p> <p><strong>This is part 2 of 4. The following dataset contains a reference the other ZIP files: </strong></p> <pre>https://doi.org/10.5281/zenodo.2598101</pre>
Microfluidic solvent extraction of poly(vinyl alcohol) droplets: effect of polymer structure on particle and capsule formation
<p>Raw data from the majority of figures of our 2018 Soft Matter Paper:</p> <p>Selected datasets from figures are excluded, owing to them being transformations of the raw data provided in the same figure.</p> <p> </p>
VAMDC extraction with identifier = 67191e75-86b9-4f84-8a69-1e9c615ab33b
<div>This is a dataset extracted from http://vald.astro.uu.se/atoms-12.07/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( atomsymbol in ['ca'] and radtranswavelength <= 8527.568983881622 and radtranswavelength >= 8526.246307878626 ); </div><div> Data source version: 2018-04-04</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 67191e75-86b9-4f84-8a69-1e9c615ab33b</div>
MALICE: Vial Imaging and Label Extraction example image set
<p>48 images of Collection vials taken using Mirrored Angle Label Image Capture Extraction (MALICE). This data set is intended for development of automated cropping and label extraction solutions</p>
Extended Data for Publication "Testing the Spectroscopic Extraction of Suppression of Convective Blueshift"
<p>Efforts to detect low-mass exoplanets using stellar radial velocities (RVs) are currently limited by magnetic photospheric activity. Suppression of convective blueshift is the dominant magnetic contribution to RV variability in low-activity Sun-like stars. Due to convective plasma motions, the magnitude of RV contributions from the suppression of convective blueshift is roughly correlated with the depth of formation of photospheric spectral lines used to compute the RV time series. Meunier et al. (2017), used this relation to demonstrate a method for spectroscopic extraction of the suppression of convective blueshift in order to isolate RV contributions, including planetary RVs, that contribute equally to the timeseries for each spectral line. In this publication, we extract disk-integrated solar RVs from observations over a 2.5 year time span made with the solar telescope integrated with the HARPS-N spectrograph at the Telescopio Nazionale Galileo (La Palma, Canary Islands, Spain). We apply the methods outlined by Meunier et al. (2017) - as part of this analysis, we fit Gaussian line profiles to 765 iron lines measured over 457 exposures.</p> <p>Here, we provide the complete line list (Table 1; Table1_LineList.csv) used in our analysis, and the resulting RVs time series in their entirety (Table 3; Table3_TimeSeries.csv). Wavelengths are given in Angstroms, and RVs in m/s.</p> <p>We also include 4 CSV files with the line fit parameters of each line profile: Each row corresponds to a single exposure time (corresponding to the JDs in Table 3) and each column corresponds to a specific spectral line (with wavelength specified in Table 1).</p> <p>We fit each spectral line to a Gaussian of the form:</p> <p><span class="math-tex">\(f(\lambda) = p_1 - p_2 \exp \left[- {1 \over 2} \left({{\lambda - p_3} \over p_4}\right)^2 \right]\)</span></p> <p>p<sub>1</sub> is the continuum level in arbitrary units (LineProfiles_Continuum.csv)<br> p<sub>2</sub> is the line strength in arbitrary units (LineProfiles_Amplitude.csv)<br> p<sub>3</sub> is the line shift in Angstroms (LineProfiles_Shift.csv)<br> p<sub>4</sub> is the line width in Angstroms (LineProfiles_Width.csv)</p>
VAMDC extraction with identifier = f29e648a-7c00-4ff7-afe5-5cff38891a3d
<div>This is a dataset extracted from http://tipbase.obspm.fr/12.07/vamdc/tap/ VAMDC node.</div><div>Query originating this dataset: query=select species; </div><div> Data source version: 2017-01-30</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: f29e648a-7c00-4ff7-afe5-5cff38891a3d</div>
VAMDC extraction with identifier = c4819a00-901e-4fec-90cf-997e1566a464
<div>This is a dataset extracted from http://topbase.obspm.fr/12.07/vamdc/tap/ VAMDC node.</div><div>Query originating this dataset: query=select species where ( radtranswavelength < 1.4275831333333E7 and radtranswavelength > 1.3626929909091E7 ); </div><div> Data source version: 2017-01-30</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: c4819a00-901e-4fec-90cf-997e1566a464</div>
VAMDC extraction with identifier = e2352465-ebdb-4347-abc2-96c83da81c73
<div>This is a dataset extracted from https://cdms.astro.uni-koeln.de/cdms/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( inchikey = 'bojpitgaffyfjk-uhfffaoysa-n' ); </div><div> Data source version: 2019-11-27</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: e2352465-ebdb-4347-abc2-96c83da81c73</div>
VAMDC extraction with identifier = 4bac99d4-20a0-4625-aac1-e6255edb376e
<div>This is a dataset extracted from http://topbase.obspm.fr/12.07/vamdc/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( radtranswavelength <= 4819.05078125 and radtranswavelength >= 4816.38671875 ); </div><div> Data source version: 2017-01-30</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 4bac99d4-20a0-4625-aac1-e6255edb376e</div>
Figures 2–6 in A reliable and efficient BioPulverizer method in preparing and grinding nematodes for nucleic acid extraction and molecular identification
Figures 2–6 PCR amplification product with primers: (2) PCR products from the seminested primer pairs (NemF and 18Sr2b; NF1 and 18Sr2b) obtained from soil nematode samples with BioPulverizer grinding; (3) PCR amplification with the first cycle of the primer pair (NemF and 18Sr2b) from soil samples without BioPulverizer grinding; (4–5) Two amplification bands, 181 bp with the species-specific primer pair GlyF1/rDNA2 (4) and 477 bp with SCNF1/SCNR1 (5), were amplified for Heterodera glycines; (6) PCR products with the universal primer pair 194F/195R and the species-specific primer pair (Meloidogyne incognita) from potato tuber samples. All molecular markers (M) are 100 bp DNA ladders. The concentrations of agarose gel are 1.8% in Figs 2–3 and 1% in Figs 4–6.
Figure 1 in A reliable and efficient BioPulverizer method in preparing and grinding nematodes for nucleic acid extraction and molecular identification
Figure 1 Equipment used for nematode preparation and grinding. The names of all the equipment are listed above or under each respective one.
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.