Skip to main content
Powered by ShareScore

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.

22

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

22 results for “ASL”

Learn how ShareScore rates datasets ↗
zenodo40/100

Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography

<p>This repository contains the raw K-space data and all MATLAB (The MathWorks, Natick, MA) code used for reconstruction, simulations, data analysis, and figure generation used in the article titled &quot;Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography&quot;.</p> <p>## Referencing</p> <p>If you use any of the data or the code provided here, please cite:</p> <p>1. Woods JG, Schauman SS, Chiew M, Chappell MA, Okell TW. Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography. Magnetic Resonance in Medicine. 2023; doi:10.1002/mrm.29491<br> 2. This Zenodo repository: Joseph G. Woods, S. Sophie Schauman, Mark Chiew, Michael A. Chappell &amp; Thomas W. Okell. (2022). Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6791097</p> <p>&nbsp;</p> <p>If you use the reconstruction code provided here, please also cite:</p> <p>1. Fessler JA, Sutton BP. Nonuniform fast fourier transforms using min-max interpolation. IEEE Transactions on Signal Processing. 2003;51(2):560-574. doi:10.1109/TSP.2002.807005<br> 2. Fessler JA. Michigan Image Reconstruction Toolbox. https://web.eecs.umich.edu/~fessler/code/. Accessed February 26, 2018.<br> 3. Schauman SS. Accelerated_TEASL. https://github.com/SophieSchau/Accelerated_TEASL. Accessed October 19, 2020.<br> 4. Chiew M. MR Linear Encoding Operators. https://users.fmrib.ox.ac.uk/~mchiew/Tools.html. Accessed March 30, 2020.</p> <p>## Notes for use:</p> <p>All data processing is performed in MATLAB (tested with 2021a and 2021b on macOS 10.14 (Mojave) and 12 (Monterey))</p> <p>The &quot;code/&quot; and &quot;data/&quot; folders should be placed within the same folder. The necessary file paths within each script in &quot;code/&quot; will be set up automatically.</p> <p>**Note**: the file paths use &quot;/&quot;, so would need to be manually changed for use on Windows, which uses &quot;\&quot; in file paths.</p> <p>- For performing full reconstruction of in vivo K-space data, **run reconalldata.m**.<br> &nbsp;&nbsp;&nbsp; - All code provided<br> &nbsp;&nbsp;&nbsp; - Uses:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1. Jeff Fessler&#39;s MIRT: http://web.eecs.umich.edu/~fessler/irt/fessler.tgz<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2. Mark Chiew&#39;s: xfm_NUFFT.m, etc: https://users.fmrib.ox.ac.uk/~mchiew/Tools.html<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 3. Sophie Schauman&#39;s Accelerated_TEASL: https://github.com/SophieSchau/Accelerated_TEASL</p> <p>- For plotting in-vivo data, **run figures_invivo.m**.<br> &nbsp;&nbsp;&nbsp; - FSL&#39;s read_avw to read in NIFTIs (but can replace this with MATLAB&#39;s in-built niftiread instead).<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; - (Install FSL from here: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation)<br> &nbsp;&nbsp;&nbsp; - All other code provided</p> <p>- For performing simulation and plotting results, **run figures_simulation.m**.<br> &nbsp;&nbsp;&nbsp; - All code provided</p> <p>- Location of specific Figure generation code:<br> &nbsp;&nbsp;&nbsp; - Figure 1: no code - manually made.<br> &nbsp;&nbsp;&nbsp; - Figure 2: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Figure 3: figures_simulation.m<br> &nbsp;&nbsp;&nbsp; - Figure 4: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Figure 5: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Figure 6: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Figure 7: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Figure 8: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Figure 9: figures_simulation.m<br> &nbsp;&nbsp;&nbsp; - Figure 10: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S1: figures_simulation.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S2: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S3: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S4: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S5: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S6: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S7: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S8: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S9: figures_invivo.m<br> &nbsp;&nbsp;&nbsp; - Supporting Information Figure S10: figures_simulation.m</p>

opencc-by-4.0Mar 2022View details →
zenodo40/100

VESPA ASL: VElocity and SPAtially Selective Arterial Spin Labeling

<p>This repository contains the simulation code, in vivo data, preprocessing code, and analysis code used in the&nbsp;Magnetic Resonance in Medicine article titled &quot;VESPA ASL: VElocity and SPAtially Selective Arterial Spin Labeling&quot; (<a href="https://doi.org/10.1002/mrm.29159">https://doi.org/10.1002/mrm.29159</a>). Please cite this article and this repository&nbsp;(<a href="https://doi.org/10.5281/zenodo.6870683">https://doi.org/10.5281/zenodo.6870683</a>) if you use any of this code or data in your work.</p> <p>Software requirements: BASH, FSL6, and MATLAB (tested with MATLAB versions 2021a and 2021b; requires the Optimization Toolbox and the Statistics and Machine Learning Toolbox). Preprocessing steps tested on macOS 12.4 (Monterey) and 10.14 (Mojave).</p> <p>This updated version (V2.0) simplifies and streamlines the setup of command line and MATLAB paths, making it easier to re-run the preprocessing and analysis steps.</p>

opencc-by-4.0Jan 2022View details →
zenodo40/100

Dataset: AerSale Corporation (ASLE) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →
zenodo40/100

Dataset: AerSale Corporation (ASLE) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →
zenodo40/100

Linked collectors and determiners for: The Shiny Cowbird, Molothrus bonariensis (Gmelin, 1789) (Aves: Icteridae), at 2,800 m asl in Quito, Ecuador.

Natural history specimen data linked to collectors and determiners held within, "The Shiny Cowbird, Molothrus bonariensis (Gmelin, 1789) (Aves: Icteridae), at 2,800 m asl in Quito, Ecuador". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/e801b9b4-5a23-4112-8f4a-98bf2fe60ceb">https://bionomia.net/dataset/e801b9b4-5a23-4112-8f4a-98bf2fe60ceb</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/e801b9b4-5a23-4112-8f4a-98bf2fe60ceb">https://gbif.org/dataset/e801b9b4-5a23-4112-8f4a-98bf2fe60ceb</a>. Formatted as a Frictionless Data package.

opencc-zeroJan 2024View details →
zenodo40/100

ASL-Skeleton3D

<p>The ASL-Skeleton3D introduces a representation based&nbsp;on mapping into the three-dimensional space the coordinates of the signers in the ASLLVD dataset. This enables a more accurate observation of the body parts and&nbsp;the signs articulation, allowing researchers to better understand the language and explore other approaches to&nbsp;the SLR field.</p>

opencc-by-4.0Sep 2021View details →
zenodo40/100

ASL-Phono

<p>The ASL-Phono introduces a novel linguistics-based representation, which describes the signs in the ASLLVD&nbsp;dataset in terms of a set of attributes of the American&nbsp;Sign Language phonology.</p>

opencc-by-4.0Sep 2021View details →
ClinicalTrials.gov40/100

Deaf Weight Wise: Community-engaged Implementation Research to Promote Healthy Lifestyle Change With Deaf ASL Users

ClinicalTrials.gov study NCT05211596. IPD Sharing: YES. Countries: 1. Publications: 2.

controlledIPD-YESFeb 2026View details →
zenodo36/100

Escapement and ASL data of salmon in the Salcha River, Alaska

<p>This data was collected as part of the AKSSF funding #4634 awarded to the Alaska Department of Fish and Game, Sportfish division in Region III. The Salcha River, located outside of Fairbanks, Alaska, is home to the largest spawning population of Chinook salmon in the U.S. portion of the Yukon River drainage. Tower techniques were used in the Salcha River to establish an escapement estimate and carcass surveys were conducted to collect age, sex and length data to assess run compositions. The data in this spreadsheet includes separate tabs for daily passage estimates with uncertainty and final estimate for each year of the project (2017-2019) and a single tab with all years of the data collected during carcass surveys.&nbsp; The citiation for the operational plan for this project is below:</p> <p>Stuby, L., and M. Tyers. 2016. Chinook salmon escapement in the Chena, Salcha, and Goodpaster Rivers and coho salmon escapement in the Delta Clearwater River, 2015. Alaska Department of Fish and Game, Fishery Data Series No. 16-45, Anchorage.</p> <p>Matter, A. N., and M. Tyers. 2019. Chinook salmon escapement in the Chena and Salcha Rivers and Coho salmon escapement in the Delta Clearwater River, 2019-2023. Alaska Department of Fish and Game, Regional Operational Plan ROP.SF.3F.2019.03, Anchorage.</p>

opencc-by-4.0Oct 2020View details →
zenodo32/100

Escapement and ASL data of salmon in the Chena River, Alaska

<p>&nbsp;This data was collected as part of the AKSSF funding #52011 awarded to the Alaska Department of Fish and Game, Sportfish division in Region III. Chinook salmon are an important subsistence resource throughout the Yukon River drainage and the Chena River supports one of the largest spawning populations in the Alaska portion. This project will estimate Chinook and chum salmon by visually counting fish as they pass over a continuous band of white fabric panels strung across the river bottom on the upstream side of the Moose Creek Dam. A DIDSON sonar unit and an ARIS sonar unit will be deployed upstream of the tower site on both sides of the river to ensonify the river at all times and record the number of migrating salmon throughout the run. A mixture model will be used to estimate Chinook and chum salmon during extended periods of high water when tower counts cannot be completed. In addition to enumeration, carcasses of spawned-out Chinook and chum salmon will be collected during the last week of July through the first two weeks of August to estimate the ASL composition of the escapement. The citation for the operational plan for this project is below:&nbsp;</p> <p>Matter, A. N., and M. Tyers. 2019. Chinook salmon escapement in the Chena and Salcha Rivers and Coho salmon escapement in the Delta Clearwater River, 2019-2023. Alaska Department of Fish and Game, Regional Operational Plan ROP.SF.3F.2019.03, Anchorage.</p>

opencc-by-3.0-usApr 2022View details →
dryad32/100

Air temperature data recorded in a shaded area near the shore of the study site Laguna Toreadora (3,920 m asl) from August 2014 to September 2016 using a HOBO Water Temperature Pro v2 Data Logger.

<p class="MsoNormal">Air temperature data (°C) recorded in a shaded area near the shore of the study site Laguna Toreadora (<span>S 02° 46.792", W 079° 13.411"; </span>3,920 m asl) in Cajas National Park, Ecuador from August 2014 to September 2016 using a HOBO Water Temperature Pro v2 Data Logger. Air temperatures were recorded hourly over this period, with an interruption in data collection from May to July 2015.</p>

opencc-zeroApr 2022View details →
ClinicalTrials.gov32/100

Assessment and Quantification of Collateral by ASL MRI

ClinicalTrials.gov study NCT02479243. IPD Sharing: NO. Countries: 1. Publications: 5.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Cerebral Perfusion Associated With Postural Changes: an ASL MR Perfusion Study

ClinicalTrials.gov study NCT02912546. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Trial to Evaluate the Effectiveness of Angular Stable Locking System (ASLS) in Patients With Distal Tibial Fractures

ClinicalTrials.gov study NCT00875992. IPD Sharing: Not stated. Countries: 3. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad32/100

Air temperature data recorded in a shaded area near the shore of the study site Laguna Toreadora (3,920 m asl) from August 2014 to September 2016 using a HOBO Water Temperature Pro v2 Data Logger.

Open the record for dataset details and reuse information.

publicApr 2022View details →
ClinicalTrials.gov24/100

ASL in Brain Metastasis MRI Following Gamma Knife Treatment

ClinicalTrials.gov study NCT04833335. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Racemic Ketamine Versus S-ketamine With Arterial Spin Labeling (ASL)-MRI in Healthy Volunteers

ClinicalTrials.gov study NCT01506921. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Evaluation of Handling and Possible Complications Related to the Newly Developed Angular Stable Locking System (ASLS)

ClinicalTrials.gov study NCT00793637. IPD Sharing: Not stated. Countries: 2. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Family ASL: Longitudinal Study of Deaf Children and Hearing Parents Who Receive Services to Support the Learning of ASL

ClinicalTrials.gov study NCT04988451. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov24/100

Arterial Spin Labeling (ASL) MRI for Cognitive Decline

ClinicalTrials.gov study NCT01727622. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record