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.

1,211

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

1,211 results for “Instruments”

Learn how ShareScore rates datasets ↗
zenodo36/100

Boulez_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Pierre Boulez, Le Marteau sans Maître pour voix d'alto et 6 instruments (1953–57), no. 7: après "l'artisanat furieux". Rapide

<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files.</p> <p>This dataset<strong> Boulez_dataset_PoD </strong>contains eight files:</p> <ul> <li>Boulez_01_ReadMe.pdf</li> <li>Boulez_02_data.xlsx (processed data for this work)</li> <li>Boulez_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Boulez_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Boulez_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Berg_04_audio.mp3 to display correctly]</li> <li>Boulez_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Boulez_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> <li>Boulez_08_annotated_score.pdf (model analysis annotated in the score)</li> </ul>

opencc-by-4.0Oct 2024View details →
zenodo36/100

The Role of Ethnic Enclaves in the Labour Market During the Covid-19 Crisis: An Instrumental Variable Approach

<p>Replication package for &quot;The Role of Ethnic Enclaves in the Labour Market During the Covid-19 Crisis: An Instrumental Variable Approach&quot;</p>

opencc-by-4.0Oct 2021View details →
zenodo36/100

Introduction to assessment and instrument design

<p>This video has been prepared by Dr. Anna Beniermann (Substitute Professor, University of Kassel, Germany) for the Euroscitizen WG1/WG3 joint workshop on assessment as&nbsp;a short and basic introduction into&nbsp;the&nbsp;planning&nbsp;of&nbsp;surveys&nbsp;and&nbsp;the&nbsp;development&nbsp;of&nbsp;measurement&nbsp;instruments.&nbsp;The&nbsp;focus of this introduction&nbsp;is on&nbsp;the&nbsp;design&nbsp;of&nbsp;questionnaires&nbsp;to collect quantitative data. Starting with general questions on which steps to take when planning a survey like formulating aims and research questions, the video gives insights into aspects of operationalization and quality criteria. By addressing objectivity, reliability and validity,&nbsp; the video points out central aspects and potential barriers for conducting a sound survey.</p> <p>Euroscitizen WG1/WG3 joint workshop was held online in April 2021, with the participation of members from all working groups of the Euroscitizen COST action. The goal of the workshop was to co-design&nbsp;a&nbsp;general assessment tool/framework to allow practitioners to evaluate the impact of their non-formal learning activities, including assessing the general quality of the activity and specific knowledge, attitudes and improving scientific literacy.</p> <p>The video is shared under a Creative commons licence&nbsp;CC-BY-NC-SA.</p> <p>When citing please use the following format:&nbsp;Beniermann, Anna. (2021)&nbsp;Introduction to assessment and instrument design. Zenodo.&nbsp;http://doi.org/10.5281/zenodo.5700923</p>

opencc-by-4.0Apr 2021View details →
zenodo36/100

Validation of Work Values Instrument in Final Year University Students

<p><em>This is the raw dataset when we conducted the&nbsp;adaptation of the work values instrument in final year students. The number of participants in this study was 316 students, comprised of final year students from various majors who were selected by quota sampling. The raw dataset has been disseminated&nbsp;in&nbsp;the undergraduate thesis defense, so the publication&nbsp;date stated above is referring&nbsp;to it. The&nbsp;raw data set has never been published elsewhere.&nbsp;</em></p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Instrument response files for seismic stations in South Korea (accelerometer)

<p><strong>To do</strong></p><p>[1.01] I have found something wrong in poles and zeros for the KG and KN networks. Please do not use them until update. I am sorry for it. (14 November 2023)</p><p>&nbsp;</p><p><strong>Example 1 (Seismic Analysis Code)</strong></p><p>Examples to deconvolve the instrument response from raw data are below, using the&nbsp;Seismic Analysis Code (SAC, version sac-101.6a).&nbsp;</p><p>&nbsp;</p><p>1. A unit of output is 'm/s2'</p><p>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 w acc.sac q</p><p>&nbsp;</p><p>2. A unit of output is&nbsp;'m/s'</p><p>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL w vel.sac q</p><p>&nbsp;</p><p>3. A unit of output is 'm'</p><p>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL rtr rmean taper TRANS FROM VEL TO NONE w disp.sac q</p><p>&nbsp;</p><p>Note that the unit of the output is incoherent with the SAC header 'IDEP'.</p><p><strong>Example 2 (StationXML with obspy)</strong></p><p>#this is same as the code for the velocity seismometers.</p><p>&nbsp;</p><p><strong>Update notes</strong></p><ul><li>[1.01]<ul><li>Typo at INPUT UNIT for KG is modified (M/S -&gt; M/S**2)</li><li>Stations KS.CE2A,&nbsp;KS.HA2B&nbsp;are&nbsp;added</li><li>StationXML file is added (ksgn.xml)</li></ul></li><li>[1.00] The files for the KG network are made based on the logs until 12 April 2019 (personal&nbsp;communication with the Korea Institute of Geoscience and Mineral Resources).</li></ul><p><strong>Others</strong></p><p>Velocity seismometer <a href="https://doi.org/10.5281/zenodo.3700312">https://doi.org/10.5281/zenodo.3700312</a><br>Accelerometer&nbsp;<a href="https://doi.org/10.5281/zenodo.3872436">https://doi.org/10.5281/zenodo.3872436</a></p><p>&nbsp;</p><p><strong>License</strong></p><p>This&nbsp;distribution follows the Creative Commons Attribution 4.0 International. You are free to modify and redistribute the files.</p><p>&nbsp;</p>

opencc-by-4.0May 2021View details →
zenodo36/100

Instrument response files for seismic stations in South Korea

<p>&nbsp;</p> <p><strong>Citation</strong></p> <p>If you use it, please cite the following article in your work:&nbsp;</p> <p>Lim and Kim (2020), A dataset of seismic sensor responses of South Korea seismic stations.&nbsp;Journal of the Geological Society of Korea, 56(4), 515-524,&nbsp;http://dx.doi.org/10.14770/jgsk.2020.56.4.515 (Korean with English abstract)</p> <p>&nbsp;</p> <p><strong>Example 1 (Seismic Analysis Code)</strong></p> <p>Examples to deconvolve the instrument response from raw data are below, using the&nbsp;Seismic Analysis Code (SAC, version sac-101.6a).&nbsp;</p> <p>&nbsp;</p> <p>1. A unit of output is &#39;m/s&#39;</p> <pre><code>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 w vel.sac q</code></pre> <p>&nbsp;</p> <p>2. A unit of output is&nbsp;&#39;m&#39;</p> <pre><code>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM VEL TO NONE w disp.sac q</code></pre> <p>&nbsp;</p> <p>3. A unit of output is &#39;m/s2&#39;</p> <pre><code>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM VEL TO ACC w acc.sac q</code></pre> <p>Note that the unit of the output is incoherent with the SAC header &#39;IDEP&#39;.</p> <p>&nbsp;</p> <p><strong>Example 2 (StationXML with obspy)</strong></p> <pre><code class="language-python">#!/usr/bin/env python3 from obspy import read_inventory from obspy import read st = read('/path/to/waveforms') inv = read_inventory('ksgn.xml') st.detrend(type="linear") st.detrend(type="demean") pref = [0.1, 0.2, 15, 20] #output = m/s**2 st2 = st.copy() st2.remove_response(inventory=inv,output='ACC',pre_filt=pref,taper=True,zero_mean=False) st2[0].write('acc.sac',format="SAC") #... #output = m/s st2 = st.copy() st2.remove_response(inventory=inv,output='VEL',pre_filt=pref,taper=True,zero_mean=False) st2[0].write('vel.sac',format="SAC") #... #output = m st2 = st.copy() st2.remove_response(inventory=inv,output='DISP',pre_filt=pref,taper=True,zero_mean=False) st2[0].write('disp.sac',format="SAC") #...</code></pre> <p>&nbsp;</p> <p><strong>Update notes</strong></p> <ul> <li>[1.02] Typo in station name of KS.HA2B is modified (KS.HA2B -&gt; HA2B)</li> <li>[1.01] <ul> <li>Files for the sensor JC-V100 are provided from Won-Young Kim (2 Dec 2021)</li> <li>Station KS.HA2B is added</li> <li>StationXML file is added (ksgn.xml)</li> </ul> </li> <li>[1.00] The files for the KG network are made based on the logs until 12 April 2019 (personal&nbsp;communication with the Korea Institute of Geoscience and Mineral Resources).&nbsp;</li> </ul> <p>&nbsp;</p> <p><strong>Pending works</strong></p> <p>Reflecting a change in logger of KS.DGY2</p> <p>&nbsp;</p> <p><strong>Others</strong></p> <p>Velocity seismometer <a href="https://doi.org/10.5281/zenodo.3700312">https://doi.org/10.5281/zenodo.3700312</a><br> Accelerometer&nbsp;<a href="https://doi.org/10.5281/zenodo.3872436">https://doi.org/10.5281/zenodo.3872436</a></p> <p>&nbsp;</p> <p><strong>License</strong></p> <p>This&nbsp;distribution follows the Creative Commons Attribution 4.0 International. You are free to modify and redistribute the files.</p>

opencc-by-4.0May 2020View details →
zenodo36/100

Comparing black-carbon- and aerosol-absorption-measuring instruments – a new system using lab-generated soot coated with controlled amounts of secondary organic matter

<p>A preprint of the publication can be found here:&nbsp;<a href="https://amt.copernicus.org/preprints/amt-2021-214/">AMTD - Response of black carbon and aerosol absorption measuring instruments to laboratory-generated soot coated with controlled amounts of secondary organic matter (copernicus.org)</a>&nbsp;(doi.org/10.5194/amt-2021-214).</p> <p>The files correspond to the raw data sets&nbsp;used for Figures 3 and 4 of the aforementioned publication.</p> <p>The date and start/stop time of the measurements are listed in the file &quot;overview_measurements&quot;.</p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Proxemics and Social Interactions in an Instrumented Virtual Reality Workshop

<p>Supplemental code and dataset for the&nbsp;<a href="https://doi.org/10.1145/3411764.3445729">ACM CHI 2021 paper on &quot;Proxemics and Social Interactions in an Instrumented Virtual Reality Workshop&quot;</a>. In this research paper we&nbsp;<a href="https://hubs.mozilla.com/">instrumented Mozilla Hubs Cloud</a>&nbsp;to record where participants were during the event. From there, we measured proxemic and plotted the activity along with some semi-structured interviews.</p> <p>Updates to the Hubs logger can be found in the&nbsp;<a href="https://github.com/ayman/hubs-research-acm-chi-2021/">repository</a>.</p>

openmpl-2.0Apr 2021View details →
zenodo36/100

China Daily Instrumental Weather Database

<p>Please cite as source: Junjian Yi, Junhong Chu, and I.P.L. Png, &quot;Early-life exposure to hardship increased risk tolerance and entrepreneurship in adulthood with gender differences&quot;, Proceedings of the National Academy of Sciences, forthcoming.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Dataset for the publication Review of Scientific Instruments 92, 063205 (2021)

<p>Datasets for Fig. 3 and 5&nbsp;of the publication &quot;Long distance optical transport of ultracold atoms: A compact setup using a Moir&eacute; lens&quot;,&nbsp;Review of Scientific Instruments&nbsp;<strong>92</strong>, 063205 (2021)</p>

opencc-by-4.0Jun 2021View details →
zenodo36/100

Photos of participants of Turin Workshop (11 and 12 April 2022): Skull collections. Series, standardization and instruments

<p>During the two days of the workshop in the Museum of Human Anatomy was inaugurated the&nbsp; Exhibition: &quot;The art of trepanning&quot;.</p> <p>The artworks of the Peruvian artist Fernando Bedoya, exhibited near the showcase where the two South American mummies are preserved, are intended to dialogue with the human findings as well as evoking the ancient surgical practices of the Incas, known as trepanation, which consisted of the perforation of the skull.</p> <p>Bedoya, through his ceramic replicas of ancient heads, imitates the act of trepanation by perforating twice the head. One hole is left open, following the sign of the surgical intervention, while the other hole is covered with a bottle cap of Coca-Cola, a brand of the modern global exploiter.</p> <p>On display are also four of his engravings from the &ldquo;Fardos&rdquo; series, where the use of collage and silkscreen techniques bind together like the bandaging of a mummy.</p>

opencc-by-4.0Apr 2022View details →
zenodo36/100

Slow practice and tempo management strategies in instrumental music learning: Investigating prevalence and cognitive functions

<p>This dataset corresponds to the publication of the same title and the following DOI:&nbsp;<a href="https://doi.org/10.1177%2F03057356211073481">https://doi.org/10.1177/03057356211073481</a></p> <p>The&nbsp;dataset contains 3 excel files. The file named&nbsp;QuantiativeSurveyDataClean_withKey contains all collected, unprocessed, cleaned data variables from the quantitative questionnaire. This includes all variables used for the principle components analysis. The file named&nbsp;ANOVA_data contains the variables used for the ANOVA analyses, and the file named regression_data contains the variables used for the regressions analyses. In all three files, descriptions of the variables can be found in the sheet titled &quot;key&quot;, and the data can be found in the sheet titled &quot;data&quot;.</p>

opencc-by-4.0Jun 2022View details →
zenodo36/100

Drop characteristics from the UNIGE calibration device for non-catching precipitation instruments

<p>These data are from the paper &quot;Calibration uncertainty of non-catching precipitation gauges&quot;, by Baire, Q. et al., accepted for publication on the journal Sensors. A rain drop generator, developed at the University of Genova, is presented in that paper using two high-precision syringe pumps, with a capacity of 20 and 1 ml (20 and 4.5 mm piston diameter, respectively), to produce water drops of the required volume. An electric field, generated by a high voltage trigger, allows releasing each single drop on demand. Each drop is generated at the tip of a suitable nozzle by dispensing the necessary volume to achieve the desired drop size and then detached by exploiting a 5 kV potential difference, where the water is negatively charged and attracted by a metal ring (positively charged), positioned just below the tip of the nozzle. By using different nozzles/needles and the proper syringe pump, drops of various size are produced.</p> <p>Validation of drop size measurements was obtained by weighing the total volume of samples of about 20 to 45 drops with a precision balance having a resolution of 0.001 g. Drops were released at 1.20 m above the center of the measurement plane of the camera.</p> <p>Results are summarized in Table 2 in the paper in terms of the average drop diameter obtained from the software and the balance, and their difference. Drop size characteristics as obtained from the photogrammetric system are included in the database for the generated sets of drops. A second set of tests was conducted using the photogrammetric system alone, without weighing the overall water volume. Statistics of the detected drop diameter and fall velocity are listed in Tables 3 and 4 in the paper, together with the number of released drops during each test, while the single drop size and fall velocity characteristics are included in the dataset.</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Multi-instrument observations of the ionospheric response to the 26 December 2019 solar eclipse over Indian and Southeast Asian longitudes

<p>Here, the impact of the 26 December 2019 solar eclipse on the equatorial and low latitude ionosphere has been investigated using ground and space-based observations over Indian and Southeast Asian longitudes. The high-resolution Ionosonde observations at Tirunelveli, GPS TEC observations from a chain of GPS receivers along and across the eclipse path, TIMED-SABER, and Ionospheric Connection Explorer (ICON) satellites were utilized to investigate the eclipse-induced variations in electron density and thermospheric cooling. We noticed a tremendous increase and decrease in the base height of the F-layer, resembling the nighttime Pre-Reversal Enhancement (PRE). Near the eclipse maximum, a strong blanketing sporadic E layer was observed at Tirunelveli with a top frequency of ~18 MHz for 1 hour and 26 minutes. Satellite traces (STs) and &lsquo;U&rsquo; shaped ionograms were noticed for the first time over Tirunelveli during eclipse maximum and end phases. The &lsquo;STs&rsquo; and &lsquo;U&rsquo; shaped traces indicate the presence of short-period gravity waves or TID type of wave perturbations over the Indian region. A maximum of ~5-7 TECU (30-40%) decrease in TEC is observed on the eclipse day for iisc, hyde, and tiru stations. Periodogram analyses of TEC data showed the presence of wavelike structures with periodicities of 18-24 minutes for different stations. Simultaneous observations from the ICON satellite showed an increase and decrease in hmF2 and NmF2 which matches well with the ionosonde observations from Tirunelveli. The temperature profiles from TIMED-SABER and ICON satellites showed a reduction and enhancement in the lower and upper E regions respectively.</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Experimental data: Low-velocity out-of-plane impact tests on double-wythe unreinforced brick masonry walls instrumented with optical measurements

<p>This dataset includes the results of laboratory impact tests conducted on natural-scale double-wythe unreinforced brick masonry walls. The walls were spanning vertically between two reinforced concrete slabs and were subjected to low-velocity drop-weight pendulum tests in which they were repeatedly hit until the opening of a breach in the center of the wall. The tests were instrumented with both hard-wired and optical measurements, the latter consisting of high-speed cameras and digital image correlation techniques. Investigated in these tests were the out-of-plane response of the walls and their capacity to resist the impacts. The axial load applied on the top of the walls was varied for two wall configurations and monitored throughout the tests to study the effect of arching on the failure mechanism produced and number of repeated hits needed to open the breach. Of interest was also the evidence of cracking, more specifically the way it initiated on the undamaged walls and next propagated upon consecutive hits.&nbsp;</p> <p>The data generated from the tests is made here available and documented to support further investigations on masonry structures subjected to extreme actions. The dataset includes&nbsp;four ZIP files, ordered from 01 to 05, along with an auxiliary PDF document describing the content and organization of the data.&nbsp;</p> <p>Test implementation and test results that are built upon this data are presented and discussed in the following research article:</p> <blockquote> <p><a href="https://www.sciencedirect.com/science/article/pii/S0734743X23001082?via%3Dihub">Godio M, Flansbjer M,&nbsp;Williams Portal N (2023) Low-velocity out-of-plane impact tests on double-wythe unreinforced brick masonry walls instrumented with optical measurements, International Journal of Impact Engineering</a></p> </blockquote> <p>To cite this data in your work please refer to the article.</p> <p>The Authors</p>

openother-atAug 2022View details →
zenodo36/100

Music tracks from Lakh with different instrument bodies

<p>The current demo of the dataset contains 10 audio multi-tracks generated with three different sound bodies from the Lakh MIDIs (https://colinraffel.com/projects/lmd/) . The full version contains 3599 tracks.</p> <table> <tbody> <tr> <td>E1.tar.gz</td> <td>The first corpus of 10 multi-tracks</td> </tr> <tr> <td>E2.tar.gz</td> <td>The second corpus of 10 multi-tracks</td> </tr> <tr> <td>E3.tar.gz</td> <td>The third corpus of 10 multi-tracks</td> </tr> <tr> <td>mix1.flac</td> <td>Track 1 from E1 (example)</td> </tr> <tr> <td>mix2.flac</td> <td>Track 1 from E2 (example)</td> </tr> <tr> <td>mix3.flac</td> <td>Track 1 from E3 (example)</td> </tr> </tbody> </table> <p>&nbsp;</p>

opencc-by-4.0Sep 2022View details →
zenodo36/100

Real-time imaging of thermally induced microcracks in granite with ultrahigh-temperature instrument

<p>An ultrahigh-temperature heating platform (HS1400G, Instec, Britain) on the optical microscope (BX51M, Olympus, Japan) was developed to observe the microcrack propagation of thin-section samples during heating in real time.</p> <p>Singapore Bukit Timah granite rock cores were examined in this study. The granite rock is widespread and one of the major rock formations in Singapore. It shows significant mechanical deterioration under the influence of heat. The rock sample was prepared as doubly polished thin sections of approximately 60 &mu;m in thickness for petrographic analysis and microthermometric observation. Before the experiment, the slide was heated with an alcohol lamp to dissolve the resin, and the thin-slice sample was removed and immersed in acetone to wash the surface glue to avoid affecting the observation.</p> <p>The granite sample was heated in the following heating process: heat from room temperature of 25℃ to 100℃ at a rate of 20℃/min; maintain the temperature for 5 min, as the thin-section sample is sufficiently small to generate a homogeneous thermal field quickly; heat to 100℃, 200℃, 300℃, 400℃, 500℃, 600℃, 700℃, 800℃ and 900℃ successively; finally, reduce the temperature to room temperature at a cooling rate of 20℃/min from the maximum temperature.</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Supplementary data for "Upward leaders from instrumented lightning rods competing to connect a downward leader during a lightning attachment process"

<p>High-speed videos of the lightning attachment to lightning rods observed by the Vision Reserch Phantom V12 and V711 cameras. See Instructions file to play the videos.</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Heinkel HE 111 Instrument Panel

Salvaged from the wreckage of a crashed WW2 German bomber in Hertfordshire by British Soldiers from 334 Searchlight Battery, Royal Artillery. Now located in the Imperial War Museum, London. Date: (Salvaged/crashed) 30th August 1940 https://www.iwm.org.uk/collections/item/object/30106874 102 photos taken in September 2020 (through glass) with a Sony a6000 and processed in Reality Capture. Source: Objaverse 1.0 / Sketchfab

opencc-bySep 2020View details →
zenodo36/100

Doncamatic (instrument)

An instrument that Gorillaz use in Doncamatics song. one of Plastic Beach's songs. https://en.wikipedia.org/wiki/Doncamatic Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2016View 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