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Text-fig. 7. a. Worn section through a horizontally bedded body-chamber and phragmocone, body-chamber showing oyster attached to inside of aperture as well as burrow mottling. Tape measure provides scale. b. Body-chamber and crushed phragmocone with body-chamber and phragmocone entirely filled with bioturbated matrix containing stringers of crinoid and molluscan debris. Flank of phragmocone encrusted by oysters. Tape measure for scale. c. Complex of Thallassinoides and Diplocraterion burrows associated with conch that has been eroded out by wave action. A few 'Ghostly' fragments of ammonite are also present. Original scope of the image approximately 400 mm. c. Verically embedded conch with largely intact septa and camera infilled with burrowed matrix containing crinoid debris. Tape measure for scale. in 'Cenoceras Islands' In The Blue Lias Formation (Lower Jurassic) Of West Somerset, Uk: Nautilid Dominance And Influence On Benthic Faunas
Text-fig. 7. a. Worn section through a horizontally bedded body-chamber and phragmocone, body-chamber showing oyster attached to inside of aperture as well as burrow mottling. Tape measure provides scale. b. Body-chamber and crushed phragmocone with body-chamber and phragmocone entirely filled with bioturbated matrix containing stringers of crinoid and molluscan debris. Flank of phragmocone encrusted by oysters. Tape measure for scale. c. Complex of Thallassinoides and Diplocraterion burrows associated with conch that has been eroded out by wave action. A few 'Ghostly' fragments of ammonite are also present. Original scope of the image approximately 400 mm. c. Verically embedded conch with largely intact septa and camera infilled with burrowed matrix containing crinoid debris. Tape measure for scale.
Text-fig. 8. a. Shell belonging to one flank of the conch a horizontally bedded individual with sveral large oysters attached to its underside indicating that the shell was either originally vertical or was flipped from one surface to the other by turbulance. Approximately 300 mm across. b. Crushed individual showing oysters encrusting both flanks of the conch. 250 mm in diameter. c. Wave-worn conch showing oysters attached to the umbilicus, the venter and possibly the inside of the body-chamber. Tape measure for scale. d. Flank of conch with crinoid debris and oysters spread around its periphery. Scope of image approximately 350 mm. in 'Cenoceras Islands' In The Blue Lias Formation (Lower Jurassic) Of West Somerset, Uk: Nautilid Dominance And Influence On Benthic Faunas
Text-fig. 8. a. Shell belonging to one flank of the conch a horizontally bedded individual with sveral large oysters attached to its underside indicating that the shell was either originally vertical or was flipped from one surface to the other by turbulance. Approximately 300 mm across. b. Crushed individual showing oysters encrusting both flanks of the conch. 250 mm in diameter. c. Wave-worn conch showing oysters attached to the umbilicus, the venter and possibly the inside of the body-chamber. Tape measure for scale. d. Flank of conch with crinoid debris and oysters spread around its periphery. Scope of image approximately 350 mm.
Text-fig. 9. a. Shorn-off, vertically embedded conch surrounded by layer of crinoid debris at level of planation of shell and with some debris within the conch at this level. Lateral width of body-chamber 80 mm. b. Example of ammonite that occurs rarely in the Main Cenoceras Bed. Note the poorly defined shell particularly on the outer whorl, suggesting partial dissolution. Tape measure for scale. in 'Cenoceras Islands' In The Blue Lias Formation (Lower Jurassic) Of West Somerset, Uk: Nautilid Dominance And Influence On Benthic Faunas
Text-fig. 9. a. Shorn-off, vertically embedded conch surrounded by layer of crinoid debris at level of planation of shell and with some debris within the conch at this level. Lateral width of body-chamber 80 mm. b. Example of ammonite that occurs rarely in the Main Cenoceras Bed. Note the poorly defined shell particularly on the outer whorl, suggesting partial dissolution. Tape measure for scale.
Fig. 2. Water level oscillation measured between August 1998 and July 2000 in Flow seasonality and fish assemblage in a tropical river, French Guiana, South America
Fig. 2. Water level oscillation measured between August 1998 and July 2000 at the Hydrological station on the Comté River. The numbers indicate the mean water level during the month of sampling.
Figure 1. Tooth measurements. A in Late Oligocene mesotheriids (Mammalia, Notoungulata) from Salla and Lacayani (Bolivia): implications for basal mesotheriid phylogeny and distribution
Figure 1. Tooth measurements. A, upper cheekteeth, SAL 280. B, lower cheekteeth, SAL 8. Scale bar = 1 cm.
Proccessed data for Trend Validation of Metabolic Models Against Measurements Using Indirect Calorimetry
<p>A cleaned data set used to validate metabolism models in a muscuskeletal modeling software.<br> The dataset contains 240 rows and 18 columns. </p> <p>Labels:</p> <ul> <li>AnyMet = Metabolic output by the modelling software. Calculated as the mean energy cost per repetition [J] .</li> <li>VynMet = Metabolic output by the indirect calorimetry system (Vyntus CPX). Calculated as the mean energy cost per repetition [J].</li> <li>rest_energy = total energy cost during rest [J]. Measured with Indirect caliometry</li> <li>rest_time = total time of rest [min]</li> <li>Work = Energy cost times the displacement per rep [J].</li> <li>watt = Work divided by total duration of a repetition [J/s]</li> <li>extension time = duration of the extension part of the movement [s]</li> <li>flexion time = duration of the flexion part of the movement [s]</li> <li>bw = bodyweight [kg]</li> <li>height [m]</li> <li>CV = coefficient of variation for the measured rest_energy. </li> <li>model = model type used for AnyMet. </li> <li>Subject </li> <li>Contraction = Contraction type performed</li> <li>intensity = Intensity to overcome created by the dynamometer. </li> <li>mech_watt_kg = mechcanical watt, watt divided by bodyweight</li> <li>any_met_watt_kg = watt pr kg: (AnyMet / bw) / (extension time + flexion time)</li> <li>vyn_met_watt_kg = watt pr kg: (VynMet / bw) / (extension time + flexion time)<br> <br> There is also a zip file containing the raw data from the dynanometer and the Vyntus PGE system.</li> </ul>
MAX-DOAS tropospheric NO2 column measurements in Islamabad, Pakistan (33°N, 73°E) from 2015 to 2019 and comparisons with OMI and TROPOMI satellite data
<p>This data presents an intercomparison of NO<sub>2</sub> retreival settings using Differential Optical Absorption Spectroscopy (DOAS) and those based on literature published over last 20 years. Moreover, it presents comparison of NO<sub>2</sub> Vertical Column Densities(VCD) obtained from ground based MAX-DOAS in Islamabad, Pakistan with satellite data from 2015-2019. MAX-DOAS has retrieved data at seven elevation angles i.e., 2, 4, 5, 10, 15, 30, 45. On the other hand, VCDs are in molecules per cm<sup>2</sup>. However, in order to collect NO2 dataset, DOASIS was used was used to obtain data from MAX-DOAS and further analyzed using QDOAS. Then geometric approximation was applied to obtain VCDs that are presented in this data set.</p>
Control Accuracy Measurement of a Mixed Reality Application for Digital Twin based Crane Operation
<p>The dataset corresponds the measurement that was implemented on the control accuracy of a mixed reality application for a digital twin based crane. </p> <p>The dataset contains two CSV files, one "Target" ", which is the selected target positions, and one "Measurement results", which is the actual crane position after moving to the target position. </p>
Zebra finch song and distance call amplitude measurements: A transmission experiment and observational transects in the natural environment
<p>Birdsong is typically seen as a long-range signal functioning in mate attraction and territory defense. Among birds, the zebra finch is the prime model organism in bioacoustics, yet almost exclusively studied in the lab. In the wild, however, zebra finch song differs strikingly from songbirds commonly studied in the wild as zebra finch males sing most after mating and in the absence of territoriality. Using data from the wild, we here provide an ecological context for a wealth of laboratory studies. By integrating calibrated sound recordings, sound transmission experiments and social ecology of zebra finches in the wild with insights from hearing physiology we show that wild zebra finch song is a very short-range signal with an audible range of about nine meters and that even the louder distance calls do not carry much farther (up to about fourteen meters). These integrated findings provide an ecological context for the interpretation of laboratory studies of this species and indicate that the vocal communication distance of the main laboratory species for avian acoustics contrasts strikingly with songbirds that use their song as a long-range advertisement signal.</p>
Astroclimate measurements on several points over Eastern hemisphere in 2-mm and 3-millimeter atmospheric transparency windows using tipping radiometer
<p>We are presenting results of the atmospheric propagation observations which our research group has been conducting since 2012. Over this time, we have gathered statistical data of atmospheric propagation over a number of sites which possibly can be used for radio astronomical observations in the millimetre and sub-millimetre bandwidths. The Zenith opacity was studied by the atmospheric dip method in the 3 mm and 2 mm atmospheric windows. The dataset is recommended to use for estimation of atmospheric propagation for the purpose of radio astronomy and telecommunications.</p> <p>The “tau-meter” (named MIAP-2) allows us to estimate an integral absorption by using the atmospheric dip method. The hardware includes a radiometric system comprising two self-contained radiometers operating in two different bands of 84-99 GHz (λ ~ 3 mm) and 132-148 GHz (λ ~ 2 mm), a rotary support, a control, and a firmware system. The radiometers work in modulation mode within 36 Hz modulation frequency. Floating mirror allows radiometer to scan the sky in the interval of 0 – 88.5 elevation angles (6 total). The output record contains the voltages of synchronous detector for each angle in 2 wavebands. The voltage is proportional to brightness temperature of the sky in corresponding waveband. (It has negative value for technical reasons.)</p> <p>The dataset contains raw data observed by radiometer: Local date and time, a several detector voltages on different elevation angles for 2 wavebands, as well as service information header. The first 6 columns contain optical depth calculated by old method and it’s no more used in data processing since the new algorithm has been invented in 2018.</p>
Dataset of RQA-based measures of a minimalist perceptual task using sonification
<p>Dataset of RQA-based measures of a minimal perceptual task using sonification</p>
Dataset for Agile 5G Network Measurements: Operator Benefits of Employing Aerial Mobility
<p>Dataset of paper "Agile 5G Network Measurements: Operator Benefits of Employing Aerial Mobility".</p> <p>The measurement data contains two different scenarios: Scenario 1 and Scenario 2, according to the paper. These two datasets include two different kinds of files: those related to measurements taken with a phone and those taken with a drone (UAV).</p>
Worldwide savanna monkey (Chlorocebus spp.) body measures
<p>Objectives: Direct comparative work in morphology and growth on widely dispersed wild primate taxa is rarely accomplished, yet critical to understanding ecogeographic variation, plastic local varia- tion in response to human impacts, and variation in patterns of growth and sexual dimorphism. We investigated population variation in morphology and growth in response to geographic variables (i.e., latitude, altitude), climatic variables (i.e., temperature and rainfall), and human impacts in the vervet monkey (<em>Chlorocebus</em> spp.).</p> <p>Methods: We trapped over 1,600 wild vervets from across Sub-Saharan Africa and the Caribbean, and compared measurements of body mass, body length, and relative thigh, leg, and foot length in four well-represented geographic samples: Ethiopia, Kenya, South Africa, and St. Kitts & Nevis.</p> <p>Results: We found significant variation in body mass and length consistent with Bergmann's Rule in adult females, and in adult males when excluding the St. Kitts & Nevis population, which was more sexually dimorphic. Contrary to Rensch's Rule, although the South African population had the largest average body size, it was the least dimorphic. There was significant, although very small, variation in all limb segments in support for Allen's Rule. Females in high human impact areas were heavier than those with moderate exposures, while those in low human impact areas were lighter; human impacts had no effect on males.</p> <p>Conclusions: Vervet monkeys appear to have adapted to local climate as predicted by Bergmann's and, less consistently, Allen's Rule, while also responding in predicted ways to human impacts. To better understand deviations from predicted patterns will require further comparative work in vervets.</p>
Dark Photon Exclusions from Existing Axion Haloscope Measurements
<p>Dark photon exclusions for polarized and unpolarized dark photons converted from axion measurements are each in a .mat file.</p> <p>Keys for the data are 'RBF_ueV', 'RBF_chi', 'UF_ueV', 'UF_chi', 'HAYSTAC_ueV', 'HAYSTAC_chi', 'ADMX_ueV', 'ADMX_chi', 'CAPP_ueV', and 'CAPP_chi' to obtain exclusions for dark photons for each of these experiments in the polarized and unpolarized cases. Each case has its own .mat file.</p> <p>The .py file is the Python code used to calculate cos<sup>2</sup>(theta), the square of the dot product between the dark photon polarization and the axis of the haloscope cavity in the slowly varying polarized case described in <a href="https://arxiv.org/abs/2104.09334">the associated manuscript</a>. The code shows how to calculate cos<sup>2</sup>(theta) using probability, taking the rotation of the earth into account for longer measurements. (If your computer is slow, you can use the find and replace function in your IDE to change all 'block=True' statements to 'block=False' and also change num_pts=50 instead of 500.)</p> <p>To use the .mat file format in Python, use a script like the following:</p> <pre>import matplotlib.pyplot as plt from scipy.io import loadmat mat_file = loadmat('haloscope_exclusions_unpolarized.mat') masses_in_ueV = mat_file['HAYSTAC_ueV'][0] chi_exclusion = mat_file['HAYSTAC_chi'][0] plt.figure() plt.semilogy(masses_in_ueV, chi_exclusion) plt.xlabel('Mass ($\mu$eV)') plt.ylabel('$\chi$') plt.title('HAYSTAC unpolarized dark photon exclusions') plt.show() </pre>
Data for: Analysis of Conformational Exchange Processes using Methyl-TROSY-Based Hahn Echo Measurements of Quadruple-Quantum Relaxation
<p>Raw experimental data used in associated publication. A full list of experiments is provided in the README.md file.</p>
Surface elevation (2012-2020) and ice thickness (2014-2020) datasets measured at Artesonraju Glacier, Cordillera Blanca, Perú
<p>We present a set of data of interpreted ice thickness and ice surface elevation of Artesonraju glacier.<br> The ice thickness was obtained by means of Ground Penetrating Radar (GPR) which was measured by Instituto Nacional de Investigación en Glaciares y Ecosistemas de Montaña (INAIGEM) and Autoridad Nacional de Agua (ANA). The years of ice thickness records include 2013, 2014, 2015, 2017, 2018, and 2020. On the other hand, the surface elevation points were obtained by means of automated total stations and mass balance stakes, integrally measured by ANA. The years of measurements are 2012, 2014, 2015, 2017, 2018, 2019, and 2020.<br> The results from GPR data show a maximum depth of 235±18 m and a decreasing mean depth of ranging from 134±18 m in 2013 to 110±18 m in 2020. Additionally, we estimate a mean ice thickness change rate of 4.2±3.2 m yr<sup>-1</sup> between 2012 and 2020 with GPR data alone, which is in agreement with the elevation change in the same period. The latter was estimated with the more accurate surface elevation data, yielding a change rate of -3.2±0.2 m yr<sup>-1</sup>, and hence, confirming a negative glacier mass balance. The datasets can be valuable for further analysis when combined with other data types, and as input for glacier dynamics modeling, ice volume estimations, and GLOF risk assessment.</p>
Code & Data from: Development of a low cost open-source ultrasonic device for plant height measurements
<p>We here provide code and data for the study "Development of a low cost open-source ultrasonic device for plant height measurements"</p> <p>Code:<br> - Arduino code (management of the electronic circuit): "Arduino_ultrasonic_sensor.ino"<br> - OpenSCAD code (3D-printing): "3DShells_ultrasonic_sensor.scad"<br> - R code (statistical analysis of field test): "Statistical_analysis.R"</p> <p>Data:<br> - "manual_vs_sensor_controlled.csv": this file contains the comparison between the ultrasonic device and the ruler in standardized laboratory conditions. It has three columns: "manual_value", the height value measured manually; "sensor_value", the height value obtained from the ultrasonic device; "height_range", the interval to which the height value belongs (we worked with 25 cm intervals).<br> - "manual_vs_ruler_field.csv": this file contains the comparison between the ultrasonic device and the ruler in field conditions. Plant height measurements were performed on 26 sorghum genotypes. The file has four columns: "Genotype", the id of the measured genotype; "rep" the replicate (3 plants were measured for each genotype); "manual_value", the height value measured manually; "sensor_value", the height value obtained from the ultrasonic device. When using the ruler, the operator spent 15 min and 23 s to complete all measurements in the field, and 3 min and 27 s to enter all data manually in a digital file. When using the sensor, the operator spent 10 min and 52 s to complete all measurements in the field, and manual transcription was not needed since all measurements are instantaneously saved on an SD card.</p> <p>More details on the experimental data can be found in the article "Development of a low cost open-source ultrasonic device for plant height measurements".</p> <p>We also provide a tutorial to explain how to build the ultrasonic-sensor ("tutorial.docx")</p>
Measuring hidden phenotype: quantifying the shape of barley seeds using the Euler characteristic transform
<p>Shape plays a fundamental role in biology. Traditional phenotypic analysis methods measure some features but fail to measure the information embedded in shape comprehensively. To extract, compare and analyse this information embedded in a robust and concise way, we turn to topological data analysis (TDA), specifically the Euler characteristic transform. TDA measures shape comprehensively using mathematical representations based on algebraic topology features. To study its use, we compute both traditional and topological shape descriptors to quantify the morphology of 3121 barley seeds scanned with X-ray computed tomography (CT) technology at 127 μm resolution. The Euler characteristic transform measures shape by analysing topological features of an object at thresholds across a number of directional axes. A Kruskal–Wallis analysis of the information encoded by the topological signature reveals that the Euler characteristic transform picks up successfully the shape of the crease and bottom of the seeds. Moreover, while traditional shape descriptors can cluster the seeds based on their accession, topological shape descriptors can cluster them further based on their panicle. We then successfully train a support vector machine to classify 28 different accessions of barley based exclusively on the shape of their grains. We observe that combining both traditional and topological descriptors classifies barley seeds better than using just traditional descriptors alone. This improvement suggests that TDA is thus a powerful complement to traditional morphometrics to comprehensively describe a multitude of 'hidden' shape nuances which are otherwise not detected.</p>
Agronomic performance of cultivar mixtures and pure stands of 8 winter wheat varieties, obtained from mixture field trials in Switzerland from 2021 to 2023, together with associated functional traits measurements
<p>This dataset contains agronomic performance data for 8 Swiss winter wheat cultivars, grown in pure stands and in mixtures at 3 locations in Switzerland during 3 growing seasons (2021-2023). The dataset has been used to analyse the effects of cultivar mixtures on agronomic performance and stability, which is published in <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.eja.2024.127504" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.eja.2024.127504</a>. </p> <p>The dataset contains notably grain yield, protein content, thousand kernel weight, specific weight, and Zeleny sedimentation value, as well as functional traits measured at flowering for each mixture and pure stand plot. </p> <p>The field trials were performed under the Swiss Extenso (low input) conditions, conducted by Agroscope and DSP. </p> <h3>Methods </h3> <p> <em>Field trials </em></p> <div>Field trials were set up over the course of three growing seasons – 2020/2021, 2021/2022 and 2022/2023 – in three sites across the Swiss Central Plateau. The experimental sites were located in Changins (46°19′ N 6°14′ E, 455m a.s.l), Delley (46°55′ N 6°58′ E, 494m a.s.l) and Utzenstorf (47°97′ N 7°33′ E, 483m a.s.l.). </div> <div>Experimental communities consisted of pure stand plots, 2-cultivars mixtures, and one plot with the 8 cultivars mixed. We sowed every possible combination of 2-cultivar mixtures, amounting to a total of 28 2-cultivar mixtures treatments, to which we added the 8-cultivar mixture. Each community was grown in a plot of 7.1 m<sup>2</sup> (1.5m∗4.7m). We used a complete randomized block design, with 3 replicates, the plots being randomized at each site within each block. Sowing was performed with a small plot drill (Wintersteiger plotseed TC). Density of sowing was 350 viable seeds/m<sup>2</sup>. For the mixtures, seeds were mixed beforehand at a 2 × 50 % mass ratio for 2-cultivars mixtures and 8 × 12.5 % for the 8-cultivar mixture. We chose this method of mixing as this is what is commonly done by farmers in Switzerland. Plots were sowed mechanically each autumn and fertilized with ammonium nitrate at a rate of 140 N/ha in 3 applications (40 N/ha at tillering stage/BBCH 22–29; 60 N/ha at the beginning of stem elongation/BBCH 30–31; 40 N/ha at booting stage/BBCH 45–47). The trials were grown according to the Swiss <em>Extenso</em> scheme, i.e. without any fungicide, insecticide, and growth regulator. Weeds were regulated twice or thrice per season with the application of herbicides commonly used in Switzerland.</div> <div> </div> <div><em>Ear density</em></div> <div> </div> <div>Before harvest, we manually harvested horizontal bands of 1.5 × 0.3 square meters per plot. The location of the band was randomly chosen but we avoided plot edges (i.e. the band was located at more than 0.5 m from the lower and upper edge of each plot). We counted the heads, and obtained ear density from the head counts.</div> <div> </div> <div><em>Trait measurements </em></div> <div> </div> <div>At flowering time, we randomly sampled 6 healthy leaves per plot. We immediately wrapped this leaf in moist cotton; this was stored overnight at room temperature in open plastic bags. The following day, we removed excess surface water on the leaf and weighted it to obtain its water saturated weight. This leaf was then scanned with a flatbed scanner (Perfection V39II, Epson), oven-dried in a paper envelope at 80°C for 72 hours, and subsequently weighed again to obtain its dry weight. Leaf Dry Matter Content (LDMC) was calculated as the ratio of leaf dry mass (g) to water saturated leaf mass (g). Using the leaf scans, we measured leaf area with the image processing software ImageJ. Specific Leaf Area (SLA) was calculated as the ratio of leaf area (cm2) to leaf dry mass (g).</div> <div> </div> <div><em>Phenology and height </em></div> <div> </div> <div>For each plot, we recorded the heading date as the day of the year, in which 50 % of the ears of the plot had fully emerged from the flag leaf. Plant height was measured in each plot at BBCH 59–75, by taking the average height in centimeters from the ground to the top of five random ears, excluding awns.</div> <div> </div> <p><em>Harvest and post harvest measurements</em></p> <p>At maturity, we harvested each plot with a combine harvester (Zürn 150, Schontal-Westernhausen, Switzerland). The harvested grains were dried when needed, weighed a first time, then sorted and cleaned by air and with a sieve cleaner, and subsequently weighted again. We measured hectoliter weight (test weight, HLW, kg/hl) and water content at the plot level using a Dickey-John machine (GAC 2100). Grain yield was subsequently standardized to 15 % of humidity. Protein content (% of dry matter) was measured at the site level with a near-infrared instrument (ProxiMate™, Büchi instruments). Thousand kernel weight (TKW, g) was measured at the plot level with a Marvin seed analyzer (GTA Sensorik, Neubrandenburg, Germany). Zeleny sedimentation value was measured by the laboratory of Delley Seeds and Plants. </p> <p> </p>
BLE RSS measurements database and supporting materials
<p>BLE RSS measurements database and supporting materials</p> <p>The database contains over 4,700 fingerprints of measurement from Bluettoth Low Energy (BLE) beacons. The beacons were Accent System's IBKS105, and the RSS were measured in two zone from the Universitat Jaume I, in Spain. One zone is an area among bookshelves that belong to the university library, for which beacons were configured to advertise at the -12 dBm power and the collection was performed using three smartphones: aBQ Aquaris X5 plus, a Samsung Galaxy S6 (SM-G920F) and a Samsung Galaxy A5 2017 (SM-A520F). The other zone is an office space area, for which beacons were configured at -4dBm, -12 dBm, and -20dBm and the collection was performed using the only Samsung Galaxy A5 smartphone. The supporting material includes Matlab® scripts to load and filter the desired data, and provides examples that depict common challenges for BLE RSS-based indoor positioning. The supporting material also includes the beacon deployment and the obstacles local coordinates.</p> <p>Citation request:</p> <p>Mendoza-Silva, G.M.; Matey-Sanz, M.; Torres-Sospedra, J.; Huerta, J. BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning. Data 2019, 4, 12</p> <p>Mendoza-Silva, G.M.; Matey-Sanz, M.; Torres-Sospedra, J.; Huerta, J. "BLE RSS meaurements database and supporting materials". Zenodo repository, DOI 10.5281/zenodo.1618692</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.