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.
559
datasets available to search
ShareScore release 0.9.0
Dataset results
559 results for “Track data”
Simulated data for "Spot-On: robust model-based analysis of single-particle tracking experiments" (MATLAB format)
<p>See 10.5281/zenodo.834787 for a more complete description.</p>
Data for "Tracking the nearfield evolution of an initially shallow, neutrally-buoyant plane jet over a sloping bottom boundary"
<p>This folder contains all the data set for figures in the paper titled as "Tracking the nearfield evolution of an initially shallow, neutrally-buoyant plane jet over a sloping bottom boundary". </p>
YAP single particle tracking data accompanying the paper "YAP condensates are highly organized hubs".
<p><span><span>·<span> </span></span></span><span>Actual_masks: data files “DataAnalyzed” 1-28 (excluding 20) containing the original YAP masks in the variable “MaskIn”.</span></p> <p><span><span>·<span> </span></span></span><span>original_tracks: contains all the trajectories for each cell.</span></p> <p><span><span>·<span> </span></span></span><span>initial_final_nuclearMasks: contains initial and final manually segmented nuclear masks used to extrapolate nuclear masks by “interpolateNuclearMask”.</span></p> <p><span><span>·<span> </span></span></span><span>tracks: tracks pre-segmented manually to only include nuclear tracks (created by “trackDivider”).</span></p> <p> </p>
Raw data of the speed tracking of the KT2440 strain
Open the record for dataset details and reuse information.
Raw data of the speed tracking of the UWC1 strain
Open the record for dataset details and reuse information.
Raw data for TrackMate tracking output and R script for data analysis
Open the record for dataset details and reuse information.
Supplementary Data Sets for Machine Learning Tracks the Role of Slab-Derived Fluids in Large Igneous Province/CUGBZL
<p>Supplementary Dataset S1: All data collcted from both the GEOROC database and recent literature published in Chinese and English journals and books.<span></span></p> <p>Supplementary Dataset S2: Data after cleaning.</p> <p>Supplementary Dataset S3: Prediction results.</p>
Gładysz, K., Wrochna M., & Popek, R. (2024) Tracking Particulate Matter Accumulation on Green Roofs: A Comparative Study at Warsaw University Library - DATA
Open the record for dataset details and reuse information.
Objective African Easterly Tracks in Reanalysis Data using "QTrack"
<p>Objective track data for African Easterly Waves in reanalysis data (ERA5 and MERRA2) through 2024. Waves are tracked from June 1st through October 31st of each year. These tracks are produced using <a href="https://github.com/qlawton/QTrack">QTrack</a>, following the method described in <a href="https://doi.org/10.1175/MWR-D-21-0321.1">Lawton et al. (2022)</a>. Note that starting in 2024, tracks including both the ATL and EPAC basins will be included.</p> <p>AEW Track data is updated on a yearly basis, typically in January of the following year. However, because the year 2024 uses preliminary HURDAT data to determine "developing" AEW classification, users are cautioned that these designiations could change pending finialization of the 2024 HURDAT year. </p> <p><strong>Updated with Eastern Pacific Tracks:</strong> New easterly tracks have been produced through 2024 that included systems over the Eastern Pacific basin <em>in addition to </em>those over the Atlantic Ocean. These are stored as "ERA5_WITH_EPAC" and "MERRA2_WITH_EPAC". Please note that while the Atlantic Ocean tracks have been evaluated, the Eastern Pacific tracks have not. So use these data cautiously. </p> <p><strong>If you use this data for your research, please cite:</strong></p> <blockquote> <p>Lawton, Q. A., S. J. Majumdar, K. Dotterer, C. Thorncroft, and C. J. Schreck, 2022: The Influence of Convectively Coupled Kelvin Waves on African Easterly Waves in a Wave-Following Framework. Monthly Weather Review, 150(8), 2055-2072, <a href="https://doi.org/10.1175/MWR-D-21-0321.1" rel="nofollow">https://doi.org/10.1175/MWR-D-21-0321.1</a>.</p> </blockquote> <p>GitHub Repo for QTrack can be found here: <a href="https://github.com/qlawton/QTrack">https://github.com/qlawton/QTrack</a></p> <p>Installable Python Module can be found here: <a href="https://pypi.org/project/qtrack/">https://pypi.org/project/qtrack/</a></p>
GPS data and plotting codes for Remote Sensing paper titled Utilizing Seismic Station Internal GPS for Tracking Surging Glacier Sliding Velocity
<p>Data files (meteorological data, sattelite derived velocity time series, and seismic station GPS data) and plotting codes to reproduce the dataset and plots presented in the paper Gajek et al., Utilizing Seismic Station Internal GPS for Tracking Surging Glacier Sliding Velocity</p>
Data from: A new solution to an old riddle: elongate dinosaur tracks explained as deep penetration of the foot, not plantigrade locomotion
<p class="western"><span><span>The dinosaur track record features numerous examples of trackways with elongate metatarsal marks. Such "elongate tracks" are often highly variable and characterised by indistinct outlines and abbreviated or missing digit impressions. Elongate dinosaur tracks are well-known from the Paluxy River bed of Texas, where some had been interpreted as "man tracks" by </span><span>creationists</span><span> due to their superficially human-like appearance. The horizontal orientation of the metatarsal marks led to the now widely accepted idea of a facultative plantigrade, or "flat-footed", mode of locomotion in a variety of dinosaurian trackmakers small to large. This hypothesis, however, is at odds with the observation that elongate tracks do not indicate reduced locomotion speeds and increased pace angulation values, but instead are correlated with low anatomical fidelity. We here interpret elongate tracks as deep penetrations of the foot in soft sediment. Sediment may collapse above parts of the descending foot, leaving a shallow surface track that preserves a metatarsal mark. The length of a metatarsal mark is determined by multiple factors and is not necessarily correlated with the length of the metatarsus. Other types of posterior marks in dinosaur footprints, such as drag and slip marks, are reviewed.</span></span></p>
MaskUKF: An Instance Segmentation Aided Unscented Kalman Filter for 6D Object Pose and Velocity Tracking - Accompanying Data
<p>Dataset and evaluation data associated to the publication "MaskUKF: An Instance Segmentation Aided Unscented Kalman Filter for 6D Object Pose and Velocity Tracking".</p>
Publication data of How to improve data quality in dog eye tracking
<p>Publication data of How to improve data quality in dog eye tracking</p>
Data from: Synergistic use of UAV surveys, satellite tracking data and mark-recapture to estimate abundance of elusive species
<p>Estimating population abundance is central to many ecological studies and important in conservation planning. Yet the elusive nature of many species makes estimating their abundance challenging. Abundance estimates of sea turtles, marine birds and seals are usually made when breeding adults are ashore, while life-stages spent at sea, including as juveniles, are often poorly sampled. We used a combination of high-resolution satellite tracking (Fastloc-GPS), Unmanned Aerial Vehicle (UAV) surveys and catch-mark-recapture approaches to assess abundance of immature hawksbills (Eretmochelys imbricata) and green turtles (Chelonia mydas) in a tidal lagoon of the Chagos Archipelago (Indian Ocean). We captured, marked, and released 50 turtles (48 hawksbill and 2 green turtles) prior to UAV surveys and used satellite tracking data from 27 immature turtles (25 hawksbill and 2 green turtles) to refine the estimated numbers of marked turtles available for resighting and those likely to have emigrated from the study area. We estimated a total of 339 turtles in the lagoon with a density between 265 turtles km-2 at high water and 499 turtles km-2 at low water. Of these 84% were hawksbills and 16% were green turtles. These hawksbill densities are the highest reported amongst 17 foraging sites recorded around the world, likely reflecting successful long-term protection of turtles in the Chagos Archipelago. </p>
dynseq tracks data
<p>This record contains data and models relevant to the manuscript on dynamic sequence (dynseq) genome browser tracks. See https://github.com/kundajelab/dynseq-paper for more information.</p> <p>It contains data for 2 vignettes:</p> <p>1) <strong>beta globin:</strong> observed data for relevant experiments (bigwig), BPNet model TF/keras (h5) files trained on those experiments, predicted data from the models (bigwig) and importance scores (bigwig) from the models.</p> <p>2) <strong>SPI1 variant analysis: </strong>BPNet model TF/keras (h5) files trained GM12878 ATAC-seq and SPI1 ChIP-seq in GM12878 (ENCSR000BGQ), predicted data from the models (bigwig) and importance scores (bigwig) from the models for ref and alt alleles at rs5764238.</p>
Data from: Tracking trends in monarch abundance over the 20th century is currently impossible using museum records
[No abstract entered]
Eye-tracking data of translation evaluation
<p>Students and lecturers were asked to evaluate translations and select their favourite. On some of the slides, they were also provided with extrinsic information. </p> <p>Dataset includes project files, which need to be opened using GazePoint software. We have also included an Excel file which provides explanations on the participant background and selections. </p> <p> </p>
Training data for ship track detection machine learning algorithms
<p>The training data and labels used to train the linked machine learning algorithm</p>
Data and code for whole group tracking reveals that relatedness drives consistent subgrouping patterns in white-nosed coatis
<p>Three groups of wild white-nosed coatis were tracked with GPS collars between 2021 and 2023. Two groups (Galaxy and Trago) were tracked in Soberania National Park (SNP) (9° 12’ N, -79° 70’ W) and one group (Presidente) were tracked on Barro Colorado Island (BCI) (9° 16’ N, -79° 83’ W), Panama. Almost all group members were equipped with GPS collars that recorded one GPS fix every 10 minutes from 0600-1800 and 1 fix every hour from 1800-0600. Collars collected data for 15-21 days depending on the group. Adult males and one adult female from a different group were also collared during the Presidente collar period.</p> <p>Analysis was done in R, all scripts are in the coati_subgrouping_code folder, where there is a README file describing the code in more detail. Data are in the coati_subgrouping_data folder where there is a README describing the how the data are organised and structured. </p>
ECMWF IFS potential salinity and temperature data interpolated to ALAMO float positions. Results of tropical cyclone tracking algorithm for TC Irma, Florence, Teddy and Ida simulations with ECMWF IFS.
<p>ECMWF IFS potential salinity and temperature data interpolated to ALAMO float positions. The data is from forecasts of tropical cyclone Irma, Florence, Teddy and Ida performed at horizontal atmosphere resolutions of TCo1279, TCo2559, TCo3999, TCo7999 and ocean resolutions of eORCA025 and eORCA025.</p> <p> </p> <p>Data also contains the results of tracking these tropical cyclones in the ECMWF IFS simulations. </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.