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30 results for “animal tracking”

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zenodo44/100

Data and Videos for Argos: a toolkit for tracking multiple animals in complex visual environments

<p>Original videos used and data generated for the article &quot;Argos: a toolkit for tracking multiple animals in complex visual environments&quot;.</p> <p>The data contains original videos used as input to the Argos Tracking tool, the generated raw tracks in Pandas-HDF5 format, and the corrected tracks after processing with Argos Review tool.</p> <p>It also includes a zip archive with ground truth tracks along with tracks detected from two videos by Argos and several other tracking tools for comparison using the HOTA metric organized in a folder structure suitable for the TrackEval tool.</p>

opencc-zeroMar 2021View details →
zenodo40/100

Data from: An Easily Compatible Eye Tracking System for Free-moving Small Animals

<p>These datasets are associated with human labled eye tracking datasets&nbsp;in DLC formate and pixel formate&nbsp;from the paper Huang et. al.,&nbsp;<em>An Easily Compatible Eye Tracking System for Free-moving Small Animals, </em>2021.<em>&nbsp;</em></p>

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

ALICE Pb-Pb Run 2 event display with red/blue tracks: animation

<div> <p>This animated event display shows tracks in a Pb-Pb event recorded during Run 2 of the LHC. Individual tracks are shown following a red/blue colour code according to their charge, and tracks expand outwards with a velocity calculated with their measured momenta and using the pion mass hypothesis. Outer detectors are not shown for simplicity.&nbsp;</p> </div>

opencc-by-4.0Sep 2024View details →
dryad40/100

Tracking small animals in complex landscapes: a comparison of localisation workflows for automated radio telemetry systems

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publicSep 2024View details →
zenodo36/100

Animated GIF of simulated plume and virtual flight tracks

<p>The animated GIF shows the dispersion of an exhaust plume modelled with WRF 3.8.1 as a large eddy simulation, as well as virtual cross sectional flight tracks, in the left panel. The right panel shows the emission rates retrieved by the virtual cross sectional overflights. Every two minutes a virtual measurement is performed. The daily solar irradiation causes a deep, convective boundary layer with turbulent plume dispersion within. In the nocturnal absence of solar irradiation, the boundary layer shrinks, leading to narrow, homogeneous plume dispersion, within a laminar flow.</p>

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

Dataset supporting the article "Megapixel camera arrays for high-resolution animal tracking in multiwell plates"

<p>IB and LF contributed equally.</p> <p>&nbsp;</p> <p>This deposition contains the supporting dataset for the article:</p> <p><strong>Megapixel camera arrays for high-resolution animal tracking in multiwell plates</strong></p> <p>Ida Barlow, Luigi Feriani,&nbsp;Eleni&nbsp;Minga, Adam McDermott-Rouse, Thomas J O&#39;Brien, Ziwei Liu, Maximilian Hofbauer, John R Stowers, Erik C Andersen, Siyu S Ding,&nbsp;Andr&eacute; EX&nbsp;Brown</p> <p>&nbsp;</p> <p>&nbsp;</p> <p><strong>Acknowledgements</strong>:</p> <p>This project has received funding from the European Research Council (ERC) under the European Union&rsquo;s Horizon 2020 research and innovation programme (Grant agreement No. 714853) and was supported by the Medical Research Council through grant MC-A658-5TY30. This work was supported by a Research Grant from HFSP (Ref.-No: RGP0001/2019). AMR was supported by a BBSRC CASE studentship part-funded by Syngenta.</p>

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

Evaluation of tracking devices and elicitation of wearability requirements for animal-centred biotelemetry in cats

<p>Thirteen cat participants wearing GPS&nbsp;devices were monitored through ethologically-informed observations, designed specifically to measure the behaviour of the animals with the biotelemetry tags. Here,&nbsp;findings from the behavioural analysis are presented.</p>

opencc-by-4.0May 2019View details →
dryad36/100

Integrating animal tracking datasets at a continental scale for mapping wildlife habitat

<div><em>Aim:</em></div> <div> </div> <div>The increasing availability of animal tracking datasets collected across many sites provides new opportunities to move beyond local assessments to enable detailed and consistent habitat mapping at biogeographic scales. However, integrating wildlife datasets across large areas and study sites is challenging, as species' varying responses to different environmental contexts must be reconciled. Here, we compare approaches for large-area habitat mapping and assess available habitat for a recolonizing large carnivore, the Eurasian lynx (Lynx lynx).</div> <div> </div> <div> <em>Location: </em>Europe</div> <div> </div> <div><em>Methods:</em></div> <div> </div> <div>We use a continental-scale animal tracking database (450 individuals from 14 study sites) to systematically assess modeling approaches, comparing (1) global strategies that pool all data for training vs. building local, site-specific models and combining them, (2) different approaches for incorporating regional variation in habitat selection, and (3) different modeling algorithms, testing nonlinear mixed effects models as well as machine-learning algorithms.</div> <div> </div> <div><em>Results:</em></div> <div> </div> <div>Both global and local modeling strategies allowed building transferable habitat models with overall similar predictive performance. Model performance was the highest using flexible machine-learning algorithms and when incorporating variation in habitat selection as a function of environmental variation. Our best-performing model used a weighted combination of local, site-specific habitat models. Our habitat maps identified large areas of suitable, but currently unoccupied lynx habitat, with many of the most suitable unoccupied areas located in regions that could foster connectivity between currently isolated populations.</div> <div> </div> <div><em>Main conclusions:</em></div> <div> </div> <div>We demonstrate that global and local modeling strategies can achieve robust habitat models at the continental scale and that considering regional variation in habitat selection improves broad-scale habitat mapping. More generally, we highlight the promise of large wildlife tracking databases for large-area habitat mapping. Our maps provide the first high-resolution, yet continental assessment of lynx habitat across Europe, providing a consistent basis for conservation planning for restoring the species within its former range.</div>

opencc-zeroOct 2023View details →
dryad36/100

Visual tracking of animals in three-dimensions using mobile handheld independent GoPro cameras and VSLAM software

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publicFeb 2021View details →
dryad36/100

Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat

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publicOct 2023View details →
dryad32/100

Data from - Ecological insights from three decades of animal movement tracking across a changing Arctic

<p>We provide here the data used in analysis of 3 test cases, presented in the manuscript "Ecological insights from three decades of animal movement tracking across a changing Arctic". We utilized the new Arctic Animal Movement Archive (AAMA), a growing collection of 201 standardized terrestrial and marine animal tracking studies from 1991–present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With three AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.  </p>

opencc-zeroOct 2020View details →
dryad32/100

Data from: From animal tracks to fine-scale movement modes: a straightforward approach for identifying multiple, spatial movement patterns

1. Thanks to developments in animal tracking technology, detailed data on the movement tracks of individual animals are now attainable for many species. However, straightforward methods to decompose individual tracks into high-resolution, spatial modes are lacking but are essential to understand what an animal is doing. 2. We developed an analytical approach that combines separately-validated methods into a straightforward tool for converting animal GPS tracks to short-range movement modes. Our three-step analytical process comprises: (1) decomposing data into separate movement segments using behavioural change point analysis; (2) defining candidate movement modes and translating them into non-linear or linear equations between net squared displacement (NSD) and time; and (3) fitting each candidate equation to NSD segments and determining the best-fitting modes using Concordance Criteria, Akaike's Information Criteria and other fine-scale segment characteristics. We illustrate our approach for three sub-adults, male wild boar Sus scrofa tracked at 15 min intervals over 4 months using GPS collars. We defined five candidate movement modes based on previously published studies of short-term movements: encamped, ranging, round trips (complete and partial), and wandering. 3. Our approach successfully classified over 80% of the tracks into these movement modes lasting between 5 and 54 hours and covering between 300 m to 20 km. Repeated analyses of GPS data resampled at different rates indicated that one positional fix every 3-4 h was sufficient for &gt;70% classification success. Classified modes were consistent with published observations of wild boar movement, further validating our method. 4. The proposed approach advances the status quo by permitting classification into multiple movement modes (where these are adequately discernable from spatial fixes) facilitating analyses at high temporal and spatial resolutions, and is straightforward, largely objective, and without restrictive assumptions, necessary parameterizations or visual interpretation. Thus, it should capture the complexity and variability of tracked animal movement mode for a variety of taxa across a wide range of spatial and temporal scales.

opencc-zeroDec 2016View details →
zenodo32/100

SpaceAnimal: Pose estimation and tracking dataset for multi-animal behavior analysis on the China Space Station

<p>Pose estimation and tracking dataset for multi-animal behavior analysis on the China Space Station. Scientific Data, 2025</p>

opencc-by-4.0Jul 2024View details →
zenodo32/100

Supplementary File 9; Table of total frequencies and mean frequencies for various sightings, tracks, spoor and other signs of wild animals per camp radial survey and per transect survey segment:

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opencc-by-4.0Jun 2024View details →
zenodo32/100

Supplementary File 8; Dot plots summarising the total frequencies of direct observations, tracks, spoor, and other signs of all wild animals detected in radial and transect surveys over the course of the study:

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opencc-by-4.0Jun 2024View details →
dryad32/100

Call for a critical review of widespread use of animal tracking devices

<p><span>Animal tracking has undergone a technological revolution providing insight into biological details that were impossible to address until now. However, the increasing ease of access to tracking devices (biologgers) may lead to trivializing this technology. Consequently, many projects may not extract as much scientific knowledge as possible and neglect the ethical duties towards the tagged animals. Here we demonstrate this process of trivialization empirically on a local and global scale and propose some guidelines to avoid it.</span></p>

opencc-zeroSep 2023View details →
dryad32/100

Call for a critical review of widespread use of animal tracking devices

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publicSep 2023View details →
dryad32/100

Data from: The role of social and ecological processes in structuring animal populations: a case study from automated tracking of wild birds

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publicMar 2015View details →
dryad32/100

Data from - Ecological insights from three decades of animal movement tracking across a changing Arctic

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publicNov 2020View details →
dryad32/100

Data from: From animal tracks to fine-scale movement modes: a straightforward approach for identifying multiple, spatial movement patterns

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publicMar 2018View details →

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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