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40 results for “Urban Mobility”

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zenodo32/100

TUT Urban Acoustic Scenes 2018 Mobile, Evaluation dataset

<p>TUT Urban Acoustic Scenes 2018 Mobile evaluation dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Recordings were made with three devices that captured audio simultaneously.&nbsp;The dataset contains in total 42 hours of audio.</p>

openother-ncJun 2018View details →
zenodo32/100

TAU Urban Acoustic Scenes 2019 Mobile, Development dataset

<p>TUT Urban Acoustic Scenes 2019 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Recordings were made with three devices that captured audio simultaneously. Each acoustic scene has 1440 segments (240 minutes of audio) recorded with device A (main device) and 108 segments of parallel audio (18 minutes) each recorded with devices B and C. The dataset contains in total 46 hours of audio.</p>

openother-ncMar 2019View details →
zenodo32/100

TAU Urban Acoustic Scenes 2019 Mobile, Evaluation dataset

<p>TAU Urban Acoustic Scenes 2019 Mobile, Evaluation dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>The dataset contains in total 30 hours of audio.</p>

openother-ncJun 2019View details →
zenodo32/100

Anonymised human location data for urban mobility research

Open the record for dataset details and reuse information.

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

TAU Urban Acoustic Scenes 2019 Mobile, Leaderboard dataset

<p>TAU Urban Acoustic Scenes 2019 Mobile, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul>

openother-ncMay 2019View details →
zenodo32/100

TAU Urban Acoustic Scenes 2023 Mobile, Evaluation dataset

<p>TAU Urban Acoustic Scenes 2023 Mobile evaluation dataset consists of 1-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Traveling by a tram - <em>tram</em></li> <li>Traveling by a bus - <em>bus</em></li> <li>Traveling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul>

openother-ncApr 2023View details →
ClinicalTrials.gov32/100

Promoting Community Mobility for Wellness in Older Adults in Urban Environments

ClinicalTrials.gov study NCT02916758. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
dryad32/100

Data from: Assessing the spatial ecology and resource use of a mobile and endangered species in an urbanized landscape using satellite telemetry and DNA faecal metabarcoding

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publicDec 2017View details →
dryad32/100

Data from: Patterns and limitations of urban human mobility resilience under the influence of multiple types of natural disaster

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publicJan 2017View details →
dryad32/100

Data from: Calling in sick: impacts of fever on intra-urban human mobility

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publicJun 2016View details →
dryad28/100

Urban specialization reduces habitat connectivity by a highly mobile wading bird

<p>Background</p> <p>Mobile animals transport nutrients and propagules across habitats, and are crucial for the functioning of food webs and for ecosystem services. Human activities such as urbanization can alter animal movement behavior, including site fidelity and resource use. Because many urban areas are adjacent to natural sites, mobile animals might connect natural and urban habitats. More generally, understanding animal movement patterns in urban areas can help predict how urban expansion will affect the roles of highly mobile animals in ecological processes.</p> <p>Methods</p> <p>Here, we examined movements by a seasonally nomadic wading bird, the American white ibis (Eudocimus albus), in South Florida, USA. White ibis are colonial wading birds that forage on aquatic prey; in recent years, some ibis have shifted their behavior to forage in urban parks, where they are fed by people. We used a spatial network approach to investigate how individual movement patterns influence connectivity between urban and non-urban sites. We built a network of habitat connectivity using GPS tracking data from ibis during their non-breeding season and compared this network to simulated networks that assumed individuals moved indiscriminately with respect to habitat type.</p> <p>Results</p> <p>We found that the observed network was less connected than the simulated networks, that urban-urban and natural-natural connections were strong, and that individuals using urban sites had the least-variable habitat use. Importantly, the few ibis that used both urban and natural habitats contributed the most to connectivity.</p> <p>Conclusions</p> <p>Habitat specialization in urban-acclimated wildlife could reduce the exchange of propagules and nutrients between urban and natural areas, which has consequences both for beneficial effects of connectivity such as gene flow and for detrimental effects such as the spread of contaminants or pathogens.</p>

opencc-zeroDec 2019View details →
zenodo28/100

Data from: Assessing urban-scale spatiotemporal heterogeneous metro station coverage using multi-source mobility data

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opencc-by-4.0Dec 2024View details →
zenodo28/100

DAS Urban Mobility Pattern Database

<p>DISCONTINUED!!!! New version:&nbsp;https://doi.org/10.5281/zenodo.8068608</p> <p>This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading.</p> <p>In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat).</p> <p>&nbsp;</p>

opencc-by-4.0May 2023View details →
dryad28/100

Urban specialization reduces habitat connectivity by a highly mobile wading bird

Open the record for dataset details and reuse information.

publicDec 2020View details →
zenodo24/100

DAS Urban Mobility Patterns Database

<p>This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading.</p> <p>In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat).</p> <p>New version of&nbsp;https://doi.org/10.5281/zenodo.7981219</p>

opencc-by-4.0May 2023View details →
zenodo24/100

DAS Urban Mobility Patterns Database

<p>This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading.</p> <p>In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat).</p> <p>New version of&nbsp;https://doi.org/10.5281/zenodo.7981219</p>

opencc-by-4.0May 2023View details →
ClinicalTrials.gov24/100

Increasing HIV Testing in Urban Emergency Departments Via Mobile Technology

ClinicalTrials.gov study NCT02154802. IPD Sharing: Not stated. Countries: 1. Publications: 0.

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

Heat Waves, Urban Heat Islands, and Wellbeing and Health: a Mobile Sensing Approach

ClinicalTrials.gov study NCT06850025. IPD Sharing: Not stated. Countries: 1. Publications: 0.

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

Fighting Climate Change: Urban Greennes, Active Mobility and Health Co-benefits.

ClinicalTrials.gov study NCT04742179. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
zenodo16/100

Original survey data of conventional office workers and mobile workers in urban third places about flexible work behaviour

<p>3 simular surveys targeting conventional office workers and mobile workers in Guangzhou's Starbucks and Guangzhou Library. They examine workers' spatio-temporal behaviour and attitudes on flexible working.</p>

restrictedcc-by-4.0Aug 2024View 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.
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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