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.
103
datasets available to search
ShareScore release 0.9.0
Dataset results
103 results for “Soundscapes”
Marine soundscape variation reveals insights into baleen whales and their environment: a case study in central New Zealand
Open the record for dataset details and reuse information.
The soundscape of swarming: Proof of concept for a non-invasive acoustic species identification of swarming Myotis bats
Open the record for dataset details and reuse information.
Data and code from: At the intersection of soundscapes and roads: Quantifying anthrophony’s influence on wildlife crossing structure use
Open the record for dataset details and reuse information.
Time series methods for the analysis of soundscapes and other cyclical ecological data
Open the record for dataset details and reuse information.
Neotropical forest soundscapes with call identifications for katydids
Open the record for dataset details and reuse information.
Ecosystem services enhanced through soundscape management link people and wildlife
<p><span>Burgeoning urbanization, development and human activities have led to reduced opportunities for nature experience in quiet acoustic environments. Increasing noise affects both humans and wildlife alike. </span></p> <p><span>We experimentally altered human-caused sound levels in a paired study using informational signs that encouraged quiet behaviours in week-on, week-off blocks on the trail system of Muir Woods National Monument, California, USA to test if the soundscape influences both wildlife and human experiences. </span></p> <p><span>Using continuous measurements from acoustic recording units (n = 13) spatially distributed within the park, we found signs significantly lowered sound levels by approximately 1.2 decibels (A-weighted), thereby increasing listening area by </span><span>24% and bird availability by approximately </span><span>5.8% for every 1 decibel decrease. </span></p> <p><span>Visitor-intercept surveys (n = 537) revealed that our mitigation increased the number of birds perceived by visitors, rankings of soundscape pleasantness, and importantly, preferences for soundscape management. </span></p> <p><span>By lowering human-caused sound levels we created an acoustic environment equivalent to a ~21% reduction in visitors. The positive feedback cycle we describe may lead to increased conservation support in a time when the extinction of nature experience looms.</span></p>
Data for Less predictable global rhythms in human than wildlife contributions to soundscapes
<p>Dataset to the article: Somervuo, P., Roslin, T., Fisher, B.L. et al. Human contributions to global soundscapes are less predictable than the acoustic rhythms of wildlife. Nat Ecol Evol (2025). https://doi.org/10.1038/s41559-025-02786-5</p>
Ingleborough Soundscapes Project - Pilot Study Data from Colt Park Wood
<p>The audio recordings contained within the ‘Ingleborough Soundscape Project’ folders are free to download and may be copied, shared, modified, or commercialised, provided that the following written citation,<strong> Pheasant. R. J., (2021). Ingleborough Soundscape Project</strong> acknowledges the origin of the data.</p>
A collection of fully-annotated soundscape recordings from the Southwestern Amazon Basin
<p>This collection contains 21 hour-long soundscape recordings, which have been annotated with 14,798 bounding box labels for 132 different bird species from the Southwestern Amazon Basin. The data were recorded in 2019 in the Inkaterra Reserva Amazonica, Madre de Dios, Peru. This collection has partially been featured as test data in the 2020 BirdCLEF competition and can primarily be used for training and evaluation of machine learning algorithms.</p> <p><strong>Data collection</strong></p> <p>This acoustic data was collected at the Inkaterra Reserva Amazonica (ITRA) between January 14th and February 2nd, 2019, during the rainy season. ITRA is a 2 km<sup>2</sup> lowland rainforest reserve on the banks of the Madre de Dios river, approximately 20 km east of the frontier town of Puerto Maldonado. The region's extraordinary biodiversity is threatened by accelerating rates of deforestation, degradation, and fragmentation, which are driven primarily by expanding road networks, mining, agriculture, and an increasing population. The acoustic data from this site were collected as part of a study designed to assess spatio-temporal variation in avian species richness and vocal activity levels across intact, degraded, and edge forest, and between different days at the same point locations. </p> <p>Ten SWIFT recording units, provided by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology, were placed at separate sites spanning edge habitat, degraded forest, and intact forest within the reserve. These omnidirectional recorders were set to record uncompressed WAVE files continuously for the duration of their deployment, with a sampling rate of 48 kHz. The sensitivity of the used microphones was -44 (+/-3) dB re 1 V/Pa. The microphone's frequency response was not measured but is assumed to be flat (+/- 3 dB) in the frequency range 100 Hz to 7.5 kHz. The analog signal was amplified by 35 dB and digitized (16-bit resolution) using an analog-to-digital converter (ADC) with a clipping level of -/+ 0.9 V. For this collection, recordings were resampled at 32 kHz and converted to FLAC. Recorders were placed at a consistent height of approximately 1.5 m above the ground. To minimize background noise, all sites used for data analysis were located at a minimum distance of 450 m from the river.</p> <p><strong>Sampling and annotation protocol</strong></p> <p>A total of 21 dawn-hours, from 05:00-06:00 PET (10:00-11:00 UTC), representing 7 of the 10 sites on three randomly-selected dates, were manually annotated. Many neotropical bird species sing almost exclusively during the dawn hour, so this time window was selected to maximize the number of species present in the recordings. A single annotator boxed every bird call he could identify and ignored those that were too faint. Raven Pro software was used to annotate the data. Provided labels contain full bird calls that are boxed in time and frequency. The annotator was allowed to combine multiple consecutive calls of one species into one bounding box label if pauses between calls were shorter than five seconds. In this collection, we use eBird species codes as labels, following the 2021 eBird taxonomy (Clements list). Parts of this dataset have previously been featured in the 2020 BirdCLEF competition.</p> <p><strong>Files in this collection</strong></p> <p>Audio recordings can be accessed by downloading and extracting the “soundscape_data.zip” file. Soundscape recording filenames contain a sequential file ID, recording site, date, and timestamp in UTC. As an example, the file “PER_001_S01_20190116_100007Z.flac” has sequential ID 001 and was recorded at site S01 on Jan 16th, 2019 at 10:00:07 UTC. Ground truth annotations are listed in “annotations.csv” where each line specifies the corresponding filename, start and end time in seconds, low and high frequency in Hertz, and an eBird species code. These species codes can be assigned to scientific and common name of a species with the “species.csv” file. Unidentifiable calls have been marked with “????” and are included in the ground truth annotations. The approximate recording location and a short habitat description for all sites can be found in the “recording_location.txt” file.</p> <p><strong>Acknowledgements </strong></p> <p>We would like to thank the Inkaterra Association (ITA) staff for providing logistical support and excellent field station facilities, particularly Noe Huaraca, Dennis Osorio, and Kevin Jiménez Gonzales, who helped set up recorders. Noe Huaraca, John Fitzpatrick, Fernando Angulo, Will Sweet, Ken Rosenburg, and Alex Wiebe helped identify unknown vocalizations. Funding for equipment was provided by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology, with support from Innóvate Perú, CORBIDI, and the Inkaterra Association. Travel expenses were funded by the Cornell Lab of Ornithology.</p>
Supplementary material 1 from: Symes LB, Madhusudhana S, Martinson SJ, Kernan CE, Hodge KB, Salisbury DP, Klinck H, ter Hofstede H (2022) Estimation of katydid calling activity from soundscape recordings. Journal of Orthoptera Research 31(2): 173-180. https://doi.org/10.3897/jor.31.73373
Supplementary material 1 from: Symes LB, Madhusudhana S, Martinson SJ, Kernan CE, Hodge KB, Salisbury DP, Klinck H, ter Hofstede H (2022) Estimation of katydid calling activity from soundscape recordings. Journal of Orthoptera Research 31(2): 173-180. https://doi.org/10.3897/jor.31.73373
A framework for the quantification of soundscape diversity using Hill numbers
<p>This is the data underlying the case study and supplementary material described in Luypaert et al. (2021): A framework for the quantification of soundscape diversity using Hill numbers. </p>
Soundscape enrichment enhances recruitment and habitat building on new oyster reef restorations
<p>Biogenic marine soundscapes provide important navigational cues to dispersing larvae in search of suitable habitat. Yet, widespread habitat loss has degraded marine soundscapes and their functional role in recruitment. Habitat restorations can provide suitable substrate for habitat regeneration, such as reefs constructed to facilitate recruitment and habitat growth by oysters, but typically occur where soundscapes are degraded and recruitment limited. Enhancing marine soundscapes on newly constructed reefs using speaker technology may ensure sufficient recruitment to establish a trajectory of recovery for the desired habitat.</p> <p>Across two of the largest oyster reef restorations in Australia, we deployed speakers at four sites and at three times throughout the recruitment season to test whether soundscape enhancement could boost recruitment and habitat building by oysters. In the presence and absence of soundscape playback, we compared oyster recruitment rates to settlement panels across space and time, and oyster habitat formation on newly constructed boulder reefs.</p> <p>On the settlement panels deployed across the two reef restorations, soundscape playback significantly increased oyster recruitment at 8 of the 10 sites by an average (±1SE) 5.1 ± 1.9 times (5,281 ± 1,384 more larvae per m2), and by as much as 18 times.</p> <p>On boulders atop newly constructed reefs, where the restoration goal is for oysters to form three-dimensional habitat, the surface area covered by oysters after 5 months did not differ between speaker and control treatments. However, soundscape playback appeared to influence the earlier recruitment of oysters, resulting in significantly more large oysters per boulder that formed significantly more three-dimensional habitat building by an average 4.3 ± 1.2 times relative to non-speaker controls.</p> <p>Synthesis and applications. Our results show that using speakers to enhance marine soundscapes boosts the number of oyster recruits, resulting in more larger oysters that form more three-dimensional habitat atop reef restorations. In accelerating the formation of these vertical growth forms, which provide the ecological functions that motivate restoration efforts, the early application of speaker technology on new reef restorations may help steer ecological succession on a trajectory of desired habitat recovery, potentially reducing the substantial cost of ongoing intervention.</p>
A collection of fully-annotated soundscape recordings from neotropical coffee farms in Colombia and Costa Rica
<p>This collection contains 34 hour-long soundscape recordings, which have been annotated by expert ornithologists who provided 6,952 bounding box labels for 89 different bird species from Colombia and Costa Rica. The data were recorded in 2019 at two highly diverse neotropical coffee farm landscapes from the towns of Jardín, Colombia and San Ramon, Costa Rica. This collection has partially been featured as test data in the 2021 BirdCLEF competition and can primarily be used for training and evaluation of machine learning algorithms.</p> <p><strong>Data collection</strong></p> <p>Monitoring the avifauna of coffee farms is a useful tool to measure the impact of sustainability efforts in productive landscapes. Diverse bird communities provide services to coffee farms that are enhanced with increased tree cover (e.g. shade trees, wind breaks), and the protection of forest remnants within or in close proximity to coffee farms. Our limited knowledge on the relative contributions of different types of tree cover has incentivized the scientific community to collect bird data in coffee landscapes in order to correlate different management strategies with the presence or absence of target species using bioacoustics. To accomplish this, we collected a set of bird recordings to track the presence of target species on coffee farms. The annotated data set is currently being used to measure the impact of pesticide applications and other types of management practice (e.g. pruning) to test for differences in bird activity before and after one of these interventions. In addition, the bird call annotations help us train machine learning models that will help us monitor these farms in an automatic way.</p> <p>Soundscapes for this collection were recorded using SWIFT recorders, positioned 3m above the ground. We recorded 48kHz one-hour long sound files from 4:30 to 7:30 to capture the most active time frame of the avian dawn chorus. In the same way, we recorded from 16:00 to 19:00, to capture the second avian bioacoustics activity peak that occurs before sunset, and to include nocturnal species. </p> <p>All audio was unified, converted to FLAC, and resampled to 32 kHz for this collection. Parts of this dataset have previously been used in the 2021 BirdCLEF competition.</p> <p><strong>Sampling and annotation protocol</strong></p> <p>We subsampled data for this collection by randomly selecting recordings coming from different farm locations and dates.</p> <p>Using Raven Pro, annotators were asked to create a selection box around every bird call they could recognize, ignoring those that were too faint or unidentifiable. We allowed overlapping selections. Provided labels contain full bird calls that are boxed in time and frequency. Annotators were allowed to combine multiple consecutive calls of the same species into one bounding box label if pauses between calls were shorter than 5 seconds. We converted labels to eBird species codes, following the 2021 eBird taxonomy (Clements list). Unidentifiable calls have been marked with “????” and were added as bounding box labels to the ground truth annotations.</p> <p><strong>Files in this collection</strong></p> <p>Audio recordings can be accessed by downloading and extracting the “soundscape_data.zip” file. Soundscape recording filenames contain a sequential file ID, site ID, recording date, and timestamp in local time (Costa Rica: GMT-6; Colombia: GMT-5). As an example, the file “NES_001_S01_20190914_043000.flac” has sequential ID 001 and was recorded at site S01 on Sep 14th, 2019 at 04:30:00 local time. Ground truth annotations are listed in “annotations.csv” where each line specifies the corresponding filename, start and end time in seconds, low and high frequency in Hertz, and an eBird species code. These species codes can be assigned to the scientific and common name of a species with the “species.csv” file. Geographical coordinates of San Ramon and Jardín regions can be found in the “recording_location.txt” file. Recording location coordinates are not included due to data privacy.</p> <p><strong>Acknowledgements </strong></p> <p>Compiling this extensive dataset was a major undertaking, and we are very thankful to the domain experts who helped to collect and manually annotate the data for this collection. Specifically, we want to thank (in alphabetical order): Alejandro Quesada, José Castaño, Luis Parra. We also thank Carlos Gamboa-Venegas (RedCONARE, CeNAT), for providing technical assistance for information transfer.</p> <p>We would also like to acknowledge our funding source: Nespresso AAA Sustainable Quality<sup>TM</sup> Program.</p>
Effect of Soundscape on People With Dementia.
ClinicalTrials.gov study NCT04809545. IPD Sharing: NO. Countries: 1. Publications: 2.
A framework for the quantification of soundscape diversity using Hill numbers
Open the record for dataset details and reuse information.
Data from: The signal in noise: acoustic information for soundscape orientation in two North American tree frogs
Open the record for dataset details and reuse information.
Data from: The soundscapes of lakes across an urbanization gradient
Open the record for dataset details and reuse information.
Ecosystem services enhanced through soundscape management link people and wildlife
Open the record for dataset details and reuse information.
Soundscape enrichment enhances recruitment and habitat building on new oyster reef restorations
Open the record for dataset details and reuse information.
Chew Magna Reservoir Soundscape
<p>A one hour hydrophone recording of Chew Magna Reservoir, North Somerset, UK. </p> <p>The recording was made on the 25.06.20 between 15:00 - 16:00 BST. </p> <p>The recording was collected using a calibrated Wildlife Acoustics SM3H1 hydrophone (sensitivity: −165 dB re: 1V/μPa, frequency response: 2 Hz to 40 kHz: flat to +/- 1 dB) that was submerged at least 20 cm beneath the surface. The hydrophone was connected to a Wildlife Acoustics SM4BAT FS recorder set at maximum gain (12) with a sample rate of 192 kHz/32-bit. </p> <p>The raw .wav file has been uploaded without any effects or modification. </p> <p> </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.