Logistikon/acoustic-PUUM

Dataset Card for PUUM_passive_recordings

Dataset Details

Dataset Description

This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the Pu'u Maka'ala Natural Area Reserve (PUUM) in Hawaii. This dataset is intended for use in unsupervised audio analysis methods, classification using existing models, and other machine learning and ecology research purposes. Additionally, this dataset contains dataframes with the weather and bird detections.

• Curated by: Kate Nepovinnykh, Ted Zolotarev, Maksim Kholiavchenko
• Repository: [https://github.com/Imageomics/amakiki-project/tree/phenology]

Supported Tasks and Leaderboards

This dataset contains passive acoustic recordings collected as part of the Experiential Introduction to AI and Ecology course through the Imageomics Institute and ABC Global Center during January 2025.

This dataset is intended for use with unsupervised computer vision or acoustic machine learning models. No labels are provided, but recorder locations and recording timestamps are included, allowing for analysis of the relationship between ecological factors and variations in birdsong.

The dataset contains ~1623 hours of recording from 19 different recorders located in the Upper Waiākea Forest Reserve.

Dataset Structure

/csv/
    grouped_with_dist.csv
    koa_birds_single_species.csv
    koa_birds_ss_multiple_species_001.csv
    phenology_birds_single_species.csv
    phenology_birds_ss_multiple_species_001.csv
    Phenology sound recorders.csv
    Pukiawe_detections_w_visits.csv
    weather.csv
/phenology_data/
    <recorder_id>/
          <recorder_id>_Summary.txt
          Data/
              <recorder_id>_YYYYMMDD_HHMMSS.wav
              ...
      <recorder_id>/
          ...
      ...
    phenology_metadata.csv
/koa_data/
    <recorder_id>/
          <recorder_id>_Summary.txt
          Data/
              <recorder_id>_YYYYMMDD_HHMMSS.wav
              ...
      <recorder_id>/
          ...
      ...
    recorder_data_summary.txt

Data Instances

All audio files are named (recorder_id)-YYYYMMDD-HHMMSS.wav inside a folder named after the recorder id. Each recording starts at the time listed in the filename. Most recordings are 1 hour long, but some may be shorter. Recordings were taken using a SongMeter Micro 2.

Data Fields

phenology_metadata.csv

• recorder_id: Unique identifier for each recorder
• card_code: Unique identifier for SD card used in each recorder
• point_id: Unique identifier for each point where a recorder was placed
• Deployment Date: Date the recorder was deployed
• Retrieval Date: Date the recorder was retrieved.
• Latitude: Latitude of recorder
• Longitude: Longitude of recorder

Phenology sound recorders.csv

• Microphone id: Unique identifier for each acoustic recorder
• SD card: Identifier for SD card used in the recorder
• N: Latitude coordinate (decimal degrees)
• W: Longitude coordinate (decimal degrees)
• Elevation (ft): Elevation in feet where recorder was placed
• Camera trap sd card: Identifier for SD card used in nearby camera trap (if applicable)
• Camera trap id: Unique identifier for nearby camera trap (if applicable)
• Installation time: Time when the recorder was installed (HH:MM format)
• Date(MM/DD/YYYY): Date when the recorder was installed
• Note: Additional information about the location or installation
• Swapped out date: Date when the SD card was exchanged (if applicable)
• Habitat: Type of habitat where the recorder was placed (appears in an unnamed column)
• Birds: Species of birds observed or targeted at the location

Pukiawe_detections_w_visits.csv

• date: Date when the image was captured (YYYY-MM-DD format)
• common_name: Common name of the plant species detected (e.g., pukiawe)
• species: Scientific name of the species (if identified)
• visit_number: Sequential number for visits of the same object/animal
• ...

grouped_with_dist.csv

• recorder_id: Unique identifier for the acoustic recorder
• camera_ids: Array of identifiers for camera traps associated with the recorder
• camera_names: Array of plant names associated with each camera
• distances_m: Array of distances in meters between the recorder and plants

koa_birds_single_species.csv

• Label: Species code or abbreviation (e.g., omao)
• Date: Recording date
• Time: Recording time
• Common Name: Full common name of the bird species
• Recorder: Identifier for the acoustic recorder that captured the bird call
• Habitat: Type of habitat where the recording was made
• Time label: Categorized time of day (e.g., Morning, Afternoon)

phenology_birds_single_species.csv

• Label: Species code or abbreviation (e.g., omao)
• Date: Recording date
• Time: Recording time
• Common Name: Full common name of the bird species
• Recorder: Identifier for the acoustic recorder that captured the bird call
• Plant: Closest plant
• Time label: Categorized time of day (e.g., Morning, Afternoon)

koa_birds_ss_multiple_species_001.csv/phenology_birds_ss_multiple_species_001.csv Same as single species with the addition of a Probability column specifying the probability assigned by Perch

weather.csv

• Date: Date of environmental measurements
• Rainfall (mm): Daily rainfall measurement in millimeters
• Humidity (%): Relative humidity percentage
• MeanTemp (°C): Mean temperature in degrees Celsius
• NDVI: Normalized Difference Vegetation Index (measure of vegetation health/density)
• Coordinates: Geographic coordinates (latitude/longitude)
• MinTemp: Minimum temperature (°C)
• MaxTemp: Maximum temperature (°C)

Data Splits

Only one data split: data. If being used for training/testing/validation of models, splits must be made manually.

Dataset Creation

This dataset was compiled as part of the field component of the Experiential Introduction to AI and Ecology Course run by the Imageomics Institute and the AI and Biodiversity Change (ABC) Global Center. This field work was done on the island of Hawai'i January 15-30, 2025.

Curation Rationale

This dataset was created in order to study correlation Hawaiian birds and phenology in natural and restored habitats.

Source Data

These data were originally created by placing recorders in kipuka in the Upper Waiākea Forest Reserve on Hawaii island, recording bird calls.

Data Collection and Processing

Recorder locations were selected based on historic datasets (specifically data from Patrick Hart from UH Hilo). These data have significant overlap with historic data, while retaining only minimally sufficient overlap with recently collected data to allow for calibration between datasets.

Who are the source data producers?

These data are produced by members of the ABC Global Center.

Considerations for Using the Data

Bias, Risks, and Limitations

Recommendations

Licensing Information

This dataset is available to share and adapt for any use under the CC BY 4.0 license, provided appropriate credit is given. We ask that you cite this dataset if you make use of these data in any work or product.

Citation

[More Information Needed]

BibTeX:

Acknowledgements

This work was supported by both the Imageomics Institute and the AI and Biodiversity Change (ABC) Global Center. The Imageomics Institute is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under Award #2118240 (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning). The ABC Global Center is funded by the US National Science Foundation under Award No. 2330423 and Natural Sciences and Engineering Research Council of Canada under Award No. 585136. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or Natural Sciences and Engineering Research Council of Canada.

This material is based in part upon work supported by the National Ecological Observatory Network (NEON), a program sponsored by the U.S. National Science Foundation (NSF) and operated under cooperative agreement by Battelle.

Dataset Card Authors

Kate Nepovinnykh, Ted Zolotarev, Maksim Kholiavchenko

Dataset Card Contact

[email protected] [email protected] [email protected]