Update readme + formatting

README.md

@@ -25,9 +25,9 @@ size_categories: 1K<n<10K
 
 
 ### 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.
+This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the [Pu'u Maka'ala Natural Area Reserve](https://www.neonscience.org/field-sites/puum) (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
+- **Curated by:** Kate Nepovinnykh, Fedor Zolotarev, Maksim Kholiavchenko
 <!-- Provide the basic links for the dataset. These will show up on the sidebar to the right of your dataset card ("Curated by" too). -->
 - **Repository:** [https://github.com/Imageomics/amakiki-project/tree/phenology]
 
@@ -38,24 +38,27 @@ This is a dataset containing unlabelled, unprocessed passive acoustic recordings
 
 
 ### 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](https://github.com/imageomics) and [ABC Global Center](https://www.abcresearchcenter.org/) during January 2025.
+This dataset contains passive acoustic recordings collected as part of the Experiential Introduction to AI and Ecology course through the [Imageomics Institute](https://imageomics.org) and [ABC Global Center](https://www.abcresearchcenter.org/) 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. 
+The dataset contains passive acoustic recordings from 9 recorders (6 along a phenology transect, 3 in koa restoration sites) located in the Pu'u Maka'ala Natural Area Reserve (PUUM).
+
+![Recorder Placement Map](figures/Metadata_labeled.png)
+*Map showing the locations of acoustic recorders at PUUM. The phenology transect includes 6 recorders placed along an 800m transect in forested habitat. Three additional recorders were placed in koa restoration sites of varying maturity: Open Grassland, Park Land, and Closed Canopy.*
 
 ## Dataset Structure
 ```
-/csv/
+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
+    phenology_sound_recorders.csv
+    pukiawe_detections_w_visits.csv
     weather.csv
-/phenology_data/
+koa_data/ # 3 recorders
     <recorder_id>/
 		  <recorder_id>_Summary.txt
 		  Data/
@@ -64,8 +67,8 @@ The dataset contains ~1623 hours of recording from 19 different recorders locate
 	  <recorder_id>/
 		  ...
 	  ...
-    phenology_metadata.csv
-/koa_data/
+    recorder_data_summary.txt
+phenology_data/ # 6 recorders
     <recorder_id>/
 		  <recorder_id>_Summary.txt
 		  Data/
@@ -74,51 +77,78 @@ The dataset contains ~1623 hours of recording from 19 different recorders locate
 	  <recorder_id>/
 		  ...
 	  ...
-    recorder_data_summary.txt
+    phenology_metadata.csv
 ```
+
+**File Descriptions:**
+
+- `recorder_data_summary.txt`: Summary statistics file for koa_data recordings, including file counts, total size in MB, count of files shorter/longer than 5 minutes, and total recording duration in hours for each recorder.
+
+- `check.py`: Python script that generates the `recorder_data_summary.txt` file by analyzing WAV files in the koa_data folder. Requires Python with standard libraries: `wave`, `contextlib`, `os`, `datetime`.
+
 ### 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.
+All audio files are named `<recorder_id>_YYYYMMDD_HHMMSS.wav` and included inside a folder named after the recorder ID. The audio files are within a `Data/` folder under the recorder ID folder (for koa_data) or directly under the recorder ID folder (for phenology_data). 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**
+Metadata for phenology recorders including deployment details and geographic coordinates.
+
+  - `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`: 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)
+
+**phenology_sound_recorders.csv**
+Detailed field installation data for phenology recorders, including exact coordinates, installation timing, and habitat information.
+
+  - `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`: 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
+  - `birds`: Species of birds observed or targeted at the location
+
+**pukiawe_detections_w_visits.csv**
+Camera trap detections of visitors to pukiawe plants, tracking visit patterns and species interactions. Includes image embeddings for classification.
+
+  - `filepath`: Path to the cropped detection image
   - `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)
+  - `bbox`: Bounding box coordinates for the detection
+  - `confidence`: Detection confidence score
+  - `class`: Detected class (e.g., Aves, Magnoliopsida)
+  - `timestamp`: Full timestamp of the image capture
+  - `common_name`: Common name of the plant species (e.g., pukiawe)
+  - `camera_id`: Identifier for the camera trap
+  - `species`: Identified bird species visiting the plant (if applicable)
   - `visit_number`: Sequential number for visits of the same object/animal
-  - ...
+  - `feature_0` to `feature_511`: 512-dimensional image embedding features
 
 **grouped_with_dist.csv**
+Spatial relationships between acoustic recorders and camera trap locations, with distances in meters.
+
   - `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**
+Bird detections from koa habitat recordings with single species identifications per detection.
+
   - `Label`: Species code or abbreviation (e.g., omao)
   - `Date`: Recording date
   - `Time`: Recording time
@@ -128,6 +158,8 @@ All audio files are named (recorder_id)-YYYYMMDD-HHMMSS.wav inside a folder name
   - `Time label`: Categorized time of day (e.g., Morning, Afternoon)
 
 **phenology_birds_single_species.csv**
+Bird detections from phenology study recordings with single species identifications and associated plant data.
+
   - `Label`: Species code or abbreviation (e.g., omao)
   - `Date`: Recording date
   - `Time`: Recording time
@@ -136,18 +168,52 @@ All audio files are named (recorder_id)-YYYYMMDD-HHMMSS.wav inside a folder name
   - `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
+**koa_birds_ss_multiple_species_001.csv**
+Bird detections from koa habitat recordings processed with sound separation, allowing for multiple species detections per recording segment.
+
+Same as koa_birds_single_species.csv with the addition of a `Probability` column specifying the probability assigned by Perch.
+
+**phenology_birds_ss_multiple_species_001.csv**
+Bird detections from phenology study recordings processed with sound separation, allowing for multiple species detections per recording segment.
+
+Same as phenology_birds_single_species.csv 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)
+Daily environmental measurements including temperature, rainfall, humidity, and vegetation indices for correlation with bird activity.
+
+  - `date`: Date of environmental measurements
+  - `rainfall_mm`: Daily rainfall measurement in millimeters
+  - `humidity_percent`: Relative humidity percentage
+  - `mean_temp_c`: Mean temperature in degrees Celsius
+  - `ndvi`: Normalized Difference Vegetation Index (measure of vegetation health/density)
+  - `coordinates`: Geographic coordinates (latitude/longitude)
+  - `min_temp`: Minimum temperature (°C)
+  - `max_temp`: Maximum temperature (°C)
+
+### Data Coverage and Distribution
+
+The following figures illustrate the temporal coverage of audio recordings and the distribution of detected bird species across different habitat types.
+
+**Recording Coverage:**
+
+![Phenology Audio Presence](figures/phenology_audio_presence_recorder.png)
+*Temporal coverage of audio recordings across the six phenology transect recorders, showing recording availability by date and recorder.*
+
+![Koa Audio Presence](figures/koa_audio_presence_recorder.png)
+*Temporal coverage of audio recordings across the three koa restoration site recorders.*
+
+**Species Detection Patterns:**
+
+![Phenology Species Count](figures/phenology_species_count_by_plant.png)
+*Number of unique bird species detected at phenology transect recorders, grouped by focal plant type. Comparison shows species counts before and after source separation processing.*
+
+![Koa Species Count](figures/koa_species_count_by_plant.png)
+*Number of unique bird species detected across koa restoration sites with different maturity levels (Open Grassland, Park Land, Closed Canopy).*
+
+**Community Dissimilarity:**
+
+![KL Divergence](figures/kl_divergence_heatmap.png)
+*Kullback-Leibler divergence heatmap showing bird community dissimilarity between recorders. Lower values (darker colors) indicate more similar bird communities, while higher values (lighter colors) indicate greater dissimilarity.*
 
 ### Data Splits
 Only one data split: `data`. If being used for training/testing/validation of models, splits must be made manually.
@@ -163,15 +229,15 @@ This dataset was created in order to study correlation Hawaiian birds and phenol
 <!-- Motivation for the creation of this dataset. For instance, what you intended to study and why that required curation of a new dataset (or if it's newly collected data and why the data was collected (intended use)), etc. -->
 
 ### Source Data
-These data were originally created by placing recorders in kipuka in the Upper Waiākea Forest Reserve on Hawaii island, recording bird calls.
-
-<!-- This section describes the source data (e.g., news text and headlines, social media posts, translated sentences, ...). As well as an original source it was created from (e.g., sampling from Zenodo records, compiling images from different aggregators, etc.) -->
+These data were collected at the Pu'u Maka'ala Natural Area Reserve (PUUM), a NEON field site located on the windward slope of Mauna Loa volcano at approximately 1700m elevation on Hawai'i Island. The site includes diverse habitats ranging from grasslands to tropical rainforest, with active koa-dominated forest restoration.
 
 #### 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. 
+Nine SongMeter Micro 2 audio recorders (Wildlife Acoustics) were deployed between January 23 and April 3, 2025. Six recorders were arranged along an 800-meter phenology transect in a forested area, while three additional recorders were installed at separate koa tree (\textit{Acacia koa}) restoration sites representing different maturity stages (Open Grassland, Park Land, and Closed Canopy).
+
+Each recorder was programmed to collect acoustic data daily: 30 minutes during the dawn chorus (6:00-7:00) and 15 minutes every hour from 7:00 to 19:00. Raw audio files were processed using Bird-MixIT, an unsupervised sound source separation model based on Mixture Invariant Training, to isolate individual bird vocalizations from overlapping environmental sounds. Separated sources were then classified using the Perch bird sound recognition model, retaining all Hawaiian species detections with probability >0.01. 
 
 #### Who are the source data producers?
-These data are produced by members of the ABC Global Center.
+These data were produced through a collaborative effort involving members of the AI and Biodiversity Change (ABC) Global Center, the Imageomics Institute, participants in the Experiential Introduction to AI and Ecology Course, and the National Ecological Observatory Network (NEON) team. NEON team members provided crucial support for recorder deployment and field logistics at the Pu'u Maka'ala Natural Area Reserve.
 <!-- This section describes the people or systems who originally created the data.
 
 Ex: This dataset is a collection of images taken of the butterfly collection housed at the Ohio State University Museum of Biological Diversity. The associated labels and metadata are the information provided with the collection from biologists that study butterflies and supplied the specimens to the museum.
@@ -179,20 +245,32 @@ Ex: This dataset is a collection of images taken of the butterfly collection hou
 
 
 ## Considerations for Using the Data
-<!--
-Things to consider while working with the dataset. For instance, maybe there are hybrids and they are labeled in the `hybrid_stat` column, so to get a subset without hybrids, subset to all instances in the metadata file such that `hybrid_stat` is _not_ "hybrid".
--->
 
 ### Bias, Risks, and Limitations
-<!-- These data are unlabelled, unprocessed, and may still contain significant noise due to some recorder's proximity to the road or footpaths.  Because of this, humans, cars, or helicopters may also be audible in some recordings.  -->
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. Could also address misuse, malicious use, and uses that the dataset will not work well for.-->
+**Temporal Coverage**: Recordings span January 23 - April 3, 2025, capturing late winter through early spring conditions. This temporal window may not represent year-round patterns in bird activity, particularly for migratory or seasonally variable species. Users should be cautious when extrapolating findings beyond this period.
+
+**Weather Effects**: Heavy rainfall events can introduce acoustic interference and reduce detection rates. The negative correlation between rainfall and bird detections observed in the data may reflect both actual behavioral changes and technical limitations of the classification pipeline during precipitation events.
+
+**Spatial Variation**: The six phenology transect recorders were placed near specific focal plant species, which may introduce vegetation-related bias in bird community observations. The three koa restoration sites represent different maturity stages but may not capture the full range of restoration conditions.
+
+**Classification Limitations**: Bird species classifications were generated using the Perch model with a probability threshold of 0.01, which may result in false positives for rare species or misclassifications in complex acoustic environments. The model was trained on directional recordings, and performance may degrade in passive monitoring contexts with overlapping vocalizations despite source separation preprocessing.
+
+**Incomplete Coverage**: Not all recorders operated continuously throughout the study period due to battery limitations, memory capacity, or equipment issues. See the audio presence figures in this dataset for detailed coverage by recorder and date.
 
-<!-- For instance, if your data exhibits a long-tailed distribution (and why). -->
+**Road and Human Noise**: Some recorders may be affected by nearby footpaths, roads, or human activity, potentially introducing non-biological acoustic interference.
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+**Data Validation**: For critical analyses, consider manually validating a subset of automated detections, particularly for rare or endangered species where accurate counts are essential.
+
+**Weather Integration**: When analyzing bird activity patterns, incorporate the provided weather data (rainfall, temperature, humidity) to distinguish behavioral responses from technical artifacts.
+
+**Habitat Context**: Use the provided metadata (recorder locations, focal plant associations, habitat classifications) to control for spatial and habitat-related variation in analyses.
+
+**Probability Thresholding**: The provided CSVs include probability scores for all detections. Users may wish to apply stricter probability thresholds (e.g., >0.1 or >0.5) depending on their tolerance for false positives versus false negatives.
+
+**Cross-Validation with Camera Traps**: Where available, acoustic detections can be cross-referenced with camera trap observations from nearby locations to validate species presence.
 
 ## Licensing Information
 This dataset is available to share and adapt for any use under the [CC BY 4.0](https://creativecommons.org/licenses/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. 
@@ -211,23 +289,19 @@ This dataset (the compilation) has been marked as dedicated to the public domain
 -->
 
 ## Citation
-[More Information Needed]
 
-**BibTeX:**
-<!--
-If you want to include BibTex, replace "<>"s with your info 
+If you use this dataset in your research, please cite it as:
 
-**Data**
-```​
-@misc{<ref_code>,
-  author = {<author1 and author2>},
-  title = {<title>},
-  year = {<year>},
-  url = {https://huggingface.co/datasets/imageomics/<dataset_name>},
-  doi = {<doi once generated>},
+**BibTeX:**
+```
+@misc{acoustic_puum_2025,
+  author = {Nepovinnykh, Kate and Zolotarev, Fedor and Kholiavchenko, Maksim},
+  title = {PUUM Passive Acoustic Recordings},
+  year = {2025},
+  url = {https://huggingface.co/datasets/imageomics/acoustic-PUUM},
   publisher = {Hugging Face}
 }
-```​
+```
 
 -for an associated paper:
 **Paper**
@@ -268,8 +342,8 @@ This material is based in part upon work supported by the National Ecological Ob
 
 <!-- [optional] Any other relevant information that doesn't fit elsewhere. -->
 
-## Dataset Card Authors 
-Kate Nepovinnykh, Ted Zolotarev, Maksim Kholiavchenko
+## Dataset Card Authors
+Kate Nepovinnykh, Fedor Zolotarev, Maksim Kholiavchenko
 
 
 ## Dataset Card Contact

csv/{Phenology sound recorders.csv → phenology_sound_recorders.csv}

@@ -1,4 +1,4 @@
-Microphone id,SD card,N,W,Elevation (ft),Camera trap sd card,Camera trap id,Installation time,Date(MM/DD/YYYY),Note,Swapped out date,,Birds
+microphone_id,sd_card,n,w,elevation_ft,camera_trap_sd_card,camera_trap_id,installation_time,date,note,swapped_out_date,habitat,birds
 2MM04716,4544,19.560777,155.315055,5548,,,13:07,01/23/2025,On the big spherical koa in the middle of the area of camera traps,1/27,Closed canopy,
 2MM04416,4543,19.55371,155.3148,5561,37A,37,13:26,01/22/2025,On an alapa ,,,small leaf kolea
 2MM04599,4546,19.558222,155.315583,5561,,,15:02,01/23/2025,Open area koa tree in the middle of camera traps ,1/27,Park land,

csv/weather.csv

@@ -1,4 +1,4 @@
-Date,Rainfall (mm),Humidity (%),MeanTemp (°C),NDVI,Coordinates,MinTemp,MaxTemp
+date,rainfall_mm,humidity_percent,mean_temp_c,ndvi,coordinates,min_temp,max_temp
 Jan-22,0.1,64.97,11.8,0.63,"Lat: 19.5618, Lon: -155.3148",6.1,17.6
 Jan-23,0.0,74.57,12.5,-,"Lat: 19.5618, Lon: -155.3148",6.8,18.2
 Jan-24,2.05,76.3,12.5,-,"Lat: 19.5618, Lon: -155.3148",7.3,17.7

phenology_data/phenology_metadata.csv

@@ -1,4 +1,4 @@
-Microphone id,SD card,N,W,Elevation (ft),Camera trap sd card,Camera trap id,Installation time,Date(MM/DD/YYYY),Note,Swapped out date
+microphone_id,sd_card,n,w,elevation_ft,camera_trap_sd_card,camera_trap_id,installation_time,date,note,swapped_out_date
 4716,4544,19.560777,155.315055,5548,,,13:07,01/23/2025,On the big spherical koa in the middle of the area of camera traps,1/27
 4416,4543,19.55371,155.3148,5561,37A,37,13:26,01/22/2025,On an alapa ,
 4599,4546,19.558222,155.315583,5561,,,15:02,01/23/2025,Open area koa tree in the middle of camera traps ,1/27