Update README.md

README.md

@@ -52,7 +52,7 @@ Escape underscores ("_") with a "\". Example: image\_RGB
 
 
 ### Dataset Description
-This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the Upper Waiākea Forst Reserve 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. 
+This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the [Upper Waiākea Forst Reserve in Hawaii](https://dlnr.hawaii.gov/forestry/frs/reserves/hawaii-island/upper-waiakea/). This dataset is intended for use in unsupervised audio analysis methods, classification using existing models, and other machine learning and ecology research purposes. 
 
 - **Curated by:** Namrata Banerji, Jacob Beattie, Hikaru Keebler, Kate Nepovinnykh
 <!-- Provide the basic links for the dataset. These will show up on the sidebar to the right of your dataset card ("Curated by" too). -->
@@ -92,13 +92,13 @@ All audio files are named (recorder_id)-YYYYMMDD-HHMMSS.wav inside a folder name
 recorder_id,card_code,point_id,HDD Path,Deployment Date,Retrieval Date,Latitude,Longitude
 
 **kipuka_metadata.csv**
-  - `recorder_id`: Unique identifier for each recorder
+  - `recorder_id`: Unique identifier for each recorder. Corresponds to the manufacturer ID found on each SongMeter recorder used.
   - `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
+  - `deployment_date`: Date the recorder was deployed
+  - `retrieval_date`: Date the recorder was retrieved.
+  - `latitude`: Latitude of recorder
+  - `longitude`: Longitude of recorder
 
 ### Data Splits
 Only one data split: `data`. If being used for training/testing/validation of models, splits must be made manually.
@@ -107,7 +107,9 @@ Give your train-test splits for benchmarking; could be as simple as "split is in
 -->
 
 ## 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.
+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. Audio was recorded in the [Upper Waiākea Forst Reserve in Hawaii](https://dlnr.hawaii.gov/forestry/frs/reserves/hawaii-island/upper-waiakea/), at the following sites:
+
+![Recorder Locations](https://cdn-uploads.huggingface.co/production/uploads/66f1eacc9be7680df701cdb8/yKDg20J05w_O_EDjt4XH6.png)
 
 ### Curation Rationale
 This dataset was created in order to study Hawaiian bird call variation across kipuka. Passive acoustic monitoring was done to capture Hawaiian bird calls across varying kipuka.
@@ -137,6 +139,10 @@ Things to consider while working with the dataset. For instance, maybe there are
 ### 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. 
 
+Additionally, the number of calls recorded for each species is likely long-tailed. Below is a chart depicting the number of occurrences of each species found during different portions of the day using source separation + Perch for species identification:
+
+![Species Count Birds](https://cdn-uploads.huggingface.co/production/uploads/66f1eacc9be7680df701cdb8/HOUXxVwVuQVY6Maj6_gf2.png)
+
 <!-- 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.-->
 
 <!-- For instance, if your data exhibits a long-tailed distribution (and why). -->