Update README.md

README.md

@@ -2,117 +2,203 @@
 license: cc0-1.0
 task_categories:
 - image-classification
+- object-detection
 language:
 - en
 tags:
 - animal
 - ecology
+- camera-trap
+- wildlife
+- biology
+- image
+- animals
+- CV
 size_categories:
-- 1K<n<10K
+- 10K<n<100K
+pretty_name: The Wilds Camera Trap Data
 ---
 
 # Dataset Card for The Wilds Camera Trap Data
 
 This dataset contains images and video captured from camera traps deployed at The Wilds safari park in Ohio during Summer 2025. It supports ecological monitoring, animal behavior analysis, and biodiversity studies.
 
+## Dataset Details
 
-## Dataset Description
+### Dataset Description
 
-- **Curated by:** Imageomics Institute, Ohio State University  
-- **Language(s):** EN
+- **Curated by:** Tanishka Wani, Vedant Patil, Rugved Katole, Bharath Pillai, Anirudh Potlapally, Ally Bonney, and Jenna Kline
+- **Language(s) (NLP):** EN
 - **Homepage:** [https://imageomics.org](https://imageomics.org)  
 - **Repository:** [https://github.com/Imageomics/naturelab](https://github.com/Imageomics/naturelab)  
 - **Paper:** TBD
 
-This dataset was created to support wildlife monitoring research using camera traps. Data were collected using various camera trap models, with each camera recording photos and videos in the wild. The images are organized by device and deployment session.
+This dataset was created to support wildlife monitoring research using camera traps. Data were collected using various camera trap models, with each camera recording photos and videos in the wild. The images are organized by site deployment session, providing valuable data for species detection, behavioral analysis, and biodiversity monitoring.
 
-## Dataset Details
 ### Supported Tasks and Leaderboards
 
+- **Image Classification:** Species identification from camera trap images
+- **Object Detection:** Animal detection and localization in natural environments
+- **Behavioral Analysis:** Activity pattern studies and wildlife monitoring
+- **Biodiversity Assessment:** Species richness and abundance estimation
+
 [No benchmarks currently available]
 
 ## Dataset Structure
 
+The dataset is organized hierarchically by site and deployment session:
+
+```
+/dataset/
+    camera_trap.txt
+    The_Wilds_Camera_Trap_Log2025-06-30_21_56_00.csv
+    The_Wilds_Camera_Trap_Log2025-07-04_20_18_08.csv
+    TW01-CT02/
+        SD02_20250630_20250703/
+            images/
+                <image files>
+            metadata.txt
+    TW02-CT03/
+        SD03_20250630_20250703/
+            images/
+                <image files>
+            metadata.txt
+    TW03-CT01/
+        SD01_20250630_20250703/
+            images/
+                <image files>
+            metadata.txt
+    TW04-CT04/
+        SD04_20250630_20250704/
+            101MEDIA/
+                <image and video files>
+            metadata.txt
+```
+
 ### Data Instances
 
-Each camera trap folder contains images in .jpg and .mp4 formats, along with metadata files describing the deployment context. Metadata are organized in Markdown files per deployment, providing key information such as camera settings, location, and environmental conditions.
+Each camera trap deployment folder (e.g., `TW01-CT02/SD02_20250630_20250703/`) contains:
+- **Images folder:** Contains .jpg image files captured by motion detection
+- **Video files:** .mp4 format videos in some deployments (stored in 101MEDIA for CT04)
+- **Metadata file:** `metadata.txt` with deployment information and camera settings
+
+Images vary in resolution and quality depending on camera model and environmental conditions. Videos are typically short clips (10 seconds) triggered by motion detection.
 
 ### Data Fields
 
-**metadata.md**  
-Each camera trap folder contains a `metadata.md` file with the following fields:
-  - **Camera Trap ID:** Unique device identifier (e.g., CT01)
-  - **Trap Model:** Model name (e.g., GardePro T5NG)
-  - **Camera Serial Number:** Manufacturer-assigned serial number
-  - **Site ID:** Location code where the camera trap was deployed (e.g., TW05)
-  - **Deployment Location Description:** Short text description of the site (e.g., "Near the waterhole")
-  - **GPS Coordinates:** Latitude and longitude in decimal format (e.g., 39.83537, -81.73842)
-  - **Deployment Date and Time:** When the camera was deployed (YYYY-MM-DD HH:MM, 24-hour format)
-  - **Retrieval Date and Time:** When the camera was retrieved (YYYY-MM-DD HH:MM, 24-hour format)
-  - **Camera Configuration:** Camera settings (e.g., Hybrid mode, Photo (4MP), Video (1080p, 10 sec))
-  - **Maintenance Notes:** Any configuration changes or issues during deployment
-  - **Observer:** Name or initials of the person who completed the metadata
+**metadata.txt** (found in each deployment folder):
+- **Camera Trap ID:** Unique device identifier (e.g., CT01, CT02, CT03, CT04)
+- **Trap Model:** Camera model name (e.g., GardePro T5NG, Trail Camera)
+- **Camera Serial Number:** Manufacturer-assigned serial number
+- **Site ID:** Location code where deployed (e.g., TW01, TW02, TW03, TW04)
+- **Deployment Location Description:** Text description of deployment site
+- **GPS Coordinates:** Latitude and longitude in decimal format
+- **Deployment Date and Time:** Camera deployment timestamp (YYYY-MM-DD HH:MM format)
+- **Retrieval Date and Time:** Camera retrieval timestamp (YYYY-MM-DD HH:MM format)
+- **Camera Configuration:** Settings including photo/video mode, resolution, trigger sensitivity
+- **Maintenance Notes:** Configuration changes or technical issues during deployment
+- **Observer:** Name or initials of person completing metadata
+
+**CSV Log Files:**
+- `The_Wilds_Camera_Trap_Log2025-06-30_21_56_00.csv`: Deployment log from June 30, 2025
+- `The_Wilds_Camera_Trap_Log2025-07-04_20_18_08.csv`: Retrieval log from July 4, 2025
 
 ### Data Splits
 
-This dataset has no training/validation/test splits. Data are organized by site and deployment session. Users may define their own splits depending on modeling goals.
+This dataset has no predefined training/validation/test splits. Data are organized by site (TW01-TW04) and deployment session. Users may create their own splits based on:
+- **Temporal splits:** Using deployment dates
+- **Spatial splits:** Using different site locations
+- **Camera-based splits:** Using different camera trap IDs
+
+Recommended approach depends on modeling goals and research questions.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-This dataset supports behavioral ecology research, the development of species detection models, and studies of animal activity patterns from camera trap images and videos.
+This dataset supports behavioral ecology research, development of automated species detection models, and studies of animal activity patterns. Camera traps provide non-invasive monitoring of wildlife behavior and are essential tools for conservation biology and ecological research.
 
 ### Source Data
 
 #### Data Collection and Processing
 
-Camera trap data were collected at The Wilds safari park using GardePro and Trail Camera models. Cameras were set up to capture both photos and videos based on motion detection and pre-set schedules. Upon retrieval, data were organized into folders by camera ID and deployment session.
+Camera trap data were collected at The Wilds safari park during summer 2025 using GardePro and Trail Camera models. Cameras were strategically deployed at four sites (TW01-TW04) using four different camera units (CT01-CT04). 
+
+Cameras were configured to capture both photos and videos based on motion detection. The deployment period was from June 30 to July 3-4, 2025. Upon retrieval, data were organized into folders by site and deployment session, with each deployment containing an images folder and metadata file describing camera settings and deployment context.
 
 #### Who are the source data producers?
 
-The dataset was collected and curated by researchers and students from the Imageomics Institute and Ohio State University in collaboration with conservation staff at The Wilds.
+The dataset was collected and curated by researchers and students from the Imageomics Institute and Ohio State University in collaboration with conservation staff at The Wilds safari park in Ohio.
 
 ### Annotations
 
 #### Annotation process
 
-No annotations are currently provided. Manual and AI-assisted labeling efforts are planned for future versions.
+No species or behavioral annotations are currently provided with this initial dataset release. Manual and AI-assisted labeling efforts for species identification, behavioral classification, and bounding box annotations are planned for future versions.
 
 #### Who are the annotators?
 
-N/A
+N/A - annotations will be added in future releases
 
 ### Personal and Sensitive Information
 
-The dataset includes GPS coordinates within a public conservation park. Endangered or sensitive species may be present, but the data do not identify them specifically. Spatial redaction has not been applied.
+The dataset includes GPS coordinates within The Wilds, a public conservation park in Ohio. Some images may contain endangered or sensitive species, though specific species identifications are not currently provided. Spatial coordinates have not been redacted as they fall within a public conservation area.
 
 ## Considerations for Using the Data
 
-Images and videos vary in quality due to weather conditions, motion blur, and camera settings. Some footage may be partially obstructed by vegetation or camera malfunctions. Additionally, sampling bias exists due to non-random camera placement at targeted ecological hotspots.
+Images and videos exhibit natural variation in quality due to weather conditions, lighting changes, motion blur, and camera settings. Some footage may be partially obstructed by vegetation, contain false triggers from wind-blown plants, or show camera malfunctions. The data represent a specific temporal window (summer 2025) and geographic location, which should be considered when generalizing findings.
 
 ### Bias, Risks, and Limitations
 
-- Camera traps were deployed purposively in areas likely to capture significant wildlife activity, leading to a potential bias in species representation.
-- Cameras were set to capture a range of species from small mammals to large ungulates, but may not capture rare or nocturnal species as effectively.
-- Data are limited to the specific deployment window (summer 2025) and may not reflect full seasonal biodiversity or behavioral patterns.
+- **Sampling bias:** Camera traps were deployed strategically at ecological hotspots rather than randomly, potentially overrepresenting certain species or behaviors
+- **Temporal limitations:** Data represent only a 3-4 day deployment period in summer 2025, limiting seasonal representation
+- **Detection bias:** Motion-triggered cameras may miss slow-moving species or have reduced detection rates for small animals
+- **Spatial bias:** Limited to four sites within The Wilds, may not represent broader regional wildlife patterns
+- **Technical limitations:** Variable image quality due to different camera models and environmental conditions
 
 ### Recommendations
 
-Use with ecological and methodological context in mind. Future versions may include additional seasonal data to complement this initial dataset.
+Users should consider the ecological and methodological context when analyzing this data. The dataset is best suited for proof-of-concept studies, algorithm development, and preliminary ecological analyses. For robust ecological conclusions, combination with additional seasonal data and broader spatial sampling would be beneficial.
+
+Future dataset releases may include additional deployment periods, seasonal data, and species annotations to address current limitations.
 
 ## Licensing Information
 
-This dataset is dedicated to the public domain under a [CC0 license](https://creativecommons.org/publicdomain/zero/1.0/). Users are encouraged to cite the dataset and acknowledge contributors.
+This dataset is dedicated to the public domain under a [CC0 license](https://creativecommons.org/publicdomain/zero/1.0/) for the benefit of scientific pursuits. Users are encouraged to cite the dataset and acknowledge contributors when using this data in research or applications.
 
 ## Citation
 
 **BibTeX:**
+
+**Data**
 ```bibtex
 @misc{thewilds_cameratraps_2025,
-  author = {Tanishka Wani, Vedant Patil, Rugved Katole, Bharath Pillai, Anirudh Potlapally, Ally Bonney, and Jenna Kline},
+  author = {Tanishka Wani and Vedant Patil and Rugved Katole and Bharath Pillai and Anirudh Potlapally and Ally Bonney and Jenna Kline},
   title = {The Wilds Camera Trap Data},
   year = {2025},
   url = {https://huggingface.co/datasets/imageomics/thewilds_cameratraps},
   publisher = {Hugging Face}
-}
+}
+```
+
+## Acknowledgements
+
+This work was supported by the [Imageomics Institute](https://imageomics.org), which is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under [Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240) (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning). 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.
+
+Special thanks to The Wilds safari park in Ohio for providing access to deployment sites and supporting this wildlife monitoring research.
+
+## Glossary 
+
+- **Camera Trap:** Motion-activated camera used for wildlife monitoring
+- **Deployment:** Period when a camera trap is installed and actively recording
+- **Site ID:** Geographic location identifier (TW01-TW04 in this dataset)
+- **Camera Trap ID:** Individual camera device identifier (CT01-CT04 in this dataset)
+- **SD Card Session:** Data collection period identified by SD card and date range
+
+## Dataset Card Authors 
+
+Tanishka Wani, Vedant Patil, Rugved Katole, Bharath Pillai, Anirudh Potlapally, Ally Bonney, and Jenna Kline
+
+## Dataset Card Contact
+
+For questions about this dataset, please open a discussion on the Hugging Face dataset page or contact the Imageomics Institute.