Update README.md

Updated dataset card

README.md

@@ -5,111 +5,258 @@ language:
 pretty_name: The Wilds Drones
 task_categories:
 - image-classification
+- object-detection
+- video-classification
 tags:
 - biology
 - animals
 - conservation
+- drone
+- aerial
+- video
+- wildlife
+- CV
 size_categories:
-- 1K<n<10K
+- 10<n<100
 ---
+
 # Dataset Card for The Wilds Drones
 
 This dataset contains drone mission data collected at The Wilds safari park in Ohio during Summer 2025. 
-Manual drone flights captured video footage of specific sites at The Wilds to support ecological monitoring, animal behavior analysis, and object detection modeling.
+Manual drone flights captured video footage of specific sites at The Wilds to support ecological monitoring, animal behavior analysis, and aerial object detection modeling.
 
 ## Dataset Details
 
 ### Dataset Description
 
-- **Curated by:** Imageomics Institute, Ohio State University  
+- **Curated by:** Tanishka Wani, Vedant Patil, Rugved Katole, Bharath Pillai, Anirudh Potlapally, Ally Bonney, and Jenna Kline
 - **Language(s):** N/A  
-- **Homepage:** https://imageomics.org  
-- **Repository:** https://github.com/Imageomics/naturelab  
-- **Paper:** [More Information Needed]
+- **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 multimodal wildlife monitoring research. Bioacoustic data were collected using Wildlife Acoustics Song Meter Mini recorders deployed across multiple field sites. Files are organized by device and deployment window.
+This dataset was created to support multimodal wildlife monitoring research using unmanned aerial vehicle (UAV) technology. Drone missions were conducted using Parrot ANAFI drones to capture aerial video footage across The Wilds safari park. The dataset provides aerial perspectives for species detection, habitat assessment, and behavioral analysis that complement ground-based camera trap and bioacoustic monitoring efforts.
 
 ### Supported Tasks and Leaderboards
 
+- **Object Detection:** Animal detection and tracking from aerial video footage
+- **Video Classification:** Species identification and behavioral classification from drone videos
+- **Image Classification:** Frame-level analysis of wildlife and habitat features
+- **Wildlife Monitoring:** Population assessment and distribution mapping
+- **Habitat Analysis:** Landscape and vegetation assessment from aerial perspectives
+- **Behavioral Analysis:** Movement patterns and group dynamics from aerial viewpoints
+
 [No benchmarks currently available]
 
 ## Dataset Structure
 
+The dataset is organized by mission date and flight number:
+
+```
+/dataset/
+    20250701_parrotanafi_1/
+        metadata/
+            0914_2025-07-01T083438-0400_10D6BC_0018.json
+            File.jpg
+            mission_notes.txt
+        video_files/
+            VID_001.MP4
+            VID_002.MP4
+            VID_003.MP4
+            VID_004.MP4
+    20250703_parrotanafi_1/
+        metadata/
+            0914_2025-07-03T154754-0400_16A458_0019.json
+            0914_2025-07-03T155059-0400_54039C_001A.json
+            mission_notes_1.txt
+        video_files/
+            VID_001.MP4
+            VID_002.MP4
+            VID_003.MP4
+    20250703_parrotanafi_2/
+        metadata/
+            0914_2025-07-03T162104-0400_BF7B18_001D.json
+            mission_notes_2.txt
+        video_files/
+            VID_001.MP4
+            VID_002.MP4
+            VID_003.MP4
+    20250703_parrotanafi_3/
+        metadata/
+            0914_2025-07-03T165620-0400_D602EB_001F.json
+            mission_notes_3.txt
+        video_files/
+            VID_001.MP4
+            VID_002.MP4
+    20250703_parrotanafi_4/
+        metadata/
+            0914_2025-07-03T172345-0400_75DB7A_0021.json
+            mission_notes_4.txt
+        video_files/
+            VID_001.MP4
+            VID_002.MP4
+            VID_003.MP4
+    20250703_parrotanafi_5/
+        metadata/
+            0914_2025-07-03T172555-0400_0F0BAD_0008.json
+            mission_notes_5.txt
+            PNG image.png
+        videos/
+            VID_001.MP4
+            VID_002.MP4
+            VID_003.MP4
+            VID_004.MP4
+            VID_005.MP4
+```
+
 ### Data Instances
 
-Each .MP4 file is a field recording in format. File names follow a consistent timestamped naming scheme. Metadata are stored alongside each recorder folder in Markdown format.
+Each drone mission folder contains:
+- **Video files:** .MP4 format recordings captured during flight
+- **Metadata folder:** Contains telemetry data, flight path images, and mission notes
+
+**Mission Summary:**
+- **July 1, 2025:** 1 mission (4 video files)
+- **July 3, 2025:** 5 missions (16 video files)
+- **Total missions:** 6 drone flights
+- **Total video files:** 20 .MP4 recordings
+
+**File Counts by Mission:**
+- **20250701_parrotanafi_1:** 4 video files + 3 metadata files
+- **20250703_parrotanafi_1:** 3 video files + 3 metadata files (includes 2 telemetry JSON files)
+- **20250703_parrotanafi_2:** 3 video files + 2 metadata files
+- **20250703_parrotanafi_3:** 2 video files + 2 metadata files
+- **20250703_parrotanafi_4:** 3 video files + 2 metadata files
+- **20250703_parrotanafi_5:** 5 video files + 3 metadata files (includes PNG flight path image)
+
+**Video File Specifications:**
+- **Format:** .MP4 (H.264 encoding typical for Parrot ANAFI)
+- **Resolution:** Variable based on drone settings and mission requirements
+- **Frame rate:** Variable based on recording settings
+- **Duration:** Variable based on mission objectives and flight time
+
+**Filename Conventions:**
+- **Videos:** VID_00#.MP4 (sequential numbering within each mission)
+- **Telemetry:** 0914_YYYY-MM-DDTHHMISS-SSSS_XXXXXX_00##.json (timestamp and unique identifiers)
+- **Mission folders:** YYYYMMDD_parrotanafi_# (date and mission number)
 
 ### Data Fields
 
-**metadata.txt** 
-Each drone flight folder contains a .json file with the mission telemetry data, a .jpg with an image of the flight path, and a mission_notes.txt file with the following fields:
-  - Flight objectives: The primary goal of the mission
-  - Drone: Drone model name
-  - Date/Time: The date and approximate time of the mission
-  - Observations: Notable events or sights captured
-  - Lead pilot: The primary pilot controlling the drone
-  - Co-pilot: Any other pilots assisting with the mission
--->
-**
+**mission_notes.txt/mission_notes_#.txt** (found in each mission metadata folder):
+- **Flight objectives:** Primary goal of the mission
+- **Drone:** Drone model name (Parrot ANAFI)
+- **Date/Time:** Date and approximate time of the mission
+- **Observations:** Notable events or wildlife sightings captured
+- **Lead pilot:** Primary pilot controlling the drone
+- **Co-pilot:** Any other pilots assisting with the mission
+
+**Telemetry JSON files:**
+- **Flight telemetry data:** GPS coordinates, altitude, speed, camera angles
+- **Timestamp information:** Precise timing data for video synchronization
+- **Mission metadata:** Flight parameters and settings
+
+**Additional files:**
+- **Flight path images:** .jpg/.png visualization of drone flight routes (File.jpg, PNG image.png)
+- **Mission documentation:** Supporting materials for flight planning and execution
 
-This dataset has no training/validation/test splits. Data are organized by date and mission number. Users may define their own splits depending on modeling goals.
+### Data Splits
+
+This dataset has no predefined training/validation/test splits. Data are organized by mission date and flight number. Users may create their own splits based on:
+- **Temporal splits:** Using July 1 vs July 3 missions
+- **Mission-based splits:** Using different flight objectives or locations
+- **Video-based splits:** Random assignment of individual video files
+
+The concentrated data collection (2 days, 6 missions) limits temporal splitting options. Recommended approach depends on modeling goals and available data size requirements.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-This dataset supports biodiversity monitoring, behavioral ecology research, and the development of species detection and classification models from drone mission flight videos.
+This dataset supports aerial wildlife monitoring, behavioral ecology research, and development of automated species detection and tracking models from drone video footage. Aerial perspectives provide unique viewpoints for population assessment, habitat evaluation, and observation of animal behaviors that may be difficult to capture from ground-based sensors.
 
 ### Source Data
 
 #### Data Collection and Processing
 
-Missions were conducted at The Wilds safari park using Parrot ANAFI drones. Flight telemetry data and appropriate metadata were uploaded along with the video footage. No filtering, video processing, or annotation was applied.
+Drone missions were conducted at The Wilds safari park during July 1-3, 2025, using Parrot ANAFI unmanned aerial vehicles. Six missions were flown across two days with different objectives and flight patterns. 
+
+Missions were planned to complement ground-based sensor deployments (camera traps and bioacoustic monitors) and provide aerial coverage of key wildlife areas. Flight operations followed appropriate regulations and park protocols. Telemetry data and mission metadata were recorded alongside video footage. No video processing, filtering, or annotation was applied to preserve raw footage quality.
 
 #### 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 identification, object detection, or behavioral annotations are currently provided with this initial dataset release. Manual and AI-assisted labeling efforts for wildlife detection, species classification, and behavioral annotation 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 telemetry data and coordinates within The Wilds, a public conservation park in Ohio. Some video footage may contain endangered or sensitive species, though specific species identifications are not currently provided. Spatial coordinates have not been redacted as flights occurred within a public conservation area under appropriate permissions.
 
 ## Considerations for Using the Data
 
-Because missions were conducted in a non-random but systematic way, sampling bias may exist.
+Video quality varies based on weather conditions, lighting, flight altitude, and camera settings. The limited temporal scope (2 days) and small number of missions should be considered when developing models or drawing ecological conclusions. Some videos may contain motion blur, varying lighting conditions, or other technical artifacts typical of aerial videography.
 
 ### Bias, Risks, and Limitations
 
-- Species present at The Wilds are non-random and include both native and exotic species.
-- Missions were planned to compliment sensor placement, which followed a non-random, purposive design based on site features such as structural suitability for mounting and the anticipated likelihood of detecting ecologically relevant activity.
-- Missions were conducted in fair weather and only during a short summer window and may not capture full seasonal variation.
+- **Temporal limitations:** Data represent only 2 days in summer 2025, severely limiting temporal and seasonal representation
+- **Spatial bias:** Limited to specific areas within The Wilds, flight paths determined by mission objectives rather than systematic sampling
+- **Weather dependency:** Missions conducted only in fair weather conditions, may not represent challenging environmental conditions
+- **Flight restrictions:** Aerial access limited by regulations, wildlife disturbance considerations, and operational constraints
+- **Technical limitations:** Variable video quality due to different flight conditions, altitudes, and camera settings
+- **Species bias:** Detection capabilities vary by animal size, behavior, and habitat visibility from aerial perspectives
+- **Sample size:** Limited number of missions (6) and concentrated timeframe reduce dataset diversity
 
 ### Recommendations
 
-Use with ecological and methodological context in mind. Future data from different seasons or years may complement these recordings.
+Users should consider the limited temporal and spatial scope when analyzing this data. The dataset is best suited for proof-of-concept studies, algorithm development, and preliminary aerial wildlife monitoring analyses. The small sample size makes it more appropriate for technique development rather than robust ecological conclusions.
+
+Future dataset releases with additional missions, seasonal coverage, and diverse weather conditions would significantly enhance the dataset's utility for comprehensive aerial wildlife monitoring research.
 
 ## 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:**
-bibtex
+
+**Data**
+```bibtex
 @misc{thewilds_drones_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 Drones},
   year = {2025},
   url = {https://huggingface.co/datasets/imageomics/thewilds_drones},
   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 airspace access and supporting this aerial wildlife monitoring research.
+
+## Glossary 
+
+- **UAV/Drone:** Unmanned aerial vehicle used for remote sensing and monitoring
+- **Parrot ANAFI:** Specific drone model used for data collection
+- **Mission:** Individual flight operation with specific objectives
+- **Telemetry:** Flight data including GPS coordinates, altitude, and flight parameters
+- **Aerial Monitoring:** Wildlife observation and data collection from airborne platforms
+
+## 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.