updating readme

README.md

@@ -88,19 +88,11 @@ mission:
 
 ### Dataset Description
 
-<<<<<<< HEAD
 - **Curated by:** Jenna M. Kline, Elizabeth Campolongo
 - **Language(s):** English (metadata and documentation)
 - **Homepage:** [KABR Project](https://imageomics.github.io/KABR/)
 - **Repository:** [kabr-behavior-telemetry](https://github.com/Imageomics/kabr-behavior-telemetry)
 - **Paper:** In preparation 
-=======
-- **Curated by:** Jenna M. Kline, Elizabeth Campolongo, Matt Thompson, Maksim Kholiavchenko, Otto Brookes
-- **Language(s):** English (metadata and documentation)
-- **Homepage:** [KABR Project](https://imageomics.github.io/KABR/)
-- **Repository:** [kabr-behavior-telemetry](https://github.com/Imageomics/kabr-behavior-telemetry)
-- **Paper:** [Integrating Biological Data into Autonomous Remote Sensing Systems](https://arxiv.org/abs/2407.16864)
->>>>>>> 6b503d0331e742072a14db5d7a7dc6bc465cc15d
 
 This dataset provides frame-level integration of drone telemetry (GPS position, altitude, camera settings), animal detection bounding boxes, and expert-annotated behaviors from aerial wildlife monitoring in Kenyan savannas. Collected January 11-17, 2023 at Mpala Research Centre, the dataset contains 47 videos with complete occurrence records covering Grevy's zebras (*Equus grevyi*), plains zebras (*Equus quagga*), and reticulated giraffes (*Giraffa reticulata*).
 
@@ -394,11 +386,8 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
 - Uncertain behaviors marked for expert review
 
 **Quality Control:**
-- Annotator training: 4 hours on example videos with expert feedback
-- Inter-annotator agreement: Not formally quantified (small expert team)
-- Review process: Senior ecologist (Kline) reviewed 100% of behavior labels
-- Difficult cases: Discussed in team meetings, consensus labels applied
-- Annotation confidence: Not explicitly scored
+- Training included intensive review of species-specific behavioral definitions with video examples, technical instruction on the CVAT interface, and practice annotation sessions until achieving greater than 90\% agreement with expert annotations
+- Weekly calibration sessions throughout the annotation period to address interpretation drift and maintain consistency across all annotators. These included random double-annotation of 10\% of mini-scenes to monitor inter-annotator reliability (achieving $\kappa=0.88$ for primary behavioral categories), weekly calibration sessions to address any annotation drift, and final expert review by field-experienced team members for all completed annotations. 
 
 **Annotation Coverage:**
 - Fully annotated: No (not all frames have animals)
@@ -409,9 +398,9 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
 #### Who are the annotators?
 
 **Annotator Team:**
-- Number of annotators: 3 primary, 2 reviewers
-- Expertise: Graduate students in ecology/computer science with wildlife identification training
-- Training provided: 4 hours initial training + ongoing feedback
+- Number of annotators: 10, including expert reviewers
+- Expertise: Research staff, professors, and students in ecology/computer science with wildlife identification training
+- Training provided: 2 hours initial training + ongoing feedback
 - Compensation: Academic credit and authorship
 
 **Subject Matter Experts:**
@@ -565,10 +554,9 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
 
 **Dataset:**
 ```bibtex
-@misc{kline2024kabr_telemetry,
-  author = {Kline, Jenna M. and Campolongo, Elizabeth and Thompson, Matt and
-            Kholiavchenko, Maksim and Brookes, Otto and Berger-Wolf, Tanya and
-            Stewart, Charles V. and Stewart, Christopher},
+@misc{kline2024kabr_behavior_telemetry,
+  author = {Jenna Kline and Maksim Kholiavchenko and Michelle Ramirez and Sam Stevens and Alec Sheets and Reshma Ramesh Babu and
+    Namrata Banerji and Elizabeth Campolongo and Matthew Thompson Nina Van Tiel and Jackson Miliko and Isla Duporge and Neil Rosser and Eduardo Bessa and Charles Stewart and Tanya Berger-Wolf and Daniel Rubenstein},
   title = {KABR Behavior Telemetry: Frame-Level Drone Wildlife Monitoring Dataset},
   year = {2024},
   publisher = {Hugging Face},
@@ -619,6 +607,20 @@ Namrata Banerji (The Ohio State University) - ORCID: 0000-0001-6813-0010
 Elizabeth Campolongo (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0846-2413
 Matthew Thompson (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0583-8585
 Nina Van Tiel (Eidgenössische Technische Hochschule Zürich) - ORCID: 0000-0001-6393-5629
+Daniel Rubenstein (Princeton University) - ORCID: 0000-0002-8285-1233
+- **Data Collection Team:**
+Jenna M. Kline (The Ohio State University)
+Michelle Ramirez (The Ohio State University)
+Sam Stevens (The Ohio State University)
+Reshma Ramesh Babu (The Ohio State University) - ORCID: 0000-0002-2517-5347
+Isla Duporge (The Ohio State University) - ORCID: 0000-0002-9873-1233
+Neil Rosser (The Ohio State University) - ORCID: 0000-0002
+- **Project Oversight and Guidance:**
+Elizabeth Campolongo (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0846-2413
+Matthew Thompson (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0583-858
+Tanya Berger-Wolf (Imageomics Institute, The Ohio State University) - ORCID: 0000-0002-1236-4153
+Charles Stewart (Rensselaer Polytechnic Institute) - ORCID: 0000-0002-5204-1862
+Daniel Rubenstein (Princeton University) - ORCID: 0000-0002-8285-1233
 
 
 **Conservation Partners:**