This page outlines the workflow for data tagging and review in our collaborative project.

Dataset Structure

Our dataset is stored Here and includes the following elements:

• dataset_v0:
  • reports: Audit report on C4
  • repos: Contest codebase
  • dataset.csv: Dataset Labeling Table

****Key Fields

• assigned_to: Assignee responsible for tagging the data.
• status: TODO, Done.
• reviewed_status: Needs Revision❗,Approved✅.
• comments: Comments or feedback during tagging and reviewing.

Dataset Labeling Workflow

Step 0: Understand the Tag Definitions

Before begin labeling, please read the 🔖 Tag Definitions carefully. This ensures consistent understanding and application of each tag across all contributors, helping to maintain high-quality and accurate labels throughout the dataset.

Step 1 : Start Labeling

• Open the 🗂️ Dataset to begin labeling.
• Start tagging the relevant entries.
• If you need to add a new tag, please refer 🥧 Collaboration and Decision Process for New Tags.

Step 2: After Labeling

• Change the Assign to field to your ID.
• Update the Status field to Done.