Update README.md

README.md

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   - split: train
     path: data/train-*
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+Graphitti Issues and Pull Requests
+Dataset Summary
+
+This dataset contains issues, pull requests, and their associated comments from the UW Bothell Graphitti Project, a high-speed graph simulator. It includes metadata such as:
+
+    Issue/PR metadata: title, body, state (open/closed/merged), labels, milestone, timestamps, author, etc.
+
+    Comments: discussion threads associated with each issue or PR.
+
+    Pull request-specific details: lines changed, commits, merged status, etc.
+
+Use Cases:
+
+    Researchers can analyze open-source development practices, bug triaging, and collaboration dynamics.
+
+    Machine learning tasks like text classification (by label, severity, or topic), summarization (of long discussion threads), or sentiment analysis are all possible with these data.
+
+Supported Tasks and Leaderboards
+
+Potential tasks include:
+
+    Issue Classification / Triage
+    Classifying issues by type (bug, enhancement, question, etc.) or priority.
+
+    Topic Modeling
+    Discovering common themes or recurring issues in the project.
+
+    Summarization
+    Summarizing multi-turn issue or pull request discussions.
+
+    Sentiment Analysis
+    Analyzing the tone of contributors’ messages (helpful, frustrated, neutral, etc.).
+
+    Pull Request Analysis
+    Examining typical code contribution patterns or changes over time.
+
+There are no official leaderboards associated with this dataset.
+Languages
+
+Most text in this dataset is English, as GitHub issues and pull requests are typically written in English.
+Additionally, code snippets or references may appear in C++ (the Graphitti project’s primary language).
+Dataset Structure
+
+Each row in this dataset corresponds to either an Issue or a Pull Request from the Graphitti repository. Key fields include:
+
+    id: The numerical GitHub ID.
+
+    type: Indicates issue or pull_request.
+
+    title: Title of the issue or PR.
+
+    body: Main description text.
+
+    state: For example, open, closed, merged.
+
+    user: GitHub user metadata (e.g., username, user ID).
+
+    comments: A sequence of comments (string text).
+
+    created_at, updated_at, closed_at: Timestamps in ISO format.
+
+    Additional fields like labels, milestone, reactions, etc.
+
+Splits:
+According to the YAML front matter, the dataset is currently organized into a single train split containing 923 examples (issues/PRs). Users can choose to create validation/test splits as needed.
+Dataset Creation
+Curation Rationale
+
+The Graphitti project is a significant academic and open-source effort at UW Bothell, focusing on high-speed graph simulation. Collecting issues and pull requests offers insight into:
+
+    Common bugs, feature requests, or usage patterns.
+
+    Developer collaboration and communication.
+
+    Code quality and testing practices in real-world open-source projects.
+
+Source Data
+
+    Repository: UWB-Biocomputing/Graphitti on GitHub
+
+    Collection Method: The dataset was extracted via GitHub’s REST API (e.g., issues and pulls endpoints), capturing all available public issues and pull requests, along with their comment threads.
+
+Annotations
+
+    No additional manual annotations: The labels, states, and statuses are those used in the original GitHub repository.
+
+    Who are the annotators?: All metadata and labels are generated by GitHub or by Graphitti’s contributors.
+
+Considerations for Using the Data
+Social Impact
+
+    Can facilitate research on open-source community practices, academic software projects, and HPC (high-performance computing) collaboration patterns.
+
+    Offers an educational perspective on real-world software engineering processes.
+
+Potential Risks and Ethical Considerations
+
+    Personal Data:
+
+        GitHub usernames (and potentially user profiles, if included) could be considered personal data. While publicly available, re-publishing them in new contexts might raise privacy questions.
+
+        Users may inadvertently share personal information within issue discussions.
+
+    Code Snippets:
+
+        Issues or PRs may contain code under specific licenses (Graphitti is presumably under an open-source license). Ensure compliance with the original project’s license when reusing the code.
+
+    Toxic or Sensitive Language:
+
+        While not likely in an academic project, some discussions could contain rude or offensive language. Screening is recommended if you plan to use it for moderation or sentiment tasks.
+
+    GitHub Terms of Service:
+
+        This dataset is derived from content hosted on GitHub. Users should adhere to GitHub’s TOS regarding data usage and redistribution.
+
+Discussion of Biases
+
+    The content reflects a specific project’s topics (high-speed graph simulation), so it may not generalize to other domains.
+
+    Language usage, patterns of communication, and culture are shaped by a small academic open-source community.
+
+Additional Information
+Dataset Curators
+
+UW Bothell CS Team (and community contributors).
+If you contributed to Graphitti’s issues or pull requests, you may be represented in the dataset.
+Licensing Information
+
+    Data License: GitHub repository data is generally subject to GitHub Terms of Service.
+
+    Code License: Graphitti’s source code is licensed under [ADD LICENSE HERE] (e.g., MIT, BSD, GPL?).
+
+        If you redistribute code snippets, confirm it aligns with the project’s open-source license.
+
+Citation Information
+
+If you use this dataset, please cite:
+
+@misc{graphitti_issues_prs_2025,
+  title        = {Graphitti Issues and Pull Requests},
+  author       = {UW Bothell CS Team},
+  howpublished = {Hugging Face, https://huggingface.co/datasets/<your_dataset_slug>},
+  year         = {2025}
+}
+
+Contributions
+
+Special thanks to:
+
+    Justin Madison for dataset creation and curation.
+
+    Graphitti Maintainers and UW Bothell for hosting the original codebase and issue discussions.