Datasets:

NyssaW
/

github-issues

license: apache-2.0
task_categories:
  - text-classification
  - feature-extraction
language:
  - en
pretty_name: >-
  This dataset contains GitHub issues (and their comments) collected from  
  the   [huggingface/datasets](https://github.com/huggingface/datasets) public  
  repository.   It was created as part of an NLP pipeline exercise to  
  demonstrate data collection, augmentation, semantic search, and transformers  
  inference.
tags:
  - github
  - issues
  - nlp
  - text-classification
  - semantic-search
  - huggingface
size_categories:
  - 1K<n<10K

version: v1.0

Data Collection Process

Data Source: Publicly available records fetched from the GitHub REST API.
Collection Method: Using Python-based "requests" library to fetch issue titles, descriptions and metadata.
Augmentation: The raw data was transformed into a structured format and saved locally as a .jsonl file before being uploaded to Hugging Face.
Tools Used: Use Pandas to manipulate the dataset, drop irrelevant data rows, and use datasets for final repository hosting.

Compliance and policy alignment

Data Access and Classification Policy: The dataset is classified as "Public". This data is approved for public release as its disclosure causes no harm to the organization.
AI Use Policy: The use of the sentence-transformers model for indexing is "Low-Risk" AI use cases. It focuses on information retrieval rather than autlmated decision-making.

Risks

Data Breach - Low: There aren't personal information in the issues, also only few relevant columns are kept during data cleaning stage.
Model Bias - Medium: There is only one repo used in this dataset, which is very limited. Should have included multiple repo resources in the future.