Update README.md

README.md

@@ -26,4 +26,122 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc0-1.0
+task_categories:
+- summarization
+language:
+- en
+tags:
+- code
+pretty_name: Github Issues - TensorFlow
+size_categories:
+- n<1K
 ---
+# Dataset Card for Github Issues - TensorFlow
+
+## Dataset Details
+
+### Dataset Description
+
+This dataset contains 50 open issues collected from the public TensorFlow GitHub repository. 
+Each record includes the issue ID, title, body text, creation date, anonymized user ID, 
+body length, and a flag indicating whether the issue mentions a bug. 
+The dataset has been structured for analysis and learning purposes.
+
+- **Curated by:** Lin Shi
+- **Language(s) (NLP):** English
+- **License:** Create Commons Zero v1.0 Universal (CC0 1.0)
+
+### Dataset Sources [optional]
+
+- **Repository:** https://github.com/tensorflow/tensorflow
+
+## Uses
+
+### Direct Use
+
+This dataset can be used for text analysis, summarization, or bug detection exercises.
+
+### Out-of-Scope Use
+
+Not intended for production software bug tracking or any commercial purpose. 
+User information has been anonymized.
+
+## Dataset Structure
+
+- **id**: int64, unique identifier for each issue
+- **title**: string, issue title
+- **body**: string, issue content
+- **created_at**: string, creation date
+- **user**: string, anonymized user ID
+- **body_length**: int64, number of characters in the body
+- **has_bug**: int64, 1 if the body mentions 'bug', otherwise 0
+
+- **Split:** train, 50 examples
+
+## Dataset Creation
+
+### Curation Rationale
+
+This dataset was created to provide a small, structured sample of GitHub issues for 
+learning and experimentation in text analysis and bug detection.
+
+### Source Data
+
+Collected via the GitHub API using `requests` library. Data was filtered and structured in a Pandas DataFrame.
+Usernames were anonymized for privacy.
+
+#### Data Collection and Processing
+
+The latest 50 open issues were retrieved from the TensorFlow GitHub repository. 
+Each issue's ID, title, body, creation date, and username were extracted. 
+Usernames were anonymized using a hashing method to protect privacy. 
+Additional derived fields include `body_length` and `has_bug`.
+
+#### Who are the source data producers?
+
+The source data producers are the contributors of the TensorFlow repository on GitHub. 
+No personal information beyond publicly available usernames (which were anonymized) is included.
+
+#### Annotation process
+
+No manual annotation was performed for this dataset.  
+The only derived labels are programmatically generated fields such as `body_length` and  
+`has_bug`, which were computed automatically using simple text-processing rules.  
+No annotation tools or human annotators were involved.
+
+#### Who are the annotators?
+
+There were no human annotators.  
+All derived fields were generated automatically through Python code written by the dataset curator (Lin Shi).
+
+#### Personal and Sensitive Information
+
+All usernames have been anonymized, and no sensitive or private information is included.  
+The dataset only contains publicly available GitHub issue text.  
+It is intended solely for educational use as part of a TAFE coursework assignment.
+
+## Bias, Risks, and Limitations
+
+The dataset only contains 50 open issues from one repository, so it is not representative 
+of all GitHub projects or issue types. Derived fields like `has_bug` are simplistic and may not fully capture actual bugs.
+
+### Recommendations
+
+Users should be aware that this dataset is for educational purposes only and should not 
+be used for production bug tracking or commercial analysis.
+
+**BibTeX:**
+
+No formal citation is available. Please cite the TensorFlow GitHub repository if needed.
+
+**APA:**
+
+No formal citation available. Refer to the TensorFlow GitHub repository for source data.
+
+## Dataset Card Contact
+
+For questions about this dataset, please contact:
+
+- **Name:** Lin Shi  
+- **Purpose:** Educational use only (TAFE coursework)