Update README.md

README.md

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-Here to put :
-Document data collection process.
-Identify compliance with applicable legislation/codes and your organisational policy alignment.
-Identify any risks; propose any required corrective action or possible future mitigation steps.
-Store dataset, notebook(s), and outputs according to organisational policies; document locations and versioning.
+<u>Data Collection Process</u><br>
+1. Data Source: Publicly available records fetched from the GitHub REST API.<br>
+2. Collection Method: Using Python-based "requests" library to fetch issue titles, descriptions and metadata.<br>
+3. Augmentation: The raw data was transformed into a structured format and saved locally as a .jsonl file before being uploaded to Hugging Face.<br>
+4. Tools Used: Use <b>Pandas</b> to manipulate the dataset, drop irrelevant data rows, and use <b>datasets</b> for final repository hosting.<p>
+
+<u>Compliance and policy alignment</u><p>
+1. Data Access and Classification Policy: The dataset is classified as "<b>Public</b>". This data is approved for public release as its disclosure causes no harm to the organization.<br>
+2. AI Use Policy: The use of the sentence-transformers model for indexing is "<b>Low-Risk</b>" AI use cases. It focuses on information retrieval rather than autlmated decision-making.
+
+<u>Risks</u><p>
+1. Data Breach - Low: There aren't personal information in the issues, also only few relevant columns are kept during data cleaning stage. <br>
+2. 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.
+3.