Data Classification refers to the act of categorizing data according to its sensitivity and risk, ensuring it is handled appropriately according to policies and regulations. McMaster has adopted a Data and Information Classification policy that provides a framework for all institutional data. 

Purpose and Context:  

Classifications allow the University to assess the sensitivity level of data.Knowing the sensitivity level allows users to apply best practices related to privacy and IT security, protect sensitive information, and comply with legal and regulatory requirements. It also informs data handling practices such as storage, sharing, and retention. 

Why it matters:  

Classification drives key aspects of governance, such as access control, compliance checks, security measures, and risk management. Misclassified data can lead to data breaches, unauthorized access, or misuse. 

Practical application for users: 

• Always verify the classification of the data you are using. 

• Apply the classification framework when creating, sharing, or storing data. 

• Working with Data Stewards to ensure new data is classified correctly and updated if its sensitivity changes. 

• Understand that classification affects who can see or use data and under what circumstances/