The data lifecycle can be divided into the following stages
The data lifecycle can be divided into the following stages:
Data generation: This is the stage where data is first recorded or created. In a laboratory environment, this may involve experimental measurements, recording of observation results, etc. The data integrity policy will require the use of appropriate instrument calibration, standardized operating procedures, and real-time recording measures at this stage to ensure the accuracy of the data.
Data processing: including data cleaning, conversion, and analysis. The data integrity policy will require the use of validated algorithms and software, and record all processing steps for tracking and review.
Data storage: Data should be securely stored to prevent unauthorized access, tampering, or loss. The data integrity policy will stipulate security measures such as data backup frequency, selection of storage media, access control, and encryption.
Data transmission: When data is transmitted between different systems or locations, encryption and other security measures should be taken to prevent data leakage or damage during transmission.
Data retrieval and utilization: Data should be easily accessible and usable when needed. The data integrity policy will require the establishment of data indexing and documentation to ensure data traceability and availability.
Data retention and destruction: Policies should specify the retention period of data and how to securely destroy data when it is no longer needed to comply with regulatory requirements and protect privacy.
The above is an introduction to the data lifecycle. Feel free to leave a comment in the comment section and let's explore together.