The data life cycle is the sequence of stages through which data moves, from its creation or collection to its preservation, reuse, or deletion. It is a prescribed area for inquiry in IB Digital Society topic 3.1 Data and is shared by SL and HL.
The life cycle shows that data does not remain in one state or location. Different people, organizations, and digital systems interact with it at each stage, creating opportunities and dilemmas involving privacy, ownership, security, accuracy, and access.
| Stage | What happens |
|---|---|
| Creation or collection | Data is generated or gathered through sources such as sensors, transactions, surveys, or online activity. |
| Storage | Data is retained in databases, devices, servers, or cloud infrastructure. |
| Processing | Data is cleaned, organized, combined, or transformed into a usable form. |
| Analysis | Patterns and relationships are identified so that information can be produced. |
| Access and use | People or digital systems retrieve data to make decisions, provide services, or conduct research. |
| Preservation | Data is archived and maintained so that it remains accessible and reliable over time. |
| Reuse or deletion | Data may be used for a new purpose, anonymized, transferred, or securely erased. |
The cycle is not always a single fixed sequence. For example, reused data may be processed and analysed again, while inaccurate data may return to an earlier stage for correction. The exact stage labels can vary, but the central idea is that decisions made at one stage affect later stages.
A common misconception is that the data life cycle describes only storage. Storage is one stage; the model covers the entire movement and management of data.
In an IB exam, an outline question requires a brief account of the stages. For an explain or analyse question, connect stages to consequences for people and communities, such as how weak collection practices can produce biased analysis or how poor deletion procedures can create privacy risks.
