IB Digital Society 3.1 Data Key Definitions

The design of digital systems so that people with disabilities can use them, through features like screen readers, captions, and alternative ways to input. Well-designed systems widen inclusion, while poorly designed ones create new barriers.

Systematic, unfair outcomes produced by a computer system, often because the data it learned from under-represents some groups or encodes past inequality. In healthcare it can mean a tool works well for some patients and poorly for others.

A systematic error in an algorithm that produces unfair outcomes, often by favouring one group over another.

Datasets so large, fast-moving, and varied that ordinary tools cannot store or process them, usually described by the four Vs: volume, velocity, variety, and veracity.

A shared, append-only record made of blocks linked by cryptographic codes, so that any later tampering is easy to detect and the data stays trustworthy without a central authority.

Raw, unprocessed facts that lack context or meaning.

A systematic skew in a dataset, from how it was collected or what it left out, that makes any system built on it treat some groups unfairly.

The stages data passes through from the moment it is created, through storage, use, and preservation, to its eventual destruction.

Combining separate datasets about the same people or things so that together they reveal far more than any single dataset could on its own.

Replacing real values in a dataset with realistic but fake ones, so the data can be used for testing or analysis without exposing the real people behind it.

An automatic check that data entered is reasonable and in the correct format, such as rejecting a date of birth in the future or an email address with no @ sign.

A check that data entered actually matches the original, true source, such as typing a password twice or confirming a record against the real document.

The presentation of data in a visual form such as a chart, graph, or map, so that patterns, comparisons, and trends become easy for a person to see.

Large digital collection of data that serves a specified purpose.

Technologies, applications, and platforms that create, store, process, and distribute digital data and information. Smartphones, social media platforms, AI assistants, and robots are all digital systems.

Scrambling data using a key so that only someone with the correct key can read it, protecting the data both while it is stored and while it is being sent.

A machine learning application that identifies or verifies a person from an image or video by comparing patterns in their facial features against stored data.

A visual that combines data, images, and short text to tell a clear story about a topic for a general audience, prioritising quick understanding over completeness.

Processed data that is organized and structured to provide context and meaning.

The application of information to solve problems or make decisions.

Any data that can identify a specific person on its own or when combined with other data, such as a name, an address, a device ID, or a location trail.

Using patterns found in past data to estimate what is likely to happen in the future, from a weather forecast to a product recommendation to a risk score.

Data collected directly from the source for a specific purpose.

A person's ability to control what information about themselves is collected, who can see it, and how it is used.