Glossary

The rules and requirements that determine who can access a dataset and how it can be used. These conditions are typically set by the data owner and depend on factors such as the level of detail in the data and any confidentiality or sensitivity concerns.

A computational model for simulating the actions and interactions of autonomous agents, which can be individual entities or groups like organisations, to understand the behaviour of a system and what governs its outcomes.

Aggregate or macro data are data about populations, groups, regions or countries. These are data that have been averaged, totalled or otherwise derived from the individual level data found in the survey datasets.

Outputs from AI models that appear confident and plausible but are completely fabricated or incorrect. 

The principle of making computational systems, AI, and automated decision-making processes understandable, accessible, and open to review.

In quantitative computational research, the analytical process is a systematic approach for examining data, assessing relationships, and exploring trends to derive meaningful insights. This process typically involves steps such as data discovery, data cleaning, modeling, and interpretation.

A set of rules and protocols enabling various software applications to communicate and securely exchange data. In research and data analysis, APIs help learners retrieve data from online platforms, databases, or other digital services for analysis. This facilitates hands-on experience with real-world data and supports skill development in data extraction and manipulation.

AI refers to the ability of computer systems to perform tasks typically associated with human intelligence, including learning, reasoning, problem-solving, perception, and decision-making.

Sample attrition refers to the loss of study units from a sample after an initial wave of data collection. For example, individuals who take part in a first wave of a longitudinal study dropping out at a sunsequent wave.

Data created by adding new records to an existing dataset in order to increase dataset size, address gaps, or improve the performance of machine learning models. These additional records are typically generated from or based on the original data and are designed to resemble or preserve its key characteristics. See also observed data and synthetic data.

Augmented reality refers to the real-time integration of digital information into a user’s environment. This technology superimposes digital content onto the real world, enhancing the user’s perception without replacing their view of reality.

The application of technology, programs, robotics, or processes to achieve outcomes with minimal human input.

A system that makes decisions and takes actions within an environment without direct human guidance, learning from rewards or penalties to improve its performance. For example, a self-driving car continuously decides how to navigate based on sensor input. See also Reinforcement learning.