text-and-data mining

Automated methods and processes for analyzing large corpora of text or data to extract patterns, information or insights; the Act establishes a limited exception permitting TDM for non‑commercial scientific research under defined conditions. The definition clarifies the lawful scope of automated analytical activities vis‑à‑vis intellectual property rules.

Automated techniques and processes used to analyze, extract, or infer information from large collections of text or data for purposes such as indexing, statistical analysis, or model training. In this context, TDM refers to activities that may implicate copyright reservations and are covered by the DSM Directive and the AI Act obligations on training data.

Text and Data Mining (TDM) is a crucial concept, referring to the automated analytical techniques used to analyze text and data in digital form to generate information which includes patterns, trends, and correlations. For AI development, TDM involves using vast datasets, often containing copyrighted material, to train AI models. The statement addresses the debate around a potential copyright exception for TDM, particularly for commercial purposes, and the mechanisms for rights holders to 'opt-out' of such use.

Refers to the automated analytical techniques aimed at analyzing text and data for patterns, trends, and other information, which is highly relevant for AI training data and raises questions about copyright exceptions and licensing.