annotaatioon

Annotaatioon is the process and product of adding notes, explanations, metadata, or other information to a primary object such as a text, image, dataset, or media file. In Estonian usage, annotaatioon covers both the act of annotating and the annotated result. The aims of annotation include improving understanding, aiding retrieval, enabling linkage to related content, or supporting analysis and processing.

Annotations take many forms. In texts, they appear as marginal notes, inline comments, footnotes, or endnotes. Metadata annotations describe content, structure, provenance, or rights information. In linguistics and computer science, annotations may label linguistic features, transcriptions, or semantic roles. In software, code comments annotate logic and design decisions. In data science and machine learning, labeling or tagging data (for example, images or text) prepares datasets for training and evaluation.

Methods and standards vary. Annotations may be created manually by experts or crowdsourced, or generated automatically by algorithms. Standards such as the TEI guidelines for textual annotation and the Web Annotation Data Model aim to improve interoperability and sharing across systems. Often annotations are stored separately from the primary content and linked through identifiers, provenance records, or structured metadata.

Applications span education, research, digital humanities, accessibility, journalism, and knowledge management. Well-documented annotations support search, comprehension, and reproducibility, while poorly documented or biased annotations can mislead or distort interpretation. Overall, annotaatioon is a foundational practice for enriching data and texts with contextual information.