annotere

Annotere is the act of adding annotations—notes, comments, or metadata—to a text, dataset, image, audio, or video. The resulting annotated material is intended to aid interpretation, facilitate search and retrieval, support analysis, or improve organization and collaboration. Annotations can be explanations, glosses, metadata tags, or structured labels that describe content, provenance, or relationships within the item being annotated.

Etymology and scope: the term derives from Latin annotare, meaning to mark up or note, and has entered many languages through historical usage. In everyday Norwegian and many other languages, annotere is used as a general verb for the process of annotating in both academic and digital contexts.

Domains and types: textual annotation accompanies manuscripts, scholarly editions, and digital texts with marginal notes, glosses, or scholarly tags. In linguistics and corpus linguistics, annotations include part-of-speech tagging, syntactic structure, discourse labels, and semantic roles. In data science and machine learning, labeling or tagging data (images, audio, video) creates training and evaluation datasets. In media and education, image or video annotations identify objects, regions, or events, while document annotations add comments or highlights in PDFs and e-books.

Methods and standards: annotation can be manual, expert-driven, or crowdsourced, often guided by formal annotation guidelines. Inter-annotator agreement is used to assess reliability. Standards and models—such as the Web Annotation Data Model, Open Annotation, or IIIF for images, and TEI for textual markup—facilitate interoperability and reuse of annotated data.

Tools and applications: common tools include web-based annotators, image/video labeling platforms, and linguistic annotation software. Annotated resources support research, education, digital humanities, software development, and accessibility, making complex materials more navigable and analyzable.