Tyging

Tyging is a term used in information science and digital humanities to describe a data annotation practice that combines typing and tagging in a single step. It refers to the simultaneous assignment of a formal type or class to a data item and the attachment of descriptive tags or keywords that illuminate its content, context, or domain relevance. Tyging aims to create richer, more navigable metadata by linking structural classification with topical labeling.

In practice, tyging can be performed by humans, machines, or a hybrid workflow. A typist may assign a type such as Person, Location, Event, or Concept and then add tags like “travel,” “historic,” or “biography.” Automated or semi-automated tyging often relies on natural language processing, pattern learning, or rule-based systems to suggest or enforce a consistent type–tag pair for each item. The approach is particularly common in digital archives, knowledge-graph projects, and content-management systems where both category and keyword metadata improve searchability and interoperability.

History and terminology: tyging emerged as a blended concept in the 2010s among practitioners seeking tighter integration of structure and semantics. The term itself reflects the idea of “typing” (defining a data class) and “tagging” (assigning descriptive labels), and it remains a flexible reference rather than a single formal standard.

Applications and considerations: Tyging supports richer data discovery, more precise filtering, and easier aggregation across collections. Challenges include ensuring consistency across authors and datasets, aligning with existing metadata standards, and balancing granularity with usability. Related concepts include tagging, typing, and semantic annotation.