Midspecific

Midspecific is a term used in information science and related fields to denote a level of categorization that lies between generic and highly specific labels. The concept emphasizes an intermediate granularity intended to preserve useful detail while avoiding excessive fragmentation that can hinder data integration and retrieval.

Because there is no universal standard for midspecific labeling, its definition is context dependent. In practice, midspecific labels are chosen to support cross-domain queries, scalable analytics, and human readability. They are used when full-species detail is unnecessary, unknown, or impractical, but where simple categories such as "general" would be too coarse to support meaningful analysis.

Applications span taxonomy and biodiversity databases, product categorization, metadata schemas, and annotation workflows in natural language processing or computer vision. In each case, practitioners weigh factors such as data quality, audience needs, and interoperability with existing ontologies to determine an appropriate midspecific level. The approach is often part of broader discussions about granularity and the design of flexible, multi-layered classifications.

Critiques note that the lack of a formal definition can hinder reproducibility and automated reasoning. Proponents argue that midspecific labeling offers a pragmatic compromise, enabling flexible aggregation and drill-down analysis while maintaining usable diversity in descriptive categories. See also granularity, level of detail, taxonomy, tagging, and ontologies.