taxany

Taxany is a term used in discussions of knowledge organization and data management to describe a hybrid approach that combines hierarchical classification with analytic methods. In its broad sense, taxany refers to systems or workflows that organize information using taxonomic structures while also applying data analysis to derive insights from the classified data.

Because taxany is not established in major reference works, its definitions vary between sources. The term appears mainly in online forums, blogs, and some niche publications, where it is presented as a developing concept rather than a fixed standard. The etymology combines tax- from taxonomy with the suffix -any, suggested to indicate an analytical or process-oriented dimension.

Conceptually, taxany envisions a workflow that starts with a taxonomy or multi-layered classification scheme, organizes content accordingly, and then applies analytical methods—such as statistical analysis, machine learning, or semantic enrichment—to the data within or across categories. Proponents emphasize interoperability of classifiers with analytics, and some frame taxany as a bridge between knowledge organization and data science.

Applications are proposed mainly in digital libraries, content management, product catalogs, and knowledge graphs, where structured categories can facilitate retrieval while analytics uncover trends and relations. However, because the term lacks a standardized definition, practical implementations vary and evaluation standards are not yet settled. Critics caution that conflating taxonomy and analytics can lead to unclear scope or duplicated effort.

Status: Taxany remains an informal or speculative term rather than a formal discipline. As such, it should be understood as a concept in flux, with ongoing debates about its boundaries, best practices, and measurable benefits.