Compare methods

	Domain Analysis	Facet Analysis	Thesaurus Construction
Field	Library Information Science	Library Information Science	Library Information Science
Family	Process / pipeline	Process / pipeline	Process / pipeline
Year of origin	1995	1967	2000
Originator	Birger Hjørland & Hanne Albrechtsen	S. R. Ranganathan; Brian C. Vickery	Jean Aitchison, Alan Gilchrist & David Bawden; ANSI/NISO Z39.19
Type	Socio-cognitive pipeline for studying knowledge domains	Analytico-synthetic pipeline for decomposing a subject into facets	Standards-based pipeline for building an information-retrieval thesaurus
Seminal source	Hjørland, B., & Albrechtsen, H. (1995). Toward a new horizon in information science: Domain-analysis. Journal of the American Society for Information Science, 46(6), 400-425.	Ranganathan, S. R. (1967). Prolegomena to Library Classification (3rd ed.). Bombay: Asia Publishing House. ISBN: 9788170004707	Aitchison, J., Gilchrist, A., & Bawden, D. (2000). Thesaurus Construction and Use: A Practical Manual (4th ed.). London: Aslib/IMI. ISBN: 9780851424460
Aliases	Knowledge-Domain Analysis, Hjørland Domain Analysis, Discourse-Community Analysis, Subject-Domain Analysis	Analytico-Synthetic Analysis, Categorial Analysis, Facet Decomposition, PMEST Facet Analysis	Thesaurus Building, Thesaurus Development, Controlled Vocabulary Thesaurus Design, Information Retrieval Thesaurus Construction
Related	3	3	3
Summary	Domain analysis is the socio-cognitive research programme proposed by Birger Hjørland and Hanne Albrechtsen in 1995, which holds that the most fruitful object of study for information science is the knowledge domain understood as a discourse or thought community within society's division of labour. Rather than grounding information organization in the isolated mental processes of an individual user, domain analysis grounds it in the shared literature, paradigms, terminology, and social practices of a subject field. Hjørland and Albrechtsen set out eleven complementary approaches — from producing literature guides and special classifications to bibliometric, historical, and epistemological study — and Clare Beghtol's work on literary warrant and consensus showed how a domain's own published discourse supplies the empirical basis for its categories. The method turns the design of classifications, thesauri, and retrieval systems into an evidence-based study of how a community actually thinks and writes.	Facet analysis is the analytico-synthetic technique, pioneered by S. R. Ranganathan and systematized for special schemes by Brian Vickery, for decomposing a subject into its fundamental conceptual components. Instead of trying to enumerate every compound topic in advance, the analyst breaks a subject down into elementary concepts (isolates), sorts those isolates into a small number of fundamental categories — in Ranganathan's canonical scheme Personality, Matter, Energy, Space, and Time (PMEST) — and arranges each resulting facet as an ordered array. A defined citation order then prescribes how facets recombine, so any compound subject can be synthesized from its parts. Facet analysis is the conceptual engine beneath faceted classification, thesaurus structure, and much modern metadata, taxonomy, and interface design.	Thesaurus construction is the systematic building of a controlled vocabulary in which preferred terms are linked by a standardized set of relationships — equivalence, hierarchy, and association — to support consistent indexing and effective retrieval. The definitive practical methodology was set out by Jean Aitchison, Alan Gilchrist, and David Bawden in their manual Thesaurus Construction and Use, and the controlling standard in the United States is ANSI/NISO Z39.19, with ISO 25964 as its international counterpart. A thesaurus collects the terms a domain uses, resolves synonyms and homographs so each concept has one preferred label, and then wires the preferred terms together with USE/UF, BT/NT, and RT relationships plus scope notes. The result is a structured map of a subject's concepts that indexers and searchers share, reducing the mismatch between the words authors, indexers, and users choose.