Non-agricultural databases and thesauri: Retrieval of subject headings and non-controlled terms in relation to agriculture

摘要

The paper aims to assess the utility of non-agriculture-specific information systems, databases, and respective controlled vocabularies (thesauri) in organising and retrieving agricultural information. The purpose is to identify thesaurus-linked tree structures, controlled subject headings/terms (heading words, descriptors), and principal database-dependent characteristics and assess how controlled terms improve retrieval results (recall) in relation to free-text/uncontrolled terms in abstracts and document titles. Design/methodology/approach: Several different hosts (interfaces, platforms, portals) and databases were used: CSA Illumina (ERIC, LISA), Ebscohost (Academic Search Complete, Medline, Political Science Complete), Ei-Engineering Village (Compendex, Inspec), OVID (PsycINFO), ProQuest (ABI/Inform Global). The search-terms agriculture and agricultural and truncated word-stem agricultur- were employed. Permuted (rotated index) search fields were used to retrieve terms from thesauri. Subject-heading search was assessed in relation to free-text search, based on abstracts and document titles. Findings: All thesauri contain agriculture-based headings; however, associative, hierarchical and synonymous relationships show important inter-database differences. Using subject headings along with abstracts and titles in search syntax (query) sometimes improves retrieval by up to 60 per cent. Retrieval depends on search fields and database-specifics, such as autostemming (lemmatization), explode function, word-indexing, or phrase-indexing. Research limitations/implications: Inter-database and host comparison, on consistent principles, can be limited because of some particular host- and database-specifics. Practical implications: End-users may exploit databases more competently and thus achieve better retrieval results in searching for agriculture-related information. Originality/value: The function of as many as ten databases in different disciplines in providing information relevant to subject matter that is not a topical focus of databases is assessed.