Data structuring and classification in newly‐emerging scientific fields

Purpose – The article seeks to address a methodological procedure based on keyword analysis and the structuring of data into information systems in the field of functional foods, a newly‐emerging scientific field within the broader scope of food sciences and technology. Design/methodology/approach – An experiment was undertaken by selection of a research field or research subject, selection of search profile, selection and processing of relevant databases, keyword analysis, and the arrangement of data (keywords) according to tree‐structures. Keyword analysis was employed to identify narrower research fields within the broader scientific field. The structuring of data into systems was used to classify the terms within the particular narrow field. Keywords with higher and lower frequency were identified. A classification tree was set up, based on keywords (thesaurus‐based descriptors) extracted from the FSTA (Food Science and Technology Abstracts) database available online. The tree was supplemented and upgraded with some additional topical terms that have not as yet been included in the existing thesaurus. To serve as a comparison a completely new classification tree was designed, based on online full‐text data. Findings – Comparison of the two trees suggests that the previous existing tree is sufficiently accurate in representing the field of functional foods, provided that it is upgraded with some additional terms. A more accurate classification should improve thesauri and consequently enhance retrieval in international databases. Originality/value – Presents a methodology of database analysis which may serve to improve database patterns, especially with regard to information retrieval.