| KRATKA VSEBINA | Članek obravnava tri najpomebnejše biotehniške/kmetijske podatkovne zbirke Agricola, Agris, in CAB Abstracts (CABA) glede na predmetne oznake o znanosti o živalih (proizvodnja in varstvo živali, veterina). Podan je obsežen pregled zbirk, indeksiranje in klasifikacijske sheme. Predstavljeni so koncepti, kot so ontologije in metapodatki. Prikazane so predmetne kategorije in razlike med zbirkami pri opisovanju vsebin o živalih, akvakulturi in ribištvu. Različni pojmi se uporabljajo za podobne koncepte. Drevesaste strukture, tezavri, ključne besede oz. deskriptorji so predstavljeni glede na ožje in širše pojme, preferenčne pojme, nedeskriptorje in sorodne pojme oz. gesla. Obstajajo različne hierarhične smeri glede na proizvodne ali taksonomske koncepte. CABA ima najbolj kompleksno hierarhično drevo v smislu taksonomije. V različnih zbirkah se uporabljajo različne relacije med deskriptorji, nedeskriptorji in sorodnimi gesli, zato je kartiranje vsebine odvisno od podatkovne zbirke. Zaslonske slike opisujejo rabo spletnih tezavrov. Prikazane so večjezikovne funkcije tezavra Agrovoc. Portali oz. platforme so obravnavane glede na iskalno sintakso, fraze, boolovo logiko, znake za krajšanje ali maskiranje. Razlike med zbirkami vplivajo na natančnost in odziv oz. priklic ter šum. Za učinkovitejšo rabo bi morali uporabniki pridobiti več znanj o učinkovitih rabah podatkovnih zbirk in informacijskihsistemov. // The article tackles three most important agricultural databases (DB) Agris, Agricola CAB Abstracts (CABA), produced by FAO, NAL, CABI, with regard to subject headings related to animal sciences, production, protection or health-related veterinary issues. The initial part reviews different approaches to DB and respective indexing and classification schemes. Concepts, such as ontologies and metadata, are presented. Animal, aquatic sciences and fisheries subject categories are shown. Inter-database differences are addressed, e.g. employment of different names for similar concepts. Tree-structures, indexing systems of thesaurus-based keywords-descriptors (DE) are analyzed with emphasis on narrow and broader terms, preferntial terms (non-descriptors) and related terms. There exist different tree-structures, depending either on productiion or taxonomy. CABA exibits hierarchically the most complex tree with regard to taxonomy. In different DB, keywords are used in realtions DEvs. non-DE vs. related terms. Mapping of a concept depends on particular DB. Subject headings are assigned by information specialists, indexers, thus possessing an important degree of subjective choice. Original web-based thesauri screenshots are presented. Emphasis is pleced on multilingual functionality of Agrovoc. Portals or search platforms are tackled with regard to retrieval, search syntax, priority, phrases, Booleanlogic, wildcards and truncation. Inter-database differences affect retrieval precision, recall, and noise. The complex schemas, subject trees,and headings can sometimes account for a less successful retrieval because they may be too sophisticated and can remain disregarded by users. End-users should acquire better expertise in order to use more effectively the existing information systems and databases. |