Pregled in analiza izbranih podatkovnih zbirk ter predmetnih oznak za področje lesarskih znanosti in tehnologije

Uporabniki morajo znati identificirati najrelevantnejše vire kakovostnih znanstvenih in tehničnih informacij. Razumeti morajo strukturo zbirk, iskalne tehnike, kontroliran besednjak, terminologijo in klasifikacijske sheme. V članku podajamo glavne značilnosti bibliografskih podatkovnih zbirk (Agricola,Agris, Cab Abstracts (CABI), Compendex, Inspec, Iconda), statističnih zbirk (Eurostat, Faostat) in zbirk tehničnih dokumentov - standardov in patentov (ISO, WIPO) glede na značilnosti lesarstva oz. predelave gozdnih proizvodov. Opisane so razlike v posameznih iskalnih poljih in iskalna načela (platforme, Boolovi logični operatorji, predpone, pripone, znaki za krajšanje ali maskiranje). Posebno pozornost namenjamo predmetnim oznakam: ožje ključne besede (Descriptors, Heading Words, Controlled Terms, Keywords) in širše predmetne kategorije (Subject Categories, Concept Codes, CABI Codes, Classification Codes). Podani so seštevki besed oz. indeksnih gesel ali pojmov z najvišjo pojavnostjo. S tem pregledom želimo spodbuditi rabo dodatnih podatkovnih zbirk ter rabo strukturiranih besednjakov, kar naj se izrazi v boljših iskalnih rezultatih. End-users should be able to identify the most relevant scientific and technical information resources. They must understand database structure, query techniques, controlled dictionaries, terminology and indexing schemes. In the present article, we review principal characteristics of the following information systems: bibliographic databases (Agricola, Agris, Cab Abstracts (CABI), Compendex, Inspec, Iconda, statistical collections Eurostat and Faostat, and technical standards and patents ISO and WIPO with regard to the field of wood sciences or processing of forest products. Differences in database fields and search characteristics (search platforms, Boolean logic, prefixes, suffixes, wildcards) are described. Special attention is placed on subject headings in each respective database: narrow keywords (Descriptors, Heading Words, Controlled Terms, Keywords) and broader categories (Subject Categories, Concept Codes, CABI Codes, Classification Codes). Word counts are shown for the terms with the highest frequency of occurrences. This review promotes the use of additional databases, encourages employment of structured vocabularies, which should result in improved search results.