Quality of indexing in online data bases

Abstract

We describe practical tests by which the quality of subject indexing in online bibliographic data bases can be compared and judged. The tests are illustrated with 18 clusters of documents from the medical behavioral science literature and with terms drawn from MEDLINE, PsycINFO, BIOSIS, and Excerpta Medica. Each test involves obtaining a cluster of about five documents known on some grounds to be related in subject matter, and retrieving their descriptors from at least two data bases. We then tabulate the average number of descriptors applied to the documents, the number of descriptors applied to all and to a majority of the documents in the cluster, and the relative rarity of the applied descriptors. Comparable statistics emerge on how each data base links related documents and discriminates broadly and finely among documents. We also gain qualitative insights into the expressiveness and pertinence of the available indexing terms.