The FachRef-Assistant: Personalised, subject specific, and transparent stock management

Abstract

We present in this paper a personalized web application for the weeding of printed resources: the FachRef-Assistant. It offers an extensive range of tools for evidence based stock management, based on the thorough analysis of usage statistics. Special attention is paid to the criteria individualization, transparency of the parameters used, and generic functions. Currently, it is designed to work with the Aleph-System from ExLibris, but efforts were spent to keep the application as generic as possible. For example, all procedures specific to the local library system have been collected in one Java package. The inclusion of library specific properties such as collections and systematics has been designed to be highly generic as well by mapping the individual entries onto an in-memory database. Hence simple adaption of the package and the mappings would render the FachRef-Assistant compatible to other library systems. The personalization of the application allows for the inclusion of subject specific usage properties as well as of variations between different collections within one subject area. The parameter sets used to analyse the stock and to prepare weeding and purchase proposal lists are included in the output XML-files to facilitate a high degree of transparency, objectivity and reproducibility.