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.

The library literature contains many examples of automated and semi-automated approaches to harvest electronic theses and dissertations (ETD) metadata from institutional repositories (IR) to the Online Computer Library Center (OCLC). However, most of these approaches could not be implemented with the institutional repository software Digital Commons because of various reasons including proprietary schema incompatibilities and high level programming expertise requirements our institution did not want to pursue. Only one semi-automated approach was found in the library literature which met our requirements for implementation, and even though it catered to the particular needs of the DSpace IR, it could be implemented to other IR software if further customizations were applied.

The following paper presents an extension of this semi-automated approach originally created by Deng and Reese, but customized and adapted to address the particular needs of the Digital Commons community and updated to integrate the latest Resource Description & Access (RDA) content standards for ETDs. Advantages and disadvantages of this workflow are discussed and presented as well.