Analysis of journal usage by Wageningen UR staff members via article references - Veller, Marco G.P. van (Qualitative and Quantitative Methods in Libraries, 2017)
The research activities of Wageningen University and Research (or Wageningen UR) are concentrated around food and food production, living environment and health, lifestyle and livelihood. To facilitate the scientific information access of Wageningen UR staff members, the library strives to provide a balanced collection of relevant journals. For such a balanced collection, appropriate collection management is a necessity. For information on journal usage by staff members of Wageningen UR, the library has developed an alternative analysis based upon information from article references. An inventory is made on a yearly basis of the journals from which articles are listed in the references of articles published by Wageningen UR staff in the three previous years. For each of the inventoried journals the number of times (abundance) articles from this journal are included in the references of the published articles is counted. The published articles are collected from Wageningen UR's institutional repository, which contains updated affiliation information for the authors of the articles. The institutional repository also contains, for each published article, a link to its corresponding Web of Science record for collecting information on the articles’ references.  The use of the institutional repository, in combination with Web of Science, as input for this alternative analysis enables customized, evidence-based measures of journal usage by Wageningen UR as a whole or parts thereof (e.g. research groups). Customized lists of accessed journals can be used by staff members to select journals that are relevant for their research. The library uses the lists to evaluate its journal collections and allocate costs to organizational units of Wageningen UR.  Customized lists of used journals also can be applied in a similarity analysis of journal usage by different research groups. Via cluster analysis and mapping this similarity in journal usage by research groups can be visualized over time.