Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Hi-index | 0.00 |
We investigate different approaches based on correlation analysis to reduce the complexity of a space of quantitative indicators for the assessment of research performance. The proposed methods group bibliometric indicators into clusters of highly intercorrelated indicators. Each cluster is then associated with a representative indicator. The set of all representatives corresponds to a base of orthogonal metrics capturing independent aspects of research performance and can be exploited to design a composite performance indicator. We apply the devised methodology to isolate orthogonal performance metrics for scholars and journals in the field of computer science and to design a global performance indicator. The methodology is general and can be exploited to design composite indicators that are based on a set of possibly overlapping criteria. © 2009 Wiley Periodicals, Inc.