| Literature DB >> 27073290 |
María Del Carmen Calatrava Moreno1, Thomas Auzinger2, Hannes Werthner1.
Abstract
The accuracy of interdisciplinarity measurements is directly related to the quality of the underlying bibliographic data. Existing indicators of interdisciplinarity are not capable of reflecting the inaccuracies introduced by incorrect and incomplete records because correct and complete bibliographic data can rarely be obtained. This is the case for the Rao-Stirling index, which cannot handle references that are not categorized into disciplinary fields. We introduce a method that addresses this problem. It extends the Rao-Stirling index to acknowledge missing data by calculating its interval of uncertainty using computational optimization. The evaluation of our method indicates that the uncertainty interval is not only useful for estimating the inaccuracy of interdisciplinarity measurements, but it also delivers slightly more accurate aggregated interdisciplinarity measurements than the Rao-Stirling index.Entities:
Keywords: Bibliometrics; Interdisciplinarity; Missing data; Optimization ; Rao–Stirling index; Spanning tree; Uncertainty
Year: 2016 PMID: 27073290 PMCID: PMC4819562 DOI: 10.1007/s11192-016-1842-4
Source DB: PubMed Journal: Scientometrics ISSN: 0138-9130 Impact factor: 3.238