Composing a Publication List for Individual Researcher Assessment by Merging Information from Different Sources

TL;DR

This paper discusses the challenges and importance of accurately compiling publication lists from multiple sources for individual researcher assessment, emphasizing data quality's impact on bibliometric indicators.

Contribution

It introduces a method for merging information from different sources to improve the accuracy of publication profiles for researcher evaluation.

Findings

Merging data sources enhances publication list completeness.

Data quality critically affects bibliometric evaluation accuracy.

The approach supports more reliable researcher assessments.

Abstract

Citation and publication profiles are gaining importance for the evaluation of top researchers when it comes to the appropriation of funding for excellence programs or career promotion judgments. Indicators like the Normalized Mean Citation Rate, the hindex or other distinguishing measures are increasingly used to picture the characteristics of individual scholars. Using bibliometric techniques for individual assessment is known to be particularly delicate, as the chance of errors being averaged away becomes smaller whereas a minor incompleteness can have a significant influence on the evaluation outcome. The quality of the data becomes as such crucial to the legitimacy of the methods used.