Measuring international research collaboration (IRC) is essential to various research assessment tasks but the effect of various measurement decisions, including which data sources to use, has not been thoroughly studied. To better understand the effect of data source choice on IRC measurement we design and implement a data quality assessment framework specifically for bibliographic data by reviewing and selecting available dimensions and designing appropriate computable metrics, and then validate the framework by applying it to four popular sources of bibliographic data: Microsoft Academic Graph, Web of Science, Dimensions, and the ACM Digital Library. Successful validation of the framework suggests it is consistent with the popular conceptual framework of information quality proposed by Wang and Strong (1996) and adequately identifies the differences in quality in the sources examined. Application of the framework reveals that Web of Science has the highest overall quality among the sets considered; and that the differences in quality can be explained primarily by how the data sources are organised. Our study comprises a methodological contribution that enables researchers to apply this IRC measurement tool in their studies; makes an empirical contribution by further characterising four popular sources of bibliographic data and their impact on IRC measurement.

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https://publons.com/publon/10.1162/qss_a_00211

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Handling Editor: Ludo Waltman

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