In science, reproducibility is key for making systematic progress. Scientometrics is no exception to this. Reproducibility requires that a different team can replicate the results of another team. A crisis in the reproducibility of published results has been hotly debated in fields such as biomedicine and psychology, where the irreproducibility of published research seems to have reached pervasive levels.

The causes for irreproducibility, its prevalence and consequences likely vary between scientific fields. Reflection on the situation in the field of scientometrics and informetrics was kicked-off at an international workshop on October 17, 2017 held at the ISSI 2017 conference in Wuhan, China: Where do we have problems with irreproducibility in scientometrics? What might be key actions to take to address threats to the reproducibility of scientific knowledge in our field?

Workshop Report

Presentations

Workshop Agenda & Introduction (Theresa Velden & Sybille Hinze)

Reproducibility in Scientometrics — Data Enclaves, Open Code, and Open Education (Katy Börner) [video]

Reproducibility in Scientometrics Through Quality Assurance (Sybille Hinze)

A Vendor's View on Reproducibility — Datasets, Tools, & Partnerships (Jason  Rollins)

Reproducibility concerns in scientometrics differ from other fields (Ludo Waltman)

Reproducibility —Principles and Challenges (Jesper Schneider)

Reproducibility & the Performativity of Methods (Theresa Velden)

Discussion outcomes

Reports from Break-out Groups