Next Generation Metrics for Scientific and Scholarly Research in Europe - LERU position paper April 2024

Oct 16, 2026

This LERU position paper examines how European universities can and should use currently available metrics and data to assess research processes together with qualitative expertise and information. It argues that next-generation metrics are a crucial part of responsible research evaluation, while warning against using metrics out of context. The paper highlights resource, competence, and data-quality constraints faced by universities, and reviews technical, ethical, and governance challenges across academic levels, including open science, societal impact, innovation, and rankings.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages52

Reading Time2 h 11 min

AccessFree to download

Consolidated Overview and Recommendations

Scientific communication and the transition to next generation metrics

The role of metrics in informing and supporting academic policy development

The challenges for scientometrics 2.0

The limitations of peer review and score-based grant criteria

Next generation metrics’ complex interrelationship across multiple levels of the academic system

The metric ‘trickle-down’ challenge

Next generation metrics and university rankings

New metrics and the emergence of related ethical and technical challenges

Current practices and policies on Open Science at LERU universities

The challenge of data availability for next generation metrics

Appendix I: Metrics terminology

Appendix II: Recommendations from previous declarations and reports

Next Generation Metrics for Scientific and Scholarly Research in Europe LERU position paper April 2024 University of Amsterdam • Universitat de Barcelona • University of Cambridge • University of Copenhagen Trinity College Dublin • University of Edinburgh • University of Freiburg • Université de Genève Universität Heidelberg • University of Helsinki • Universiteit Leiden • KU Leuven • Imperial College London • University College London • Lund University • University of Milan • Ludwig-Maximilians-Universität München • University of Oxford • Sorbonne University • Université Paris-Saclay • University of Strasbourg • Utrecht University • ETH Zurich • University of Zurich Table of contents Consolidated Overview and Recommendations 3 1. Scientific communication and the transition to next generation metrics 8 2. The role of metrics in informing and supporting academic policy development 10 3. The challenges for scientometrics 2.0 13 4. The limitations of peer review and score-based grant criteria 16 5. Next generation metrics’ complex interrelationship across multiple levels of the academic system 18 6. The metric ‘trickle-down’ challenge 20 7. Next generation metrics and university rankings 22 8. New metrics and the emergence of related ethical and technical challenges 26 9. Current practices and policies on Open Science at LERU universities 28 10. The challenge of data availability for next generation metrics 38 Appendix I: Metrics terminology 45 Appendix II: Recommendations from previous declarations and reports 46 Acknowledgements Authors: Jeroen Bosman (Utrecht University), Koenraad Debackere (KU Leuven), William P. Cawthorn (University of Edinburgh), Paola Galimberti (University of Milan), Mikael Graffner (Lund University), Leonhard Held (University of Zurich), Karlijn Hermans (Universiteit Leiden), Fiona Killard (formerly Trinity College Dublin and The University of Dublin, at present The National Institute for Bioprocessing Research and Training, Ireland), Ignasi Labastida (Universitat de Barcelona), Andrew Millar (University of Edinburgh), Mark Robinson (University of Zurich), Kristell Roser (Sorbonne University), Terhi Sangren (University of Helsinki), Michael Svendsen (University of Copenhagen), and Chair Paul Wouters (Universiteit Leiden) With thanks to the LERU colleagues who contributed: Bernd Kortmann, Rens Vliegenthart, Immo Warntjes. Consolidated Overview and Recommendations What this report is about The field of evaluating academic activities is vast, complex, and highly dynamic, as are the roles of any data and indicators used to support these evaluations. This report explores how universities can and should use currently available metrics and data to assess their research processes, in conjunction with qualitative expertise and information. While this report does not comprehensively cover responsible research evaluation, we recognise the need for next-generation metrics as a crucial aspect of responsible research evaluation. Using metrics out of context simply does not make sense, regardless of their ease of availability. As if the challenge of evaluating academic work were not complex enough, universities are also confronted with the problem that they often lack the required resources, competences, and experiences to deal with each dimension in an expert manner. So, they improvise and make do with what they have. To make matters worse, many university administrative systems and processes are not able to easily produce validated, reliable, and meaningful data in-house due to fragmented data collection, incompatibility of datasets , lack of data standardisation, lack of maintenance, outdated ICT systems, and lack of expertise. As the LERU review of Open Science activities has shown, the simple act of monitoring what we are already doing requires a significant time investment and is mostly done manually. In this context, we have chosen to focus this report on the aspec

FAQs

What is the main purpose of this LERU position paper?

It explores how universities can use currently available metrics and data, alongside qualitative expertise, to assess research processes and to advance responsible research evaluation through next-generation metrics.

Why does the report warn against using metrics out of context?

Because the report frames evaluation as complex and dynamic; indicators need contextual relevance and responsible application, otherwise they fail to meaningfully support evaluation goals.

What major challenges does the paper identify for implementing next-generation metrics?

It highlights institutional constraints such as lack of resources, fragmented and incompatible data collection, limited data standardisation and maintenance, outdated ICT systems, and the time-intensive, often manual nature of monitoring current Open Science practices.

Oct 16, 2026

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