White paper on Next Generation Metrics
Report, 2020
In chapter two, we report on our findings on metrics dealing with (open) science. Ever since E. Garfield’s Journal Impact Factor (JIF) came into use in the mid-70s, and certainly with the h-index proposed by the physicist J. E. Hirsch in 2005, the rise of quantitative metrics in the assessment of research has seemed to be unstoppable - up to the use of ´views´, ´likes´ and ´tweets´. While in times of accountability and competing for visibility and funds, it is only reasonable to focus on the measurability and comparability of metrics as efficient means to display performance, the limitations of doing so are obvious. As a result, in the past years, a countermovement criticising this practice and questioning the validity of the metrics and reliability of the data used has become stronger. Moreover, there are strong (political) expectations to make science more open. Metrics for (open) education and training are the topic of chapter three. In many (global) rankings of higher education institutions, the indicators used reflect the model of traditional, established, wealthy and largely English-speaking research universities (Hazelkorn, 2015). They are, therefore, ill-suited to truly give an idea about the quality or the performance of higher education more broadly, and they are limited in helping universities to set priorities. They do, however, reveal that there is still a lack of meaningful internationally comparable information on these matters. By covering (open) innovation in chapter four, we complete the discussion of the mission of our Members. Open innovation promotes approaches that boost disruptive innovation rather than incremental, stimulate inventions produced by outsiders and founders in start-ups, and is based on a view on the world of widely distributed knowledge.
We synthesised our findings on the confrontation between ´traditional´ and ´next generation metrics´ and present ten each for science, education and innovation for use mainly within our Members and to monitor the desired progress over time (see annexe I). While this might be interpreted as sufficient responsiveness to external expectations on our behalf, we instead advanced further and in chapter five suggest that universities strive towards ´progressive metrics´ and highlight the need to acknowledge knowledge as a common good, promote a culture of quality, risk-taking and trust and measure the contribution to sustainability. That is why we conclude this paper with ideas for progressive indicators in annexe II, outlining an agenda for future work to stay at the forefront of science, education and innovation; to benchmark against like-minded institutions; and to pursue institutional development paths; and - ultimately - to optimise our contributions to society and the world.
bibliometrics
ranking
altmetrics
open science
scientometrics
Author
Ingrid Bauer
Vienna University of Technology
David Bohmert
CESAER
Alexandra Czarnecka
Delft University of Technology
Thomas Eichenberger
Swiss Federal Institute of Technology in Zürich (ETH)
Juan Garbajosa
Technical University of Madrid
Horia Iovu
Politehnica University of Bucharest (UPB)
Yvonne Kinnaird
University of Strathclyde
Ana Carla Madeira
University of Porto
Mads Nygård
Norwegian University of Science and Technology (NTNU)
Per-Anders Östling
Royal Institute of Technology (KTH)
Susanne Räder
Technische Universität Dresden
Mario Ravera
Polytechnic University of Turin
Per-Eric Thörnström
Chalmers, Communication and Learning in Science, Research support, bibliometrics and ranking
Kurt De Wit
KU Leuven
Subject Categories (SSIF 2011)
History of Ideas
Information Studies
DOI
10.5281/zenodo.3874801
Publisher
CESAER