Background

Advancing digitalization is leading to a massive increase in metadata about research, on who produced which research, where, with what money and with what impact. Based on these metadata, and increasingly also with the help of generative AI, large companies have entered the steadily growing business of ‘research analytics’, which allows research performance to be tracked and evaluated at a completely new scale. Supporters of the open science movement criticize this development as the privatization of public research information and warn that this commercialization hinders open and equal access to knowledge about research.

However, there have been few, if any systematic and comparative studies to date on the differences between commercial and open data analytics products or providers, and especially on their impact on the practices of research evaluation and research itself. This project aims to fill this gap by providing a systematic comparison between commercial and open data products and providers, and their effects on research evaluation.

Objective

First, the project examines competition between commercial and open data providers, comparing their products and unpacking their epistemic framing of research quality and how they operationalize these framings in the products they develop. Second, the project investigates how university and other research organization administrators in Canada, France, Germany, and the UK integrate commercial and open data analytics into their own institutional and sectoral evaluation systems.

In so doing, the project provides a new comparative perspective into the effects of commercial versus open data analytics on local research evaluation practices and research cultures.

Team