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This paper examines the socio-political affordances of metrics in research evaluation and the consequences of epistemic injustice in research practices and recorded knowledge.

First, the use of metrics is examined as a mechanism that promotes competition and social acceleration. Second, it is argued that the use of metrics in a competitive research culture reproduces systemic inequalities and leads to epistemic injustice. The conceptual analysis draws on works of Hartmut Rosa and Miranda Fricker, amongst others.

The use of metrics is largely driven by competition such as university rankings and league tables. Not only that metrics are not designed to enrich academic and research culture, they also suppress the visibility and credibility of works by minorities. As such, metrics perpetuate epistemic injustice in knowledge practices; at the same time, the reliability of metrics for bibliometric and scientometric studies is put into question.

As metrics leverage who can speak and who will be heard, epistemic injustice is reflected in recorded knowledge and what we consider to be information.

This paper contributes to the discussion of metrics beyond bibliometric studies and research evaluation. It argues that metrics-induced competition is antithetical to equality and diversity in research practices.

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.

This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.

This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.

The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

Anyone seeking to influence another is a potential leader. Within higher education, determining what an institution should undertake on sustainability can be daunting. Sustainability leaders face labyrinthine, multifaceted sub-cultures, influencers and viewpoints across staff, students, government, business and alumni all with an opinion on whether, how and in what order of priority sustainability should be taken forward. In this paper we take on this challenge by synthesising and critically evaluating core principles and working models for influencing and leading for sustainability in higher education. We identify a series of eight challenges affecting delivery of sustainability and seek to understand how conceptual models and principles in sustainability decision-making and leadership could address these. We draw on the experience of both authors, in tandem with comments from workshop and leadership training programme participants who attended the Environmental Association for Universities and Colleges (EAUC) Leadership Lab training in the UK, as well as reflections arising in a detailed case study from the University of Edinburgh. We bring key insights from theory and practice for the benefits of individuals or teams seeking to influence and persuade key decision-makers to embrace the sustainability agenda.