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Higher education performance is boosted through cross-border cooperation and increased transnational mobility of students. In addition, exchange students have better employability skills after staying abroad compared to the students' peers. A number of studies have investigated factors that determine whether a student studies abroad. In this study, the authors focused on the role of personality trait openness to experience and cultural intelligence (CI) in explaining Croatian students' experience with and/or intention to travel abroad for studying purposes.

The authors analyzed results from 482 students (M = 22.61, standard deviation (SD) = 2.24, 66% female), of whom 35% reported that they studied abroad or intended to study abroad. They filled in The Cultural Intelligence Scale and openness facets items from the International Personality Item Pool (IPIP-300) questionnaire.

The authors conducted a hierarchical binary logistic regression analysis and found that students who were younger, had higher adventurousness and higher motivational CI were more likely to study abroad. Results of the mediation analysis showed that the association between openness to experience facet adventurousness and intention to study abroad was partially mediated by the motivational aspect of CI.

This study contributes to the better understanding of complex interrelations between personality traits and CI in the context of higher education internationalization processes. This study offers unique insight into the mediating role CI has in the association between personality and mobility behavior.

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.