Marked by expanding and diverse forms of collaboration and competition, the investigation of contemporary developments in higher education and science systems need additional attention. Therefore, this Research Topic provides a forum for multidisciplinary exchange of pioneering research ideas and dialogues as well as complementary research that contribute to the field of knowledge, and aspires to support innovative, cutting-edge, and policy relevant research at the nexus of higher education research and science studies (HERSS), bibliometrics, scientometrics, and computational social sciences—traditionally separate communities focusing either on small scale and in-depth case studies or on large-scale 'big data' research. Researchers bringing together the aforementioned scientific communities can be classified as important bridge-builders to bolster the growing research and current initiatives in the field of science of science between diverse scientific communities and the wider public. Especially sociology, with its ambition to pair classic and innovative theoretical approaches with new methods to analyze and to qualitatively interpret quantitative 'big data' with machine learning algorithms, initiates a fascinating and promising approach to interlink the still separate scientific communities in favor of a more holistic understanding of science of science.
In this Research Topic—as part of the Lecture Series: Science of Science in the Spotlight hosted at the University of Luxembourg and funded by the Luxembourg National Research Fund (FNR)—we invite members of these diverse scientific communities and researchers who are working at the intersection as 'translators' to present their latest research.
We aim to promote and provide evidence-based insights into the drivers of multidisciplinary and international research and innovation, networks, and collaboration, including higher education developments, scientific knowledge production (e.g., publications, citations, and patents), science capacity-building, research evaluation, policy reforms, cultural and societal change processes, and institutions and organizations, as well as scientists’ geographical mobility, gender inequalities, and career paths in science. Furthermore, we want to stimulate debate on theoretical in-depth context knowledge and innovative methodological approaches (for example social network analysis and machine learning algorithms), and on data acquisition and analysis—long identified as an important research gap in science of science.
The aim of this Research Topic is to consolidate common themes and research interests to maintain and improve collaborations among researchers with different academic backgrounds and expertise from a wide range of disciplines. We welcome contributions that address the aforementioned topics and encourage to combine theory-driven, empirically-rich, multidisciplinary, historical, and comparative research, including informed and evidence-based interpretations of research results that illustrate the importance of the topic for researchers, policymakers, funding agencies, university managers, and other public research organizations.
