This paper reports on a comprehensive study, which has investigated the approaches, methods and tools being deployed in implementing living labs among higher education institutions (HEIs) around the world. Two methods were employed. First, a bibliometric analysis of the current emphasis given to living labs in a sustainable development context and in the implementation of the Sustainable Development Goals (SDGs). Second, an empirical study aimed at identifying the use levels of living labs at HEIs. This was accomplished through an analysis of selected case studies that showcased successful approaches to SDGs implementation with living labs, and resulted in a framework for action. There are three main findings from these analyses. The first is that the multidisciplinary character of living labs in the context of sustainable development needs to be considered, to maximize their impacts. Second, most of the studied living labs focus on SDGs 4 and 11, which deal with providing quality education and ensuring the sustainable development of cities and communities. Third, the challenges encountered in the implementation of living labs refer to (1) the complexities in institutional administration, (2) the tensions between different groups of interest that need to be addressed by enhanced communication, and (3) the necessity to pay attention to the demand of using sustainability and innovation as a strategy in the operations of living labs. The paper draws from the experiences and lessons learned and suggests specific measures, which will improve the use of living labs as more systemic tools towards the implementation of the SDGs.

Despite the abundance of studies focused on how higher education institutions (HEIs) are implementing sustainable development (SD) in their educational programmes, there is a paucity of interdisciplinary studies exploring the role of technology, such as data science, in an SD context. Further research is thus needed to identify how SD is being deployed in higher education (HE), generating positive externalities for society and the environment. This study aims to address this research gap by exploring various ways in which data science may support university efforts towards SD. The methodology relied on a bibliometric analysis to understand and visualise the connections between data science and SD in HE, as well as reporting on selected case studies showing how data science may be deployed for creating SD impact in HE and in the community. The results from the bibliometric analysis unveil five research strands driving this field, and the case studies exemplify them. This study can be considered innovative since it follows previous research on artificial intelligence and SD. Moreover, the combination of bibliometric analysis and case studies provides an overview of trends, which may be useful to researchers and decision‐makers who wish to explore the use of data science for SD in HEIs. Finally, the findings highlight how data science can be used in HEIs, combined with a framework developed to support further research into SD in HE.