Research Syntheses and Data Science
Research syntheses are important tools for harnessing existing scientific publications for further research and practical applications. They are used to identify, prepare, and summarize relevant studies. We use mapping reviews to systematically bring together the literature on broad, disciplinary fragmented research areas in corpora and map them in the form of broad topics. We then use scoping reviews on selected hot topics to summarize evidence on research questions that are being increasingly investigated. Finally, where possible, we prepare systematic reviews summarizing the strength of existing effects for sufficiently large groups of homogeneous papers within hot topics. In areas characterized by a dearth of studies, we examine examples of good practice using qualitative methods and extract evidence in the form of expert opinion. The aim of the work in this research focus is to document existing evidence and good practice in order to stimulate further research and enable evidence-based decision-making. This is often also part of our projects on cultural participation in the context of digital transformation and empowerment or our projects on digital regional development and social innovation.
In all projects related to research syntheses and data science, we apply research methods such as text mining, predictive modeling or topic modeling. This enables us to systematically process even broad research areas that can otherwise only be incompletely mapped in the context of mapping reviews, and to reliably identify even those works that only implicitly refer to the research area under investigation.
Recent Research Projects on Research Syntheses and Data Science |
Recent Publications on Research Syntheses and Data Science |
Publication: Two decades in the making: A scoping review on research on digital making and its potential for digital empowerment in non-formal settings
Publication: “Digitalization in aesthetics, arts and cultural education—a scoping review”
Publication: Big Data and Digital Aesthetic, Arts, and Cultural Education: Hot Spots of Current Quantitative Research