Research information systems and knowledge graphs: a review

Digital research artifacts (articles, datasets, software, etc.) are the basis for scientific research. Due to the continuous growth and complexity (e.g., due to formats) of such artifacts, ensuring their organization and long-term availability for research is becoming increasingly challenging. It is essential to manage the artifacts so that they are easily discoverable, accessible and useable by relevant communities. Research Information Systems (RISs) have become indispensable in curating, managing, and publishing research artifacts and other research objects. Diverse communities actively use the data from these systems to conduct research-intensive activities across various fields, including computer science, engineering, and life sciences. We review the current state of the art in research information systems, specifically: scholarly identifier systems, bibliographic databases, Research Data Management (RDM) services, and Knowledge Graphs (KGs). These infrastructures play a crucial role in the management of research artifacts. First, we discuss infrastructures that enable the persistent identification of research artifacts to make them globally discoverable and citeable. Second, we discuss databases that manage metadata about research artifacts. Third, we present RDM services that support publishing and accessing research data. Finally, we provide a comprehensive overview of domain-specific and domain-agnostic KGs and databases that have been widely adopted to represent scientific knowledge in different domains in structured form.