ReviewFrontiers in research metrics and analytics2026
Research information systems and knowledge graphs: a review.
Review in Frontiers in research metrics and analytics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.