Open Research Knowledge Graph

“The Open Research Knowledge Graph (ORKG) aims to describe research papers in a structured manner. With the ORKG, papers are easier to find and compare….

Research is a fundamental pillar of societal progress. Yet, scientific communities face great difficulties in sharing their findings. With approximately 2.5 million newly published scientific articles per year, it is impossible to keep track of all relevant knowledge. Even in small fields, researchers often find themselves drowning in a publication flood, contributing to major scientific crises such as the reproducibility crisis, the deficiency of peer-review and ultimately the loss of knowledge.

The underlying problem is that we never updated our methods of scholarly communication to exploit the possibilities of digitalization. This is where the Open Research Knowledge Graph comes into play!

The ORKG makes scientific knowledge human- and machine-actionable and thus enables completely new ways of machine assistance. This will help researchers find relevant contributions to their field and create state-of-the-art comparisons and reviews. With the ORKG, scientists can explore knowledge in entirely new ways and share results even across different disciplines….”

[2102.06021] Analysing the Requirements for an Open Research Knowledge Graph: Use Cases, Quality Requirements and Construction Strategies

Abstract:  Current science communication has a number of drawbacks and bottlenecks which have been subject of discussion lately: Among others, the rising number of published articles makes it nearly impossible to get a full overview of the state of the art in a certain field, or reproducibility is hampered by fixed-length, document-based publications which normally cannot cover all details of a research work. Recently, several initiatives have proposed knowledge graphs (KG) for organising scientific information as a solution to many of the current issues. The focus of these proposals is, however, usually restricted to very specific use cases. In this paper, we aim to transcend this limited perspective and present a comprehensive analysis of requirements for an Open Research Knowledge Graph (ORKG) by (a) collecting and reviewing daily core tasks of a scientist, (b) establishing their consequential requirements for a KG-based system, (c) identifying overlaps and specificities, and their coverage in current solutions. As a result, we map necessary and desirable requirements for successful KG-based science communication, derive implications, and outline possible solutions.