Case study
The Open Research Knowledge Graph (ORKG) is a platform for creating, curating, publishing, and reusing FAIR scientific knowledge, thereby shifting scholarly communication from documents to data. ORKG supports the FAIRification of scientific knowledge by integrating AI technologies, in particular Natural Language Processing, Knowledge Graphs and Crowdsourcing. It offers services like research comparisons and thematic reviews to improve productivity and data use by researchers and publishers.
Problem addressed
Millions of scientific articles are published every year, making it difficult to efficiently find and process scientific knowledge even in narrow areas of research. The problem is particularly pressing in synthesis research. A key limitation of narrative text articles is that their contents are not machine-readable. The Open Research Knowledge Graph tackles inefficiencies in document-based scholarly communication by transitioning to a knowledge-based system.
Added value
Facilitating machine-assisted reuse of scientific knowledge as FAIR research data by supporting the production and management of structured scientific knowledge.
Enabling advanced scientific knowledge search and discovery through a digital library with innovative user interfaces and machine interfaces (APIs).
Streamlining efficient scientific knowledge comparison and synthesis through novel user-facing services for FAIR scientific knowledge processing.

From paper to PDF: Digitisation of scientific articles over the past centuries without digitalising scientific knowledge. TIB – CC BY