SKG4EOSC - Scholarly Knowledge Graphs for EOSC: Establishing a backbone of knowledge graphs for FAIR Scholarly Information in EOSC Academic Article uri icon

abstract

  • In the age of advanced information systems powering fast-paced knowledge economies that face global societal challenges, it is no longer adequate to express scholarly information - an essential resource for modern economies - primarily as article narratives in document form. Despite being a well-established tradition in scholarly communication, PDF-based text publishing is hindering scientific progress as it buries scholarly information into non-machine-readable formats. The key objective of SKG4EOSC is to improve science productivity through development and implementation of services for text and data conversion, and production, curation, and re-use of FAIR scholarly information. This will be achieved by (1) establishing the Open Research Knowledge Graph (ORKG, orkg.org), a service operated by the SKG4EOSC coordinator, as a Hub for access to FAIR scholarly information in the EOSC; (2) lifting to EOSC of numerous and heterogeneous domain-specific research infrastructures through the ORKG Hub’s harmonized access facilities; and (3) leverage the Hub to support cross-disciplinary research and policy decisions addressing societal challenges. SKG4EOSC will pilot the devised approaches and technologies in four research domains: biodiversity crisis, precision oncology, circular processes, and human cooperation. With the aim to improve machine-based scholarly information use, SKG4EOSC addresses an important current and future need of researchers. It extends the application of the FAIR data principles to scholarly communication practices, hence a more comprehensive coverage of the entire research lifecycle. Through explicit, machine actionable provenance links between FAIR scholarly information, primary data and contextual entities, it will substantially contribute to reproducibility, validation and trust in science. The resulting advanced machine support will catalyse new discoveries in basic research and solutions in key application areas.

authors

  • Stocker, Markus
  • Heger, Tina
  • Schweidtmann, Artur
  • Ćwiek-Kupczyńska, Hanna
  • Penev, Lyubomir
  • Dojchinovski, Milan
  • Willighagen, Egon
  • Vidal, Maria-Esther
  • Turki, Houcemeddine
  • Balliet, Daniel
  • Tiddi, Ilaria
  • Kuhn, Tobias
  • Mietchen, Daniel
  • Karras, Oliver
  • Vogt, Lars
  • Hellmann, Sebastian
  • Jeschke, Jonathan
  • Krajewski, Paweł
  • Auer, Sören

publication date

  • 2022

volume

  • 8