Document (#43318)

Author

Auer, S.
Oelen, A.
Haris, A.M.
Stocker, M.
D'Souza, J.
Farfar, K.E.
Vogt, L.
Prinz, M.
Wiens, V.
Jaradeh, M.Y.

Title

Improving access to scientific literature with knowledge graphs : an experiment using library guidelines to judge information integrity

Source

Bibliothek: Forschung und Praxis. 44(2020) H.3, S.516-529

Year

2020

Abstract

The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually document-based-formerly printed on paper as a classic essay and nowadays as PDF. With around 2.5 million new research contributions every year, researchers drown in a flood of pseudo-digitized PDF publications. As a result research is seriously weakened. In this article, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage is that information represented in a knowledge graph is readable by machines and humans. As an example, we give an overview on the Open Research Knowledge Graph (ORKG), a service implementing this approach. For creating the knowledge graph representation, we rely on a mixture of manual (crowd/expert sourcing) and (semi-)automated techniques. Only with such a combination of human and machine intelligence, we can achieve the required quality of the representation to allow for novel exploration and assistance services for researchers. As a result, a scholarly knowledge graph such as the ORKG can be used to give a condensed overview on the state-of-the-art addressing a particular research quest, for example as a tabular comparison of contributions according to various characteristics of the approaches. Further possible intuitive access interfaces to such scholarly knowledge graphs include domain-specific (chart) visualizations or answering of natural language questions.

Content

Vgl.: DOI: https://doi.org/10.1515/bfp-2020-2042.

Theme

Wissensrepräsentation

Object

Open Research Knowledge Graph

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