Leibniz MMS Days 2022 - Abstract

Lorenz, Anna-Lena

The Open Research Knowledge Graph in Mathematics: Towards Machine Actionable Mathematical Knowledge

Scholarly knowledge is traditionally communicated via scientific articles, optimized for human cognition. Given the current proliferation of research contributions, this method is no longer sufficient. Machine assistance is needed to link the increasing amount of information in a meaningful way. In the Open Research Knowledge Graph (ORKG), the content of scientific publications is described semantically, i.e. in a machine-actionable manner. In this way, relevant information towards a research problem can be automatically found, linked and compared. This will provide researchers with an easier overview over the state-of-the-art for certain research questions. The structural science mathematics provides particularly suitable content for the ORKG: Its published prose is clear and dense from a linguistic point of view; many formulae are already machine interpretable to some extent. As a first step, literature reviews that compare (numerical) methods are ingested into the ORKG.