Kategorie: Data Science

Summary of the 1st ORKG Curation Grant Program

In 2021, we started our first curation grant program. 9 researchers from various fields of science, engineering and computer science earned a grant to push their field’s open science efforts and curate ORKG content. With over 150 Comparisons and 12 Reviews created, the program was an overwhelming success. But not only the grantees learned something: Due to the close contact to the development team, we got valuable feedback that in parts already made its way into today’s version of the ORKG and will be a basis for constant improvement.

NLP Contributions Graph: A Call for Participation

In the tipping scale of activities toward the digitalization of scholarly articles, next-generation digital library frameworks such as the Open Research Knowledge Graph, targeting scholarly contributions’ highlights, are already here! We have created the NLPContributionGraph Shared Task that formalizes the building of such a scholarly contributions-focused graph over Natural Language Processing articles as an automated task. If you are eager to build a machine learner, we have the annotated scholarly contributions’ graph data for you—come join us in this endeavor!

The Future of Scholarly Communication Survey: Preliminary Findings

Compared to the dramatic transformations of other publishing and communication domains, scholarly communication has not changed much over the last decades and centuries. To what degree are researchers satisfied with the current situation? In order to explore this topic, TIB launched a survey on information flows in science.

#EUvsVirus: Covid-19 Bioassays in the Open Research Knowledge Graph

The #EuVsVirus Pan-European Hackathon was organized as a full remote event coordinated over Slack channels over the weekend of April 24-26. Our team ‘TIB ORKG’ was a team of six people who met online in one of the 500 Slack channels created for the hackathon. We grouped on a common agreement: scholarly articles structured in the ORKG was a great idea to help researchers easily comprehend the articles’ content.