Kategorie: Data Science

NLP Should Go Beyond Commonsense Knowledge

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NLP technology is all-pervasive for commonsense knowledge. There are many causes for this. Most of the internet and its data is about commonsense knowledge and world events, so NLP technology is developed over the data domain that is most easily available. But what about the scholarly domain with its rapidly growing body of knowledge produced worldwide? These are those specialized domains of knowledge in Science, Technology, Engineering, and Mathematics (STEM), all of which open up countless doors for NLP.

The opportunities are endless!

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Summary of the 1st ORKG Curation Grant Program

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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.

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NLP Contributions Graph: A Call for Participation

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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!

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The Future of Scholarly Communication Survey: Preliminary Findings

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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.

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