Despite improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows in science publication have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. In this article, we present first steps towards representing scholarly knowledge semantically with knowledge graphs. We expand the currently popular RDF graph-based knowledge representation formalism to capture annotations, such as provenance information and describe how to manage such knowledge in a graph data base. We report on the results of a first experimental evaluation of the concept and its implementations with the participants of an international conference.
翻译:科学出版物中以文件为导向的工作流程已达到了充分性的极限,正如最近关于科学文献日益扩散、同行审查不足和可复制危机的讨论所强调的那样。在本篇文章中,我们介绍了以知识图代表学术知识的初步步骤。我们扩大了目前流行的以RDF图表为基础的知识形式主义,以捕捉说明,例如出处信息,并描述如何在图表数据库中管理这种知识。我们向国际会议的与会者报告了首次试验性评价概念及其实施情况的结果。