Wissensgraphen: Interdisziplinäre Perspektiven für Linked Data in den Geistes- und Sozialwissenschaften

Abstract

Knowledge graphs and network approaches are an increasingly vibrant research topic in quite different disciplines. This article acknowledges their parallel development in applied and mathematical fields, and the various current approaches between computer science, mathematics, data science, and the humanities and social sciences. This gives rise to key interdisciplinary perspectives: first, network approaches in the humanities and social sciences need to be broader, as knowledge networks are already implicit in the use of Linked Data. Second, the methodological breadth of knowledge graphs, in which, for example, social networks can be conceived as knowledge graphs, results in new tools and new methods of analysis. In this respect, this paper is intended as a plea for interdisciplinary exchange and in-depth discussion of methods, algorithms, and Linked Data approaches.

Keywords

• wissensgraph
• linked data
• interdisziplinarität
• graphentheorie
• geisteswissenschaften