Building a Semantic Model for Linking and Visualizing Patent Citations (SeMViPaC)

Abstract

Patents are a high-quality resource of information that is currently insufficiently leveraged. In times when continuously rising prices for basic knowledge access threaten to throttle academic research everywhere, this is a resource that can not be longer neglected. Thus, in the project we plan to extract and semantically describe citations from patents. Furthermore, we will establish linking and data integration between disparate data sources, i.e. linking patents with resources in the LOD (Linked Open Data) cloud. Based on the developed semantic citation model a visualization tool to explore and gain better insight and understanding of the extracted citation data will be developed and made available to the public.