Towards Building Live Open Scientific Knowledge Graphs
Anh Le-Tuan, Carlos Franzreb, Danh Le-Phuoc, Sonja Schimmler, Manfred Hauswirth · Companion Proceedings of the Web Conference 2022 · 2022
Due to the large number and heterogeneity of data sources, it becomes increasingly difficult to follow the research output and the scientific discourse. For example, a publication listed on DBLP may be discussed on Twitter and its underlying data set may be used in a different paper published on arXiv. The scientific discourse this publication is involved in is divided among not integrated systems, and for researchers it might be very hard to follow all discourses a publication or data set may be involved in. Also, many of these data sources—DBLP, arXiv, or Twitter, to name a few—are often updated in real-time. These systems are not integrated (silos), and there is no system for users to query the content/data actively or, what would be even more beneficial, in a publish/subscribe fashion, i.e., a system would actively notify researchers of work interesting to them when such work or discussions become available.