EVENTSKG: A knowledge graph representation for top-prestigious computer science events metadata

Abstract

Digitization has made the preparation of manuscripts as well as the organization of scientific events considerably easier and efficient. In addition, data about scientific events is increasingly published on the Web, albeit often as raw dumps in unstructured formats, immolating its semantics and relationships to other data and thus restricting the reusability of the data for, e.g., subsequent analyses. Therefore, there is a great demand to represent this data in a semantic representation using Semantic Web technologies. In this paper, we present the EVENTSKG dataset to offer a comprehensive semantic descriptions of scientific events of six computer science communities for 40 top-prestigious event series over the last five decades. We created a new, publicly available and improved release of the EVENTSKG dataset as a unified knowledge graph based on our Scientific Events Ontology (SEO). It is of primary interest to event organizers, as it helps them to assess the progress of their event over time and compare it to competing events. Furthermore, it helps potential authors looking for venues to publish their work. We shed light on these events by analyzing the EVENTSKG data.