Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

The quality of a Knowledge Graph (also known as Linked Data) is an important aspect to
indicate its fitness for use in an application. Several quality dimensions are identified, such …

Abstract Answering complex First-Order Logical (FOL) queries on large-scale incomplete
knowledge graphs (KGs) is an important yet challenging task. Recent advances embed …

Wikidata has been increasingly adopted by many communities for a wide variety of
applications, which demand high-quality knowledge to deliver successful results. In this …

Launched in 2012, Wikidata has already become a success story. It is a collaborative
knowledge graph, whose large community has produced so far data about more than 55 …

General-purpose knowledge bases (KBs) are a cornerstone of knowledge-centric AI. Many
of them are constructed pragmatically from web sources and are thus far from complete. This …

Content gaps in knowledge graphs impact downstream applications. Semantic Web
researchers have studied them mainly in relation to data quality or ontology evaluation, for …

Purpose The purpose of this paper is to review the current status of research on Wikidata
and, in particular, of articles that either describe applications of Wikidata or provide empirical …

Wikidata has become one of the most prominent open knowledge graphs (KGs) on the Web.
Relying on a community of users with different expertise, this cross-domain KG is directly …

Information related to the COVID-19 pandemic ranges from biological to bibliographic, from
geographical to genetic and beyond. The structure of the raw data is highly complex, so …