The increasing availability of semantic data has substantially enhanced Web applications.
Semantic data such as RDF data is commonly represented as entity-property-value triples …

As large-scale graphs become more widespread, more and more computational challenges
with extracting, processing, and interpreting large graph data are being exposed. It is …

Automatic knowledge graph (KG) construction is widely used in industry for data integration
and access, and there are several approaches to enable (semi-) automatic construction of …

Industrial analytics that includes among others equipment diagnosis and anomaly detection
heavily relies on integration of heterogeneous production data. Knowledge Graphs (KGs) as …

Ontology-driven conceptual models are widely used to capture information about complex
and critical domains. Therefore, it is essential for these models to be comprehensible and …

The large volume of open data on the Web is expected to be reused and create value.
Finding the right data to reuse is a non-trivial task addressed by the recent dataset search …

Abstract The adoption of Knowledge Graphs (KGs) by public and private organizations to
integrate and publish data has increased in recent years. Ontologies play a crucial role in …

The continuous and rapid growth of highly interconnected datasets, which are both
voluminous and complex, calls for the development of adequate processing and analytical …

This study presents a comprehensive framework to enhance Wikidata as an open and
collaborative knowledge graph by integrating Open Biological and Biomedical Ontologies …

Triple-structured open data creates value in many ways. However, the reuse of datasets is
still challenging. Users feel difficult to assess the usefulness of a large dataset containing …