Knowledge Graphs (KGs) are widely used to represent heterogeneous domain knowledge
on the Web and within organizations. Various methods exist to manage KGs and ensure the …

For over 50 years researchers and practitioners have searched for ways to elicit and
formalize expert knowledge to support AI applications. Expert systems and knowledge …

Knowledge graphs are only useful if they satisfy the requirements of those applications in
terms of quality. In this in-use experience paper, we present our approach and tools for …

The performance of applications, such as personal assistants and search engines, relies on
high-quality knowledge bases, aka Knowledge Graphs (KGs). To ensure their quality one …

Tourism is one of the most critical sectors of the global economy. Due to its heterogeneous
and fragmented nature, it provides one of the most suitable use cases for knowledge graphs …

Currently, knowledge networks develop to establish common data spaces. A common data-
space offers mutual exchange and reusability for data sources and their derived information …

Purpose This study aims to adjust Thesis-type properties on Schema. org using metadata
models and standards (MS)(Bibframe, electronic thesis and dissertations [ETD]-MS …

The first step in building a knowledge graph is creating knowledge from heterogeonous
sources. First, we explain how to create terminological knowledge with a focus on ontologies …

Linked-Data (LD) is a paradigm that utilises the RDF triplestore to describe numerous pieces
of knowledge linked together. When an entity is retrieved in LD, its associated data becomes …

RESUMEN (en español) Esta tesis se plantea inicialmente como una búsqueda de sistemas
capaces de extraer RDF shapes a partir de minería de contenido textual expresados en …