In this paper we motivate why it is crucial to associate linguistic information with ontologies
and why more expressive models, beyond the label systems implemented in RDF, OWL and …

In this paper we argue why it is necessary to associate linguistic information with ontologies
and why more expressive models, beyond RDFS, OWL and SKOS, are needed to capture …

Ontology learning techniques serve the purpose of supporting an ontology engineer in the
task of creating and maintaining an ontology. In this chapter, we present a comprehensive …

Increased availability of mobile computing, such as personal digital assistants (PDAs),
creates the potential for constant and intelligent access to up-to-date, integrated and …

In this paper we present the design, implementation and evaluation of SOBA, a system for
ontology-based information extraction from heterogeneous data resources, including plain …

The Multilingual Semantic Web has been in focus for over a decade. Multilingualism in
Linked Data and RDF has shown substantial adoption, but this is unclear for ontologies …

Although Arabic is the language of over two hundred million speakers, little has been
achieved in regards to computational Arabic resources, especially lexicons. Most of what …

In this chapter, we present ontology design patterns (ODPs), which are reusable modeling
solutions that encode modeling best practices. ODPs are the main tool for performing pattern …

The Open Linguistics Working Group (OWLG) is an initiative of experts from different fields
concerned with linguistic data, including academic linguistics (eg typology, corpus …

We revisit the notion of ontology localization, propose a new definition and clearly specify
the layers of an ontology that can be affected by the process of localizing it. We also work out …