Applied Ontology

We present a formal Arabic wordnet built on the basis of a carefully designed ontology hereby referred to as the Arabic Ontology. The ontology provides a formal representation of the concepts that the Arabic terms convey, and its content was built with ontological analysis in mind, and benchmarked to scientific advances and rigorous knowledge sources as much as this is possible, rather than to only speakers’ beliefs as lexicons typically are. A comprehensive evaluation was conducted thereby demonstrating that the current version of the top-levels of the ontology can top the majority of the Arabic meanings. The ontology consists currently of about 1,800 well-investigated concepts in addition to 16,000 concepts that are partially validated. The ontology is accessible and searchable through a lexicographic search engine (http://ontology.birzeit.edu) that also includes about 150 Arabic-multilingual lexicons, and which are being mapped and enriched using the ontology. The ontology is fully mapped with Princeton WordNet, Wikidata, and other resources.

Smart communities have recently gained much attention. Researchers have been trying to tackle a number of challenges faced by smart communities. Interoperability is one key challenge that occurs due to different systems using different knowledge representations. To solve interoperability problems, ontologies are seen as a promising solution as they provide a commonly agreed vocabulary for representing data that are understandable by stakeholders of smart communities. Smart communities make use of Internet of Things (IoT) and ubiquitous networks to support communication among objects and devices in such environments. Smart campuses are examples of smart communities. Recently, many articles related to ontologies focusing on smart communities and smart campuses in IoT environments, have been published. This paper presents a Systematic Literature Review that has been conducted using Google Scholar. 18 ontologies for smart communities/smart campuses have been identified and analyzed out of 341 articles from year 2010 to 2019. The review classifies the ontologies in terms of domain, ontologies being reused, availability online, limitations, language adopted and coverage. It additionally discusses on the standards, the level of expressiveness, the ontology development approaches and methodologies adopted by the identified ontologies. Our analysis shows that the identified ontologies have been developed based on different ontological commitments. None of them have come up with a core semantic model that models different collaborating domains in a smart campus such as smart learning, smart management, smart governance, smart room, smart health, smart library and smart parking among others and that enhances cross-domain interoperability in a such an environment. Further details on our findings are presented and discussed in the paper.

The paper discusses the problem of diachronic criteria of identity for historic localities. We argue that such criteria are needed not just for the sake of ontological clarity but also are indispensable for database management and maintenance. Our survey of the current research in database management and engineering ontology literature found no satisfactory candidates thereof. Therefore we attempt to search for such criteria in the historic-geographical scholarship by exposing the ontological assumptions the researchers made there and by stating them explicitly. This attempt consisted of us presenting a number of brief scenarios taken from the historical studies whereby localities are claimed to maintain their identity through certain types of change or to be destroyed due to other types of change. Generalising these cases we provide a tentative formulation of the criterion and discuss its limitations.

Standards and ontologies for manufacturing understand resources differently. Because of this heterogeneity, misunderstandings arise concerning the basic features that characterize them. The purpose of the paper is to investigate how to ontologically model resources with the goal of facilitating the development of knowledge representation models for manufacturing. By reviewing the literature, we discuss and compare three approaches for the representation of resources depending on whether they are conceived in connection to either processes, plans or goals. By addressing the advantages and shortcomings of each view, we present a unifying perspective to enable the modeling of resources in an integrated manner. In this way, the intended meanings of the used notions are harmonized and, as a result, one can facilitate multiple experts to interact e.g., via data sharing and/or data integration procedures. Differently, by keeping three separated views, there is no guarantee that data coming from different parties will share common meanings even if the same terms are used. By the end of the paper, we present a case study to show the application of our approach and to compare it with an existing ontology for manufacturing.