Why are ontologies not reused across the same domain?

Even though one of the main characteristics of ontologies has always been claimed to be their reusability, throughout this paper it will be shown that ontology reuse across a given domain is not a consolidated practice. We have carried out a statistical study on ontology reuse in the ontologies collected in Linked Open Vocabularies (LOV), in addition to a particular analysis of a use case. The results of the present work show that, when building an ontology, the heterogeneity between the needed conceptualization and that of available ontologies, as well as the deficiencies in some of such ontologies (concerning documentation, licensing, etc.) are important obstacles for reusing ontologies of the same domain of the ontology under development. A possible approach to lessen these problems could be the creation of communities similar to open software ones in charge of developing and maintaining ontologies

Linked Data

In this chapter, an overview of the current state of the art, future trends and conceptual underpinnings of Linked Data in the field of Architecture and Construction is provided. A short brief introduction to the fundamental concepts of Linked Data and the Semantic Web is followed by practical applications in the building sector that include the use of OpenBIM information exchange standards and the creation of dynamic model extensions with external vocabularies and data sets. An introduction into harnessing the Linked Data standards for domain-specific, federated multi-models and the use of well-established query and reasoning mechanisms to address industry challenges is introduced. The chapter is concluded by a discussion of current developments and future trends

A survey on ontologies for human behavior recognition

Describing user activity plays an essential role in ambient intelligence. In this work, we review different methods for human activity recognition, classified as data-driven and knowledge-based techniques. We focus on context ontologies whose ultimate goal is the tracking of human behavior. After studying upper and domain ontologies, both useful for human activity representation and inference, we establish an evaluation criterion to assess the suitability of the different candidate ontologies for this purpose. As a result, any missing features, which are relevant for modeling daily human behaviors, are identified as future challenges