V.R. Benjamins

Bio: V.R. Benjamins is an academic researcher. The author has contributed to research in topics: IDEF5 & Applications of artificial intelligence. The author has an hindex of 2, co-authored 2 publications receiving 1989 citations.

What are ontologies, and why do we need them?

Abstract: This survey provides a conceptual introduction to ontologies and their role in information systems and AI. The authors also discuss how ontologies clarify the domain's structure of knowledge and enable knowledge sharing.

Mobile Big Data in the fight against COVID-19

Abstract: Abstract In this editorial, Guest Editors Richard Benjamins (Telefónica), Jeanine Vos (GSMA), and Stefaan Verhulst (Data & Policy Editor-in-Chief) draw insights from a set of peer-reviewed, open access articles in a Data & Policy special collection dedicated to the use of Telco Big Data Analytics for COVID-19.

Social and ethical challenges of the metaverse

Abstract: The metaverse is attracting a huge amount of attention as the next version of the internet, and companies are starting to explore the many new business opportunities it provides. However, based on experience with artificial intelligence, we know that there are also potential negative ethical and social consequences of the massive use of technology that must be dealt with. In this white paper [Social and ethical challenges of the metaverse. Preprint at https://www.telefonica.com/en/communication-room/the-social-andethical- challenges-of-the-metaverse/ (2022). Accessed Dec 2022], we briefly describe what the metaverse is, what technologies are part of its ecosystem, and where it comes from. We then focus on the potential societal/social and ethical risks of the metaverse. We argue that companies that are implementing the responsible use of AI are well prepared for the social and ethical risks of the metaverse. Not because they know the future, but because they have the right governance and culture in place to deal with such risks.

IoT-Based Smart Rehabilitation System

Abstract: Internet of Things (IoT) makes all objects become interconnected and smart, which has been recognized as the next technological revolution. As its typical case, IoT-based smart rehabilitation systems are becoming a better way to mitigate problems associated with aging populations and shortage of health professionals. Although it has come into reality, critical problems still exist in automating design and reconfiguration of such a system enabling it to respond to the patient's requirements rapidly. This paper presents an ontology-based automating design methodology (ADM) for smart rehabilitation systems in IoT. Ontology aids computers in further understanding the symptoms and medical resources, which helps to create a rehabilitation strategy and reconfigure medical resources according to patients' specific requirements quickly and automatically. Meanwhile, IoT provides an effective platform to interconnect all the resources and provides immediate information interaction. Preliminary experiments and clinical trials demonstrate valuable information on the feasibility, rapidity, and effectiveness of the proposed methodology.

Model Driven Architecture and Ontology Development

Abstract: Part I: Basics - Knowledge Representation - Ontologies - Semantic Web - Model Driven Architecture - Modeling Spaces.- Part II: Model Driven Architecture and Ontologies - Software Engineering Approaches for Ontology Development - MDA-Based Ontology Infrastructure - Ontology Definition Metamodel - Ontology UML Profile - Mappings of MDA Based Languages and Ontologies.- Part III: Application - Using UML Tools for Ontology Modeling - MDA Based Ontology Platform: AIR - Ontology Examples.

Using Ontological Engineering to Overcome Common AI-ED Problems

Abstract: This paper discusses long-term prospects of AI-ED research with the aim of giving a clear view of what we need for further promotion of the research from both the AI and ED points of view. An analysis of the current status of AI-ED research is done in the light of intelligence, conceptualization, standardization and theory-awareness. Following this, an ontology-based architecture with appropriate ontologies is proposed. Ontological engineering of IS/ID is next discussed followed by a road map towards an ontology-aware authoring system. Heuristic design patterns and XML-based documentation are also discussed.