1,720,976 research outputs found
An evaluation of agile Ontology Engineering Methodologies for the digital transformation of companies
No full textOntologies are increasingly recognised among the key enablers of the digital transformation of knowledge management processes, but still with a low level of adoption in manufacturing companies. Because ontologies and underlying technologies are complex, Ontology Engineering Methodologies (OEMs) provide a set of guidelines to move from an informal to a formal representation of the company's knowledge base. This study evaluates three agile OEMs, i.e. UPONLite, SAMOD and RapidOWL, in terms of their process and outcome features, i.e. the OEM steps and the expected quality of the ontological models produced. The assessment is performed from the viewpoint of developers of ontology-based technologies in real industrial use cases. Results show that the three agile OEMs reflect different features to effectively support the digital transformation of companies' knowledge management; thus, they cannot be interchangeable. UPONLite is more effective in contexts where there is a lack of skills in OE, with the need for a structured approach in involving domain experts and generating documentation. SAMOD requires a more extended development period, but with several cycles that allow to map different types of knowledge and enable a “try-and-learn” approach. Conversely, RapidOWL lacks a structured sequence of modelling activities and encourages developers to be creative, but at the same time requires higher expertise in OE. Thus, companies and personnel dedicated to OE should choose the methodology according to the main aims guiding their digitalisation process, the current development status, and the level of expertise
Collaborative Ontology Engineering Methodologies for the Development of Decision Support Systems: Case Studies in the Healthcare Domain
Full text linkNew models and technological advances are driving the digital transformation of healthcare systems. Ontologies and Semantic Web have been recognized among the most valuable solutions to manage the massive, various, and complex healthcare data deriving from different sources, thus acting as backbones for ontology-based Decision Support Systems (DSSs). Several contributions in the literature propose Ontology engineering methodologies (OEMs) to assist the formalization and development of ontologies, by providing guidelines on tasks, activities, and stakeholders' participation. Nevertheless, existing OEMs differ widely according to their approach, and often lack of sufficient details to support ontology engineers. This paper performs a meta-review of the main criteria adopted for assessing OEMs, and major issues and shortcomings identified in existing methodologies. The key issues requiring specific attention (i.e., the delivery of a feasibility study, the introduction of project management processes, the support for reuse, and the involvement of stakeholders) are then explored into three use cases of semantic-based DSS in health-related fields. Results contribute to the literature on OEMs by providing insights on specific tools and approaches to be used when tackling these issues in the development of collaborative OEMs supporting DSS
Natural resources in health tourism: A systematic literature review
Full text linkNatural resources are recognized among the key determinants for the improvement of wellness, and thus the development and sustainability of health tourism destinations. This study applied a systematic review to investigate the contributions mapping and analyzing under different perspectives the value of the natural resources of a destination and related activities for health tourism. The main research topics identified from a review of 52 papers include the analysis and exploitation of natural resources in health tourism, the nature-based factors considered in clustering of tourists and their motivations, the development of value offer and marketing, as well as the cultural issues. Research gaps and future directions are summarized in a research agenda laying the foundations for the development of a multidisciplinary research stream focused on nature-based health tourism. Results also represent a key reference for managers and policy makers to identify key issues, areas of intervention and practices for industry development in the health tourism destinations through an effective and sustainable exploitation of natural resources
HEALPS 2: Tourism Based on Natural health Resources for the Development of Alpine Regions
No full textThe HEALPS 2 project is using digital solutions and stakeholder engagement to unlock the potential of health tourism in the alpine regions
A review of domain ontologies for disability representation
No full textHealthcare 5.0 is a research trend promoting a patient-centric approach leveraging Artificial Intelligence (AI)-based solutions. It aims to enhance care and quality of life for all patients, including those with a disability. However, when applied to the health sector, AI may be perceived as not transparent: the Explainable AI (xAI) paradigm attempts to solve this issue by providing more understandable, reliable, and human-interpretable AI-based applications. In a field such as disability – characterized by various impairments, limitations in performing activities, or other kinds of restrictions – the possibility to rely on computable representations of domain knowledge in the form of ontologies can support the development of xAI for healthcare. This work proposes a systematic literature review to identify which disabilities are currently represented in domain ontologies, examining which applicative contexts the ontologies were developed for. This review also investigates how the domain ontologies are modelled, underlining several relevant aspects that may foster their adoption in xAI systems. The review process results allow for shedding light on the main disabilities represented in ontologies, tracing the research trends that were at the basis of their development. Results also enable the identification of research lines that can support semantic interoperability – thus enabling ontologies to play a significant role in explaining decision processes performed by AI-based systems in healthcare
A novel agile ontology engineering methodology for supporting organizations in collaborative ontology development
Full text linkOntologies can represent technological enablers for knowledge elicitation and management in different kinds of organizations, especially with the exponential growth of sources and types of data fostered by digital transformation. However, their adoption in business applications is still limited, with existing Ontology Engineering Methodologies (OEMs) lacking adequate support during knowledge elicitation, authoring and reuse phases. This paper introduces a novel agile ontology engineering methodology (AgiSCOnt) to support ontologists (especially novice ones) in ontology development workflow, fostering collaboration with domain experts in an iterative, flexible and customizable approach. AgiSCOnt combines macro-level instructions with micro-level guidance, leveraging existing techniques and a management framework to help novice ontologists throughout the whole ontology engineering process. The methodology is compared to existing OEMs and assessed with three other agile methodologies (UPONLite, SAMOD, and RapidOWL). The evaluation is conducted with a sample of novice ontologists in a learning environment on Industry 4.0 technologies. Both the development process with a methodology from a user perspective and the quality of the developed ontologies were considered in the evaluation. Preliminary results show that AgiSCOnt effectively supports authoring and reuse, with developed ontologies of good quality. It is perceived as clear and simple, while being flexible and adaptable enough, thus supporting knowledge management and sharing in industrial organizations through the documentation of the ontologies
Roomfort: An ontology-based comfort management application for hotels
Full text linkBusiness traveling is attracting growing attention due to the expansion of international markets. This fact calls for an increasing attention of the tourism sector toward the needs of business travellers, who often require services that are different from the ones desired by leisure tourists. The application of smart solutions coming from Context Awareness and Ambient Intelligence aimed at promoting guests' comfort and well-being, also in cases in which they have special needs, represents a promising solution to tackle business travellers' requirements and thus, to increase hotels attractiveness and incomes. In this context, this work introduces RoomFort, a smart comfort management system aimed at enhancing comfort of hotel room guests and leveraging on semantic representations of comfort, environment, and sensors. RoomFort provides a set of domain ontologies to formalize comfort-related metrics and to exploit the automatic reasoning capabilities provided by Semantic Web technologies, while gathering data through a network of sensors to ensure guests are provided with tailored comfort profiles during their stays in the hotel. Particular focus has been placed on visual comfort, since indoor lighting features constitute one of the main factors influencing the two main activities that most business travellers accomplish in their hotel room: working and relaxing
A Semantic-Based Collaborative Ambient-Assisted Working Framework
No full textOver the last two decades an utmost interest has been shown to Ambient Intelligence (AmI), with most of the related applications focusing on home settings. However, considering the ever-increasing number of ageing people occupied in the workforce, the Ambient-Assisted Working (AAW) is arguably at the beginning of its development. For an effective development and integration of AAW systems, cooperation among and shared knowledge from different stakeholders are required. This work proposes an AmI framework leveraging on Semantic Web technologies to foster employees’ wellbeing. The AAW framework makes use of a domain ontology, outcome of the cooperation between different stakeholders (employer, employees and environment) to adjust, modify and correct indoor comfort metrics in workplaces. In this paper, the proposed framework’s architecture and its underlying ontology are described, along with a use case scenario that illustrates how collaboratively modelled data can actively support ageing workers
Comfont: A semantic framework for indoor comfort and energy saving in smart homes
No full textThis work introduces ComfOnt, a semantic framework developed within the context of ambient assisted living, context awareness, and ambient intelligence Italian research projects. ComfOnt leverages knowledge regarding Smart Home inhabitants and their particular needs, the devices deployed inside the domestic environment (appliances, sensors, and actuators), the amount of their energy consumption, and indoor comfort metrics to provide dwellers with customized services. Developed reusing widely adopted ontologies, ComfOnt aims at providing inhabitants with the possibility of having personalized indoor comfort in their living environments and at helping them in scheduling their daily activities requiring appliances; in fact, the proposed semantic framework enables the representation of appliances’ energy consumption and the energy profile of the Smart Home, thus assisting the dwellers in avoiding power cuts and fostering energy savings. ComfOnt serves as a knowledge base for a prototypical application (DECAM) dedicated to Smart Home inhabitants; the architecture and the functionalities of DECAM are here presented
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