User interface design patterns and ontology models for adaptive mobile applications

• Published in: Personal and ubiquitous computing Vol. 26; no. 6; pp. 1395 - 1411
• Main Authors: Braham, Amani, Buendía, Félix, Khemaja, Maha, Gargouri, Faiez
• Format: Journal Article
• Language: English
• Published: London Springer London 01.12.2022; Springer Nature B.V
• Subjects: Adaptation; Ambient intelligence; Applications programs; Computer architecture; Computer Science; Context; Electronic devices; Inference; Knowledge bases (artificial intelligence); Knowledge representation; Mobile Computing; Ontology; Original Article; People with disabilities; Personal Computing; Ubiquitous computing; User interface; User interfaces; User Interfaces and Human Computer Interaction; User needs; Design patterns; Inference rules; User case scenarios; Mobile applications; Adaptive user interface; Ontology models; Runtime pattern selection
• ISSN: 1617-4909; 1617-4917
• DOI: 10.1007/s00779-020-01481-5

Mobile applications are an essential element in pervasive and ubiquitous computing, and they face many challenges during their generation process from the analysis of user needs to the design of specific mobile interfaces and their development in several technological platforms. Moreover, the rise of Ambient Intelligent and context-aware environments also introduces multiple interaction aspects to be considered when using mobile devices in this kind of scenarios. The present work seeks to examine the role of design patterns and ontology models in order to help with the generation of mobile applications, which can be adapted at runtime to the various user needs, different context scenarios, interactive design modes, or technology requirements. In this way, an ontology-based framework is introduced to represent, design, and support the adaptation of user interfaces in mobile applications by using design patterns according to these user needs or preferences and the context around them. This framework provides developers with a client-server architecture that enables the access to an expert knowledge base of user, context, and pattern information together with a set of inference rules, which allow the dynamic selection of interface design patterns and the runtime adaptation of the user interface features. These ontology models and inference rules are key components of the proposed framework, and their implementation has helped to produce an example of mobile application supporting user interface adaptation processes for disabled people, which can be required in Ambient Intelligent environments. Three examples of user scenarios have been considered to assess the framework potential, and usability dimensions have been tested by a limited set of users through the produced mobile application, making the usefulness of generated adaptive user interfaces apparent.