Remarkable Objects: Supporting Collaboration in a Creative Environment

In this paper, we report the results of a field trial of a Ubicomp system called CAM that is aimed at supporting and enhancing collaboration in a design studio environment. CAM uses a mobile-tagging application which allows designers to collaboratively store relevant information onto their physical design objects in the form of messages, annotations and external web links. The purpose of our field trial was to explore the role of augmented objects in supporting and enhancing creative work. Our results show that CAM was used not only used to support participants’ mutual awareness and coordination but also to facilitate designers in appropriating their augmented design objects to be explorative, extendable and playful supporting creative aspects of design work. In general, our results show how CAM transformed static design objects into ‘remarkable’ objects that made the creative and playful side of cooperative design visible

Mental health and the impact of ubiquitous technologies

This Theme issue focuses on the emerging research of ubiquitous technologies to support mental health. So far, the majority of work presented in the field of ubiquitous healthcare has focused on supporting people affected by somatic diseases. However, increasing number of diseases affecting mental health has prompted research on technologies to support people suffering from these diseases. This Theme issue provides a number of examples of research on the potential impact of ubiquitous technologies in the field of mental health

The Java Context Awareness Framework (JCAF) – A Service Infrastructure and Programming Framework for Context-Aware Applications

Abstract. Context-awareness is a key concept in ubiquitous computing. But to avoid developing dedicated context-awareness sub-systems for specific applica-tion areas there is a need for more generic programming frameworks. Such frame-works can help the programmer to develop and deploy context-aware applications faster. This paper describes the Java Context-Awareness Framework – JCAF, which is a Java-based context-awareness infrastructure and programming API for creating context-aware computer applications. The paper presents the design principles behind JCAF, its runtime architecture, and its programming API. The paper presents some applications of using JCAF in three different applications and discusses lessons learned from using JCAF.

A Semiotic Approach for Guiding the Visualizing of Time and Space in Enterprise Models

Part 2: Organizational Semiotics and ApplicationsInternational audienceEven if geographical aspects such as location are included already in the Zachman framework (as the where-perspective), it is not common to have detailed geographical aspects included in enterprise models. Cartography is the science of visualizing geographical information in maps. Traditionally the field has not included conceptual relationships that you find in enterprise models. Both cartography and enterprise modelling have developed guidelines for obtaining high quality visualizations. SEQUAL is a quality framework developed for understanding quality of models and modelling languages based on semiotic theory. In cartography such frameworks are not common. An adaptation of SEQUAL in the context of cartographic maps called MAPQUAL has been presented earlier. Differences between quality of maps and quality of conceptual models, pointing to guidelines for combined representations have been performed, and we try in this paper to investigate the utility of these guidelines in a simple trial. The result of the trial is presented, indicating that it is possible to represent conceptual, temporal, and spatial aspects in the same models in many ways, but that the choice of main perspective should depend on participant appropriateness

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

The SOFIA Pilot Trial:A cluster-randomized trial of coordinated, co-produced care to reduce mortality and improve quality of life in people with severe mental illness in the general practice setting

Abstract Background People with severe mental illness (SMI) have an increased risk of premature mortality, predominantly due to somatic health conditions. Evidence indicates that primary and tertiary prevention and improved treatment of somatic conditions in patients with SMI could reduce this excess mortality. This paper reports a protocol designed to evaluate the feasibility of a coordinated co-produced care program (SOFIA model, a Danish acronym for Severe Mental Illness and Physical Health in General Practice) in the general practice setting to reduce mortality and improve quality of life in patients with severe mental illness. Methods The SOFIA pilot trial is designed as a cluster randomized controlled trial targeting general practices in two regions in Denmark. We aim to include 12 practices, each of which is instructed to recruit up to 15 community-dwelling patients aged 18 and older with SMI. Practices will be randomized by a computer in a ratio of 2:1 to deliver a coordinated care program or usual care during a 6-month study period. A randomized algorithm is used to perform randomization. The coordinated care program includes educational training of general practitioners and their clinical staff educational training of general practitioners and their clinical staff, which covers clinical and diagnostic management and focus on patient-centered care of this patient group, after which general practitioners will provide a prolonged consultation focusing on individual needs and preferences of the patient with SMI and a follow-up plan if indicated. The outcomes will be parameters of the feasibility of the intervention and trial methods and will be assessed quantitatively and qualitatively. Assessments of the outcome parameters will be administered at baseline, throughout, and at end of the study period. Discussion If necessary the intervention will be revised based on results from this study. If delivery of the intervention, either in its current form or after revision, is considered feasible, a future, definitive trial to determine the effectiveness of the intervention in reducing mortality and improving quality of life in patients with SMI can take place. Successful implementation of the intervention would imply preliminary promise for addressing health inequities in patients with SMI. Trial registration The trial was registered in Clinical Trials as of November 5, 2020, with registration number NCT04618250 . Protocol version: January 22, 2021; original versio