Open AccessArticle
Visual Analysis of Stochastic Trajectory Ensembles in Organic Solar Cell Design
Informatics 2017, 4(3), 25; doi:10.3390/informatics4030025 -
Abstract
We present a visualization system for analyzing stochastic particle trajectory ensembles, resulting from Kinetic Monte-Carlo simulations on charge transport in organic solar cells. The system supports the analysis of such trajectories in relation to complex material morphologies. It supports the inspection of individual
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We present a visualization system for analyzing stochastic particle trajectory ensembles, resulting from Kinetic Monte-Carlo simulations on charge transport in organic solar cells. The system supports the analysis of such trajectories in relation to complex material morphologies. It supports the inspection of individual trajectories or the entire ensemble on different levels of abstraction. Characteristic measures quantify the efficiency of the charge transport. Hence, our system led to better understanding of ensemble trajectories by: (i) Capturing individual trajectory behavior and providing an ensemble overview; (ii) Enabling exploration through linked interaction between 3D representations and plots of characteristics measures; (iii) Discovering potential traps in the material morphology; (iv) Studying preferential paths. The visualization system became a central part of the research process. As such, it continuously develops further along with the development of new hypothesis and questions from the application. Findings derived from the first visualizations, e.g., new efficiency measures, became new features of the system. Most of these features arose from discussions combining the data-perspective view from visualization with the physical background knowledge of the underlying processes. While our system has been built for a specific application, the concepts translate to data sets for other stochastic particle simulations. Full article
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Open AccessArticle
Big Data Management with Incremental K-Means Trees–GPU-Accelerated Construction and Visualization
Informatics 2017, 4(3), 24; doi:10.3390/informatics4030024 -
Abstract
While big data is revolutionizing scientific research, the tasks of data management and analytics are becoming more challenging than ever. One way to remit the difficulty is to obtain the multilevel hierarchy embedded in the data. Knowing the hierarchy enables not only the
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While big data is revolutionizing scientific research, the tasks of data management and analytics are becoming more challenging than ever. One way to remit the difficulty is to obtain the multilevel hierarchy embedded in the data. Knowing the hierarchy enables not only the revelation of the nature of the data, it is also often the first step in big data analytics. However, current algorithms for learning the hierarchy are typically not scalable to large volumes of data with high dimensionality. To tackle this challenge, in this paper, we propose a new scalable approach for constructing the tree structure from data. Our method builds the tree in a bottom-up manner, with adapted incremental k-means. By referencing the distribution of point distances, one can flexibly control the height of the tree and the branching of each node. Dimension reduction is also conducted as a pre-process, to further boost the computing efficiency. The algorithm takes a parallel design and is implemented with CUDA (Compute Unified Device Architecture), so that it can be efficiently applied to big data. We test the algorithm with two real-world datasets, and the results are visualized with extended circular dendrograms and other visualization techniques. Full article
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Open AccessArticle
Constructing Interactive Visual Classification, Clustering and Dimension Reduction Models for n-D Data
Informatics 2017, 4(3), 23; doi:10.3390/informatics4030023 -
Abstract
Abstract: The exploration of multidimensional datasets of all possible sizes and dimensions is a long-standing challenge in knowledge discovery, machine learning, and visualization. While multiple efficient visualization methods for n-D data analysis exist, the loss of information, occlusion, and clutter continue to be
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Abstract: The exploration of multidimensional datasets of all possible sizes and dimensions is a long-standing challenge in knowledge discovery, machine learning, and visualization. While multiple efficient visualization methods for n-D data analysis exist, the loss of information, occlusion, and clutter continue to be a challenge. This paper proposes and explores a new interactive method for visual discovery of n-D relations for supervised learning. The method includes automatic, interactive, and combined algorithms for discovering linear relations, dimension reduction, and generalization for non-linear relations. This method is a special category of reversible General Line Coordinates (GLC). It produces graphs in 2-D that represent n-D points losslessly, i.e., allowing the restoration of n-D data from the graphs. The projections of graphs are used for classification. The method is illustrated by solving machine-learning classification and dimension-reduction tasks from the domains of image processing, computer-aided medical diagnostics, and finance. Experiments conducted on several datasets show that this visual interactive method can compete in accuracy with analytical machine learning algorithms. Full article
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Open AccessArticle
PERSEUS-HUB: Interactive and Collective Exploration of Large-Scale Graphs
Informatics 2017, 4(3), 22; doi:10.3390/informatics4030022 -
Abstract
Graphs emerge naturally in many domains, such as social science, neuroscience, transportation engineering, and more. In many cases, such graphs have millions or billions of nodes and edges, and their sizes increase daily at a fast pace. How can researchers from various domains
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Graphs emerge naturally in many domains, such as social science, neuroscience, transportation engineering, and more. In many cases, such graphs have millions or billions of nodes and edges, and their sizes increase daily at a fast pace. How can researchers from various domains explore large graphs interactively and efficiently to find out what is ‘important’? How can multiple researchers explore a new graph dataset collectively and “help” each other with their findings? In this article, we present Perseus-Hub, a large-scale graph mining tool that computes a set of graph properties in a distributed manner, performs ensemble, multi-view anomaly detection to highlight regions that are worth investigating, and provides users with uncluttered visualization and easy interaction with complex graph statistics. Perseus-Hub uses a Spark cluster to calculate various statistics of large-scale graphs efficiently, and aggregates the results in a summary on the master node to support interactive user exploration. In Perseus-Hub, the visualized distributions of graph statistics provide preliminary analysis to understand a graph. To perform a deeper analysis, users with little prior knowledge can leverage patterns (e.g., spikes in the power-law degree distribution) marked by other users or experts. Moreover, Perseus-Hub guides users to regions of interest by highlighting anomalous nodes and helps users establish a more comprehensive understanding about the graph at hand. We demonstrate our system through the case study on real, large-scale networks. Full article
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Open AccessArticle
Modeling the Construct of an Expert Evidence-Adaptive Knowledge Base for a Pressure Injury Clinical Decision Support System
Informatics 2017, 4(3), 20; doi:10.3390/informatics4030020 -
Abstract
The selection of appropriate wound products for the treatment of pressure injuries is paramount in promoting wound healing. However, nurses find it difficult to decide on the most optimal wound product(s) due to limited live experiences in managing pressure injuries resulting from successfully
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The selection of appropriate wound products for the treatment of pressure injuries is paramount in promoting wound healing. However, nurses find it difficult to decide on the most optimal wound product(s) due to limited live experiences in managing pressure injuries resulting from successfully implemented pressure injury prevention programs. The challenges of effective decision-making in wound treatments by nurses at the point of care are compounded by the yearly release of wide arrays of newly researched wound products into the consumer market. A clinical decision support system for pressure injury (PI-CDSS) was built to facilitate effective decision-making and selection of optimal wound treatments. This paper describes the development of PI-CDSS with an expert knowledge base using an interactive development environment, Blaze Advisor. A conceptual framework using decision-making and decision theory, knowledge representation, and process modelling guided the construct of the PI-CDSS. This expert system has incorporated the practical and relevant decision knowledge of wound experts in assessment and wound treatments in its algorithm. The construct of the PI-CDSS is adaptive, with scalable capabilities for expansion to include other CDSSs and interoperability to interface with other existing clinical and administrative systems. The algorithm was formatively evaluated and tested for usability. The treatment modalities generated after using patient-specific assessment data were found to be consistent with the treatment plan(s) proposed by the wound experts. The overall agreement exceeded 90% between the wound experts and the generated treatment modalities for the choice of wound products, instructions, and alerts. The PI-CDSS serves as a just-in-time wound treatment protocol with suggested clinical actions for nurses, based on the best evidence available. Full article
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Open AccessArticle
Visual Exploration of Large Multidimensional Data Using Parallel Coordinates on Big Data Infrastructure
Informatics 2017, 4(3), 21; doi:10.3390/informatics4030021 -
Abstract
The increase of data collection in various domains calls for an adaptation of methods of visualization to tackle magnitudes exceeding the number of available pixels on screens and challenging interactivity. This growth of datasets size has been supported by the advent of accessible
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The increase of data collection in various domains calls for an adaptation of methods of visualization to tackle magnitudes exceeding the number of available pixels on screens and challenging interactivity. This growth of datasets size has been supported by the advent of accessible and scalable storage and computing infrastructure. Similarly, visualization systems need perceptual and interactive scalability. We present a complete system, complying with the constraints of aforesaid environment, for visual exploration of large multidimensional data with parallel coordinates. Perceptual scalability is addressed with data abstraction while interactions rely on server-side data-intensive computation and hardware-accelerated rendering on the client-side. The system employs a hybrid computing method to accommodate pre-computing time or space constraints and achieves responsiveness for main parallel coordinates plot interaction tools on billions of records. Full article
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Open AccessReview
Ambient Assisted Living and Health-Related Outcomes—A Systematic Literature Review
Informatics 2017, 4(3), 19; doi:10.3390/informatics4030019 -
Abstract
The active ageing paradigm aims to contribute to the expectation of a long, autonomous, independent and healthy life. Ambient Assisted Living (AAL) promotes the development of technological solutions that might have a key role in not only the optimization of support services for
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The active ageing paradigm aims to contribute to the expectation of a long, autonomous, independent and healthy life. Ambient Assisted Living (AAL) promotes the development of technological solutions that might have a key role in not only the optimization of support services for older adults but also in the mitigation of their disabilities. This article presents a systematic literature review of how the impact of AAL technologies, products and services is being assessed in terms of its health-related outcomes. The main objective of this article is to contribute to the understanding of how state-of-the-art AAL solutions might influence the health conditions of older adults. The method used to conduct this systematic literature review followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The results show that the reviewed articles report not only the use of technological assessment instruments but also instruments to measure health-related outcomes such as quality of life. Full article
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Open AccessArticle
TOPCAT: Desktop Exploration of Tabular Data for Astronomy and Beyond
Informatics 2017, 4(3), 18; doi:10.3390/informatics4030018 -
Abstract
TOPCAT, the Tool for OPerations on Catalogues And Tables, is an interactive desktop application for retrieval, analysis and manipulation of tabular data, offering a powerful and flexible range of interactive visualization options amongst other features. Its visualization capabilities focus on enabling interactive exploration
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TOPCAT, the Tool for OPerations on Catalogues And Tables, is an interactive desktop application for retrieval, analysis and manipulation of tabular data, offering a powerful and flexible range of interactive visualization options amongst other features. Its visualization capabilities focus on enabling interactive exploration of large static local tables—millions of rows and hundreds of columns can easily be handled on a standard desktop or laptop machine, and various options are provided for meaningful graphical representation of such large datasets. TOPCAT has been developed in the context of astronomy, but many of its features are equally applicable to other domains. The software, which is free and open source, is written in Java, and the underlying high-performance visualisation library is suitable for re-use in other applications. Full article
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Open AccessArticle
Web-Scale Multidimensional Visualization of Big Spatial Data to Support Earth Sciences—A Case Study with Visualizing Climate Simulation Data
Informatics 2017, 4(3), 17; doi:10.3390/informatics4030017 -
Abstract
The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the understanding of these changes and their impacts, with regional and global simulation models
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The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the understanding of these changes and their impacts, with regional and global simulation models producing vast amounts of data. Comprehending these multidimensional data and fostering collaborative scientific discovery requires the development of new visualization techniques. In this paper, we present a cyberinfrastructure solution—PolarGlobe—that enables comprehensive analysis and collaboration. PolarGlobe is implemented upon an emerging web graphics library, WebGL, and an open source virtual globe system Cesium, which has the ability to map spatial data onto a virtual Earth. We have also integrated volume rendering techniques, value and spatial filters, and vertical profile visualization to improve rendered images and support a comprehensive exploration of multi-dimensional spatial data. In this study, the climate simulation dataset produced by the extended polar version of the well-known Weather Research and Forecasting Model (WRF) is used to test the proposed techniques. PolarGlobe is also easily extendable to enable data visualization for other Earth Science domains, such as oceanography, weather, or geology. Full article
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Open AccessArticle
Reinforcement Learning for Predictive Analytics in Smart Cities
Informatics 2017, 4(3), 16; doi:10.3390/informatics4030016 -
Abstract
The digitization of our lives cause a shift in the data production as well as in the required data management. Numerous nodes are capable of producing huge volumes of data in our everyday activities. Sensors, personal smart devices as well as the Internet
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The digitization of our lives cause a shift in the data production as well as in the required data management. Numerous nodes are capable of producing huge volumes of data in our everyday activities. Sensors, personal smart devices as well as the Internet of Things (IoT) paradigm lead to a vast infrastructure that covers all the aspects of activities in modern societies. In the most of the cases, the critical issue for public authorities (usually, local, like municipalities) is the efficient management of data towards the support of novel services. The reason is that analytics provided on top of the collected data could help in the delivery of new applications that will facilitate citizens’ lives. However, the provision of analytics demands intelligent techniques for the underlying data management. The most known technique is the separation of huge volumes of data into a number of parts and their parallel management to limit the required time for the delivery of analytics. Afterwards, analytics requests in the form of queries could be realized and derive the necessary knowledge for supporting intelligent applications. In this paper, we define the concept of a Query Controller (QC) that receives queries for analytics and assigns each of them to a processor placed in front of each data partition. We discuss an intelligent process for query assignments that adopts Machine Learning (ML). We adopt two learning schemes, i.e., Reinforcement Learning (RL) and clustering. We report on the comparison of the two schemes and elaborate on their combination. Our aim is to provide an efficient framework to support the decision making of the QC that should swiftly select the appropriate processor for each query. We provide mathematical formulations for the discussed problem and present simulation results. Through a comprehensive experimental evaluation, we reveal the advantages of the proposed models and describe the outcomes results while comparing them with a deterministic framework. Full article
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Open AccessArticle
Development and Evaluation of a Mobile Application Suite for Enhancing the Social Inclusion and Well-Being of Seniors
Informatics 2017, 4(3), 15; doi:10.3390/informatics4030015 -
Abstract
Smart mobile devices, due to their ubiquitous nature and high level penetration in everyday life, can be a key component of an Ambient Assisted Living system to improve the quality of life of older people. This paper presents the development and evaluation of
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Smart mobile devices, due to their ubiquitous nature and high level penetration in everyday life, can be a key component of an Ambient Assisted Living system to improve the quality of life of older people. This paper presents the development and evaluation of Senior App Suite, a system created for assisting seniors’ personal independence and social inclusion. The system integrates mobile computing combined with web and service-oriented technologies to offer a mobile application suite that seniors can easily use to access services, spanning various application areas such as social networking, emergency detection and overall well-being. The research hypothesis is that using such services can be beneficial for decreasing social isolation. There is quantitative indication that this assumption is realistic backed up also by the qualitative analysis from the user’s feedback derived during a pilot study (n= 22) suggesting that Senior App Suite can motivate people in new activities, maintain connection with social ties, give joy and self-confidence, and increase the frequency and quality of social interactions. Our contribution is a detailed methodology spanning the research, design, development, and evaluation of a solution that aims to improve the quality of life of seniors while addressing open issues identified in related initiatives. Full article
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Open AccessArticle
Medical and Para-Medical Personnel’ Perspectives on Home Health Care Technology
Informatics 2017, 4(2), 14; doi:10.3390/informatics4020014 -
Abstract
User-based research is strongly recommended in design for older adults.The aim of this paper is to focus the attention on the poorly explored role of medical and para-medical personnel’s perspective on home health care technologies using data that have been gained during
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User-based research is strongly recommended in design for older adults.The aim of this paper is to focus the attention on the poorly explored role of medical and para-medical personnel’s perspective on home health care technologies using data that have been gained during the “Active Ageing At Home” (AA@H) project. A focus group was organized at the National Institute of Health & Science on Ageing (INRCA) in Italy. Results demonstrate that several challenges deserve a stronger effort by the whole research sector on ageing and technology: (1) a leading role of the participatory design process; (2) the assessment of the added value of health technologies through robust methods; (3) the definition of an unique identity and well established practices among disciplines; (4) the creation of favorable prerequisites and conditions to the technology uptake. Full article
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Open AccessArticle
Evaluation of the Omaha System Prototype Icons for Global Health Literacy
Informatics 2017, 4(2), 13; doi:10.3390/informatics4020013 -
Abstract
Omaha System problem concepts describe a comprehensive, holistic view of health in simple terms that have been represented in a set of prototype icons intended for universal use by consumers and clinicians. The purpose of this study was to evaluate Omaha System prototype
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Omaha System problem concepts describe a comprehensive, holistic view of health in simple terms that have been represented in a set of prototype icons intended for universal use by consumers and clinicians. The purpose of this study was to evaluate Omaha System prototype icons internationally across ten languages through an on-line survey and in-person focus groups. The icons were generally rated above 3 on a scale of 1 to 5 by 1568 survey respondents, with notable exceptions for some of the more abstract concepts. Overall, the icons were rated 3.49 on a scale of 1 = strongly disagree to 5 = strongly agree, with a range of 3.09 (Japanese language) to 3.88 (Norwegian language). A pattern of differential agreement was noted among respondents from Asiatic languages compared to all other languages. Feedback from survey respondents and focus group participants was used to refine the icons. General themes related to icon development were synthesized from focus group interviews. Further research should continue to refine and evaluate the icons in different languages for international use to support health literacy through visual literacy. Full article
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Open AccessFeature PaperArticle
Modelling Digital Knowledge Transfer: Nurse Supervisors Transforming Learning at Point of Care to Advance Nursing Practice
Informatics 2017, 4(2), 12; doi:10.3390/informatics4020012 -
Abstract
Limited adoption of mobile technology for informal learning and continuing professional development within Australian healthcare environments has been explained primarily as an issue of insufficient digital and ehealth literacy of healthcare professionals. This study explores nurse supervisors’ use of mobile technology for informal
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Limited adoption of mobile technology for informal learning and continuing professional development within Australian healthcare environments has been explained primarily as an issue of insufficient digital and ehealth literacy of healthcare professionals. This study explores nurse supervisors’ use of mobile technology for informal learning and continuing professional development both for their own professional practice, and in their role in modelling digital knowledge transfer, by facilitating the learning and teaching of nursing students in the workplace. A convenience sample of 27 nurse supervisors involved with guiding and supporting undergraduate nurses participated in one of six focus groups held in two states of Australia. Expanding knowledge emerged as the key theme of importance to this group of clinicians. Although nurse supervisors regularly browsed Internet sources for learning and teaching purposes, a mixed understanding of the mobile learning activities that could be included as informal learning or part of formal continuing professional development was detected. Participants need educational preparation and access to mobile learning opportunities to improve and maintain their digital and ehealth literacy to appropriately model digital professionalism with students. Implementation of mobile learning at point of care to enable digital knowledge transfer, augment informal learning for students and patients, and support continuing professional development opportunities is necessary. Embedding digital and ehealth literacy within nursing curricula will promote mobile learning as a legitimate nursing function and advance nursing practice. Full article
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Open AccessArticle
Visual Analysis of Relationships between Heterogeneous Networks and Texts: An Application on the IEEE VIS Publication Dataset
Informatics 2017, 4(2), 11; doi:10.3390/informatics4020011 -
Abstract
The visual exploration of large and complex network structures remains a challenge for many application fields. Moreover, a growing number of real-world networks is multivariate and often interconnected with each other. Entities in a network may have relationships with elements of other related
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The visual exploration of large and complex network structures remains a challenge for many application fields. Moreover, a growing number of real-world networks is multivariate and often interconnected with each other. Entities in a network may have relationships with elements of other related datasets, which do not necessarily have to be networks themselves, and these relationships may be defined by attributes that can vary greatly. In this work, we propose a comprehensive visual analytics approach that supports researchers to specify and subsequently explore attribute-based relationships across networks, text documents and derived secondary data. Our approach provides an individual search functionality based on keywords and semantically similar terms over the entire text corpus to find related network nodes. For examining these nodes in the interconnected network views, we introduce a new interaction technique, called Hub2Go, which facilitates the navigation by guiding the user to the information of interest. To showcase our system, we use a large text corpus collected from research papers listed in the visualization publication dataset that consists of 2752 documents over a period of 25 years. Here, we analyze relationships between various heterogeneous networks, a bag-of-words index and a word similarity matrix, all derived from the initial corpus and metadata. Full article
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Open AccessArticle
Identifying Opportunities to Integrate Digital Professionalism into Curriculum: A Comparison of Social Media Use by Health Profession Students at an Australian University in 2013 and 2016
Informatics 2017, 4(2), 10; doi:10.3390/informatics4020010 -
Abstract
Social media has become ubiquitous to modern life. Consequently, embedding digital professionalism into undergraduate health profession courses is now imperative and augmenting learning and teaching with mobile technology and social media on and off campus is a current curriculum focus. The aim of
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Social media has become ubiquitous to modern life. Consequently, embedding digital professionalism into undergraduate health profession courses is now imperative and augmenting learning and teaching with mobile technology and social media on and off campus is a current curriculum focus. The aim of this study was to explore whether patterns of social media use for personal or informal learning by undergraduate health profession students enrolled at an Australian university across four campuses has changed over time. A previously validated online survey was administered in 2013 to a cohort of health profession students as part of an Australian survey. In 2016, the same survey was distributed to a later cohort of health profession students. Three open-ended questions to elicit descriptive information regarding the use of social media for study purposes were added to the later survey. A comparative analysis of both cohorts was undertaken and social media acceptance and penetration was shown to increase. Health profession students are now more interactive users of Facebook and Twitter, and they have become more familiar with career development sites, such as LinkedIn. The maturation of social media platforms within a three-year period has created realistic opportunities to integrate social media for personal and study purposes into the health profession education curriculum to ensure student understanding of the necessity for maintaining digital professionalism in the workplace. Full article
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Open AccessArticle
Social Media Providing an International Virtual Elective Experience for Student Nurses
Informatics 2017, 4(2), 9; doi:10.3390/informatics4020009 -
Abstract
The advances in social media offer many opportunities for developing understanding of different countries and cultures without any implications of travel. Nursing has a global presence and yet it appears as though students have little knowledge of the health and social care needs
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The advances in social media offer many opportunities for developing understanding of different countries and cultures without any implications of travel. Nursing has a global presence and yet it appears as though students have little knowledge of the health and social care needs and provision outside their local environment. Our collaboration across three countries, New Zealand, United Kingdom, and the United States of America, brought the two themes together with the aim of senior student nurses having a communication channel to explore public health issues in each country. Using a closed Facebook™ page, third year undergraduate adult nursing students were invited to take part in a three month pilot study to test the feasibility of virtual collaboration through exchanging public health issues. Here we report upon the collaboration, operation of the social media, and main findings of the study. Three core areas will be reported upon, these being the student’s views of using social media for learning about international perspectives of health, seeing nursing as a global profession and recommendations for future development of this positively reviewed learning technique. To conclude consideration will be given to further development of this work by the collaborative team expanding the countries involved. Full article
Open AccessArticle
ICNP® R&D Centre Ireland: Defining Requirements for an Intersectoral Digital Landscape
Informatics 2017, 4(2), 7; doi:10.3390/informatics4020007 -
Abstract
The apparent speed and impact of creating a global digital landscape for health and social care tells us that the health workforce is playing catch-up with eHealth national programmes. Locating how and where the profession of nursing fits with future models of health
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The apparent speed and impact of creating a global digital landscape for health and social care tells us that the health workforce is playing catch-up with eHealth national programmes. Locating how and where the profession of nursing fits with future models of health service delivery is critical to provide focused engagement for the populations they serve. In 2016, Dublin City University (DCU) School of Nursing and Human Sciences (SNHS) created a research and development centre for International Classification for Nursing Practice (ICNP®) in Ireland. This paper provides a summary of the first year of the centre’s research, describing how the initial activities link to the development of global eHealth policy. A key aspect of service delivery relates to defining care requirements, specifically to support sustainable intersectoral healthcare. Considering how nursing-sensitive language (clinical terminology) is best mapped is necessary to articulate the care requirements and processes to achieve optimal patient outcome. The World Health Organisational Framework for Integrated Care provides a pathway for crystallising the steep learning curve that the profession has currently found itself situated in, to deliver on contemporary digital healthcare. Full article
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Open AccessArticle
Preparation for Working in a Knowledge-Based Society: New Zealand Student Nurses’ Use of Social Media
Informatics 2017, 4(2), 8; doi:10.3390/informatics4020008 -
Abstract
The increasing use of social media is revolutionizing the way students learn, communicate and collaborate. Many of the skills used with social media are similar to those needed to work in a knowledge-based society. To better understand student nurses’ use of social media
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The increasing use of social media is revolutionizing the way students learn, communicate and collaborate. Many of the skills used with social media are similar to those needed to work in a knowledge-based society. To better understand student nurses’ use of social media in relation to their learning, an anonymous survey was distributed to all undergraduate nursing students enrolled at one nursing school in New Zealand in 2015. A 75% response rate (n = 226) found that almost all (99%) students use social media outside their studies. However, in relation to their study, 61% use social networking sites (such as Facebook) on a daily basis and only four students (2%) do not use social media at all. Professional networking sites are used far less in relation to study, with 65% not using these networks at all. The most common digital option used to communicate and work with fellow students was online groups and document sharing sites, such as Google docs, were also popular. The study provides a useful baseline on social media use by student nurses. Implications from this study include opportunities for educators to incorporate social media into teaching and learning activities, including its safe and ethical use. Full article
Open AccessArticle
Visualizing 3D Terrain, Geo-Spatial Data, and Uncertainty
Informatics 2017, 4(1), 6; doi:10.3390/informatics4010006 -
Abstract
Visualizing geo-spatial data embedded into a three-dimensional terrain is challenging. The problem becomes even more complex when uncertainty information needs to be presented as well. This paper addresses the question of how to visually communicate all three aspects: the 3D terrain, the geo-spatial
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Visualizing geo-spatial data embedded into a three-dimensional terrain is challenging. The problem becomes even more complex when uncertainty information needs to be presented as well. This paper addresses the question of how to visually communicate all three aspects: the 3D terrain, the geo-spatial data, and the data-associated uncertainty. We argue that visualizing all aspects with a high degree of detail will likely exceed the visual budget. Therefore, we propose a visualization strategy based on prioritizing a selected aspect and presenting the remaining two with less detail. We discuss various design options that allow us to obtain differently prioritized visual representations. Our approach has been implemented as a tool for rapid visualization prototyping in the context of avionics applications. Practical solutions are described for a use case related to the visualization of 3D terrain and uncertain weather data. Full article
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