Special Issue: Visualizing the (Data) Future

As libraries and academic institutions evolve into “data-driven” organizations, they are looking for meaningful ways in which to convey their data to funding and regulatory agencies, licensing and accreditation boards, and institutional students, faculty and staff. This data-driven culture is being integrated into all facets of library operations, and data visualization services is emerging as a distinct library research and service development area

Scientific Visualization Using the Flow Analysis Software Toolkit (FAST)

Over the past few years the Flow Analysis Software Toolkit (FAST) has matured into a useful tool for visualizing and analyzing scientific data on high-performance graphics workstations. Originally designed for visualizing the results of fluid dynamics research, FAST has demonstrated its flexibility by being used in several other areas of scientific research. These research areas include earth and space sciences, acid rain and ozone modelling, and automotive design, just to name a few. This paper describes the current status of FAST, including the basic concepts, architecture, existing functionality and features, and some of the known applications for which FAST is being used. A few of the applications, by both NASA and non-NASA agencies, are outlined in more detail. Described in the Outlines are the goals of each visualization project, the techniques or 'tricks' used lo produce the desired results, and custom modifications to FAST, if any, done to further enhance the analysis. Some of the future directions for FAST are also described

Research Weaving: Visualizing the Future of Research Synthesis

We propose a new framework for research synthesis of both evidence and influence, named research weaving. It summarizes and visualizes information content, history, and networks among a collection of documents on any given topic. Research weaving achieves this feat by combining the power of two methods: systematic mapping and bibliometrics. Systematic mapping provides a snapshot of the current state of knowledge, identifying areas needing more research attention and those ready for full synthesis. Bibliometrics enables researchers to see how pieces of evidence are connected, revealing the structure and development of a field. We explain how researchers can use some or all of these tools to gain a deeper, more nuanced understanding of the scientific literature

A practical approach to product design for future worlds using scenario-development

The focus of consumer product design is shifting from primarily offering functionality, towards\ud experience and emotion driven product characteristics [1]. At the same time the functioning of\ud products is more and more defined in its social context. Product designers can play a major role in\ud developing our future social context, as long as they are aware of the responsibility towards users,\ud society and environment. In the master ‘Design & Styling’ of the Industrial Design Engineering\ud program of the University of Twente, we created a course “Create the Future”, addressing both these\ud future- and society oriented aspects of design. In this paper we describe the course structure and the\ud associated teaching methods, give examples of student results and discuss the points of interest and\ud application possibilities. In the 2008 edition the students explored the future of food. First the students\ud created a future context by investigating, building and visualizing multiple scenarios. Subsequently\ud they designed a future product concept within these scenario contexts. It showed that the structure of\ud this course was particularly suitable for designing products for the not so near future, i.e. 15-20 years\ud ahead. Especially scenario development proved to be a good instrument for the students to be able to\ud create a tangible context for designing future products and services

Initial results of in vivo non-invasive cancer imaging in the human breast using near-infrared photoacoustics

Near-infrared photoacoustic images of regions-of-interest in 4 of the 5 cases of patients with symptomatic breasts reveal higher intensity regions which we attribute to vascular distribution associated with cancer. Of the 2 cases presented here, one is especially significant where benign indicators dominate in conventional radiological images, while photoacoustic images reveal vascular features suggestive of malignancy, which is corroborated by histopathology. The results show that photoacoustic imaging may have potential in visualizing certain breast cancers based on intrinsic optical absorption contrast. A future role for the approach could be in supplementing conventional breast imaging to assist detection and/or diagnosis.\ud \u

An Integrative Neurological Model for Basic Observable Human Behavior

The scientific method uncovers information from the natural world in small increments. This spurs the design of models to explain how the pieces fit together and to identify future targets of research. This is especially the case in psychology, where visualizing concepts is an advantageous practice. One all too common criticism of cognitive and behavioral models in psychology is the lack of a biological basis. This paper aims to alleviate part of this issue by integrating currently understood biological and neurological mechanisms that drive psychological phenomena into a predictive and descriptive model for basic human behavior. To accomplish this task, this paper explores numerous scientific reviews and studies regarding sensory perception, emotion, learning, and memory. This paper also features original research about decision making. Creating this model is a necessary first step for targeting possible future research and clinical practices related to human behavior

Continuous glucose monitoring sensors: Past, present and future algorithmic challenges

Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration in real time almost continuously for several days and are provided with hypo/hyperglycemic alerts and glucose trend information. CGM sensors have revolutionized Type 1 diabetes (T1D) management, improving glucose control when used adjunctively to self-monitoring blood glucose systems. Furthermore, CGM devices have stimulated the development of applications that were impossible to create without a continuous-time glucose signal, e.g., real-time predictive alerts of hypo/hyperglycemic episodes based on the prediction of future glucose concentration, automatic basal insulin attenuation methods for hypoglycemia prevention, and the artificial pancreas. However, CGM sensors’ lack of accuracy and reliability limited their usability in the clinical practice, calling upon the academic community for the development of suitable signal processing methods to improve CGM performance. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, to show how they have been tackled by our research group, and to identify the possible future ones