Organizing information on the next generation web - Design and implementation of a new bookmark structure

The next-generation Web will increase the need for a highly organized and ever evolving method to store references to Web objects. These requirements could be realized by the development of a new bookmark structure. This paper endeavors to identify the key requirements of such a bookmark, specifically in relation to Web documents, and sets out a suggested design through which these needs may be accomplished. A prototype developed offers such features as the sharing of bookmarks between users and groups of users. Bookmarks for Web documents in this prototype allow more specific information to be stored such as: URL, the document type, the document title, keywords, a summary, user annotations, date added, date last visited and date last modified. Individuals may access the service from anywhere on the Internet, as long as they have a Java-enabled Web browser

E-Voting in an ubicomp world: trust, privacy, and social implications

The advances made in technology have unchained the user from the desktop into interactions where access is anywhere, anytime. In addition, the introduction of ubiquitous computing (ubicomp) will see further changes in how we interact with technology and also socially. Ubicomp evokes a near future in which humans will be surrounded by “always-on,” unobtrusive, interconnected intelligent objects where information is exchanged seamlessly. This seamless exchange of information has vast social implications, in particular the protection and management of personal information. This research project investigates the concepts of trust and privacy issues specifically related to the exchange of e-voting information when using a ubicomp type system

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

What Google Maps can do for biomedical data dissemination: examples and a design study

BACKGROUND: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. RESULTS: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. CONCLUSIONS: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations

Entanglement, local measurements, and symmetry

A definition of entanglement in terms of local measurements is discussed. Viz, the maximum entanglement corresponds to the states that cause the highest level of quantum fluctuations in all local measurements determined by the dynamic symmetry group of the system. A number of examples illustrating this definition is considered.Comment: 10 pages. to be published in Journal of Optics

Wearable Haptic Devices for Gait Re-education by Rhythmic Haptic Cueing

This research explores the development and evaluation of wearable haptic devices for gait sensing and rhythmic haptic cueing in the context of gait re-education for people with neurological and neurodegenerative conditions. Many people with long-term neurological and neurodegenerative conditions such as Stroke, Brain Injury, Multiple Sclerosis or Parkinson’s disease suffer from impaired walking gait pattern. Gait improvement can lead to better fluidity in walking, improved health outcomes, greater independence, and enhanced quality of life. Existing lab-based studies with wearable devices have shown that rhythmic haptic cueing can cause immediate improvements to gait features such as temporal symmetry, stride length, and walking speed. However, current wearable systems are unsuitable for self-managed use for in-the-wild applications with people having such conditions. This work aims to investigate the research question of how wearable haptic devices can help in long-term gait re-education using rhythmic haptic cueing. A longitudinal pilot study has been conducted with a brain trauma survivor, providing rhythmic haptic cueing using a wearable haptic device as a therapeutic intervention for a two-week period. Preliminary results comparing pre and post-intervention gait measurements have shown improvements in walking speed, temporal asymmetry, and stride length. The pilot study has raised an array of issues that require further study. This work aims to develop and evaluate prototype systems through an iterative design process to make possible the self-managed use of such devices in-the-wild. These systems will directly provide therapeutic intervention for gait re-education, offer enhanced information for therapists, remotely monitor dosage adherence and inform treatment and prognoses over the long-term. This research will evaluate the use of technology from the perspective of multiple stakeholders, including clinicians, carers and patients. This work has the potential to impact clinical practice nationwide and worldwide in neuro-physiotherapy

Interfaces for science: Conceptualizing an interactive graphical interface

6,849.32 new research journal articles are published every day. The exponential growth of Scientific Knowledge Objects (SKOs) on the Web, makes searches time-consuming. Access to the right and relevant SKOs is vital for research, which calls for several topics, including the visualization of science dynamics. We present an interface model aimed to represent of the relations that emerge in the science social space dynamics, namely through the visualization and navigation of the relational structures between researchers, SKOs, knowledge domains, subdomains, and topics. This interface considers the relationship between the researcher who reads and shares the relevant articles and the researcher who wants to find the most relevant SKOs within a subject matter. This article presents the first iteration of the conceptualization process of the interface layout, its interactivity and visualization structures. It is essential to consider the hierarchical and relational structures/algorithms to represent the science social space dynamics. These structures are not being used as analysis tools, because it is not objective to show the linkage properties of these relationships. Instead, they are used as a means of representing, navigating and exploring these relationships. To sum up, this article provides a framework and fundamental guidelines for an interface layout that explores the social science space dynamics between the researcher who seeks relevant SKOs and the researchers who read and share them.This work has been supported by COMPETE: POCI-01-0145-FEDER- 007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: (UID/CEC/00319/2013) and the Project IViSSEM: ref: POCI-010145-FEDER-28284