GODIVA2: interactive visualization of environmental data on the Web

GODIVA2 is a dynamic website that provides visual access to several terabytes of physically distributed, four-dimensional environmental data. It allows users to explore large datasets interactively without the need to install new software or download and understand complex data. Through the use of open international standards, GODIVA2 maintains a high level of interoperability with third-party systems, allowing diverse datasets to be mutually compared. Scientists can use the system to search for features in large datasets and to diagnose the output from numerical simulations and data processing algorithms. Data providers around Europe have adopted GODIVA2 as an INSPIRE-compliant dynamic quick-view system for providing visual access to their data.

Quantitative comparison between the use of 3D vs 2D visualization tools to present building design proposals to non-spatial skilled end users

Information technology in construction (ITC) has been gaining wide acceptance and is being implemented in the construction research domains as a tool to assist decision makers. Most of the research into visualization technologies (VT) has been on the wide range of 3D and simulation applications suitable for construction processes. Despite its development with interoperability and standardization of products, VT usage has remained very low when it comes to communicating and addressing the needs of building end-users (BEU). This paper argues that building end users are a source of experience and expertise that can be brought into the briefing stage for the evaluation of design proposals. It also suggests that the end user is a source of new ideas promoting innovation. In this research a positivistic methodology that includes the comparison of 3D models and the traditional 2D methods is proposed. It will help to identify "how much", if anything, a non-spatial specialist can gain in terms Of "understanding" of a particular design proposal presented, using both methods.

A data forest: multi-dimensional visualization

As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.

Generative topographic mapping applied to clustering and visualization of motor unit action potentials

The identification and visualization of clusters formed by motor unit action potentials (MUAPs) is an essential step in investigations seeking to explain the control of the neuromuscular system. This work introduces the generative topographic mapping (GTM), a novel machine learning tool, for clustering of MUAPs, and also it extends the GTM technique to provide a way of visualizing MUAPs. The performance of GTM was compared to that of three other clustering methods: the self-organizing map (SOM), a Gaussian mixture model (GMM), and the neural-gas network (NGN). The results, based on the study of experimental MUAPs, showed that the rate of success of both GTM and SOM outperformed that of GMM and NGN, and also that GTM may in practice be used as a principled alternative to the SOM in the study of MUAPs. A visualization tool, which we called GTM grid, was devised for visualization of MUAPs lying in a high-dimensional space. The visualization provided by the GTM grid was compared to that obtained from principal component analysis (PCA). (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Human red blood cells at work: identification and visualization of erythrocytic eNOS activity in health and disease

A nitric oxide synthase (NOS)-like activity has been demonstrated in human red blood cells (RBCs), but doubts about its functional significance, isoform identity and disease relevance remain. Using flow cytometry in combination with the NO-imaging probe DAF-FM we find that all blood cells form NO intracellularly, with a rank order of monocytes > neutrophils > lymphocytes > RBCs > platelets. The observation of a NO-related fluorescence within RBCs was unexpected given the abundance of the NO-scavenger oxyhemoglobin. Constitutive normoxic NO formation was abolished by NOS inhibition and intracellular NO scavenging, confirmed by laser-scanning microscopy and unequivocally validated by detection of the DAF-FM reaction product with NO using HPLC and LC-MS/MS. Employing immunoprecipitation, ESI-MS/MS-based peptide sequencing and enzymatic assay we further demonstrate that human RBCs contain an endothelial NOS (eNOS) that converts L-3H-Arginine to L-3H-Citrulline in a Ca2+/Calmodulin-dependent fashion. Moreover, in patients with coronary artery disease, red cell eNOS expression and activity are both lower than in age-matched healthy individuals and correlate with the degree of endothelial dysfunction. Thus, human RBCs constitutively produce NO under normoxic conditions via an active eNOS isoform the activity of which is compromised in patients with coronary artery disease.

A multi-level analytical approach for detection and visualization of intracellular NO production and nitrosation events using diaminofluoresceins

Diaminofluoresceins are widely used probes for detection and intracellular localization of NO formation in cultured/isolated cells and intact tissues. The fluorinated derivative, 4-amino-5-methylamino-2′,7′-difluorofluorescein (DAF-FM), has gained increasing popularity in recent years due to its improved NO-sensitivity, pH-stability, and resistance to photo-bleaching compared to the first-generation compound, DAF-2. Detection of NO production by either reagent relies on conversion of the parent compound into a fluorescent triazole, DAF-FM-T and DAF-2-T, respectively. While this reaction is specific for NO and/or reactive nitrosating species, it is also affected by the presence of oxidants/antioxidants. Moreover, the reaction with other molecules can lead to the formation of fluorescent products other than the expected triazole. Thus additional controls and structural confirmation of the reaction products are essential. Using human red blood cells as an exemplary cellular system we here describe robust protocols for the analysis of intracellular DAF-FM-T formation using an array of fluorescence-based methods (laser-scanning fluorescence microscopy, flow cytometry and fluorimetry) and analytical separation techniques (reversed-phase HPLC and LC-MS/MS). When used in combination, these assays afford unequivocal identification of the fluorescent signal as being derived from NO and are applicable to most other cellular systems without or with only minor modifications.

A Web Map Service implementation for the visualization of multidimensional gridded environmental data

We describe ncWMS, an implementation of the Open Geospatial Consortium’s Web Map Service (WMS) specification for multidimensional gridded environmental data. ncWMS can read data in a large number of common scientific data formats – notably the NetCDF format with the Climate and Forecast conventions – then efficiently generate map imagery in thousands of different coordinate reference systems. It is designed to require minimal configuration from the system administrator and, when used in conjunction with a suitable client tool, provides end users with an interactive means for visualizing data without the need to download large files or interpret complex metadata. It is also used as a “bridging” tool providing interoperability between the environmental science community and users of geographic information systems. ncWMS implements a number of extensions to the WMS standard in order to fulfil some common scientific requirements, including the ability to generate plots representing timeseries and vertical sections. We discuss these extensions and their impact upon present and future interoperability. We discuss the conceptual mapping between the WMS data model and the data models used by gridded data formats, highlighting areas in which the mapping is incomplete or ambiguous. We discuss the architecture of the system and particular technical innovations of note, including the algorithms used for fast data reading and image generation. ncWMS has been widely adopted within the environmental data community and we discuss some of the ways in which the software is integrated within data infrastructures and portals.

Developing a mobile visualization environment for construction applications

There is a renewed interest in immersive visualization to navigate digital data-sets associated with large building and infrastructure projects. Following work with a fully immersive visualization facility at the University, this paper details the development of a complementary mobile visualization environment. It articulates progress on the requirements for this facility; the overall design of hardware and software; and the laboratory testing and planning for user pilots in construction applications. Like our fixed facility, this new light-weight mobile solution enables a group of users to navigate a 3D model at a 1:1 scale and to work collaboratively with structured asset information. However it offers greater flexibility as two users can assemble and start using it at a new location within an hour. The solution has been developed and tested in a laboratory and will be piloted in engineering design review and stakeholder engagement applications on a major construction project.

The effect of light exposure on the degradation of latent fingerprints on brass surfaces: the use of silver electroless deposition as a visualization technique

We have studied the degradation of sebaceous fingerprints on brass surfaces using silver electroless deposition (SED) as a visualization technique. We have stored fingerprints on brass squares either (i) in a locked dark cupboard or (ii) in glass-filtered natural daylight for periods of 3 h, 24 h, 1 week, 3 weeks, and 6 weeks. We find that fingerprints on brass surfaces degrade much more rapidly when kept in the light than they do under dark conditions with a much higher proportion of high-quality prints found after 3 or 6 weeks of aging when stored in the dark. This process is more marked than for similar fingerprints on black PVC surfaces. Identifiable prints can be achieved on brass surfaces using both SED and cyanoacrylate fuming (CFM). SED is quick and straightforward to perform. CFM is more time-consuming but is versatile and can be applied to a wider range of metal surfaces than SED, for example brass surfaces which have been coated by a lacquer.

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.

Multiresolution semantic activity characterisation and abnormality discovery in videos

This paper addresses the issue of activity understanding from video and its semantics-rich description. A novel approach is presented where activities are characterised and analysed at different resolutions. Semantic information is delivered according to the resolution at which the activity is observed. Furthermore, the multiresolution activity characterisation is exploited to detect abnormal activity. To achieve these system capabilities, the focus is given on context modelling by employing a soft computing-based algorithm which automatically enables the determination of the main activity zones of the observed scene by taking as input the trajectories of detected mobiles. Such areas are learnt at different resolutions (or granularities). In a second stage, learned zones are employed to extract people activities by relating mobile trajectories to the learned zones. In this way, the activity of a person can be summarised as the series of zones that the person has visited. Employing the inherent soft relation properties, the reported activities can be labelled with meaningful semantics. Depending on the granularity at which activity zones and mobile trajectories are considered, the semantic meaning of the activity shifts from broad interpretation to detailed description.Activity information at different resolutions is also employed to perform abnormal activity detection.

Acceleration and visualization of Dynamic Network Optimization

With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.