Exploring parallel coordinates plots in virtual reality

Parallel Coordinates Plots (PCP) are a widely used approach to interactively visualize and analyze multidimensional scientific data in a 2D environment. In this paper, we explore the use of Parallel Coordinates in an immersive Virtual Reality (VR) 3D visualization environment as a means to support the decision-making process in engineering design processes. We evaluate the potential of VR PCP using a formative qualitative study with seven participants. In a task involving 54 points with 29 dimensions per point, we found that participants were able to detect patterns in the dataset compared with a previously published study with two expert users using traditional 2D PCP, which acts as the gold standard for the dataset. The dataset describes the Pareto front for a three-objective aerodynamic design optimization study in turbomachinery.Cambridge European & Trinity Hall Scholarshi

A review of data visualization: opportunities in manufacturing sequence management.

Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application

Future Directions in Astronomy Visualisation

Despite the large budgets spent annually on astronomical research equipment such as telescopes, instruments and supercomputers, the general trend is to analyse and view the resulting datasets using small, two-dimensional displays. We report here on alternative advanced image displays, with an emphasis on displays that we have constructed, including stereoscopic projection, multiple projector tiled displays and a digital dome. These displays can provide astronomers with new ways of exploring the terabyte and petabyte datasets that are now regularly being produced from all-sky surveys, high-resolution computer simulations, and Virtual Observatory projects. We also present a summary of the Advanced Image Displays for Astronomy (AIDA) survey which we conducted from March-May 2005, in order to raise some issues pertitent to the current and future level of use of advanced image displays.Comment: 13 pages, 2 figures, accepted for publication in PAS

IATK:An immersive analytics toolkit

International audienceWe introduce IATK, the Immersive Analytics Toolkit, a software package for Unity that allows interactive authoring and exploration of data visualisation in immersive environments. The design of IATK was informed by interdisciplinary expert-collaborations as well as visual analytics applications and iterative refinement over several years. IATK allows for easy assembly of visualisations through a grammar of graphics that a user can configure in a GUI— in addition to a dedicated visualisation API that supports the creation of novel immersive visualisation designs and interactions. IATK is designed with scalability in mind, allowing visualisation and fluid responsive interactions in the order of several million points at a usable frame rate. This paper outlines our design requirements, IATK’s framework design and technical features, its user interface, as well as application examples

Abstract Data Visualisation in Mobile VR Platforms

Data visualisation, as a key tool in data understanding, is widely used in science and everyday life. In order data visualisation to be effective, perceptual factors and the characteristics of the display interface play a crucial role. Virtual Reality is nowadays accepted as a valid medium for scientific visualisation, because of its inherent characteristics of real-world emulation and intuitive interaction. However, the use of VR in abstract data visualisation is still limited. In this research, I investigate the use and suitability of mobile phone-based Virtual Reality as a medium for abstract data visualisation. I develop a prototype VR Android application and visualise data using the Scatterplot and Parallel Coordinates methods. After that, I conduct a user study to compare the effectiveness of the mobile VR application compared to a similar screen-based one by implementing some data exploration scenarios. The study results, while not being statistically significant, show improved accuracy and speed in the mobile VR visualisation application. The main conclusions are two-fold: Virtual Reality is beneficial for abstract data visualisation, even in the case of limited processing power and display resolution. Mobile VR, an affordable alternative to expensive desktop VR set-ups can be utilized as a data visualisation platform

IPCP: Immersive Parallel Coordinates Plots for Engineering Design Processes

Computational engineering design methods and tools are common practice in modern industry. Such approaches are integral in enabling designers to efficiently explore larger and more complex design spaces. However, at the same time, computational engineering design methods tend to dramatically increase the number of candidate solutions that decision-makers must interpret in order to make appropriate choices within a set of solutions. Since all candidate solutions can be represented in digital form together with their assessment criteria, evaluated according to some sort of simulation model, a natural way to explore and understand the complexities of the design problem is to visualize their multidimensional nature. The task now involves the discovery of patterns and trends within the multidimensional design space. In this work, we aim to enhance the design decision-making process by embedding visual analytics into an immersive virtual reality environment. To this end, we present a system called IPCP: immersive parallel coordinates plots. IPCP combines the well-established parallel coordinates visualization technique for high-dimensional data with immersive virtual reality. We propose this approach in order to exploit and discover efficient means to use new technology within a conventional decision-making process. The aim is to provide benefits by enhancing visualizations of 3D geometry and other physical quantities with scientific information. We present the design of this system, which allows the representation and exploration of multidimensional scientific datasets. A qualitative evaluation with two surrogate expert users, knowledgeable in multidimensional data analysis, demonstrate that the system can be used successfully to detect both known and previously unknown patterns in a real-world test dataset, producing an early indicative validation of its suitability for decision support in engineering design processes.Cambridge European and Trinity Hall; Engineering and Physical Sciences Research Council (EPSRC-1788814

Exploring Engineering Applications of Visual Analytics in Virtual Reality

Recent advancements and technological breakthroughs in the development of so-called immersive interfaces, such as augmented (AR), mixed (MR), and virtual reality (VR), coupled with the growing mass-market adoption of such devices has started to attract attention from academia and industry alike. Out of these technologies, VR offers the most mature option in terms of both hardware and software, as well as the best available range of different off-the-shelf offerings. VR is a term interchangeably used to denote both head-mounted displays (HMDs) and fully immersive, bespoke 3D environments which these devices transport their users to. With modern devices, developers can leverage a range of different interaction modalities, including visual, audio, and even haptic feedback, in the creation of these virtual worlds. With such a rich interaction space it is thus natural to think of VR as a well-suited environment for interactive visualisation and analytical reasoning of complex multidimensional data. Research in \textit{visual analytics} (VA) combines these two themes, spanning the last one and a half decades, and has revealed a number of research findings. This includes a range of new advanced and effective visualisation and analysis tools for even more complex, more noisy and larger data sets. Furthermore, the extension of this research and the use of immersive interfaces to facilitate visual analytics has spun-off a new field of research: \textit{immersive analytics} (IA). Immersive analytics leverages the potential bestowed by immersive interfaces to aid the user in swift and effective data analysis. Some of the most promising application domains of such immersive interfaces in the industry are various branches of engineering, including aerospace design and in civil engineering. The range of potential applications is vast and growing as new stakeholders are adopting these immersive tools. However, the use of these technologies brings its own challenges. One such difficulty is the design of appropriate interaction techniques. There is no optimal choice, instead such a choice varies depending on available hardware, the user’s prior experience, their task at hand, and the nature of the dataset. To this end, my PhD work has focused on designing and analysing various interactive, VR-based immersive systems for engineering visual analytics. One of the key elements of such an immersive system is the selection of an adequate interaction method. In a series of both qualitative and quantitative studies, I have explored the potential of various interaction techniques that can be used to support the user in swift and effective data analysis. Here, I have investigated the feasibility of using techniques such as hand-held controllers, gaze-tracking and hand-tracking input methods used solo or in combination in various challenging use cases and scenarios. For instance, I developed and verified the usability and effectiveness of the AeroVR system for aerospace design in VR. This research has allowed me to trim the very large design space of such systems that have been not sufficiently explored thus far. Moreover, building on top of this work, I have designed, developed, and tested a system for digital twin assessment in aerospace that coupled gaze-tracking and hand-tracking, achieved via an additional sensor attached to the front of the VR headset, with no need for the user to hold a controller. The analysis of the results obtained from a qualitative study with domain experts allowed me to distill and propose design implications when developing similar systems. Furthermore, I worked towards designing an effective VR-based visualisation of complex, multidimensional abstract datasets. Here, I developed and evaluated the immersive version of the well-known Parallel Coordinates Plots (IPCP) visualisation technique. The results of the series of qualitative user studies allowed me to obtain a list of design suggestions for IPCP, as well as provide tentative evidence that the IPCP can be an effective tool for multidimensional data analysis. Lastly, I also worked on the design, development, and verification of the system allowing its users to capture information in the context of conducting engineering surveys in VR. Furthermore, conducting a meaningful evaluation of immersive analytics interfaces remains an open problem. It is difficult and often not feasible to use traditional A/B comparisons in controlled experiments as the aim of immersive analytics is to provide its users with new insights into their data rather than focusing on more quantifying factors. To this end, I developed a generative process for synthesising clustered datasets for VR analytics experiments that can be used in the process of interface evaluation. I further validated this approach by designing and carrying out two user studies. The statistical analysis of the gathered data revealed that this generative process for synthesising clustered datasets did indeed result in datasets that can be used in experiments without the datasets themselves being the dominant contributor of the variability between conditions.Engineering and Physical Sciences Research Council (EPSRC-1788814); Trinity Hall and Cambridge Commonwealth, European & International Trust; Cambridge Philosophical Societ

Mixed marker-based/marker-less visual odometry system for mobile robots

When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental test

vrmlgen: An R Package for 3D Data Visualization on the Web

The 3-dimensional representation and inspection of complex data is a frequently used strategy in many data analysis domains. Existing data mining software often lacks functionality that would enable users to explore 3D data interactively, especially if one wishes to make dynamic graphical representations directly viewable on the web. In this paper we present vrmlgen, a software package for the statistical programming language R to create 3D data visualizations in web formats like the Virtual Reality Markup Language (VRML) and LiveGraphics3D. vrmlgen can be used to generate 3D charts and bar plots, scatter plots with density estimation contour surfaces, and visualizations of height maps, 3D object models and parametric functions. For greater flexibility, the user can also access low-level plotting methods through a unified interface and freely group different function calls together to create new higher-level plotting methods. Additionally, we present a web tool allowing users to visualize 3D data online and test some of vrmlgen's features without the need to install any software on their computer.