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

One view is not enough: review of and encouragement for multiple and alternative representations in 3D and immersive visualisation

The opportunities for 3D visualisations are huge. People can be immersed inside their data, interface with it in natural ways, and see it in ways that are not possible on a traditional desktop screen. Indeed, 3D visualisations, especially those that are immersed inside head-mounted displays are becoming popular. Much of this growth is driven by the availability, popularity and falling cost of head-mounted displays and other immersive technologies. However, there are also challenges. For example, data visualisation objects can be obscured, important facets missed (perhaps behind the viewer), and the interfaces may be unfamiliar. Some of these challenges are not unique to 3D immersive technologies. Indeed, developers of traditional 2D exploratory visualisation tools would use alternative views, across a multiple coordinated view (MCV) system. Coordinated view interfaces help users explore the richness of the data. For instance, an alphabetical list of people in one view shows everyone in the database, while a map view depicts where they live. Each view provides a different task or purpose. While it is possible to translate some desktop interface techniques into the 3D immersive world, it is not always clear what equivalences would be. In this paper, using several case studies, we discuss the challenges and opportunities for using multiple views in immersive visualisation. Our aim is to provide a set of concepts that will enable developers to perform critical thinking, creative thinking and push the boundaries of what is possible with 3D and immersive visualisation. In summary developers should consider how to integrate many views, techniques and presentation styles, and one view is not enough when using 3D and immersive visualisations

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

Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review

Rapid growth in the generation of data from various sources has made data visualisation a valuable tool for analysing data. However, visual analysis can be a challenging task, not only due to intricate dashboards but also when dealing with complex and multidimensional data. In this context, advances in Natural Language Processing technologies have led to the development of Visualisation-oriented Natural Language Interfaces (V-NLIs). In this paper, we carry out a scoping review that analyses synergies between the fields of Data Visualisation and Natural Language Interaction. Specifically, we focus on chatbot-based V-NLI approaches and explore and discuss three research questions. The first two research questions focus on studying how chatbot-based V-NLIs contribute to interactions with the Data and Visual Spaces of the visualisation pipeline, while the third seeks to know how chatbot-based V-NLIs enhance users' interaction with visualisations. Our findings show that the works in the literature put a strong focus on exploring tabular data with basic visualisations, with visual mapping primarily reliant on fixed layouts. Moreover, V-NLIs provide users with restricted guidance strategies, and few of them support high-level and follow-up queries. We identify challenges and possible research opportunities for the V-NLI community such as supporting high-level queries with complex data, integrating V-NLIs with more advanced systems such as Augmented Reality (AR) or Virtual Reality (VR), particularly for advanced visualisations, expanding guidance strategies beyond current limitations, adopting intelligent visual mapping techniques, and incorporating more sophisticated interaction methods

An empirical study of virtual reality menu interaction and design

This study focused on three different menu designs each with their own unique interactions and organizational structures to determine which design features would perform the best. Fifty-four participants completed 27 tasks using each of the three designs. The menus were analyzed based on task performance, accuracy, usability, intuitiveness, and user preference. Also, an analysis was conducted between two different menu organization styles: top-down menu organization (Method-TD) and bottom-up organization (Method-BU). There was no evidence that demographic factors had any effect on the overall results. By and large, the Stacked menu design received very positive results and feedback from all the participants. The Spatial design received average feedback with some participants preferring it while others struggled to use it and felt that it was too physically demanding. The worst performer was the Radial design that consistently ranked last and failed to pass usability and accuracy tests. A NGOMSL study was conducted to determine any differences in performance between a top-down menu organizational approach and a bottom-up approach or differences between the predicted task completion times and the reported times. The results of this study predicted that the Spatial design should have taken the least amount of time to perform, however, the experimental results showed that the Stacked design in fact out-performed the Spatial design’s task completion times. A potential explanation as to why the Stacked outperformed the Spatial is the increased physical demand of the Spatial design not anticipated with the NGOMSL analysis because of a design feature which caused a high level of cumbersomeness with the interactions. Overall, there were no statistical differences found between Method-TD and Method-BU, but a large difference found between the predicted times and observed times for Stacked, Radial, and Spatial. Participants overwhelmingly performed better than the predicted completion times for the Stacked design, but then did not complete the tasks by the predicted times for the Radial and Spatial. This study recommends the Stacked menu for VR environments and proposes further research into a Stacked-Spatial hybrid design to allow for the participant’s preferred design aspects of both designs to be used in a VR environment

Immersive analytics for oncology patient cohorts

This thesis proposes a novel interactive immersive analytics tool and methods to interrogate the cancer patient cohort in an immersive virtual environment, namely Virtual Reality to Observe Oncology data Models (VROOM). The overall objective is to develop an immersive analytics platform, which includes a data analytics pipeline from raw gene expression data to immersive visualisation on virtual and augmented reality platforms utilising a game engine. Unity3D has been used to implement the visualisation. Work in this thesis could provide oncologists and clinicians with an interactive visualisation and visual analytics platform that helps them to drive their analysis in treatment efficacy and achieve the goal of evidence-based personalised medicine. The thesis integrates the latest discovery and development in cancer patients’ prognoses, immersive technologies, machine learning, decision support system and interactive visualisation to form an immersive analytics platform of complex genomic data. For this thesis, the experimental paradigm that will be followed is in understanding transcriptomics in cancer samples. This thesis specifically investigates gene expression data to determine the biological similarity revealed by the patient's tumour samples' transcriptomic profiles revealing the active genes in different patients. In summary, the thesis contributes to i) a novel immersive analytics platform for patient cohort data interrogation in similarity space where the similarity space is based on the patient's biological and genomic similarity; ii) an effective immersive environment optimisation design based on the usability study of exocentric and egocentric visualisation, audio and sound design optimisation; iii) an integration of trusted and familiar 2D biomedical visual analytics methods into the immersive environment; iv) novel use of the game theory as the decision-making system engine to help the analytics process, and application of the optimal transport theory in missing data imputation to ensure the preservation of data distribution; and v) case studies to showcase the real-world application of the visualisation and its effectiveness

Visualization and Human-Machine Interaction

The digital age offers a lot of challenges in the eld of visualization. Visual imagery has been effectively used to communicate messages through the ages, to express both abstract and concrete ideas. Today, visualization has ever-expanding applications in science, engineering, education, medicine, entertainment and many other areas. Different areas of research contribute to the innovation in the eld of interactive visualization, such as data science, visual technology, Internet of things and many more. Among them, two areas of renowned importance are Augmented Reality and Visual Analytics. This thesis presents my research in the fields of visualization and human-machine interaction. The purpose of the proposed work is to investigate existing solutions in the area of Augmented Reality (AR) for maintenance. A smaller section of this thesis presents a minor research project on an equally important theme, Visual Analytics. Overall, the main goal is to identify the most important existing problems and then design and develop innovative solutions to address them. The maintenance application domain has been chosen since it is historically one of the first fields of application for Augmented Reality and it offers all the most common and important challenges that AR can arise, as described in chapter 2. Since one of the main problem in AR application deployment is reconfigurability of the application, a framework has been designed and developed that allows the user to create, deploy and update in real-time AR applications. Furthermore, the research focused on the problems related to hand-free interaction, thus investigating the area of speech-recognition interfaces and designing innovative solutions to address the problems of intuitiveness and robustness of the interface. On the other hand, the area of Visual Analytics has been investigated: among the different areas of research, multidimensional data visualization, similarly to AR, poses specific problems related to the interaction between the user and the machine. An analysis of the existing solutions has been carried out in order to identify their limitations and to point out possible improvements. Since this analysis delineates the scatterplot as a renowned visualization tool worthy of further research, different techniques for adapting its usage to multidimensional data are analyzed. A multidimensional scatterplot has been designed and developed in order to perform a comparison with another multidimensional visualization tool, the ScatterDice. The first chapters of my thesis describe my investigations in the area of Augmented Reality for maintenance. Chapter 1 provides definitions for the most important terms and an introduction to AR. The second chapter focuses on maintenance, depicting the motivations that led to choose this application domain. Moreover, the analysis concerning open problems and related works is described along with the methodology adopted to design and develop the proposed solutions. The third chapter illustrates how the adopted methodology has been applied in order to assess the problems described in the previous one. Chapter 4 describes the methodology adopted to carry out the tests and outlines the experimental results, whereas the fifth chapter illustrates the conclusions and points out possible future developments. Chapter 6 describes the analysis and research work performed in the eld of Visual Analytics, more specifically on multidimensional data visualizations. Overall, this thesis illustrates how the proposed solutions address common problems of visualization and human-machine interaction, such as interface de- sign, robustness of the interface and acceptance of new technology, whereas other problems are related to the specific research domain, such as pose tracking and reconfigurability of the procedure for the AR domain

Exploration of multiple pathways for the development of immersive virtual reality environments

The focus of this thesis is the study and recommendation of optimal techniques for developing immersive virtual environments for generic applications. The overarching objective is to ensure that virtual environments can be created and deployed, rapidly and accurately, using commercial off-the-shelf software. Specific subjective and objective criteria have been employed to determine trade-offs between multiple pathways for designing such environments and specific recommendations are made for the applicability of each. The efficacy of the techniques developed as part of this research work has been demonstrated by applying them to three widely differing areas - visualizing arbitrary 2D surface data, synthesis of particle aggregate models from computed tomography and simulation of NASA rocket engine test stands. The objectives of this thesis were obtained by an examination of the current algorithms and software in use for the development of virtual environments. From these currently used methods, general methods were defined. The expansion of these general methods to include the inputs and situations of common applications, allowed for the development of methods for real-world examples. Results were obtained by evaluating these methods against defined measurement criteria. These criteria measured the effectiveness of these methods for increasing the value of virtual reality, while reducing the cost. In this thesis, two virtual environment platforms (vGeo® and Vizard®) were used to develop three applications. These applications were a surface plot, particle visualizations and test stand simulations. In most cases, the results found the open-ended Vizard® to be the better platform. vGeo®, a platform designed for data visualization, worked well for basic data visualization, but was not as effective as Vizard® for developing more complex visualization. This thesis found that in most cases, an open-ended development platform, with functionality for rapid development is ideal. These methods and evaluations can be applied to a more diverse set of application and datasets to build development platforms that are even more efficient