Wildfires affect many regions across the world. The accelerated progression of global warming has amplified their frequency and scale, deepening their impact on human life, the economy, and the environment. The temperature rise has been driving wildfires to behave unpredictably compared to those previously observed, challenging researchers and fire management agencies to understand the factors behind this behavioral change. Furthermore, this change has rendered fire personnel training outdated and lost its ability to adequately prepare personnel to respond to these new fires. Immersive visualization can play a key role in tackling the growing issue of wildfires. Therefore, this survey reviews various studies that use immersive and non-immersive data visualization techniques to depict wildfire behavior and train first responders and planners. This paper identifies the most useful characteristics of these systems. While these studies support knowledge creation for certain situations, there is still scope to comprehensively improve immersive systems to address the unforeseen dynamics of wildfires.

What an AI powered future might look like? Rapid evolution of computing capabilities enables transforming process of scientific discovery and inventing new ways to experience and interact with simulation outcomes in real-time, especially in the context of modern Digital Twins.

Emotions are multifaceted phenomena that affect our behaviour, perception, and cognition. Increasing evidence indicates that induction mechanisms play a crucial role in triggering emotions by simulating the sensations required for an experimental design. Over the years, many reviews have evaluated a passive elicitation mechanism where the user is an observer, ignoring the importance of self-relevance in emotional experience. So, in response to the gap in the literature, this study intends to explore the possibility of using Virtual Reality (VR) as an active mechanism for emotion induction. VR can simulate controlled environments with high immersion, presence, and interaction to induce intense emotions. Therefore, researchers can evaluate emotional experiences in a realistic context. For the success and quality of research settings, VR must select the appropriate material to effectively evoke emotions. Therefore, in the present review, we evaluated to what extent VR virtual environments, videos, games, tasks, avatar, images, and 360-degree panoramas can elicit emotions. Further, we present public datasets, discuss challenges and recommendations, and review emotion-sensing interfaces related to VR research. The conclusions reveal the VR's potential to evoke emotions effectively and naturally by generating motivational and empathy mechanisms, which makes it an ecologically valid paradigm to study emotions.

Despite Narrative Visualisation's (NarVis) proliferation in academic circles, a narrative structure designed to suit the individual challenges and needs of the discipline is yet to mature. We present both a structure and tool for NarVis that remediates narrative form and concepts using Rhetorical Structure Theory (RST). Through RST, we develop a dynamic narrative structure that avoids many of the trappings of traditional narratives.

In this study, we propose our data-driven approach to investigate the emotional experience triggered using Virtual Reality (VR) games. We considered a full Component Process Model (CPM) which theorise emotional experience as a multi-process phenomenon. We validated the possibility of the proposed approach through a pilot experiment and confirmed that VR games can be used to trigger a diverse range of emotions. Using hierarchical clustering, we showed a clear distinction between positive and negative emotion in the CPM space.

Urban modeling facilitates the generation of virtual environments for various scenarios about cities. It requires expertise and consideration, and therefore consumes massive time and computation resources. Nevertheless, related tasks sometimes result in dissatisfaction or even failure. These challenges have received significant attention from researchers in the area of computer graphics. Meanwhile, the burgeoning development of artificial intelligence motivates people to exploit machine learning, and hence improves the conventional solutions. In this paper, we present a review of approaches to urban modeling in computer graphics using machine learning in the literature published between 2010 and 2019. This serves as an overview of the current state of research on urban modeling from a machine learning perspective.

Narrative Visualisation (NarVis) is the pairing of data visualisation with narrative techniques. Due to its interdisciplinary applications and scholarship, NarVis presentations often feature vastly different interpretations of “narrative” and “visualisation”, which is echoed in NarVis authoring tools. To map the morphology of how the narratives of NarVis manifest, we identify three different trajectories for the field. These trajectories are identified through an analysis of selected NarVis presentations and tools, with an emphasis on identifying how traditional narrative techniques are adopted, transposed or indeed challenged by NarVis examples. We then populate our categories with additional examples and tools, providing a foundational point of reference for NarVis scholars, authors and tool developers.

Information visualisation researchers have posited that author-driven narratives will allow information to be conveyed efficiently and argue for the adoption of storytelling techniques in information visualisation. However, there is limited work describing the effects of author-driven narratives in users' comprehension and memorability of visualisations in relation to interactive visualisations. Recommendations for author-driven visualisation stories are largely based on anecdotal reports or research from the arts, and not on studies in information visualisation. To investigate these issues, we carried out a study that compared purely author-driven narratives with interactive visualisations devoid of author narratives, in terms of comprehension and short-term and long-term memorability. We found that the presence of narration in author-driven stories significantly aided the understanding of information but had no significant effect on the long-term recall of information from visualisations.

Whereas there are existing strategies that are used to guide the design of user interfaces, none are sufficiently comprehensive to ensure that Mixed Reality (MR) and Internet of Things (IoT) interfaces will be usable by older adults. To address the usability needs and reconcile inconsistencies among the design strategies and technology characteristics, we consulted relevant design criteria and extended these associated concepts to include MR and IoT interfaces for the ageing population. To demonstrate its utility, we develop an innovative Assistive Technology (AT) that integrates MR and IoT technologies that satisfy each guideline. We believe that the set of design guidelines can serve as a source to practitioners working on the design of ATs for elderly people, and to researchers interested in the further development of a more inclusive set of design guidelines.

In this article, we frame the process of visualisation design as a systematic transformation between two distinct domain-specific languages. As a result, we obtain a general framework, which may inform the process of visualisation design, as well as enable the creation of flexible general-purpose systems for interactive visual analytics. Our efforts aim towards raising the level of abstraction, by allowing users to express queries through a vocabulary that is specific to their problem domain. This domain-specific language is based on the conceptual model of the input data. Subsequently, a visualisation specification prescribes a language transformation, which maps from the user-defined conceptual model to the application-defined graphics grammar. The key to this approach is a formal interpretation of the conceptual data model, using rich type information in order to capture the data semantics and structure. The theoretical foundations for this approach are introduced, building on existing theories from database, type system, and visualisation literature. Subsequently, we discuss the key concepts of the proposed framework. Finally, the applications of the framework are illustrated by three use cases, which successfully applied these concepts in real-world visual analytics scenarios.

Visual data storytelling has gained widespread adoption as a means of communicating information visualisation. This is partly due to the increased interest in data journalism. Besides being engaging, it has been shown to foster better comprehension and memorability of information to target audiences. The visual data story authoring process involves several stages. However, current tools neither consolidate the visual data story creation process nor integrate the essential features, such as the recommendation of logically sequenced story pieces, for producing coherent narratives. This paper briefly demonstrates our approach and framework for supporting the creation of logically sequenced visual data stories.

Immersive analytics allows a large amount of data and complex structures to be concurrently investigated. We propose a collaborative analytics system that benefits from new advances in immersive technologies for collaborators working in the early stages of data exploration. We implemented a combination of Star Coordinates and Star Plot visualisation techniques to support the visualisation of multidimensional data and the encoding of datasets using simple and compact visual representations. To support data analytics tasks, we propose tools and interaction techniques for users to build decision trees for visualising and analysing data in a top-down method.

Effective visualisation plays a vital role in generating insights from data. The selection of graph types however, is highly dependent on the analysis tasks and data types at hand. For example, spatio-temporal visualisations encode changes in data over time and space. Although they have the potential of revealing overall tendencies and movement patterns, building effective spatio-temporal visualisations is challenging because it requires encoding all three attributes of spatio-temporal data i.e. thematic (values of attributes), temporal and spatial in a single visualisation. In this application design study, we present PedaViz for representing hour-level spatio-temporal attributes within a single visualisation; a 24-hour radial visual metaphor that encodes hour-level temporal and daily temperature attributes while utilising a thematic map display to present spatial attributes. The design was applied on city planning domain using Melbourne's pedestrian count and temperature data. Results of our preliminary user evaluation suggest that our visualisation is easily understandable by users; and supports users in carrying out selected analysis tasks.

This work presents a narrative story of a Future Mine scenario that uses Virtual Reality as a medium to replace traditional spreadsheet-based policy making framework currently widely used in government agencies for decision making process. The scenario presented envisions user exploring underground mine, where extraction processes had been almost fully automated, and environment is constantly monitored by a variety of modern and futuristic sensors. The use of story-telling using VR is explored to present novel application scenarios for sensing technologies and to facilitate better understanding of the context in which they will be used. Further the experience is translated into informed decision making.

Immersive technologies and particularly the Virtual Reality (VR) provide new exciting ways to see the world. Today, we introduce our research that successfully employed VR to the biodiversity conservation sciences. Jaguars are one of the endangered animals. It is certainly critical and compelling to preserve ecosystem for endangered animals. With the awareness of this, we endeavoured to establish a multidisciplinary VR project that implemented data from indigenous villagers (jaguar experts group A), the conventional knowledge of the field of jaguar ecosystem (from jaguar experts group B), and mathematical and statistical models. Our fascination lies in these questions: can we effectively bring together VR and analytical capabilities? Can VR be used to make this world a better place for living beings? Please enjoy our 360-degree images of jaguar habitats taken in the Peruvian Amazon.

It is a trend now that computing power through parallelism is provided by multi-core systems or heterogeneous architectures for High Performance Computing (HPC) and scientific computing. Although many algorithms have been proposed and implemented using sequential computing, alternative parallel solutions provide more suitable and high performance solutions to the same problems. In this paper, three parallelization strategies are proposed and implemented for a dynamic programming based cloud smoothing application, using both shared memory and non-shared memory approaches. The experiments are performed on NVIDIA GeForce GT750m and Tesla K20m, two GPU accelerators of Kepler architecture. Detailed performance analysis is presented on partition granularity at block and thread levels, memory access efficiency and computational complexity. The evaluations described show high approximation of results with high efficiency in the parallel implementations, and these strategies can be adopted in similar data analysis and processing applications.

This paper outlines Non-Expert User Visualisation (NEUVis), a mode of information visualisation commonly practiced by artists and designers. NEUVis, a wicked problem, accounts for design constraints related to the affective (or emotional) response by the user. This contrasts NEUVis from the tame, but complex, problems associated with scientific visualisation. Examples of scientific visualisation and NEUVis show how the challenge of NEUVis can be overcome by collaboration between artists/designers and scientists. Current Research at the Design Lab at The University of Sydney into NEUVis aims to map the different levels of cognitive and emotional response of different modes of visualisation.

In the fast changing, hybrid and multi-disciplinary practices of artful information visualisation (artful infoVis) and artists using data to inform artworks, the act of translating data into an image can be fraught with peril. There is considerable debate around modes of visualization and their relationship with the underlying data. This paper outlines the debate between the opposing ideologies and, through assessment of design considerations and comparison of creative practice and visual analytics, formulates a set of guidelines for creative practitioners developing visualisations for Non-Expert Users (NEUVis).

How we visualize graph data is important for us to make sense of it. A number of aesthetic criteria have been used in practice to guide the visualization process and judge the quality of graph drawings. These aesthetics are limited since they often conflict with each other. It is generally agreed that in order to make visualizations effective, well-grounded perception and cognitive theories and design principles are needed. Some attempts have been made to develop visualization theories. In this paper, we present a preliminary study which we conducted with a cognitive approach to add to this growing body of research. More specifically, we propose a graph visualization model, which is further conceptualized into a two-stage assessment cycle. Examples of potentially useful methodologies and theories are introduced and their implications for producing user-friendly visualizations are discussed.

Cloud computing services offer highly reliable, scalable and efficient solutions with a large pool of easily accessible, virtualized resources. They are becoming an increasingly prevalent delivery model. We have developed a cloud-based image analysis toolbox to provide a wide user base with easy access to the software tools we have developed over the last decade. The toolbox is provided as a service on an Australian national cloud infrastructure. The design and implementation of the cloud-based service are presented, including its architecture, key components and some image analysis and visualization examples showing the capabilities of the service for biomedical image analysis.

The present work concerns immersive virtual reality (IVR) experiments carried out for prospective applications in the mining industry. Demonstrated technologies are also suitable for use in generic training and e-learning fields. Visualisation is handled by the Unity3D 2.5 multiplatform game development tool, which communicates over .Net socket servers with data feeds from a 5DT Data Glove Ultra that measures finger flexures, and an iPhone based touchpad device. The iPhone also provides orientation data pertaining to acceleration and rotational attributes, such as, pitch, roll and yaw. The user is placed at the focal point of a 4-m dome and experiences the immersive virtual reality environment display. Navigation and object manipulation by the user is made possible through the combination of hardwired buttons, in-world selection techniques and gesture recognition. The techniques are directly applicable to the monitoring of mining environments, in which mining equipment is surrounded by various sensor networks.