Head-mounted augmented reality (AR) displays allow for the seamless integration of virtual visualisation with contextual tangible references, such as physical (tangible) globes. We explore the design of immersive geospatial data visualisation with AR and tangible globes. We investigate the “tangible-virtual interplay” of tangible globes with virtual data visualisation, and propose a conceptual approach for designing immersive geospatial globes. We demonstrate a set of use cases, such as augmenting a tangible globe with virtual overlays, using a physical globe as a tangible input device for interacting with virtual globes and maps, and linking an augmented globe to an abstract data visualisation. We gathered qualitative feedback from experts about our use case visualisations, and compiled a summary of key takeaways as well as ideas for envisioned future improvements. The proposed design space, example visualisations and lessons learned aim to guide the design of tangible globes for data visualisation in AR.

Geographic data visualisation on virtual globes is intuitive and widespread, but has not been thoroughly investigated. We explore two main design factors for quantitative data visualisation on virtual globes: i) commonly used primitives (2D bar, 3D bar, circle) and ii) the orientation of these primitives (tangential, normal, billboarded). We evaluate five distinctive visualisation idioms in a user study with 50 participants. The results show that aligning primitives tangentially on the globe’s surface decreases the accuracy of area-proportional circle visualisations, while the orientation does not have a significant effect on the accuracy of length-proportional bar visualisations. We also find that tangential primitives induce higher perceived mental load than other orientations. Guided by these results we design a novel globe visualisation idiom, Geoburst, that combines a virtual globe and a radial bar chart. A preliminary evaluation reports potential benefits and drawbacks of the Geoburst visualisation.

Decision systems for solving real-world combinatorial problems must be able to report infeasibility in such a way that users can understand the reasons behind it, and understand how to modify the problem to restore feasibility. Current methods mainly focus on reporting one or more subsets of the problem constraints that cause infeasibility. Methods that also show users how to restore feasibility tend to be less flexible and/or problem-dependent. We describe a problem-independent approach to feasibility restoration that combines existing techniques from the literature in novel ways to yield meaningful, useful, practical and flexible user support. We evaluate the resulting framework on two real-world applications.

MOTIVATION: Large metabolic models, including genome-scale metabolic models, are nowadays common in systems biology, biotechnology and pharmacology. They typically contain thousands of metabolites and reactions and therefore methods for their automatic visualization and interactive exploration can facilitate a better understanding of these models. RESULTS: We developed a novel method for the visual exploration of large metabolic models and implemented it in LMME (Large Metabolic Model Explorer), an add-on for the biological network analysis tool VANTED. The underlying idea of our method is to analyze a large model as follows. Starting from a decomposition into several subsystems, relationships between these subsystems are identified and an overview is computed and visualized. From this overview, detailed subviews may be constructed and visualized in order to explore subsystems and relationships in greater detail. Decompositions may either be predefined or computed, using built-in or self-implemented methods. Realized as add-on for VANTED, LMME is embedded in a domain-specific environment, allowing for further related analysis at any stage during the exploration. We describe the method, provide a use case and discuss the strengths and weaknesses of different decomposition methods. AVAILABILITY AND IMPLEMENTATION: The methods and algorithms presented here are implemented in LMME, an open-source add-on for VANTED. LMME can be downloaded from www.cls.uni-konstanz.de/software/lmme and VANTED can be downloaded from www.vanted.org. The source code of LMME is available from GitHub, at https://github.com/LSI-UniKonstanz/lmme.

Visual exploration of maps often requires a contextual understanding at multiple scales and locations. Multiview map layouts, which present a hierarchy of multiple views to reveal detail at various scales and locations, have been shown to support better performance than traditional single-view exploration on desktop displays. This paper investigates the extension of such layouts of 2D maps into 3D immersive spaces, which are not limited by the real-estate barrier of physical screens and support sensemaking through spatial interaction. Based on our initial implementation of immersive multiview maps, we conduct an exploratory study with 16 participants aimed at understanding how people place and view such maps in immersive space. We observe the layouts produced by users performing map exploration search, comparison and route-planning tasks. Our qualitative analysis identifies patterns in layoutgeometry (spherical, spherical cap, planar),overview-detail relationship (central window, occluding, coordinated) andinteraction strategy. Based on these observations, along with qualitative feedback from a user walkthrough session, we identify implications and recommend features for immersive multiview map systems. Our main findings are that participants tend to prefer and arrange multiview maps in a spherical cap layout around them and that they often rearrange the views during tasks.

Ontologies are formal representations of concepts and complex relationships among them. They have been widely used to capture comprehensive domain knowledge in areas such as biology and medicine, where large and complex ontologies can contain hundreds of thousands of concepts. Especially due to the large size of ontologies, visualisation is useful for authoring, exploring and understanding their underlying data. Existing ontology visualisation tools generally focus on the hierarchical structure, giving much less emphasis to non-hierarchical associations. In this paper we present OntoPlot, a novel visualisation specifically designed to facilitate the exploration of all concept associations whilst still showing an ontology's large hierarchical structure. This hybrid visualisation combines icicle plots, visual compression techniques and interactivity, improving space-efficiency and reducing visual structural complexity. We conducted a user study with domain experts to evaluate the usability of OntoPlot, comparing it with the de facto ontology editor Protégé. The results confirm that OntoPlot attains our design goals for association-related tasks and is strongly favoured by domain experts.

This article reviews two decades of research in topics in Information Visualisation emerging from the Data Visualisation and Immersive Analytics Lab at Monash University Australia (Monash IA Lab). The lab has been influential with contributions in algorithms, interaction techniques and experimental results in Network Visualisation, Interactive Optimisation and Geographic and Cartographic visualisation. It has also been a leader in the emerging topic of Immersive Analytics, which explores natural interactions and immersive display technologies in support of data analytics. We reflect on advances in these areas but also sketch our vision for future research and developments in data visualisation more broadly.

Virtual Reality (VR) provides immersive environments where users watch objects and scenes as if they were in front of users. This is a significant advantage while applying to 3D visualization systems. However, it is often difficult for novice users to make the best use of VR to reproduce the objects and scenes precisely and the comprehensively depending on the skills of users and the complexity of objects and scenes. One of the problems is that the allowed operations in VR are too flexible. Here, we propose a viewpoint selection method that allows every user to watch the objects and scenes easily and carefully in a VR space. The viewpoint is not fixed but can be shifted to the most favorable position according to the demand of users. Regarding the selected viewpoint as the initial position, users can easily go towards the target part with fewer movements. This system helps users to understand the complex objects in the VR space precisely with less time. We demonstrate our system on the observation of mode water pairs and discuss the comparative visualization results.

Freehand gesture interaction has long been proposed as a `natural' input method for Augmented Reality (AR) applications, yet has been little explored for intensive applications like multiscale navigation. In multiscale navigation, such as digital map navigation, pan and zoom are the predominant interactions. A position-based input mapping (e.g. grabbing metaphor) is intuitive for such interactions, but is prone to arm fatigue. This work focuses on improving digital map navigation in AR with mid-air hand gestures, using a horizontal intangible map display. First, we conducted a user study to explore the effects of handedness (unimanual and bimanual) and input mapping (position-based and rate-based). From these findings we designed DiveZoom and TerraceZoom, two novel hybrid techniques that smoothly transition between position- and rate-based mappings. A second user study evaluated these designs. Our results indicate that the introduced input-mapping transitions can reduce perceived arm fatigue with limited impact on performance.

Social media analysis is helpful to understand the behavior of people. Human behavior in social media is related to time and location, which is often difficult to understand the characteristics appropriately and quickly. We chose to apply virtual reality technologies to visualize the spatio-temporal social media data. This makes us easier to develop interactive and intuitive user interfaces and explore the data as we want. This paper presents our visualization of tweets of microblogs with location information. Our system features a three-dimensional temporal visualization which consists of the two-dimensional map and a time axis. In particular, we aggregate the number of tweets of each coordinate and time step, calculate scores and display them as piled cubes. We highlight only specific cubes so that users can understand the overall tendency of datasets. We also developed user interfaces for operating these cubes and panels which indicate details of tweets.

Fluid dynamics simulation is often repeated while changing conditions, and therefore we need to compare a large amount of results. In order to compare results under different conditions, it is effective to overlap the streamlines generated from each condition in a single 3D space. Streamline is a curved line which represents a wind flow. This paper presents a technique to automatically select and visualize important streamlines suitable for comparison of the simulation results. In addition, we present an implementation to observe the flow fields in virtual reality spaces.

BACKGROUND: Biologists make frequent use of databases containing large and complex biological networks. One popular database is the Kyoto Encyclopedia of Genes and Genomes (KEGG) which uses its own graphical representation and manual layout for pathways. While some general drawing conventions exist for biological networks, arbitrary graphical representations are very common. Recently, a new standard has been established for displaying biological processes, the Systems Biology Graphical Notation (SBGN), which aims to unify the look of such maps. Ideally, online repositories such as KEGG would automatically provide networks in a variety of notations including SBGN. Unfortunately, this is non-trivial, since converting between notations may add, remove or otherwise alter map elements so that the existing layout cannot be simply reused. RESULTS: Here we describe a methodology for automatic translation of KEGG metabolic pathways into the SBGN format. We infer important properties of the KEGG layout and treat these as layout constraints that are maintained during the conversion to SBGN maps. CONCLUSIONS: This allows for the drawing and layout conventions of SBGN to be followed while creating maps that are still recognizably the original KEGG pathways. This article details the steps in this process and provides examples of the final result.

MOTIVATION: LibSBGN is a software library for reading, writing and manipulating Systems Biology Graphical Notation (SBGN) maps stored using the recently developed SBGN-ML file format. The library (available in C++ and Java) makes it easy for developers to add SBGN support to their tools, whereas the file format facilitates the exchange of maps between compatible software applications. The library also supports validation of maps, which simplifies the task of ensuring compliance with the detailed SBGN specifications. With this effort we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner. AVAILABILITY AND IMPLEMENTATION: Milestone 2 was released in December 2011. Source code, example files and binaries are freely available under the terms of either the LGPL v2.1+ or Apache v2.0 open source licenses from http://libsbgn.sourceforge.net. CONTACT: [email protected].

BACKGROUND: In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms. RESULTS: This paper presents an image analysis pipeline (HTPheno) for high-throughput plant phenotyping. HTPheno is implemented as a plugin for ImageJ, an open source image processing software. It provides the possibility to analyse colour images of plants which are taken in two different views (top view and side view) during a screening. Within the analysis different phenotypical parameters for each plant such as height, width and projected shoot area of the plants are calculated for the duration of the screening. HTPheno is applied to analyse two barley cultivars. CONCLUSIONS: HTPheno, an open source image analysis pipeline, supplies a flexible and adaptable ImageJ plugin which can be used for automated image analysis in high-throughput plant phenotyping and therefore to derive new biological insights, such as determination of fitness.

MOTIVATION: The recently proposed Systems Biology Graphical Notation (SBGN) provides a standard for the visual representation of biochemical and cellular processes. It aims to support more efficient and accurate communication of biological knowledge between different research communities in the life sciences. However, to increase the use of SBGN, tools for editing, validating and translating SBGN maps are desirable. RESULTS: We present SBGN-ED, a tool which allows the creation of all three types of SBGN maps from scratch or the editing of existing maps, the validation of these maps for syntactical and semantical correctness, the translation of networks from the KEGG and MetaCrop databases into SBGN and the export of SBGN maps into several file and image formats. AVAILABILITY: SBGN-ED is freely available from http://vanted.ipk-gatersleben.de/addons/sbgn-ed. The web site contains also tutorials and example files.