title: Interactive visualization for data inference in the geosciences
Creators: name: Morse, PEL
Publisher: name: University of Tasmania
Year: 2021

description: Visual displays are a formidable means of conveying information to the human brain. They facilitate the formation of scientific knowledge about the physical world, based on underlying observations of diverse kinds, through representations that are understood by practitioners of the relevant discipline area. Such data visualizations are critical in the geosciences given the need to draw meaning from time-varying, spatial or volumetric data, and given the increasing size of the datasets available for analysis of the natural, physical world. The research described in this thesis aims to apply a novel set of technical resources to visualization in the geosciences. It draws on the immense potential of the human user for feature detection through connecting scientific data formats to computer graphics technologies. The software applications written in response to this opportunity therefore make strong use of interactivity in the reconnaissance exploration of example datasets. Throughout the research, a commitment to a well-posed visual display is developed, respecting underlying data values through the managed use of color and other graphic variables Following a review of the conceptual background, and the landscape of computer graphics technologies, the first original research chapter presents interactive software and workflows to visualize large geoscientific time-series datasets. It uses an animated interface and Human-Computer Interaction (HCI) to utilize the capacity of human expert observers to identify features via enhanced visual analytics. User-generated metadata allows subsets of the data to be tagged for subsequent closer investigation. The tool provides a rapid pre-pass process using fast GPU-based OpenGL graphics and data-handling. It makes use of interoperable data formats, and cloud-based (or local) data storage and computation. In a case study, the software was used to characterize a decade (2000–2009) of data recorded by the Cape Sorell Waverider Buoy, located approximately 10 km off the West coast of Tasmania, Australia. These data serve as a proxy for the understanding of Southern Ocean storminess, which has both local and global implications. Four different types of storm and non-storm events are characterized and compared with conventional analysis, noting the advantages and limitations of data analysis using animation and human interaction. The second original research chapter presents a suite of newly written computer applications for 2D data, which enable spatially varying data to be displayed and analyzed in a performant graphics environment. Color-mappings using illustrative color spaces (RGB, CIELAB) are compared with the aid of interactive displays of the applied gradient paths through the chosen color spaces. This facilitates the creation of color-maps that accommodate the non-uniformity of human color perception, producing an image where genuine features are seen, taking account of aspects of the data such as parameter uncertainty. For an illustrative case study using a seismic tomography result, interpolation in CIELAB color space is shown to enable the creation of perceptually uniform linear gradients that match the underlying data, along with a simply computable metric for color difference, ∆E. This color space assists the accuracy and reproducibility of visualization results. The well-posed use of color is further developed in the third original research chapter, for the exploratory interactive visualization of 3D volumes of global, deep Earth data. As an example, we address the challenge of reconnaissance visualization of a combined seismic tomography result, the primary means by which geoscientists infer structure and process in the deep Earth. A novel, interactive graphical application suite is presented that uses an intuitive 2.5D layer compositing approach. This allows the user to adjust the separation between data-slices, control graphics variables such as color mapping, opacity and compositing, and enables exploration and annotation of the architecture of the lithosphere. The methodology could find use in the visualization of multiple datasets representing aspects of the Earth’s deep interior, oceans and atmosphere, and in facilitating researcher interaction with the increasing number of rich datasets from missions to our neighboring planets. The three original research papers that form the core of this thesis all provide a means of amplifying analytical acuity through animated and/or interactive interfaces that enable both ‘overview’ and ‘detail’ visualization and navigation. Through all three studies, the ‘human in the loop’ aspects of the visualization process are drawn upon, e.g. in the use of perceptual color spaces for optimal display of data, or exploiting visual faculties such as stereopsis and depth perception. The dataflow software methodology employed is self-documenting, using a visual programming approach that can be replicated in alternative cross-platform software environments such as recent computer game engines. This flexible strategy assists the development of novel graphical user interfaces and interaction modalities for collaborative immersive screen technologies such as domes and future XR applications. In summary the research described herein bridges the gap between scientific data formats and the immense resources of the computer graphics and gaming industries. It exploits productive modes of HCI engagement with the data display to facilitate the search for new knowledge in the geosciences. It is anticipated that the newly written software applications will lead to wider usage of informed color-mapping in the geosciences and an awareness of the utility of emergent visualization platforms for enhancing scientific research. It is hoped that “visual literacy” and “visual numeracy” will substantially improve as a consequence of this work, and similar initiatives, as inference tasks are more routinely carried out using well-posed data visualization in the geosciences.