This thesis develops a sociosemiotic model specifically focussed upon the semiotic interpretation... more This thesis develops a sociosemiotic model specifically focussed upon the semiotic interpretation of sculpture, and proposes that this type of artefact is susceptible to a systemic-functional approach, as explored in the work of M.A.K. Halliday and Michael O'Toole. This model is then allied with a sociosemantic model, in an endeavour to draw together synchronic, diachronic and discursive aspects of the sculptural object and its situation within discursive and ideological structures. This is further explored in the second chapter where the human body is examined as a historical site of discourse, where forms of bodily legibility have been encoded and have undergone transformations across time: this posits the issue of the discourse of bodiliness, and its semiotics, as a fundamental domain within which sculptural discourse must be seen to unfold. The argument then pursues an investigation of specifically monumental sculpture, especially in its appearance in Western European cemeteries (with an emphasis upon the nineteenth-century), to delineate and explore its institutional and sociohistorical contexts and a variety of convergent discourses within which it is situated. These include such things as the history of cemeteries and their designs, the semiotics of bodily representation (both historically and in a more semiotic and phenomenological sense), the relationship between the sculptural monument per se and its associated texts: epitaphs, ordinances, public rituals, modalities of portraiture, allegory' and personification, amongst others. These discussions proliferate further into arguments about cities, architecture and bodily representation and embodiment, where the discussion necessarily problematises some of the assumptions made by the semiotic approaches utilised, and moves into a more postmodern or deconstructive mode, where the funerary monument is seen to exemplify some of the problematics of these critical approaches, especially in its counterpoint with death. Thus the trajectory of the argument moves from a concern with the specifically sculptural and funereal, outwards towards a more general concern with the constitution of the semiotics of objects and how these participate in, and reciprocate with, the sociocultural construction of the human subject.
Scientific visualization aims to present numerical values, or categorical information, in a way t... more Scientific visualization aims to present numerical values, or categorical information, in a way that enables the researcher to make an inference that furthers knowledge. Well-posed visualizations need to consider the characteristics of the data, the display environment, and human visual capacity. In the geosciences, visualizations are commonly applied to spatially varying continuous information or results. In this contribution we make use of a suite of newly written computer applications which enable spatially varying data to be displayed in a performant graphics environment. We present a comparison of color-mapping using illustrative color spaces (RGB, CIELAB). The interactive applications display the 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. We also take account of aspects of a dataset such as parameter uncertainty. For an illustrative case study using a seismic tomography result, we find that the use of RGB color-mapping can introduce non-linearities in the visualization, potentially leading to incorrect inference. Interpolation in CIELAB color space enables 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 accuracy and reproducibility of visualization results. Well-posed scientific visualization requires both "visual literacy" and "visual numeracy" on an equal footing with clearly written text. It is anticipated that this current work, with the included color-maps and software, will lead to wider usage of informed color-mapping in the geosciences.
A B S T R A C T Geoscientists are required to analyze and draw conclusions from increasingly larg... more A B S T R A C T Geoscientists are required to analyze and draw conclusions from increasingly large volumes of data. There is a need to recognise and characterise features and changing patterns of Earth observables within such large datasets. It is also necessary to identify significant subsets of the data for more detailed analysis. We present an innovative, interactive software tool and workflow to visualise, characterise, sample and tag large geoscientific datasets from both local and cloud-based repositories. It uses an animated interface and human-computer interaction to utilise the capacity of human expert observers to identify features via enhanced visual analytics. 'Tagger' enables users to analyze datasets that are too large in volume to be drawn legibly on a reasonable number of single static plots. Users interact with the moving graphical display, tagging data ranges of interest for subsequent attention. The tool provides a rapid pre-pass process using fast GPU-based OpenGL graphics and data-handling and is coded in the Quartz Composer visual programing language (VPL) on Mac OSX. It makes use of interoperable data formats, and cloud-based (or local) data storage and compute. In a case study, Tagger was used to characterise 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. This example shows use of the tool to identify and characterise 4 different types of storm and non-storm events during this time. Events characterised in this way are compared with conventional analysis, noting advantages and limitations of data analysis using animation and human interaction. Tagger provides a new ability to make use of humans as feature detectors in computer-based analysis of large-volume geosciences and other data.
—'TaggerVR' is a work-in-progress immersive Virtual Reality implementation of the 'Tagger' softwa... more —'TaggerVR' is a work-in-progress immersive Virtual Reality implementation of the 'Tagger' software application developed by the author (Morse). Tagger is an interactive software tool designed to visualize, characterize, sample and tag large geoscientific datasets hosted in local and cloud-based repositories using a THREDDS Data Server and OPeNDAP. TaggerVR implements a VR GUI using Human Interface Devices (HID) such as the Oculus Rift headset and Leap Motion Controller via Quartz Composer, Syphon and the Unity3D Game Engine.
Visual displays are a formidable means of conveying information to the human brain. They facilita... more 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, ΔE. 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.
This thesis develops a sociosemiotic model specifically focussed upon the semiotic interpretation... more This thesis develops a sociosemiotic model specifically focussed upon the semiotic interpretation of sculpture, and proposes that this type of artefact is susceptible to a systemic-functional approach, as explored in the work of M.A.K. Halliday and Michael O'Toole. This model is then allied with a sociosemantic model, in an endeavour to draw together synchronic, diachronic and discursive aspects of the sculptural object and its situation within discursive and ideological structures. This is further explored in the second chapter where the human body is examined as a historical site of discourse, where forms of bodily legibility have been encoded and have undergone transformations across time: this posits the issue of the discourse of bodiliness, and its semiotics, as a fundamental domain within which sculptural discourse must be seen to unfold. The argument then pursues an investigation of specifically monumental sculpture, especially in its appearance in Western European cemeteries (with an emphasis upon the nineteenth-century), to delineate and explore its institutional and sociohistorical contexts and a variety of convergent discourses within which it is situated. These include such things as the history of cemeteries and their designs, the semiotics of bodily representation (both historically and in a more semiotic and phenomenological sense), the relationship between the sculptural monument per se and its associated texts: epitaphs, ordinances, public rituals, modalities of portraiture, allegory' and personification, amongst others. These discussions proliferate further into arguments about cities, architecture and bodily representation and embodiment, where the discussion necessarily problematises some of the assumptions made by the semiotic approaches utilised, and moves into a more postmodern or deconstructive mode, where the funerary monument is seen to exemplify some of the problematics of these critical approaches, especially in its counterpoint with death. Thus the trajectory of the argument moves from a concern with the specifically sculptural and funereal, outwards towards a more general concern with the constitution of the semiotics of objects and how these participate in, and reciprocate with, the sociocultural construction of the human subject.
Scientific visualization aims to present numerical values, or categorical information, in a way t... more Scientific visualization aims to present numerical values, or categorical information, in a way that enables the researcher to make an inference that furthers knowledge. Well-posed visualizations need to consider the characteristics of the data, the display environment, and human visual capacity. In the geosciences, visualizations are commonly applied to spatially varying continuous information or results. In this contribution we make use of a suite of newly written computer applications which enable spatially varying data to be displayed in a performant graphics environment. We present a comparison of color-mapping using illustrative color spaces (RGB, CIELAB). The interactive applications display the 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. We also take account of aspects of a dataset such as parameter uncertainty. For an illustrative case study using a seismic tomography result, we find that the use of RGB color-mapping can introduce non-linearities in the visualization, potentially leading to incorrect inference. Interpolation in CIELAB color space enables 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 accuracy and reproducibility of visualization results. Well-posed scientific visualization requires both "visual literacy" and "visual numeracy" on an equal footing with clearly written text. It is anticipated that this current work, with the included color-maps and software, will lead to wider usage of informed color-mapping in the geosciences.
A B S T R A C T Geoscientists are required to analyze and draw conclusions from increasingly larg... more A B S T R A C T Geoscientists are required to analyze and draw conclusions from increasingly large volumes of data. There is a need to recognise and characterise features and changing patterns of Earth observables within such large datasets. It is also necessary to identify significant subsets of the data for more detailed analysis. We present an innovative, interactive software tool and workflow to visualise, characterise, sample and tag large geoscientific datasets from both local and cloud-based repositories. It uses an animated interface and human-computer interaction to utilise the capacity of human expert observers to identify features via enhanced visual analytics. 'Tagger' enables users to analyze datasets that are too large in volume to be drawn legibly on a reasonable number of single static plots. Users interact with the moving graphical display, tagging data ranges of interest for subsequent attention. The tool provides a rapid pre-pass process using fast GPU-based OpenGL graphics and data-handling and is coded in the Quartz Composer visual programing language (VPL) on Mac OSX. It makes use of interoperable data formats, and cloud-based (or local) data storage and compute. In a case study, Tagger was used to characterise 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. This example shows use of the tool to identify and characterise 4 different types of storm and non-storm events during this time. Events characterised in this way are compared with conventional analysis, noting advantages and limitations of data analysis using animation and human interaction. Tagger provides a new ability to make use of humans as feature detectors in computer-based analysis of large-volume geosciences and other data.
—'TaggerVR' is a work-in-progress immersive Virtual Reality implementation of the 'Tagger' softwa... more —'TaggerVR' is a work-in-progress immersive Virtual Reality implementation of the 'Tagger' software application developed by the author (Morse). Tagger is an interactive software tool designed to visualize, characterize, sample and tag large geoscientific datasets hosted in local and cloud-based repositories using a THREDDS Data Server and OPeNDAP. TaggerVR implements a VR GUI using Human Interface Devices (HID) such as the Oculus Rift headset and Leap Motion Controller via Quartz Composer, Syphon and the Unity3D Game Engine.
Visual displays are a formidable means of conveying information to the human brain. They facilita... more 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, ΔE. 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.
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Papers by Peter E Morse
Thesis Chapters by Peter E Morse
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, ΔE. 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.
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, ΔE. 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.