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At least 217 records · Page 12

Rethinking Visual Analytics for Streaming Data Applications

In the age of data science, the use of interactive information visualization techniques has become increasingly ubiquitous. From online scientific journals to the New York Times graphics desk, the utility of interactive visualization for both storytelling and analysis has become ever more apparent. As these techniques have become more readily accessible, the appeal of combining interactive visualization with computational analysis continues to grow. Arising out of a need for scalable, human-driven analysis, primary objective of visual analytics systems is to capitalize on the complementary strengths of human and machine analysis, using interactive visualization as a medium for communication between the two. These systems leverage developments from the fields of information visualization, computer graphics, machine learning, and human-computer interaction to support insight generation in areas where purely computational analyses fall short. Over the past decade, visual analytics systems have generated remarkable advances in many historically challenging analytical contexts. These include areas such as modeling political systems [Crouser et al. 2012], detecting financial fraud [Chang et al. 2008], and cybersecurity [Harrison et al. 2012]. In each of these contexts, domain expertise and human intuition is a necessary component of the analysis. This intuition is essential to building trust in the analytical products, as well as supporting the translation of evidence into actionable insight. In addition, each of these examples also highlights the need for scalable analysis. In each case, it is infeasible for a human analyst to manually assess the raw information unaided, and the communication overhead to divide the task between a large number of analysts makes simple parallelism intractable. Regardless of the domain, visual analytics tools strive to optimize the allocation of human analytical resources, and to streamline the sensemaking process on data that is massive, complex, incomplete, and uncertain in scenarios requiring human judgment.

97 MATHEMATICS AND COMPUTING↗

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗

Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study

National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Atypical form of Alzheimer's disease with prominent posterior cortical atrophy: a review of lesion distribution and circuit disconnection in cortical visual pathways

In recent years, the existence of visual variants of Alzheimer's disease characterized by atypical clinical presentation at onset has been increasingly recognized. In many of these cases post-mortem neuropathological assessment revealed that correlations could be established between clinical symptoms and the distribution of neurodegenerative lesions. We have analyzed a series of Alzheimer's disease patients presenting with prominent visual symptomatology as a cardinal sign of the disease. In these cases, a shift in the distribution of pathological lesions was observed such that the primary visual areas and certain visual association areas within the occipito-parieto-temporal junction and posterior cingulate cortex had very high densities of lesions, whereas the prefrontal cortex had fewer lesions than usually observed in Alzheimer's disease. Previous quantitative analyses have demonstrated that in Alzheimer's disease, primary sensory and motor cortical areas are less damaged than the multimodal association areas of the frontal and temporal lobes, as indicated by the laminar and regional distribution patterns of neurofibrillary tangles and senile plaques. The distribution of pathological lesions in the cerebral cortex of Alzheimer's disease cases with visual symptomatology revealed that specific visual association pathways were disrupted, whereas these particular connections are likely to be affected to a less severe degree in the more common form of Alzheimer's disease. These data suggest that in some cases with visual variants of Alzheimer's disease, the neurological symptomatology may be related to the loss of certain components of the cortical visual pathways, as reflected by the particular distribution of the neuropathological markers of the disease.

Review↗

Reduction of the elevator illusion from continued hypergravity exposure and visual error-corrective feedback

Ten subjects served as their own controls in two conditions of continuous, centrifugally produced hypergravity (+2 Gz) and a 1-G control condition. Before and after exposure, open-loop measures were obtained of (1) motor control, (2) visual localization, and (3) hand-eye coordination. During exposure in the visual feedback/hypergravity condition, subjects received terminal visual error-corrective feedback from their target pointing, and in the no-visual feedback/hypergravity condition they pointed open loop. As expected, the motor control measures for both experimental conditions revealed very short lived underreaching (the muscle-loading effect) at the outset of hypergravity and an equally transient negative aftereffect on returning to 1 G. The substantial (approximately 17 degrees) initial elevator illusion experienced in both hypergravity conditions declined over the course of the exposure period, whether or not visual feedback was provided. This effect was tentatively attributed to habituation of the otoliths. Visual feedback produced a smaller additional decrement and a postexposure negative after-effect, possible evidence for visual recalibration. Surprisingly, the target-pointing error made during hypergravity in the no-visual-feedback condition was substantially less than that predicted by subjects' elevator illusion. This finding calls into question the neural outflow model as a complete explanation of this illusion.

NASA Program Space Physiology and Countermeasures↗

On Development of Three-Dimensional Visualization Capabilities in Glenn Research Center Communication Analysis Suite

With NASA’s upcoming mission to return to the Moon sustainably by 2024 and using that success as a means to step onto the barren world of Mars, it remains more important than ever to conduct research and planning as thoroughly and efficiently as possible. In a mission as complex as landing humans onto another celestial body, a network of orbiting satellites and ground stations must accurately and reliably communicate with each other, enabling crucial data communications throughout the mission. Visualizing this important data communication increases the understanding of the data and can accelerate analyses efforts. The purpose of this software development is to create an interactive visualization with data taken MATLAB® scripts in the GRC Communication Analysis Suite that is easy to understand, can show all necessary data, and display the data accurately. The main types of data to visualize are from the State Propagation, Line of Sight and Dynamic Link Margin scripts. These all show positions and orbits of satellites and ground stations, while the Line of Sight data shows when they have the ability to communicate with each other based on their respective antenna positions and fields of view. Additionally, the Dynamic Link Margin mode color-codes the communication link performance onto the Line of Sight access lines. Visualization requires a graphics language that is easily accessible, has the needed features, and able to easily read data produced by the GRC Communication Analysis Suite MATLAB® scripts. ThreeJS, a graphics library for Web Graphics Library, coded in JavaScript was selected for the visualization. The next part of the software development was to move the data from MATLAB® to the JavaScript. The best way to accomplish this was to implement a MATLAB® function converting the output data of the scripts to a JavaScript Object Notation file. A key part of the development was creating the visualization within JavaScript and ThreeJS to visualize any combination of planets, moons, orbits, satellites, ground stations, line of sight links, and handle future features without changing major parts of the code. The current visualization capability runs directly from MATLAB®, and can dynamically create any scene. This software development currently supports the lunar communications analysis underway by NASA, and can be easily expanded upon in the future to aid any analysis requirements to help plan current and future space missions.

Visualization↗

Development of Level of Detail System and First-Person Camera for the GCAS Visualization Suite

The use of data-driven simulations has become standard practice as part of planning for future space missions. These simulations allow visualizing the data interactively to show what the data represents, as well as the importance of the data in the context of the mission. Using this visualized data can enhance users’ understanding of it and accelerate analysis efforts related to missions planned around it. Three-dimensional (3D) visualization software was developed to allow creating 3D representations of various communication systems, as well as the physical terrain of the Moon, for upcoming missions. The goal of this software development effort was to create interactive visualization capabilities in the Glenn Research Center Communication Analysis Suite (GCAS) using data exported from MATLAB® (MathWorks, Inc.) scripts. This software had the functionality to visualize the line of sight and dynamic link margins of the communication satellites orbiting the Earth and the Moon. One important addition to this was the visualization of the terrain data located within the GeoTIFF files, which were produced in an effort to understand the Moon’s terrain. Proper displacement values of this data have to be visualized to showcase where craters are located and how the shadow casting works with said craters at different points of the day, as well as analysis of possible landing sites for future lunar expeditions. The graphics library coded in JavaScript, three.js, had been previously selected for developing this visualization software. The software was revised to conform to modern standards, then further developed to convert the MATLAB® data into JavaScript 3D objects and Blender GL Transmission Format Binary file (GLB) objects, which were to be imported into the scene. In the process, a variety of other testing projects were created to be combined with this project at a later point; these included the first-person camera movements around spherical objects to portray human movement around the Moon, GeoTIFF loading methods, data transfer methods for incorporating the elevation data into the scene, and level of detail (LOD) capabilities to decrease memory usage and rendering time.

Visualization↗

The Effect of Information Organization on Cognitive Workload and Visual Search Performance

This study examined the relationship between how visual information is organized and people’s visual search performance. Specifically, we systematically varied how visual search information was organized (from well-organized to disorganized), and then asked participants to perform a visual search task involving finding and identifying a number of visual targets within the field of visual non-targets. We hypothesized that the visual search task would be easier when the information was well-organized versus when it was disorganized. We further speculated that visual search performance would be mediated by cognitive workload, and that the results could be generally described by the well-established speed-accuracy tradeoff phenomenon. This paper presents the details of the study we designed and our results.

99 GENERAL AND MISCELLANEOUS↗

Visual Resource Analysis for Solar Energy Zones in the San Luis Valley

This report summarizes the results of a study conducted by Argonne National Laboratory’s (Argonne’s) Environmental Science Division for the U.S. Department of the Interior Bureau of Land Management (BLM). The study analyzed the regional effects of potential visual impacts of solar energy development on three BLM-designated solar energy zones (SEZs) in the San Luis Valley (SLV) in Colorado, and, based on the analysis, made recommendations for or against regional compensatory mitigation to compensate residents and other stakeholders for the potential visual impacts to the SEZs. The analysis was conducted as part of the solar regional mitigation strategy (SRMS) task conducted by BLM Colorado with assistance from Argonne. Two separate analyses were performed. The first analysis, referred to as the VSA Analysis, analyzed the potential visual impacts of solar energy development in the SEZs on nearby visually sensitive areas (VSAs), and, based on the impact analyses, made recommendations for or against regional compensatory mitigation. VSAs are locations for which some type of visual sensitivity has been identified, either because the location is an area of high scenic value or because it is a location from which people view the surrounding landscape and attach some level of importance or sensitivity to what is seen from the location. The VSA analysis included both BLM-administered lands in Colorado and in the Taos FO in New Mexico. The second analysis, referred to as the SEZ Analysis, used BLM visual resource inventory (VRI) and other data on visual resources in the former Saguache and La Jara Field Offices (FOs), now contained within the San Luis Valley FO (SLFO), to determine whether the changes in scenic values that would result from the development of utility-scale solar energy facilities in the SEZs would affect the quality and quantity of valued scenic resources in the SLV region as a whole. If the regional effects were judged to be significant, regional compensatory mitigation was recommended. VRI data was not available for the Taos FO and it was not included in the SEZ analysis; the SEZ analysis includes BLM-administered lands in Colorado only.

14 SOLAR ENERGY↗

Association of advanced hepatic fibrosis and sonographic visualization score: a dual-center study using ACR US LI-RADS

Purpose: To evaluate the association between imaging and clinical features and visualization scores, as specified by American College of Radiology (ACR) Ultrasound Liver Imaging Reporting and Data System (LI-RADS), on hepatocellular carcinoma (HCC) screening ultrasound examinations. Methods: In this dual-center retrospective study, HCC screening ultrasound reports containing ultrasound elastography measurements (January to September, 2017) were reviewed. Ultrasound point shear wave elastography and 2-dimensional shear wave elastography were used to assess liver stiffness; median shear wave velocity was translated to METAVIR fibrosis scoring, per previously published data. Reports were analyzed for subject age, sex, reason for HCC screening, spleen size, fibrosis scores, and assigned ultrasound visualization scores. Jonckheere–Terpstra trend and Kendall’s tau-b coefficient analyses were performed. Results: 714 subjects (mean age 55; 51% male, 49% female) were included. 308 (43%) subjects had clinically declared cirrhosis; 406 (57%) did not. Majority (535, 75%) of exams were adequate (Visualization Score A), 156 (22%) moderately limited (Visualization Score B), and 23 (3%) severely limited (Visualization Score C). Increasing spleen size and patient age were associated with worsening visualization scores (p < 0.001). Suboptimal visualization was also associated with clinically significant fibrosis (≥ F2) by elastography (Kendall’s tau-b = 0.181, p < 0.001) and clinically declared cirrhosis (Kendall’s tau-b = 0.433, p < 0.001). There was no association with patient sex. Conclusion: Using ACR Ultrasound LI-RADS visualization score assessment, majority (75%) of HCC screening exams were diagnostically adequate, and only 3% were severely limited. Sonoelastographic diagnosis of clinically significant fibrosis, as well as clinical cirrhosis, increased patient age, and spleen size, were associated with greater diagnostic limitations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Visual Outcomes of Parapapillary Uveal Melanomas Following Proton Beam Therapy

Purpose: In parapapillary melanoma patients, radiation-induced optic complications are frequent and visual acuity is often compromised. We investigated dose-effect relationships for the optic nerve with respect to visual acuity after proton therapy. Methods and Materials: Of 5205 patients treated between 1991 and 2014, those treated using computed tomography (CT)-based planning to 52 Gy (prescribed dose, not accounting for relative biologic effectiveness correction of 1.1) in 4 fractions, with minimal 6-month follow-up and documented initial and last visual acuity, were included. Deterioration of ≥0.3 logMAR between initial and last visual acuity results was reported. Results: A total of 865 consecutive patients were included. Median follow-up was 69 months, mean age was 61.7 years, tumor abutted the papilla in 35.1% of patients, and tumor-to-fovea distance was ≤3 mm in 74.2% of patients. Five-year relapse-free survival rate was 92.7%. Visual acuity was ≥20/200 in 72.6% of patients initially and 47.2% at last follow-up. A wedge filter was used in 47.8% of the patients, with a positive impact on vision and no impact on relapse. Glaucoma, radiation-induced optic neuropathy, maculopathy were reported in 17.9%, 47.5%, and 33.6% of patients, respectively. On multivariate analysis, age, diabetes, thickness, initial visual acuity and percentage of macula receiving 26 Gy were predictive of visual acuity. Furthermore, patients irradiated to ≥80% of their papilla had better visual acuity when limiting the 50% (30-Gy) and 20% (12-Gy) isodoses to ≤2 mm and 6 mm of optic nerve length, respectively. Conclusions: A personalized proton therapy plan with optic nerve and macular sparing can be used efficiently with good oncological and functional results in parapapillary melanoma patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Visualization Quality Assessment

Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies. The goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images.

Grosset, Andre↗

Using Eye Tracking to Elucidate the Mechanisms Underlying Stimulation-Enhanced Visual Target Detection

Transcranial direct current stimulation (tDCS) is a noninvasive form of brain stimulation that involves passing a weak electrical current between electrodes on the scalp to modulate underlying neural tissue. TDCS has been shown to modulate cognition in a variety of domains, including memory, attention, and visual processing. Prior work from our laboratory has shown positive effects of tDCS on learning to detect target objects hidden in complex naturalistic visual scenes and learn rules for categorizing images, though the mechanism for these benefits remains unknown. One possibility is that tDCS optimizes visual search by modulating visual attention or via the reduction in search errors. One method of quantifying visual attention is to use eye tracking to record search patterns to determine if and how visual search is adjusted under verum stimulation conditions. Eye tracking data allows classification of errors into error types, including sampling errors (failing to look in the relevant region), recognition errors (looking at the critical portion of a scene, but failing to recognize it as such as evidenced by visual fixation), and decision-making errors (fixating on the relevant portion of a scene, but making the wrong determination). Our results indicate that the benefit tDCS confers on visual search for targets stems from the reduction in decision-making errors when targets are present (Cohen’s d = 0.86). Also reported is a replication of previous findings showing a tDCS-dependent improvement in learning this task, learning score (Cohen’s d = 0.88); d’ (Cohen’s d = 1.00). This provides support for moving tDCS into the application space by pairing it with analysts who are concerned with the type of search error that is corrected via stimulation.

attention↗

Motion/visual cueing requirements for vortex encounters during simulated transport visual approach and landing

This paper addresses the issues of motion/visual cueing fidelity requirements for vortex encounters during simulated transport visual approaches and landings. Four simulator configurations were utilized to provide objective performance measures during simulated vortex penetrations, and subjective comments from pilots were collected. The configurations used were as follows: fixed base with visual degradation (delay), fixed base with no visual degradation, moving base with visual degradation (delay), and moving base with no visual degradation. The statistical comparisons of the objective measures and the subjective pilot opinions indicated that although both minimum visual delay and motion cueing are recommended for the vortex penetration task, the visual-scene delay characteristics were not as significant a fidelity factor as was the presence of motion cues. However, this indication was applicable to a restricted task, and to transport aircraft. Although they were statistically significant, the effects of visual delay and motion cueing on the touchdown-related measures were considered to be of no practical consequence.

Parrish, R. V.↗

A New Method for Laminar Boundary Layer Transition Visualization in Flight: Color Changes in Liquid Crystal Coatings

The visualization of laminar to turbulent boundary layer transition plays an important role in flight and wind tunnel aerodynamic testing of aircraft wing and body surfaces. Visualization can help provide a more complete understanding of both transition location as well as transition modes; without visualization, the transition process can be very difficult to understand. In the past, the most valuable transition visualization methods for fight applications included sublimating chemicals and oil flows. Each method has advantages and limitations. In particular, sublimating chemicals are impractical to use in subsonic applications much above 20,000 feet because of the greatly reduced rates of sublimation at lower temperatures (less than -4 degrees Fahrenheit). Both oil flow and sublimating chemicals have the disadvantage of providing only one good data point per flight. Thus, for many important flight conditions, transition visualization has not been readily available. This paper discusses a new method for visualizing transition in fight by the use of liquid crystals. The new method overcomes the limitations of past techniques, and provides transition visualization capability throughout almost the entire altitude and speed ranges of virtually all subsonic aircraft flight envelopes. The method also has wide applicability for supersonic transition visualization in flight and for general use in wind tunnel research over wide subsonic and supersonic speed ranges.

Holmes, Bruce J.↗

Managing Complexity in Multidisciplinary Visualization

As high performance computing technology progresses, computational simulations are becoming more advanced in their capabilities. In the computational aerosciences domain, single discipline steady-state simulations computed on a single grid are far from the state-of-the-art. In their place are complex, time-dependent multidisciplinary simulations that attempt to model a given geometry more realistically. The product of these multidisciplinary simulations is a massive amount of data stored in different formats, grid topologies, units of measure, etc., as a result of the differences in the simulated physical domains. In addition to the challenges posed by setting up and performing the simulation, additional challenges exist in analyzing computational results. Visualization plays an important role in the advancement of multidisciplinary simulations. To date, visualization has been used to aid in the interpretation of large amounts of simulation data. Because the human visual system is effective in digesting a large amount of information presented graphically, visualization has helped simulation scientists to understand complex simulation results. As these simulations become even more complex, integrating several different physical domains, visualization will be critical to digest the massive amount of information. Another important role for visualization is to provide a common communication medium from which the domain scientists can use to develop, debug, and analyze their work. Multidisciplinary analyses are the next step in simulation technology, not only in computational aerosciences, but in many other areas such as global climate modeling. Visualization researchers must understand and work towards the challenges posed by multidisciplinary simulation scenarios. This paper addresses some of these challenges, describing technologies that must be investigated to create a useful visualization analysis tool for domain scientists.

Miceli, Kristina D.↗

Visualization of Computational Fluid Dynamics

Scientific visualization serves the dual purpose of exploration and exposition of the results of numerical simulations of fluid flow. Along with the basic visualization process which transforms source data into images, there are four additional components to a complete visualization system: Source Data Processing, User Interface and Control, Presentation, and Information Management. The requirements imposed by the desired mode of operation (i.e. real-time, interactive, or batch) and the source data have their effect on each of these visualization system components. The special requirements imposed by the wide variety and size of the source data provided by the numerical simulation of fluid flow presents an enormous challenge to the visualization system designer. We describe the visualization system components including specific visualization techniques and how the mode of operation and source data requirements effect the construction of computational fluid dynamics visualization systems.

Gerald-Yamasaki, Michael↗

Application-Controlled Demand Paging for Out-of-Core Visualization

In the area of scientific visualization, input data sets are often very large. In visualization of Computational Fluid Dynamics (CFD) in particular, input data sets today can surpass 100 Gbytes, and are expected to scale with the ability of supercomputers to generate them. Some visualization tools already partition large data sets into segments, and load appropriate segments as they are needed. However, this does not remove the problem for two reasons: 1) there are data sets for which even the individual segments are too large for the largest graphics workstations, 2) many practitioners do not have access to workstations with the memory capacity required to load even a segment, especially since the state-of-the-art visualization tools tend to be developed by researchers with much more powerful machines. When the size of the data that must be accessed is larger than the size of memory, some form of virtual memory is simply required. This may be by segmentation, paging, or by paged segments. In this paper we demonstrate that complete reliance on operating system virtual memory for out-of-core visualization leads to poor performance. We then describe a paged segment system that we have implemented, and explore the principles of memory management that can be employed by the application for out-of-core visualization. We show that application control over some of these can significantly improve performance. We show that sparse traversal can be exploited by loading only those data actually required. We show also that application control over data loading can be exploited by 1) loading data from alternative storage format (in particular 3-dimensional data stored in sub-cubes), 2) controlling the page size. Both of these techniques effectively reduce the total memory required by visualization at run-time. We also describe experiments we have done on remote out-of-core visualization (when pages are read by demand from remote disk) whose results are promising.

Cox, Michael↗