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The third Workshop of the Applied Laboratory Systems Research Program (AISRP) met at the Univeristy of Colorado's Laboratory for Atmospheric and Space Physics in August of 1993. The presentations were organized into four sessions: Artificial Intelligence Techniques; Scientific Visualization; Data Management and Archiving; and Research and Technology.
Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES, AVHRR, and SSM/I sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.
Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.
The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.
Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.
This presentation highlights the role of advanced visualization techniques at the National Renewable Energy Laboratory (NREL) in supporting cutting-edge research across diverse energy domains. From immersive analytics and uncertainty visualization to high-resolution and real-time data analysis, NREL's visualization capabilities enable scientists to explore complex datasets more effectively. These tools are critical for advancing research in materials science, renewable energy technologies, biofuels, electric vehicle infrastructure, energy efficiency - from industrial processes to entire communities - and then bringing these innovations to practice through energy systems integration. NREL's visualization tools drive innovation across renewable energy and grid modernization efforts by providing deeper insights and improving decision-making.
Numerical simulations of complex 3D time-dependent (unsteady) flows are becoming increasingly feasible because of the progress in computing systems. Unfortunately, many existing flow visualization systems were developed for time-independent (steady) solutions and do not adequately depict solutions from unsteady flow simulations. Furthermore, most systems only handle one time step of the solutions individually and do not consider the time-dependent nature of the solutions. For example, instantaneous streamlines are computed by tracking the particles using one time step of the solution. However, for streaklines and timelines, particles need to be tracked through all time steps. Streaklines can reveal quite different information about the flow than those revealed by instantaneous streamlines. Comparisons of instantaneous streamlines with dynamic streaklines are shown. For a complex 3D flow simulation, it is common to generate a grid system with several millions of grid points and to have tens of thousands of time steps. The disk requirement for storing the flow data can easily be tens of gigabytes. Visualizing solutions of this magnitude is a challenging problem with today's computer hardware technology. Even interactive visualization of one time step of the flow data can be a problem for some existing flow visualization systems because of the size of the grid. Current approaches for visualizing complex 3D time-dependent CFD solutions are described. The flow visualization system developed at NASA Ames Research Center to compute time-dependent particle traces from unsteady CFD solutions is described. The system computes particle traces (streaklines) by integrating through the time steps. This system has been used by several NASA scientists to visualize their CFD time-dependent solutions. The flow visualization capabilities of this system are described, and visualization results are shown.
Giovanni, the Goddard Earth Sciences Data and Information Services Center (GES DISC) Interactive Online Visualization and Analysis Infrastructure, has provided researchers with advanced capabilities to perform data exploration and analysis with observational data from NASA Earth observation satellites. In the past 5-10 years, examining geophysical events and processes with remote-sensing data required a multistep process of data discovery, data acquisition, data management, and ultimately data analysis. Giovanni accelerates this process by enabling basic visualization and analysis directly on the World Wide Web. In the last two years, Giovanni has added new data acquisition functions and expanded analysis options to increase its usefulness to the Earth science research community.
Video animation is becoming increasingly vital to the computational fluid dynamics researcher, not just for presentation, but for recording and comparing dynamic visualizations that are beyond the current capabilities of even the most powerful graphic workstation. To meet these needs, Lewis Research Center has recently established a facility to provide users with easy access to advanced video animation capabilities. However, producing animation that is both visually effective and scientifically accurate involves various technological and aesthetic considerations that must be understood both by the researcher and those supporting the visualization process. These considerations include: scan conversion, color conversion, and spatial ambiguities.
Visualization–the use of visual elements to explore data, form hypotheses, or convey conclusions–is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes to the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality and AI, visualization has become increasingly essential but also ever more challenging. Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing, with a special focus on DOE-relevant applications and goals. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision-making, and communication.
This paper presents the results of research into providing a means for users to flexibly create visualizations of the reasoning processes of forward-chaining rule-based expert systems using algorithm animation techniques. Levels of reasoning are described in order to identify the information necessary from the expert system development environment for these visualizations. A dual-process visualization environment is presented consisting of: (1) a version of CLIPS modified for the identified information access requirements; and (2) VISOR, an algorithm animation-based system for creating visualizations of arbitrary complexity which can be triggered by 'interesting event' messages from the running expert-system application. This is followed by examples from several visualizations performed during the scope of this work.
Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.
We report the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.
State-of-the-art research in computational aerosciences produces' complex, time-dependent datasets. Simulations can also be multidisciplinary in nature, coupling two or more physical disciplines such as fluid dynamics, structural dynamics, thermodynamics, and acoustics. Many diverse technologies are necessary for visualizing computational aerosciences simulations. This paper describes these technologies and how they contribute to building effective tools for use by domain scientists. These technologies include data management, distributed environments, advanced user interfaces, rapid prototyping environments, parallel computation, and methods to visualize the scalar and vector fields associated with computational aerosciences datasets.
Quantum dots (QDs) that absorb in the mid-wave infrared (MWIR) regime (3–5 μm) have recently generated significant interest as possible detector materials for MWIR cameras, with promises to reduce materials and device fabrication costs and potentially increase device operating temperatures. However, these materials have been primarily explored in single pixel devices – not multi-pixel cameras – and their current performance lags behind that of commercially available MWIR cameras based on single crystalline materials. To realize the potential of QD MWIR photodetectors with imaging capabilities, improvements are needed in the quality of the MWIR-absorbing QD materials, ligands dictating inter-QD charge transport, ordering of QD films, device architectures, and scalability of these methods to larger areas. With three families of QDs being researched – lead-, silver-, and mercury-based chalcogenides – as well as a multitude of possible capping ligands and film deposition techniques, the experimental phase space for MWIR QDs is vast. Here, we provide a roadmap, considering the pros and cons of various film deposition and ligand exchange techniques, as well as reintroduce lessons learned over years of research on QD film formation. We also extracted and created a database of reported quantum dot photodetectors’ performance and fabrication methods and have developed an interactive data visualization dashboard for this database, which provides researchers in the field a quick snapshot of the existing state of the art. Finally, we outline figures of merit and information that should be presented in papers moving forward which would help to clarify the reported results, as well as offer ideas for future steps. We provide a database visualization of the QD photodetector literature at https://public.tableau.com/app/profile/tom.nakotte/viz/IRQDphotodetectors_16384709473480/Dashboard1#1.
Synthetic Vision Systems and Enhanced Flight Vision System (SVS/EFVS) technologies have the potential to provide additional margins of safety for aircrew performance and enable operational improvements for low visibility operations in the terminal area environment with equivalent efficiency as visual operations. To meet this potential, research is needed for effective technology development and implementation of regulatory standards and design guidance to support introduction and use of SVS/EFVS advanced cockpit vision technologies in Next Generation Air Transportation System (NextGen) operations. A fixed-base pilot-in-the-loop simulation test was conducted at NASA Langley Research Center that evaluated the use of SVS/EFVS in NextGen low visibility approach and landing operations. Twelve crews flew approach and landing operations in a simulated NextGen Chicago O'Hare environment. Various scenarios tested the potential for using EFVS to conduct approach, landing, and roll-out operations in visibility as low as 1000 feet runway visual range (RVR). Also, SVS was tested to evaluate the potential for lowering decision heights (DH) on certain instrument approach procedures below what can be flown today. Expanding the portion of the visual segment in which EFVS can be used in lieu of natural vision from 100 feet above the touchdown zone elevation to touchdown and rollout in visibilities as low as 1000 feet RVR appears to be viable as touchdown performance was acceptable without any apparent workload penalties. A lower DH of 150 feet and/or possibly reduced visibility minima using SVS appears to be viable when implemented on a Head-Up Display, but the landing data suggests further study for head-down implementations.
We have developed an Interactive Data Language (IDL) scientific visualization software tool called GRIDVIEW that can be used in research and education to explore and study the most recent Mars Orbiter Laser Altimeter (MOLA) gridded topography of Mars (http://denali.gsfc.nasa.gov/mola_pub/gridview). Additional information is contained in the original extended abstract.
In two experiments, visually perceived eye level (VPEL) was measured while subjects viewed two-dimensional displays that were either upright or pitched 20 degrees top-toward or 20 degrees top-away from them. In Experiment 1, it was demonstrated that binocular exposure to a pair of pitched vertical lines or to a pitched random dot pattern caused a substantial upward VPEL shift for the top-toward pitched array and a similarly large downward shift for the top-away array. On the other hand, the same pitches of a pair of horizontal lines (viewed binocularly or monocularly) produced much smaller VPEL shifts. Because the perceived pitch of the pitched horizontal line display was nearly the same as the perceived pitch of the pitched vertical line and dot array, the relatively small influence of pitched horizontal lines on VPEL cannot be attributed simply to an underestimation of their pitch. In Experiment 2, the effects of pitched vertical lines, dots, and horizontal lines on VPEL were again measured, together with their effects on resting gaze direction (in the vertical dimension). As in Experiment 1, vertical lines and dots caused much larger VPEL shifts than did horizontal lines. The effects of the displays on resting gaze direction were highly similar to their effects on VPEL. These results are consistent with the hypothesis that VPEL shifts caused by pitched visual arrays are due to the direct influence of these arrays on the oculomotor system and are not mediated by perceived pitch.