The 3D widgets for exploratory scientific visualization

NASA Technical Reports Server (NTRS)

Herndon, Kenneth P.; Meyer, Tom

1995-01-01

Computational fluid dynamics (CFD) techniques are used to simulate flows of fluids like air or water around such objects as airplanes and automobiles. These techniques usually generate very large amounts of numerical data which are difficult to understand without using graphical scientific visualization techniques. There are a number of commercial scientific visualization applications available today which allow scientists to control visualization tools via textual and/or 2D user interfaces. However, these user interfaces are often difficult to use. We believe that 3D direct-manipulation techniques for interactively controlling visualization tools will provide opportunities for powerful and useful interfaces with which scientists can more effectively explore their datasets. A few systems have been developed which use these techniques. In this paper, we will present a variety of 3D interaction techniques for manipulating parameters of visualization tools used to explore CFD datasets, and discuss in detail various techniques for positioning tools in a 3D scene.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eric A. Wernert; William R. Sherman; Patrick O'Leary

Immersive visualization makes use of the medium of virtual reality (VR) - it is a subset of virtual reality focused on the application of VR technologies to scientific and information visualization. As the name implies, there is a particular focus on the physically immersive aspect of VR that more fully engages the perceptual and kinesthetic capabilities of the scientist with the goal of producing greater insight. The immersive visualization community is uniquely positioned to address the analysis needs of the wide spectrum of domain scientists who are becoming increasingly overwhelmed by data. The outputs of computational science simulations and high-resolutionmore » sensors are creating a data deluge. Data is coming in faster than it can be analyzed, and there are countless opportunities for discovery that are missed as the data speeds by. By more fully utilizing the scientists visual and other sensory systems, and by offering a more natural user interface with which to interact with computer-generated representations, immersive visualization offers great promise in taming this data torrent. However, increasing the adoption of immersive visualization in scientific research communities can only happen by simultaneously lowering the engagement threshold while raising the measurable benefits of adoption. Scientists time spent immersed with their data will thus be rewarded with higher productivity, deeper insight, and improved creativity. Immersive visualization ties together technologies and methodologies from a variety of related but frequently disjoint areas, including hardware, software and human-computer interaction (HCI) disciplines. In many ways, hardware is a solved problem. There are well established technologies including large walk-in systems such as the CAVE{trademark} and head-based systems such as the Wide-5{trademark}. The advent of new consumer-level technologies now enable an entirely new generation of immersive displays, with smaller footprints and costs, widening the potential consumer base. While one would be hard-pressed to call software a solved problem, we now understand considerably more about best practices for designing and developing sustainable, scalable software systems, and we have useful software examples that illuminate the way to even better implementations. As with any research endeavour, HCI will always be exploring new topics in interface design, but we now have a sizable knowledge base of the strengths and weaknesses of the human perceptual systems and we know how to design effective interfaces for immersive systems. So, in a research landscape with a clear need for better visualization and analysis tools, a methodology in immersive visualization that has been shown to effectively address some of those needs, and vastly improved supporting technologies and knowledge of hardware, software, and HCI, why hasn't immersive visualization 'caught on' more with scientists? What can we do as a community of immersive visualization researchers and practitioners to facilitate greater adoption by scientific communities so as to make the transition from 'the promise of virtual reality' to 'the reality of virtual reality'.« less

Methods for Creating and Animating a Computer Model Depicting the Structure and Function of the Sarcoplasmic Reticulum Calcium ATPase Enzyme.

ERIC Educational Resources Information Center

Chen, Alice Y.; McKee, Nancy

1999-01-01

Describes the developmental process used to visualize the calcium ATPase enzyme of the sarcoplasmic reticulum which involves evaluating scientific information, consulting scientists, model making, storyboarding, and creating and editing in a computer medium. (Author/CCM)

A Lightweight Remote Parallel Visualization Platform for Interactive Massive Time-varying Climate Data Analysis

NASA Astrophysics Data System (ADS)

Li, J.; Zhang, T.; Huang, Q.; Liu, Q.

2014-12-01

Today's climate datasets are featured with large volume, high degree of spatiotemporal complexity and evolving fast overtime. As visualizing large volume distributed climate datasets is computationally intensive, traditional desktop based visualization applications fail to handle the computational intensity. Recently, scientists have developed remote visualization techniques to address the computational issue. Remote visualization techniques usually leverage server-side parallel computing capabilities to perform visualization tasks and deliver visualization results to clients through network. In this research, we aim to build a remote parallel visualization platform for visualizing and analyzing massive climate data. Our visualization platform was built based on Paraview, which is one of the most popular open source remote visualization and analysis applications. To further enhance the scalability and stability of the platform, we have employed cloud computing techniques to support the deployment of the platform. In this platform, all climate datasets are regular grid data which are stored in NetCDF format. Three types of data access methods are supported in the platform: accessing remote datasets provided by OpenDAP servers, accessing datasets hosted on the web visualization server and accessing local datasets. Despite different data access methods, all visualization tasks are completed at the server side to reduce the workload of clients. As a proof of concept, we have implemented a set of scientific visualization methods to show the feasibility of the platform. Preliminary results indicate that the framework can address the computation limitation of desktop based visualization applications.

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

Molecules to maps: tools for visualization and interaction in support of computational biology.

PubMed

Kraemer, E T; Ferrin, T E

1998-01-01

The volume of data produced by genome projects, X-ray crystallography, NMR spectroscopy, and electron and confocal microscopy present the bioinformatics community with new challenges for analyzing, understanding, and exchanging this data. At the 1998 Pacific Symposium on Biocomputing, a track entitled 'Molecules to Maps: Tools for Visualization and Interaction in Computational Biology' provided tool developers and users with the opportunity to discuss advances in tools and techniques to assist scientists in evaluating, absorbing, navigating, and correlating this sea of information, through visualization and user interaction. In this paper we present these advances and discuss some of the challenges that remain to be solved.

hackseq: Catalyzing collaboration between biological and computational scientists via hackathon.

PubMed

2017-01-01

hackseq ( http://www.hackseq.com) was a genomics hackathon with the aim of bringing together a diverse set of biological and computational scientists to work on collaborative bioinformatics projects. In October 2016, 66 participants from nine nations came together for three days for hackseq and collaborated on nine projects ranging from data visualization to algorithm development. The response from participants was overwhelmingly positive with 100% (n = 54) of survey respondents saying they would like to participate in future hackathons. We detail key steps for others interested in organizing a successful hackathon and report excerpts from each project.

hackseq: Catalyzing collaboration between biological and computational scientists via hackathon

PubMed Central

2017-01-01

hackseq ( http://www.hackseq.com) was a genomics hackathon with the aim of bringing together a diverse set of biological and computational scientists to work on collaborative bioinformatics projects. In October 2016, 66 participants from nine nations came together for three days for hackseq and collaborated on nine projects ranging from data visualization to algorithm development. The response from participants was overwhelmingly positive with 100% (n = 54) of survey respondents saying they would like to participate in future hackathons. We detail key steps for others interested in organizing a successful hackathon and report excerpts from each project. PMID:28417000

EarthCube: A Community-Driven Cyberinfrastructure for the Geosciences

NASA Astrophysics Data System (ADS)

Koskela, Rebecca; Ramamurthy, Mohan; Pearlman, Jay; Lehnert, Kerstin; Ahern, Tim; Fredericks, Janet; Goring, Simon; Peckham, Scott; Powers, Lindsay; Kamalabdi, Farzad; Rubin, Ken; Yarmey, Lynn

2017-04-01

EarthCube is creating a dynamic, System of Systems (SoS) infrastructure and data tools to collect, access, analyze, share, and visualize all forms of geoscience data and resources, using advanced collaboration, technological, and computational capabilities. EarthCube, as a joint effort between the U.S. National Science Foundation Directorate for Geosciences and the Division of Advanced Cyberinfrastructure, is a quickly growing community of scientists across all geoscience domains, as well as geoinformatics researchers and data scientists. EarthCube has attracted an evolving, dynamic virtual community of more than 2,500 contributors, including earth, ocean, polar, planetary, atmospheric, geospace, computer and social scientists, educators, and data and information professionals. During 2017, EarthCube will transition to the implementation phase. The implementation will balance "innovation" and "production" to advance cross-disciplinary science goals as well as the development of future data scientists. This presentation will describe the current architecture design for the EarthCube cyberinfrastructure and implementation plan.

Recent Advances in Immersive Visualization of Ocean Data: Virtual Reality Through the Web on Your Laptop Computer

NASA Astrophysics Data System (ADS)

Hermann, A. J.; Moore, C.; Soreide, N. N.

2002-12-01

Ocean circulation is irrefutably three dimensional, and powerful new measurement technologies and numerical models promise to expand our three-dimensional knowledge of the dynamics further each year. Yet, most ocean data and model output is still viewed using two-dimensional maps. Immersive visualization techniques allow the investigator to view their data as a three dimensional world of surfaces and vectors which evolves through time. The experience is not unlike holding a part of the ocean basin in one's hand, turning and examining it from different angles. While immersive, three dimensional visualization has been possible for at least a decade, the technology was until recently inaccessible (both physically and financially) for most researchers. It is not yet fully appreciated by practicing oceanographers how new, inexpensive computing hardware and software (e.g. graphics cards and controllers designed for the huge PC gaming market) can be employed for immersive, three dimensional, color visualization of their increasingly huge datasets and model output. In fact, the latest developments allow immersive visualization through web servers, giving scientists the ability to "fly through" three-dimensional data stored half a world away. Here we explore what additional insight is gained through immersive visualization, describe how scientists of very modest means can easily avail themselves of the latest technology, and demonstrate its implementation on a web server for Pacific Ocean model output.

Art-Science-Technology collaboration through immersive, interactive 3D visualization

NASA Astrophysics Data System (ADS)

Kellogg, L. H.

2014-12-01

At the W. M. Keck Center for Active Visualization in Earth Sciences (KeckCAVES), a group of geoscientists and computer scientists collaborate to develop and use of interactive, immersive, 3D visualization technology to view, manipulate, and interpret data for scientific research. The visual impact of immersion in a CAVE environment can be extremely compelling, and from the outset KeckCAVES scientists have collaborated with artists to bring this technology to creative works, including theater and dance performance, installations, and gamification. The first full-fledged collaboration designed and produced a performance called "Collapse: Suddenly falling down", choreographed by Della Davidson, which investigated the human and cultural response to natural and man-made disasters. Scientific data (lidar scans of disaster sites, such as landslides and mine collapses) were fully integrated into the performance by the Sideshow Physical Theatre. This presentation will discuss both the technological and creative characteristics of, and lessons learned from the collaboration. Many parallels between the artistic and scientific process emerged. We observed that both artists and scientists set out to investigate a topic, solve a problem, or answer a question. Refining that question or problem is an essential part of both the creative and scientific workflow. Both artists and scientists seek understanding (in this case understanding of natural disasters). Differences also emerged; the group noted that the scientists sought clarity (including but not limited to quantitative measurements) as a means to understanding, while the artists embraced ambiguity, also as a means to understanding. Subsequent art-science-technology collaborations have responded to evolving technology for visualization and include gamification as a means to explore data, and use of augmented reality for informal learning in museum settings.

Software for visualization, analysis, and manipulation of laser scan images

NASA Astrophysics Data System (ADS)

Burnsides, Dennis B.

1997-03-01

The recent introduction of laser surface scanning to scientific applications presents a challenge to computer scientists and engineers. Full utilization of this two- dimensional (2-D) and three-dimensional (3-D) data requires advances in techniques and methods for data processing and visualization. This paper explores the development of software to support the visualization, analysis and manipulation of laser scan images. Specific examples presented are from on-going efforts at the Air Force Computerized Anthropometric Research and Design (CARD) Laboratory.

Final Report. Institute for Ultralscale Visualization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Kwan-Liu; Galli, Giulia; Gygi, Francois

The SciDAC Institute for Ultrascale Visualization brought together leading experts from visualization, high-performance computing, and science application areas to make advanced visualization solutions for SciDAC scientists and the broader community. Over the five-year project, the Institute introduced many new enabling visualization techniques, which have significantly enhanced scientists’ ability to validate their simulations, interpret their data, and communicate with others about their work and findings. This Institute project involved a large number of junior and student researchers, who received the opportunities to work on some of the most challenging science applications and gain access to the most powerful high-performance computing facilitiesmore » in the world. They were readily trained and prepared for facing the greater challenges presented by extreme-scale computing. The Institute’s outreach efforts, through publications, workshops and tutorials, successfully disseminated the new knowledge and technologies to the SciDAC and the broader scientific communities. The scientific findings and experience of the Institute team helped plan the SciDAC3 program.« less

Visually impaired researchers get their hands on quantum chemistry: application to a computational study on the isomerization of a sterol.

PubMed

Lounnas, Valère; Wedler, Henry B; Newman, Timothy; Schaftenaar, Gijs; Harrison, Jason G; Nepomuceno, Gabriella; Pemberton, Ryan; Tantillo, Dean J; Vriend, Gert

2014-11-01

In molecular sciences, articles tend to revolve around 2D representations of 3D molecules, and sighted scientists often resort to 3D virtual reality software to study these molecules in detail. Blind and visually impaired (BVI) molecular scientists have access to a series of audio devices that can help them read the text in articles and work with computers. Reading articles published in this journal, though, is nearly impossible for them because they need to generate mental 3D images of molecules, but the article-reading software cannot do that for them. We have previously designed AsteriX, a web server that fully automatically decomposes articles, detects 2D plots of low molecular weight molecules, removes meta data and annotations from these plots, and converts them into 3D atomic coordinates. AsteriX-BVI goes one step further and converts the 3D representation into a 3D printable, haptic-enhanced format that includes Braille annotations. These Braille-annotated physical 3D models allow BVI scientists to generate a complete mental model of the molecule. AsteriX-BVI uses Molden to convert the meta data of quantum chemistry experiments into BVI friendly formats so that the entire line of scientific information that sighted people take for granted-from published articles, via printed results of computational chemistry experiments, to 3D models-is now available to BVI scientists too. The possibilities offered by AsteriX-BVI are illustrated by a project on the isomerization of a sterol, executed by the blind co-author of this article (HBW).

Visually impaired researchers get their hands on quantum chemistry: application to a computational study on the isomerization of a sterol

NASA Astrophysics Data System (ADS)

Lounnas, Valère; Wedler, Henry B.; Newman, Timothy; Schaftenaar, Gijs; Harrison, Jason G.; Nepomuceno, Gabriella; Pemberton, Ryan; Tantillo, Dean J.; Vriend, Gert

2014-11-01

In molecular sciences, articles tend to revolve around 2D representations of 3D molecules, and sighted scientists often resort to 3D virtual reality software to study these molecules in detail. Blind and visually impaired (BVI) molecular scientists have access to a series of audio devices that can help them read the text in articles and work with computers. Reading articles published in this journal, though, is nearly impossible for them because they need to generate mental 3D images of molecules, but the article-reading software cannot do that for them. We have previously designed AsteriX, a web server that fully automatically decomposes articles, detects 2D plots of low molecular weight molecules, removes meta data and annotations from these plots, and converts them into 3D atomic coordinates. AsteriX-BVI goes one step further and converts the 3D representation into a 3D printable, haptic-enhanced format that includes Braille annotations. These Braille-annotated physical 3D models allow BVI scientists to generate a complete mental model of the molecule. AsteriX-BVI uses Molden to convert the meta data of quantum chemistry experiments into BVI friendly formats so that the entire line of scientific information that sighted people take for granted—from published articles, via printed results of computational chemistry experiments, to 3D models—is now available to BVI scientists too. The possibilities offered by AsteriX-BVI are illustrated by a project on the isomerization of a sterol, executed by the blind co-author of this article (HBW).

Collaborations in art/science: Renaissance teams.

PubMed

Cox, D J

1991-01-01

A Renaissance Team is a group of specialists who collaborate and provide synergism in the quest for knowledge and information. Artists can participate in Renaissance Teams with scientists and computer specialists for scientific visualization projects. Some projects are described in which the author functioned as programmer and color expert, as interface designer, as visual paradigm maker, as animator, and as producer. Examples are provided for each of these five projects.

Atomic Detail Visualization of Photosynthetic Membranes with GPU-Accelerated Ray Tracing

PubMed Central

Vandivort, Kirby L.; Barragan, Angela; Singharoy, Abhishek; Teo, Ivan; Ribeiro, João V.; Isralewitz, Barry; Liu, Bo; Goh, Boon Chong; Phillips, James C.; MacGregor-Chatwin, Craig; Johnson, Matthew P.; Kourkoutis, Lena F.; Hunter, C. Neil

2016-01-01

The cellular process responsible for providing energy for most life on Earth, namely photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers. PMID:27274603

IVAG: An Integrative Visualization Application for Various Types of Genomic Data Based on R-Shiny and the Docker Platform.

PubMed

Lee, Tae-Rim; Ahn, Jin Mo; Kim, Gyuhee; Kim, Sangsoo

2017-12-01

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Dean N.

2011-07-20

This report summarizes work carried out by the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Team for the period of January 1, 2011 through June 30, 2011. It discusses highlights, overall progress, period goals, and collaborations and lists papers and presentations. To learn more about our project, please visit our UV-CDAT website (URL: http://uv-cdat.org). This report will be forwarded to the program manager for the Department of Energy (DOE) Office of Biological and Environmental Research (BER), national and international collaborators and stakeholders, and to researchers working on a wide range of other climate model, reanalysis, and observation evaluation activities. Themore » UV-CDAT executive committee consists of Dean N. Williams of Lawrence Livermore National Laboratory (LLNL); Dave Bader and Galen Shipman of Oak Ridge National Laboratory (ORNL); Phil Jones and James Ahrens of Los Alamos National Laboratory (LANL), Claudio Silva of Polytechnic Institute of New York University (NYU-Poly); and Berk Geveci of Kitware, Inc. The UV-CDAT team consists of researchers and scientists with diverse domain knowledge whose home institutions also include the National Aeronautics and Space Administration (NASA) and the University of Utah. All work is accomplished under DOE open-source guidelines and in close collaboration with the project's stakeholders, domain researchers, and scientists. Working directly with BER climate science analysis projects, this consortium will develop and deploy data and computational resources useful to a wide variety of stakeholders, including scientists, policymakers, and the general public. Members of this consortium already collaborate with other institutions and universities in researching data discovery, management, visualization, workflow analysis, and provenance. The UV-CDAT team will address the following high-level visualization requirements: (1) Alternative parallel streaming statistics and analysis pipelines - Data parallelism, Task parallelism, Visualization parallelism; (2) Optimized parallel input/output (I/O); (3) Remote interactive execution; (4) Advanced intercomparison visualization; (5) Data provenance processing and capture; and (6) Interfaces for scientists - Workflow data analysis and visualization construction tools, and Visualization interfaces.« less

McIDAS-V: A Data Analysis and Visualization Tool for Global Satellite Data

NASA Astrophysics Data System (ADS)

Achtor, T. H.; Rink, T. D.

2011-12-01

The Man-computer Interactive Data Access System (McIDAS-V) is a java-based, open-source, freely available system for scientists, researchers and algorithm developers working with atmospheric data. The McIDAS-V software tools provide powerful new data manipulation and visualization capabilities, including 4-dimensional displays, an abstract data model with integrated metadata, user defined computation, and a powerful scripting capability. As such, McIDAS-V is a valuable tool for scientists and researchers within the GEO and GOESS domains. The advancing polar and geostationary orbit environmental satellite missions conducted by several countries will carry advanced instrumentation and systems that will collect and distribute land, ocean, and atmosphere data. These systems provide atmospheric and sea surface temperatures, humidity sounding, cloud and aerosol properties, and numerous other environmental products. This presentation will display and demonstrate some of the capabilities of McIDAS-V to analyze and display high temporal and spectral resolution data using examples from international environmental satellites.

NASA's Pleiades Supercomputer Crunches Data For Groundbreaking Analysis and Visualizations

NASA Image and Video Library

2016-11-23

The Pleiades supercomputer at NASA's Ames Research Center, recently named the 13th fastest computer in the world, provides scientists and researchers high-fidelity numerical modeling of complex systems and processes. By using detailed analyses and visualizations of large-scale data, Pleiades is helping to advance human knowledge and technology, from designing the next generation of aircraft and spacecraft to understanding the Earth's climate and the mysteries of our galaxy.

Climate@Home: Crowdsourcing Climate Change Research

NASA Astrophysics Data System (ADS)

Xu, C.; Yang, C.; Li, J.; Sun, M.; Bambacus, M.

2011-12-01

Climate change deeply impacts human wellbeing. Significant amounts of resources have been invested in building super-computers that are capable of running advanced climate models, which help scientists understand climate change mechanisms, and predict its trend. Although climate change influences all human beings, the general public is largely excluded from the research. On the other hand, scientists are eagerly seeking communication mediums for effectively enlightening the public on climate change and its consequences. The Climate@Home project is devoted to connect the two ends with an innovative solution: crowdsourcing climate computing to the general public by harvesting volunteered computing resources from the participants. A distributed web-based computing platform will be built to support climate computing, and the general public can 'plug-in' their personal computers to participate in the research. People contribute the spare computing power of their computers to run a computer model, which is used by scientists to predict climate change. Traditionally, only super-computers could handle such a large computing processing load. By orchestrating massive amounts of personal computers to perform atomized data processing tasks, investments on new super-computers, energy consumed by super-computers, and carbon release from super-computers are reduced. Meanwhile, the platform forms a social network of climate researchers and the general public, which may be leveraged to raise climate awareness among the participants. A portal is to be built as the gateway to the climate@home project. Three types of roles and the corresponding functionalities are designed and supported. The end users include the citizen participants, climate scientists, and project managers. Citizen participants connect their computing resources to the platform by downloading and installing a computing engine on their personal computers. Computer climate models are defined at the server side. Climate scientists configure computer model parameters through the portal user interface. After model configuration, scientists then launch the computing task. Next, data is atomized and distributed to computing engines that are running on citizen participants' computers. Scientists will receive notifications on the completion of computing tasks, and examine modeling results via visualization modules of the portal. Computing tasks, computing resources, and participants are managed by project managers via portal tools. A portal prototype has been built for proof of concept. Three forums have been setup for different groups of users to share information on science aspect, technology aspect, and educational outreach aspect. A facebook account has been setup to distribute messages via the most popular social networking platform. New treads are synchronized from the forums to facebook. A mapping tool displays geographic locations of the participants and the status of tasks on each client node. A group of users have been invited to test functions such as forums, blogs, and computing resource monitoring.

Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, John E.; Sener, Melih; Vandivort, Kirby L.

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. In this paper, we present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. Finally, we describemore » the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.« less

Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, John E.; Sener, Melih; Vandivort, Kirby L.

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that weremore » used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.« less

Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

DOE PAGES

Stone, John E.; Sener, Melih; Vandivort, Kirby L.; ...

2015-12-12

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. In this paper, we present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. Finally, we describemore » the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.« less

Participatory Design of Human-Centered Cyberinfrastructure (Invited)

NASA Astrophysics Data System (ADS)

Pennington, D. D.; Gates, A. Q.

2010-12-01

Cyberinfrastructure, by definition, is about people sharing resources to achieve outcomes that cannot be reached independently. CI depends not just on creating discoverable resources, or tools that allow those resources to be processed, integrated, and visualized -- but on human activation of flows of information across those resources. CI must be centered on human activities. Yet for those CI projects that are directed towards observational science, there are few models for organizing collaborative research in ways that align individual research interests into a collective vision of CI-enabled science. Given that the emerging technologies are themselves expected to change the way science is conducted, it is not simply a matter of conducting requirements analysis on how scientists currently work, or building consensus among the scientists on what is needed. Developing effective CI depends on generating a new, creative vision of problem solving within a community based on computational concepts that are, in some cases, still very abstract and theoretical. The computer science theory may (or may not) be well formalized, but the potential for impact on any particular domain is typically ill-defined. In this presentation we will describe approaches being developed and tested at the CyberShARE Center of Excellence at University of Texas in El Paso for ill-structured problem solving within cross-disciplinary teams of scientists and computer scientists working on data intensive environmental and geoscience. These approaches deal with the challenges associated with sharing and integrating knowledge across disciplines; the challenges of developing effective teamwork skills in a culture that favors independent effort; and the challenges of evolving shared, focused research goals from ill-structured, vague starting points - all issues that must be confronted by every interdisciplinary CI project. We will introduce visual and semantic-based tools that can enable the collaborative research design process and illustrate their application in designing and developing useful end-to-end data solutions for scientists. Lastly, we will outline areas of future investigation within CyberShARE that we believe have the potential for high impact.

Visual Analytics for Heterogeneous Geoscience Data

NASA Astrophysics Data System (ADS)

Pan, Y.; Yu, L.; Zhu, F.; Rilee, M. L.; Kuo, K. S.; Jiang, H.; Yu, H.

2017-12-01

Geoscience data obtained from diverse sources have been routinely leveraged by scientists to study various phenomena. The principal data sources include observations and model simulation outputs. These data are characterized by spatiotemporal heterogeneity originated from different instrument design specifications and/or computational model requirements used in data generation processes. Such inherent heterogeneity poses several challenges in exploring and analyzing geoscience data. First, scientists often wish to identify features or patterns co-located among multiple data sources to derive and validate certain hypotheses. Heterogeneous data make it a tedious task to search such features in dissimilar datasets. Second, features of geoscience data are typically multivariate. It is challenging to tackle the high dimensionality of geoscience data and explore the relations among multiple variables in a scalable fashion. Third, there is a lack of transparency in traditional automated approaches, such as feature detection or clustering, in that scientists cannot intuitively interact with their analysis processes and interpret results. To address these issues, we present a new scalable approach that can assist scientists in analyzing voluminous and diverse geoscience data. We expose a high-level query interface that allows users to easily express their customized queries to search features of interest across multiple heterogeneous datasets. For identified features, we develop a visualization interface that enables interactive exploration and analytics in a linked-view manner. Specific visualization techniques such as scatter plots to parallel coordinates are employed in each view to allow users to explore various aspects of features. Different views are linked and refreshed according to user interactions in any individual view. In such a manner, a user can interactively and iteratively gain understanding into the data through a variety of visual analytics operations. We demonstrate with use cases how scientists can combine the query and visualization interfaces to enable a customized workflow facilitating studies using heterogeneous geoscience datasets.

Accessing and Visualizing scientific spatiotemporal data

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Bergou, Attila; Berriman, Bruce G.; Block, Gary L.; Collier, Jim; Curkendall, David W.; Good, John; Husman, Laura; Jacob, Joseph C.; Laity, Anastasia;

Graphics Processing Unit Assisted Thermographic Compositing

NASA Technical Reports Server (NTRS)

Ragasa, Scott; Russell, Samuel S.

2012-01-01

Objective Develop a software application utilizing high performance computing techniques, including general purpose graphics processing units (GPGPUs), for the analysis and visualization of large thermographic data sets. Over the past several years, an increasing effort among scientists and engineers to utilize graphics processing units (GPUs) in a more general purpose fashion is allowing for previously unobtainable levels of computation by individual workstations. As data sets grow, the methods to work them grow at an equal, and often greater, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU which yield significant increases in performance. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Image processing is one area were GPUs are being used to greatly increase the performance of certain analysis and visualization techniques.

How Scientists Develop Competence in Visual Communication

ERIC Educational Resources Information Center

Ostergren, Marilyn

2013-01-01

Visuals (maps, charts, diagrams and illustrations) are an important tool for communication in most scientific disciplines, which means that scientists benefit from having strong visual communication skills. This dissertation examines the nature of competence in visual communication and the means by which scientists acquire this competence. This…

The nature of the (visualization) game: Challenges and opportunities from computational geophysics

NASA Astrophysics Data System (ADS)

Kellogg, L. H.

2016-12-01

As the geosciences enters the era of big data, modeling and visualization become increasingly vital tools for discovery, understanding, education, and communication. Here, we focus on modeling and visualization of the structure and dynamics of the Earth's surface and interior. The past decade has seen accelerated data acquisition, including higher resolution imaging and modeling of Earth's deep interior, complex models of geodynamics, and high resolution topographic imaging of the changing surface, with an associated acceleration of computational modeling through better scientific software, increased computing capability, and the use of innovative methods of scientific visualization. The role of modeling is to describe a system, answer scientific questions, and test hypotheses; the term "model" encompasses mathematical models, computational models, physical models, conceptual models, statistical models, and visual models of a structure or process. These different uses of the term require thoughtful communication to avoid confusion. Scientific visualization is integral to every aspect of modeling. Not merely a means of communicating results, the best uses of visualization enable scientists to interact with their data, revealing the characteristics of the data and models to enable better interpretation and inform the direction of future investigation. Innovative immersive technologies like virtual reality, augmented reality, and remote collaboration techniques, are being adapted more widely and are a magnet for students. Time-varying or transient phenomena are especially challenging to model and to visualize; researchers and students may need to investigate the role of initial conditions in driving phenomena, while nonlinearities in the governing equations of many Earth systems make the computations and resulting visualization especially challenging. Training students how to use, design, build, and interpret scientific modeling and visualization tools prepares them to better understand the nature of complex, multiscale geoscience data.

Advanced in Visualization of 3D Time-Dependent CFD Solutions

NASA Technical Reports Server (NTRS)

Lane, David A.; Lasinski, T. A. (Technical Monitor)

1995-01-01

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.

Tessera: Open source software for accelerated data science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sego, Landon H.; Hafen, Ryan P.; Director, Hannah M.

2014-06-30

Extracting useful, actionable information from data can be a formidable challenge for the safeguards, nonproliferation, and arms control verification communities. Data scientists are often on the “front-lines” of making sense of complex and large datasets. They require flexible tools that make it easy to rapidly reformat large datasets, interactively explore and visualize data, develop statistical algorithms, and validate their approaches—and they need to perform these activities with minimal lines of code. Existing commercial software solutions often lack extensibility and the flexibility required to address the nuances of the demanding and dynamic environments where data scientists work. To address this need,more » Pacific Northwest National Laboratory developed Tessera, an open source software suite designed to enable data scientists to interactively perform their craft at the terabyte scale. Tessera automatically manages the complicated tasks of distributed storage and computation, empowering data scientists to do what they do best: tackling critical research and mission objectives by deriving insight from data. We illustrate the use of Tessera with an example analysis of computer network data.« less

Correlative visualization techniques for multidimensional data

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Goettsche, Craig

1989-01-01

Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system.

Reducing Time to Science: Unidata and JupyterHub Technology Using the Jetstream Cloud

NASA Astrophysics Data System (ADS)

Chastang, J.; Signell, R. P.; Fischer, J. L.

2017-12-01

Cloud computing can accelerate scientific workflows, discovery, and collaborations by reducing research and data friction. We describe the deployment of Unidata and JupyterHub technologies on the NSF-funded XSEDE Jetstream cloud. With the aid of virtual machines and Docker technology, we deploy a Unidata JupyterHub server co-located with a Local Data Manager (LDM), THREDDS data server (TDS), and RAMADDA geoscience content management system. We provide Jupyter Notebooks and the pre-built Python environments needed to run them. The notebooks can be used for instruction and as templates for scientific experimentation and discovery. We also supply a large quantity of NCEP forecast model results to allow data-proximate analysis and visualization. In addition, users can transfer data using Globus command line tools, and perform their own data-proximate analysis and visualization with Notebook technology. These data can be shared with others via a dedicated TDS server for scientific distribution and collaboration. There are many benefits of this approach. Not only is the cloud computing environment fast, reliable and scalable, but scientists can analyze, visualize, and share data using only their web browser. No local specialized desktop software or a fast internet connection is required. This environment will enable scientists to spend less time managing their software and more time doing science.

Runtime visualization of the human arterial tree.

PubMed

Insley, Joseph A; Papka, Michael E; Dong, Suchuan; Karniadakis, George; Karonis, Nicholas T

2007-01-01

Large-scale simulation codes typically execute for extended periods of time and often on distributed computational resources. Because these simulations can run for hours, or even days, scientists like to get feedback about the state of the computation and the validity of its results as it runs. It is also important that these capabilities be made available with little impact on the performance and stability of the simulation. Visualizing and exploring data in the early stages of the simulation can help scientists identify problems early, potentially avoiding a situation where a simulation runs for several days, only to discover that an error with an input parameter caused both time and resources to be wasted. We describe an application that aids in the monitoring and analysis of a simulation of the human arterial tree. The application provides researchers with high-level feedback about the state of the ongoing simulation and enables them to investigate particular areas of interest in greater detail. The application also offers monitoring information about the amount of data produced and data transfer performance among the various components of the application.

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

NASA Technical Reports Server (NTRS)

Sen, Syamal K.; Shaykhian, Gholam Ali

2011-01-01

MatLab(TradeMark)(MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many countries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its real strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbox. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using symbolic operations. MatLab in its interpreter programming language form (command interface) is similar with well known programming languages such as C/C++, support data structures and cell arrays to define classes in object oriented programming. As such, MatLab is equipped with most of the essential constructs of a higher programming language. MatLab is packaged with an editor and debugging functionality useful to perform analysis of large MatLab programs and find errors. We believe there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and analysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applications. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientific problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabular format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed.

The Perspective Structure of Visual Space

PubMed Central

2015-01-01

Luneburg’s model has been the reference for experimental studies of visual space for almost seventy years. His claim for a curved visual space has been a source of inspiration for visual scientists as well as philosophers. The conclusion of many experimental studies has been that Luneburg’s model does not describe visual space in various tasks and conditions. Remarkably, no alternative model has been suggested. The current study explores perspective transformations of Euclidean space as a model for visual space. Computations show that the geometry of perspective spaces is considerably different from that of Euclidean space. Collinearity but not parallelism is preserved in perspective space and angles are not invariant under translation and rotation. Similar relationships have shown to be properties of visual space. Alley experiments performed early in the nineteenth century have been instrumental in hypothesizing curved visual spaces. Alleys were computed in perspective space and compared with reconstructed alleys of Blumenfeld. Parallel alleys were accurately described by perspective geometry. Accurate distance alleys were derived from parallel alleys by adjusting the interstimulus distances according to the size-distance invariance hypothesis. Agreement between computed and experimental alleys and accommodation of experimental results that rejected Luneburg’s model show that perspective space is an appropriate model for how we perceive orientations and angles. The model is also appropriate for perceived distance ratios between stimuli but fails to predict perceived distances. PMID:27648222

Interactive client side data visualization with d3.js

NASA Astrophysics Data System (ADS)

Rodzianko, A.; Versteeg, R.; Johnson, D. V.; Soltanian, M. R.; Versteeg, O. J.; Girouard, M.

2015-12-01

Geoscience data associated with near surface research and operational sites is increasingly voluminous and heterogeneous (both in terms of providers and data types - e.g. geochemical, hydrological, geophysical, modeling data, of varying spatiotemporal characteristics). Such data allows scientists to investigate fundamental hydrological and geochemical processes relevant to agriculture, water resources and climate change. For scientists to easily share, model and interpret such data requires novel tools with capabilities for interactive data visualization. Under sponsorship of the US Department of Energy, Subsurface Insights is developing the Predictive Assimilative Framework (PAF): a cloud based subsurface monitoring platform which can manage, process and visualize large heterogeneous datasets. Over the last year we transitioned our visualization method from a server side approach (in which images and animations were generated using Jfreechart and Visit) to a client side one that utilizes the D3 Javascript library. Datasets are retrieved using web service calls to the server, returned as JSON objects and visualized within the browser. Users can interactively explore primary and secondary datasets from various field locations. Our current capabilities include interactive data contouring and heterogeneous time series data visualization. While this approach is very powerful and not necessarily unique, special attention needs to be paid to latency and responsiveness issues as well as to issues as cross browser code compatibility so that users have an identical, fluid and frustration-free experience across different computational platforms. We gratefully acknowledge support from the US Department of Energy under SBIR Award DOE DE-SC0009732, the use of data from the Lawrence Berkeley National Laboratory (LBNL) Sustainable Systems SFA Rifle field site and collaboration with LBNL SFA scientists.

Data Cube Visualization with Blender

NASA Astrophysics Data System (ADS)

Kent, Brian R.; Gárate, Matías

2017-06-01

With the increasing data acquisition rates from observational and computational astrophysics, new tools are needed to study and visualize data. We present a methodology for rendering 3D data cubes using the open-source 3D software Blender. By importing processed observations and numerical simulations through the Voxel Data format, we are able use the Blender interface and Python API to create high-resolution animated visualizations. We review the methods for data import, animation, and camera movement, and present examples of this methodology. The 3D rendering of data cubes gives scientists the ability to create appealing displays that can be used for both scientific presentations as well as public outreach.

Multiuser Collaboration with Networked Mobile Devices

NASA Technical Reports Server (NTRS)

Tso, Kam S.; Tai, Ann T.; Deng, Yong M.; Becks, Paul G.

2006-01-01

In this paper we describe a multiuser collaboration infrastructure that enables multiple mission scientists to remotely and collaboratively interact with visualization and planning software, using wireless networked personal digital assistants(PDAs) and other mobile devices. During ground operations of planetary rover and lander missions, scientists need to meet daily to review downlinked data and plan science activities. For example, scientists use the Science Activity Planner (SAP) in the Mars Exploration Rover (MER) mission to visualize downlinked data and plan rover activities during the science meetings [1]. Computer displays are projected onto large screens in the meeting room to enable the scientists to view and discuss downlinked images and data displayed by SAP and other software applications. However, only one person can interact with the software applications because input to the computer is limited to a single mouse and keyboard. As a result, the scientists have to verbally express their intentions, such as selecting a target at a particular location on the Mars terrain image, to that person in order to interact with the applications. This constrains communication and limits the returns of science planning. Furthermore, ground operations for Mars missions are fundamentally constrained by the short turnaround time for science and engineering teams to process and analyze data, plan the next uplink, generate command sequences, and transmit the uplink to the vehicle [2]. Therefore, improving ground operations is crucial to the success of Mars missions. The multiuser collaboration infrastructure enables users to control software applications remotely and collaboratively using mobile devices. The infrastructure includes (1) human-computer interaction techniques to provide natural, fast, and accurate inputs, (2) a communications protocol to ensure reliable and efficient coordination of the input devices and host computers, (3) an application-independent middleware that maintains the states, sessions, and interactions of individual users of the software applications, (4) an application programming interface to enable tight integration of applications and the middleware. The infrastructure is able to support any software applications running under the Windows or Unix platforms. The resulting technologies not only are applicable to NASA mission operations, but also useful in other situations such as design reviews, brainstorming sessions, and business meetings, as they can benefit from having the participants concurrently interact with the software applications (e.g., presentation applications and CAD design tools) to illustrate their ideas and provide inputs.

Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists.

PubMed

Zhu, Xun; Wolfgruber, Thomas K; Tasato, Austin; Arisdakessian, Cédric; Garmire, David G; Garmire, Lana X

2017-12-05

Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

Preparing for in situ processing on upcoming leading-edge supercomputers

DOE PAGES

Kress, James; Churchill, Randy Michael; Klasky, Scott; ...

2016-10-01

High performance computing applications are producing increasingly large amounts of data and placing enormous stress on current capabilities for traditional post-hoc visualization techniques. Because of the growing compute and I/O imbalance, data reductions, including in situ visualization, are required. These reduced data are used for analysis and visualization in a variety of different ways. Many of he visualization and analysis requirements are known a priori, but when they are not, scientists are dependent on the reduced data to accurately represent the simulation in post hoc analysis. The contributions of this paper is a description of the directions we are pursuingmore » to assist a large scale fusion simulation code succeed on the next generation of supercomputers. Finally, these directions include the role of in situ processing for performing data reductions, as well as the tradeoffs between data size and data integrity within the context of complex operations in a typical scientific workflow.« less

3D Feature Extraction for Unstructured Grids

NASA Technical Reports Server (NTRS)

Silver, Deborah

1996-01-01

Visualization techniques provide tools that help scientists identify observed phenomena in scientific simulation. To be useful, these tools must allow the user to extract regions, classify and visualize them, abstract them for simplified representations, and track their evolution. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This article explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and those from Finite Element Analysis.

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Photo-realistic Terrain Modeling and Visualization for Mars Exploration Rover Science Operations

NASA Technical Reports Server (NTRS)

Edwards, Laurence; Sims, Michael; Kunz, Clayton; Lees, David; Bowman, Judd

2005-01-01

Modern NASA planetary exploration missions employ complex systems of hardware and software managed by large teams of. engineers and scientists in order to study remote environments. The most complex and successful of these recent projects is the Mars Exploration Rover mission. The Computational Sciences Division at NASA Ames Research Center delivered a 30 visualization program, Viz, to the MER mission that provides an immersive, interactive environment for science analysis of the remote planetary surface. In addition, Ames provided the Athena Science Team with high-quality terrain reconstructions generated with the Ames Stereo-pipeline. The on-site support team for these software systems responded to unanticipated opportunities to generate 30 terrain models during the primary MER mission. This paper describes Viz, the Stereo-pipeline, and the experiences of the on-site team supporting the scientists at JPL during the primary MER mission.

Alliance for Computational Science Collaboration HBCU Partnership at Fisk University. Final Report 2001

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, W. E.

2004-08-16

Computational Science plays a big role in research and development in mathematics, science, engineering and biomedical disciplines. The Alliance for Computational Science Collaboration (ACSC) has the goal of training African-American and other minority scientists in the computational science field for eventual employment with the Department of Energy (DOE). The involvements of Historically Black Colleges and Universities (HBCU) in the Alliance provide avenues for producing future DOE African-American scientists. Fisk University has been participating in this program through grants from the DOE. The DOE grant supported computational science activities at Fisk University. The research areas included energy related projects, distributed computing,more » visualization of scientific systems and biomedical computing. Students' involvement in computational science research included undergraduate summer research at Oak Ridge National Lab, on-campus research involving the participation of undergraduates, participation of undergraduate and faculty members in workshops, and mentoring of students. These activities enhanced research and education in computational science, thereby adding to Fisk University's spectrum of research and educational capabilities. Among the successes of the computational science activities are the acceptance of three undergraduate students to graduate schools with full scholarships beginning fall 2002 (one for master degree program and two for Doctoral degree program).« less

Visualizing the ground motions of the 1906 San Francisco earthquake

USGS Publications Warehouse

Chourasia, A.; Cutchin, S.; Aagaard, Brad T.

2008-01-01

With advances in computational capabilities and refinement of seismic wave-propagation models in the past decade large three-dimensional simulations of earthquake ground motion have become possible. The resulting datasets from these simulations are multivariate, temporal and multi-terabyte in size. Past visual representations of results from seismic studies have been largely confined to static two-dimensional maps. New visual representations provide scientists with alternate ways of viewing and interacting with these results potentially leading to new and significant insight into the physical phenomena. Visualizations can also be used for pedagogic and general dissemination purposes. We present a workflow for visual representation of the data from a ground motion simulation of the great 1906 San Francisco earthquake. We have employed state of the art animation tools for visualization of the ground motions with a high degree of accuracy and visual realism. ?? 2008 Elsevier Ltd.

Quantum Computing Architectural Design

NASA Astrophysics Data System (ADS)

West, Jacob; Simms, Geoffrey; Gyure, Mark

2006-03-01

Large scale quantum computers will invariably require scalable architectures in addition to high fidelity gate operations. Quantum computing architectural design (QCAD) addresses the problems of actually implementing fault-tolerant algorithms given physical and architectural constraints beyond those of basic gate-level fidelity. Here we introduce a unified framework for QCAD that enables the scientist to study the impact of varying error correction schemes, architectural parameters including layout and scheduling, and physical operations native to a given architecture. Our software package, aptly named QCAD, provides compilation, manipulation/transformation, multi-paradigm simulation, and visualization tools. We demonstrate various features of the QCAD software package through several examples.

Building a Data Science capability for USGS water research and communication

NASA Astrophysics Data System (ADS)

Appling, A.; Read, E. K.

2015-12-01

Interpreting and communicating water issues in an era of exponentially increasing information requires a blend of domain expertise, computational proficiency, and communication skills. The USGS Office of Water Information has established a Data Science team to meet these needs, providing challenging careers for diverse domain scientists and innovators in the fields of information technology and data visualization. Here, we detail the experience of building a Data Science capability as a bridging element between traditional water resources analyses and modern computing tools and data management techniques. This approach includes four major components: 1) building reusable research tools, 2) documenting data-intensive research approaches in peer reviewed journals, 3) communicating complex water resources issues with interactive web visualizations, and 4) offering training programs for our peers in scientific computing. These components collectively improve the efficiency, transparency, and reproducibility of USGS data analyses and scientific workflows.

Simulating Earthquakes for Science and Society: Earthquake Visualizations Ideal for use in Science Communication and Education

NASA Astrophysics Data System (ADS)

de Groot, R.

2008-12-01

The Southern California Earthquake Center (SCEC) has been developing groundbreaking computer modeling capabilities for studying earthquakes. These visualizations were initially shared within the scientific community but have recently gained visibility via television news coverage in Southern California. Computers have opened up a whole new world for scientists working with large data sets, and students can benefit from the same opportunities (Libarkin & Brick, 2002). For example, The Great Southern California ShakeOut was based on a potential magnitude 7.8 earthquake on the southern San Andreas fault. The visualization created for the ShakeOut was a key scientific and communication tool for the earthquake drill. This presentation will also feature SCEC Virtual Display of Objects visualization software developed by SCEC Undergraduate Studies in Earthquake Information Technology interns. According to Gordin and Pea (1995), theoretically visualization should make science accessible, provide means for authentic inquiry, and lay the groundwork to understand and critique scientific issues. This presentation will discuss how the new SCEC visualizations and other earthquake imagery achieve these results, how they fit within the context of major themes and study areas in science communication, and how the efficacy of these tools can be improved.

DIVE: A Graph-based Visual Analytics Framework for Big Data

PubMed Central

Rysavy, Steven J.; Bromley, Dennis; Daggett, Valerie

2014-01-01

The need for data-centric scientific tools is growing; domains like biology, chemistry, and physics are increasingly adopting computational approaches. As a result, scientists must now deal with the challenges of big data. To address these challenges, we built a visual analytics platform named DIVE: Data Intensive Visualization Engine. DIVE is a data-agnostic, ontologically-expressive software framework capable of streaming large datasets at interactive speeds. Here we present the technical details of the DIVE platform, multiple usage examples, and a case study from the Dynameomics molecular dynamics project. We specifically highlight our novel contributions to structured data model manipulation and high-throughput streaming of large, structured datasets. PMID:24808197

Visualizing a silicon quantum computer

NASA Astrophysics Data System (ADS)

Sanders, Barry C.; Hollenberg, Lloyd C. L.; Edmundson, Darran; Edmundson, Andrew

2008-12-01

Quantum computation is a fast-growing, multi-disciplinary research field. The purpose of a quantum computer is to execute quantum algorithms that efficiently solve computational problems intractable within the existing paradigm of 'classical' computing built on bits and Boolean gates. While collaboration between computer scientists, physicists, chemists, engineers, mathematicians and others is essential to the project's success, traditional disciplinary boundaries can hinder progress and make communicating the aims of quantum computing and future technologies difficult. We have developed a four minute animation as a tool for representing, understanding and communicating a silicon-based solid-state quantum computer to a variety of audiences, either as a stand-alone animation to be used by expert presenters or embedded into a longer movie as short animated sequences. The paper includes a generally applicable recipe for successful scientific animation production.

Voxel Datacubes for 3D Visualization in Blender

NASA Astrophysics Data System (ADS)

Gárate, Matías

2017-05-01

The growth of computational astrophysics and the complexity of multi-dimensional data sets evidences the need for new versatile visualization tools for both the analysis and presentation of the data. In this work, we show how to use the open-source software Blender as a three-dimensional (3D) visualization tool to study and visualize numerical simulation results, focusing on astrophysical hydrodynamic experiments. With a datacube as input, the software can generate a volume rendering of the 3D data, show the evolution of a simulation in time, and do a fly-around camera animation to highlight the points of interest. We explain the process to import simulation outputs into Blender using the voxel data format, and how to set up a visualization scene in the software interface. This method allows scientists to perform a complementary visual analysis of their data and display their results in an appealing way, both for outreach and science presentations.

Visualizers, Visualizations, and Visualizees: Differences in Meaning-Making by Scientific Experts and Novices from Global Visualizations of Ocean Data

ERIC Educational Resources Information Center

Stofer, Kathryn A.

2013-01-01

Data visualizations designed for academic scientists are not immediately meaningful to everyday scientists. Communicating between a specialized, expert audience and a general, novice public is non-trivial; it requires careful translation. However, more widely available visualization technologies and platforms, including new three-dimensional…

A Visual Database System for Image Analysis on Parallel Computers and its Application to the EOS Amazon Project

NASA Technical Reports Server (NTRS)

Shapiro, Linda G.; Tanimoto, Steven L.; Ahrens, James P.

1996-01-01

The goal of this task was to create a design and prototype implementation of a database environment that is particular suited for handling the image, vision and scientific data associated with the NASA's EOC Amazon project. The focus was on a data model and query facilities that are designed to execute efficiently on parallel computers. A key feature of the environment is an interface which allows a scientist to specify high-level directives about how query execution should occur.

Jim Thomas, 1946-2010

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, Maureen; Kasik, David; Bailey, Mike

Jim Thomas, a visionary scientist and inspirational leader, died on 6 August 2010 in Richland, Washington. His impact on the fields of computer graphics, user interface software, and visualization was extraordinary, his ability to personally change people’s lives even more so. He is remembered for his enthusiasm, his mentorship, his generosity, and, most of all, his laughter. This collection of remembrances images him through the eyes of his many friends.

The potential of computer software that supports the diagnosis of workplace ergonomics in shaping health awareness

NASA Astrophysics Data System (ADS)

Lubkowska, Wioletta

2017-11-01

The growing prevalence of health problems among computer workstation workers has become one of the biggest threats to the overall health of our population. That is why many modern scientists are looking for ways and methods to prevent and reverse these negative trends. The purpose of this article is to present the potential for practical use of computer programs to design an ergonomic workplace and postural loads. These programs help configure the computer workstation correctly and adopt the correct body position during work, which reduces the risk of health problems. Creating visually attractive programs helps encourage and inspire those who work with a computer to introduce ergonomic solutions and reject the sedentary lifestyle.

Software for Scientists Facing Wicked Problems: Lessons from the VISTAS Project

EPA Science Inventory

The Visualization for Terrestrial and Aquatic Systems project (VISTAS) aims to help scientists produce effective environmental science visualizations for their own use and for use in presenting their work to a wide range of stakeholders (including other scientists, decision maker...

Visualizing water

NASA Astrophysics Data System (ADS)

Baart, F.; van Gils, A.; Hagenaars, G.; Donchyts, G.; Eisemann, E.; van Velzen, J. W.

2016-12-01

A compelling visualization is captivating, beautiful and narrative. Here we show how melding the skills of computer graphics, art, statistics, and environmental modeling can be used to generate innovative, attractive and very informative visualizations. We focus on the topic of visualizing forecasts and measurements of water (water level, waves, currents, density, and salinity). For the field of computer graphics and arts, water is an important topic because it occurs in many natural scenes. For environmental modeling and statistics, water is an important topic because the water is essential for transport, a healthy environment, fruitful agriculture, and a safe environment.The different disciplines take different approaches to visualizing water. In computer graphics, one focusses on creating water as realistic looking as possible. The focus on realistic perception (versus the focus on the physical balance pursued by environmental scientists) resulted in fascinating renderings, as seen in recent games and movies. Visualization techniques for statistical results have benefited from the advancement in design and journalism, resulting in enthralling infographics. The field of environmental modeling has absorbed advances in contemporary cartography as seen in the latest interactive data-driven maps. We systematically review the design emerging types of water visualizations. The examples that we analyze range from dynamically animated forecasts, interactive paintings, infographics, modern cartography to web-based photorealistic rendering. By characterizing the intended audience, the design choices, the scales (e.g. time, space), and the explorability we provide a set of guidelines and genres. The unique contributions of the different fields show how the innovations in the current state of the art of water visualization have benefited from inter-disciplinary collaborations.

On the efficacy of cinema, or what the visual system did not evolve to do

NASA Technical Reports Server (NTRS)

Cutting, James E.

1989-01-01

Spatial displays, and a constraint that they do not place on the use of spatial instruments are discussed. Much of the work done in visual perception by psychologists and by computer scientists has concerned displays that show the motion of rigid objects. Typically, if one assumes that objects are rigid, one can then proceed to understand how the constant shape of the object can be perceived (or computed) as it moves through space. The author maintains that photographs and cinema are visual displays that are also powerful forms of art. Their efficacy, in part, stems from the fact that, although viewpoint is constrained when composing them, it is not nearly so constrained when viewing them. It is obvious, according to the author, that human visual systems did not evolve to watch movies or look at photographs. Thus, what photographs and movies present must be allowed in the rule-governed system under which vision evolved. Machine-vision algorithms, to be applicable to human vision, should show the same types of tolerance.

Extensible Computational Chemistry Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

2012-08-09

ECCE provides a sophisticated graphical user interface, scientific visualization tools, and the underlying data management framework enabling scientists to efficiently set up calculations and store, retrieve, and analyze the rapidly growing volumes of data produced by computational chemistry studies. ECCE was conceived as part of the Environmental Molecular Sciences Laboratory construction to solve the problem of researchers being able to effectively utilize complex computational chemistry codes and massively parallel high performance compute resources. Bringing the power of these codes and resources to the desktops of researcher and thus enabling world class research without users needing a detailed understanding of themore » inner workings of either the theoretical codes or the supercomputers needed to run them was a grand challenge problem in the original version of the EMSL. ECCE allows collaboration among researchers using a web-based data repository where the inputs and results for all calculations done within ECCE are organized. ECCE is a first of kind end-to-end problem solving environment for all phases of computational chemistry research: setting up calculations with sophisticated GUI and direct manipulation visualization tools, submitting and monitoring calculations on remote high performance supercomputers without having to be familiar with the details of using these compute resources, and performing results visualization and analysis including creating publication quality images. ECCE is a suite of tightly integrated applications that are employed as the user moves through the modeling process.« less

GeoChronos: An On-line Collaborative Platform for Earth Observation Scientists

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Kiddle, C.; Curry, R.; Markatchev, N.; Zonta-Pastorello, G., Jr.; Rivard, B.; Sanchez-Azofeifa, G. A.; Simmonds, R.; Tan, T.

2009-12-01

Recent advances in cyberinfrastructure are offering new solutions to the growing challenges of managing and sharing large data volumes. Web 2.0 and social networking technologies, provide the means for scientists to collaborate and share information more effectively. Cloud computing technologies can provide scientists with transparent and on-demand access to applications served over the Internet in a dynamic and scalable manner. Semantic Web technologies allow for data to be linked together in a manner understandable by machines, enabling greater automation. Combining all of these technologies together can enable the creation of very powerful platforms. GeoChronos (http://geochronos.org/), part of a CANARIE Network Enabled Platforms project, is an online collaborative platform that incorporates these technologies to enable members of the earth observation science community to share data and scientific applications and to collaborate more effectively. The GeoChronos portal is built on an open source social networking platform called Elgg. Elgg provides a full set of social networking functionalities similar to Facebook including blogs, tags, media/document sharing, wikis, friends/contacts, groups, discussions, message boards, calendars, status, activity feeds and more. An underlying cloud computing infrastructure enables scientists to access dynamically provisioned applications via the portal for visualizing and analyzing data. Users are able to access and run the applications from any computer that has a Web browser and Internet connectivity and do not need to manage and maintain the applications themselves. Semantic Web Technologies, such as the Resource Description Framework (RDF) are being employed for relating and linking together spectral, satellite, meteorological and other data. Social networking functionality plays an integral part in facilitating the sharing of data and applications. Examples of recent GeoChronos users during the early testing phase have included the IAI International Wireless Sensor Networking Summer School at the University of Alberta, and the IAI Tropi-Dry community. Current GeoChronos activities include the development of a web-based spectral library and related analytical and visualization tools, in collaboration with members of the SpecNet community. The GeoChronos portal will be open to all members of the earth observation science community when the project nears completion at the end of 2010.

Mobile Devices and GPU Parallelism in Ionospheric Data Processing

NASA Astrophysics Data System (ADS)

Mascharka, D.; Pankratius, V.

2015-12-01

Scientific data acquisition in the field is often constrained by data transfer backchannels to analysis environments. Geoscientists are therefore facing practical bottlenecks with increasing sensor density and variety. Mobile devices, such as smartphones and tablets, offer promising solutions to key problems in scientific data acquisition, pre-processing, and validation by providing advanced capabilities in the field. This is due to affordable network connectivity options and the increasing mobile computational power. This contribution exemplifies a scenario faced by scientists in the field and presents the "Mahali TEC Processing App" developed in the context of the NSF-funded Mahali project. Aimed at atmospheric science and the study of ionospheric Total Electron Content (TEC), this app is able to gather data from various dual-frequency GPS receivers. It demonstrates parsing of full-day RINEX files on mobile devices and on-the-fly computation of vertical TEC values based on satellite ephemeris models that are obtained from NASA. Our experiments show how parallel computing on the mobile device GPU enables fast processing and visualization of up to 2 million datapoints in real-time using OpenGL. GPS receiver bias is estimated through minimum TEC approximations that can be interactively adjusted by scientists in the graphical user interface. Scientists can also perform approximate computations for "quickviews" to reduce CPU processing time and memory consumption. In the final stage of our mobile processing pipeline, scientists can upload data to the cloud for further processing. Acknowledgements: The Mahali project (http://mahali.mit.edu) is funded by the NSF INSPIRE grant no. AGS-1343967 (PI: V. Pankratius). We would like to acknowledge our collaborators at Boston College, Virginia Tech, Johns Hopkins University, Colorado State University, as well as the support of UNAVCO for loans of dual-frequency GPS receivers for use in this project, and Intel for loans of smartphones.

A knowledge based system for scientific data visualization

NASA Technical Reports Server (NTRS)

Senay, Hikmet; Ignatius, Eve

1992-01-01

A knowledge-based system, called visualization tool assistant (VISTA), which was developed to assist scientists in the design of scientific data visualization techniques, is described. The system derives its knowledge from several sources which provide information about data characteristics, visualization primitives, and effective visual perception. The design methodology employed by the system is based on a sequence of transformations which decomposes a data set into a set of data partitions, maps this set of partitions to visualization primitives, and combines these primitives into a composite visualization technique design. Although the primary function of the system is to generate an effective visualization technique design for a given data set by using principles of visual perception the system also allows users to interactively modify the design, and renders the resulting image using a variety of rendering algorithms. The current version of the system primarily supports visualization techniques having applicability in earth and space sciences, although it may easily be extended to include other techniques useful in other disciplines such as computational fluid dynamics, finite-element analysis and medical imaging.

Data-proximate Visualization via Unidata Cloud Technologies

NASA Astrophysics Data System (ADS)

Fisher, W. I.; Oxelson Ganter, J.; Weber, J.

2016-12-01

The rise in cloud computing, coupled with the growth of "Big Data", has lead to a migration away from local scientific data storage. The increasing size of remote scientific data sets increase, however, makes it difficult for scientists to subject them to large-scale analysis and visualization. These large datasets can take an inordinate amount of time to download; subsetting is a potential solution, but subsetting services are not yet ubiquitous. Data providers may also pay steep prices, as many cloud providers meter data based on how much data leaves their cloud service.The solution to this problem is a deceptively simple one; move data analysis and visualization tools to the cloud, so that scientists may perform data-proximate analysis and visualization. This results in increased transfer speeds, while egress costs are lowered or completely eliminated. The challenge now becomes creating tools which are cloud-ready.The solution to this challenge is provided by Application Streaming. This technology allows a program to run entirely on a remote virtual machine while still allowing for interactivity and dynamic visualizations. When coupled with containerization technology such as Docker, we are able to easily deploy legacy analysis and visualization software to the cloud whilst retaining access via a desktop, netbook, a smartphone, or the next generation of hardware, whatever it may be.Unidata has harnessed Application Streaming to provide a cloud-capable version of our visualization software, the Integrated Data Viewer (IDV). This work will examine the challenges associated with adapting the IDV to an application streaming platform, and include a brief discussion of the underlying technologies involved.

Cloud-based data-proximate visualization and analysis

NASA Astrophysics Data System (ADS)

Fisher, Ward

2017-04-01

The rise in cloud computing, coupled with the growth of "Big Data", has lead to a migration away from local scientific data storage. The increasing size of remote scientific data sets increase, however, makes it difficult for scientists to subject them to large-scale analysis and visualization. These large datasets can take an inordinate amount of time to download; subsetting is a potential solution, but subsetting services are not yet ubiquitous. Data providers may also pay steep prices, as many cloud providers meter data based on how much data leaves their cloud service. The solution to this problem is a deceptively simple one; move data analysis and visualization tools to the cloud, so that scientists may perform data-proximate analysis and visualization. This results in increased transfer speeds, while egress costs are lowered or completely eliminated. The challenge now becomes creating tools which are cloud-ready. The solution to this challenge is provided by Application Streaming. This technology allows a program to run entirely on a remote virtual machine while still allowing for interactivity and dynamic visualizations. When coupled with containerization technology such as Docker, we are able to easily deploy legacy analysis and visualization software to the cloud whilst retaining access via a desktop, netbook, a smartphone, or the next generation of hardware, whatever it may be. Unidata has harnessed Application Streaming to provide a cloud-capable version of our visualization software, the Integrated Data Viewer (IDV). This work will examine the challenges associated with adapting the IDV to an application streaming platform, and include a brief discussion of the underlying technologies involved.

Hybrid 2-D and 3-D Immersive and Interactive User Interface for Scientific Data Visualization

DTIC Science & Technology

2017-08-01

visualization, 3-D interactive visualization, scientific visualization, virtual reality, real -time ray tracing 16. SECURITY CLASSIFICATION OF: 17...scientists to employ in the real world. Other than user-friendly software and hardware setup, scientists also need to be able to perform their usual...and scientific visualization communities mostly have different research priorities. For the VR community, the ability to support real -time user

Manifold compositions, music visualization, and scientific sonification in an immersive virtual-reality environment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaper, H. G.

1998-01-05

An interdisciplinary project encompassing sound synthesis, music composition, sonification, and visualization of music is facilitated by the high-performance computing capabilities and the virtual-reality environments available at Argonne National Laboratory. The paper describes the main features of the project's centerpiece, DIASS (Digital Instrument for Additive Sound Synthesis); ''A.N.L.-folds'', an equivalence class of compositions produced with DIASS; and application of DIASS in two experiments in the sonification of complex scientific data. Some of the larger issues connected with this project, such as the changing ways in which both scientists and composers perform their tasks, are briefly discussed.

Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, E. Wes; Frank, Randy; Fulcomer, Sam

Scientific visualization is the transformation of abstract information into images, and it plays an integral role in the scientific process by facilitating insight into observed or simulated phenomena. Visualization as a discipline spans many research areas from computer science, cognitive psychology and even art. Yet the most successful visualization applications are created when close synergistic interactions with domain scientists are part of the algorithmic design and implementation process, leading to visual representations with clear scientific meaning. Visualization is used to explore, to debug, to gain understanding, and as an analysis tool. Visualization is literally everywhere--images are present in this report,more » on television, on the web, in books and magazines--the common theme is the ability to present information visually that is rapidly assimilated by human observers, and transformed into understanding or insight. As an indispensable part a modern science laboratory, visualization is akin to the biologist's microscope or the electrical engineer's oscilloscope. Whereas the microscope is limited to small specimens or use of optics to focus light, the power of scientific visualization is virtually limitless: visualization provides the means to examine data that can be at galactic or atomic scales, or at any size in between. Unlike the traditional scientific tools for visual inspection, visualization offers the means to ''see the unseeable.'' Trends in demographics or changes in levels of atmospheric CO{sub 2} as a function of greenhouse gas emissions are familiar examples of such unseeable phenomena. Over time, visualization techniques evolve in response to scientific need. Each scientific discipline has its ''own language,'' verbal and visual, used for communication. The visual language for depicting electrical circuits is much different than the visual language for depicting theoretical molecules or trends in the stock market. There is no ''one visualization too'' that can serve as a panacea for all science disciplines. Instead, visualization researchers work hand in hand with domain scientists as part of the scientific research process to define, create, adapt and refine software that ''speaks the visual language'' of each scientific domain.« less

Developing Data System Engineers

NASA Astrophysics Data System (ADS)

Behnke, J.; Byrnes, J. B.; Kobler, B.

2011-12-01

In the early days of general computer systems for science data processing, staff members working on NASA's data systems would most often be hired as mathematicians. Computer engineering was very often filled by those with electrical engineering degrees. Today, the Goddard Space Flight Center has special position descriptions for data scientists or as they are more commonly called: data systems engineers. These staff members are required to have very diverse skills, hence the need for a generalized position description. There is always a need for data systems engineers to develop, maintain and operate the complex data systems for Earth and space science missions. Today's data systems engineers however are not just mathematicians, they are computer programmers, GIS experts, software engineers, visualization experts, etc... They represent many different degree fields. To put together distributed systems like the NASA Earth Observing Data and Information System (EOSDIS), staff are required from many different fields. Sometimes, the skilled professional is not available and must be developed in-house. This paper will address the various skills and jobs for data systems engineers at NASA. Further it explores how to develop staff to become data scientists.

Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Aritra; Poco, Jorge; Bertini, Enrico

2016-01-01

The gap between large-scale data production rate and the rate of generation of data-driven scientific insights has led to an analytical bottleneck in scientific domains like climate, biology, etc. This is primarily due to the lack of innovative analytical tools that can help scientists efficiently analyze and explore alternative hypotheses about the data, and communicate their findings effectively to a broad audience. In this paper, by reflecting on a set of successful collaborative research efforts between with a group of climate scientists and visualization researchers, we introspect how interactive visualization can help reduce the analytical bottleneck for domain scientists.

Scientific work environments in the next decade

NASA Technical Reports Server (NTRS)

Gomez, Julian E.

1989-01-01

The applications of contemporary computer graphics to scientific visualization is described, with emphasis on the nonintuitive problems. A radically different approach is proposed which centers on the idea of the scientist being in the simulation display space rather than observing it on a screen. Interaction is performed with nonstandard input devices to preserve the feeling of being immersed in the three-dimensional display space. Construction of such a system could begin now with currently available technology.

American and Greek Children's Visual Images of Scientists: Enduring or Fading Stereotypes?

ERIC Educational Resources Information Center

Christidou, Vasilia; Bonoti, Fotini; Kontopoulou, Argiro

2016-01-01

This study explores American and Greek primary pupils' visual images of scientists by means of two nonverbal data collection tasks to identify possible convergences and divergences. Specifically, it aims to investigate whether their images of scientists vary according to the data collection instrument used and to gender. To this end, 91…

How scientists develop competence in visual communication

NASA Astrophysics Data System (ADS)

Ostergren, Marilyn

Visuals (maps, charts, diagrams and illustrations) are an important tool for communication in most scientific disciplines, which means that scientists benefit from having strong visual communication skills. This dissertation examines the nature of competence in visual communication and the means by which scientists acquire this competence. This examination takes the form of an extensive multi-disciplinary integrative literature review and a series of interviews with graduate-level science students. The results are presented as a conceptual framework that lays out the components of competence in visual communication, including the communicative goals of science visuals, the characteristics of effective visuals, the skills and knowledge needed to create effective visuals and the learning experiences that promote the acquisition of these forms of skill and knowledge. This conceptual framework can be used to inform pedagogy and thus help graduate students achieve a higher level of competency in this area; it can also be used to identify aspects of acquiring competence in visual communication that need further study.

ePMV embeds molecular modeling into professional animation software environments.

PubMed

Johnson, Graham T; Autin, Ludovic; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2011-03-09

Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties, and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology. Copyright © 2011 Elsevier Ltd. All rights reserved.

ePMV Embeds Molecular Modeling into Professional Animation Software Environments

PubMed Central

Johnson, Graham T.; Autin, Ludovic; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.

2011-01-01

SUMMARY Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers, we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology. PMID:21397181

Art in Science Competition invites artworks to the annual exhibition on ISMB 2018 in Chicago.

PubMed

Welch, Lonnie; Gaeta, Bruno; Kovats, Diane E; Frenkel Morgenstern, Milana

2018-01-01

The International Society of Computational Biology and Bioinformatics (ISCB) brings together scientists from a wide range of disciplines, including biology, medicine, computer science, mathematics and statistics. Practitioners in these fields are constantly dealing with information in visual form: from microscope images and photographs of gels to scatter plots, network graphs and phylogenetic trees, structural formulae and protein models to flow diagrams, visual aids for problem-solving are omnipresent. The ISCB Art in Science Competition 2017 at the ISCB/ECCB 2017 conference in Prague offered a way to show the beauty of science in art form. Past artworks in this annual exhibition at ISMB combined outstanding beauty and aesthetics with deep insight that perfectly validated the exhibit's approach or went beyond the problem's solution. Others were surprising and inspiring through the transition from science to art, opening eyes and minds to reflect on the work being undertaken.

The Virtual Pelvic Floor, a tele-immersive educational environment.

PubMed Central

Pearl, R. K.; Evenhouse, R.; Rasmussen, M.; Dech, F.; Silverstein, J. C.; Prokasy, S.; Panko, W. B.

1999-01-01

This paper describes the development of the Virtual Pelvic Floor, a new method of teaching the complex anatomy of the pelvic region utilizing virtual reality and advanced networking technology. Virtual reality technology allows improved visualization of three-dimensional structures over conventional media because it supports stereo vision, viewer-centered perspective, large angles of view, and interactivity. Two or more ImmersaDesk systems, drafting table format virtual reality displays, are networked together providing an environment where teacher and students share a high quality three-dimensional anatomical model, and are able to converse, see each other, and to point in three dimensions to indicate areas of interest. This project was realized by the teamwork of surgeons, medical artists and sculptors, computer scientists, and computer visualization experts. It demonstrates the future of virtual reality for surgical education and applications for the Next Generation Internet. Images Figure 1 Figure 2 Figure 3 PMID:10566378

Visualization of bioelectric phenomena.

PubMed

Palmer, T C; Simpson, E V; Kavanagh, K M; Smith, W M

1992-01-01

Biomedical investigators are currently able to acquire and analyze physiological and anatomical data from three-dimensional structures in the body. Often, multiple kinds of data can be recorded simultaneously. The usefulness of this information, either for exploratory viewing or for presentation to others, is limited by the lack of techniques to display it in intuitive, accessible formats. Unfortunately, the complexity of scientific visualization techniques and the inflexibility of commercial packages deter investigators from using sophisticated visualization methods that could provide them added insight into the mechanisms of the phenomena under study. Also, the sheer volume of such data is a problem. High-performance computing resources are often required for storage and processing, in addition to visualization. This chapter describes a novel, language-based interface that allows scientists with basic programming skills to classify and render multivariate volumetric data with a modest investment in software training. The interface facilitates data exploration by enabling experimentation with various algorithms to compute opacity and color from volumetric data. The value of the system is demonstrated using data from cardiac mapping studies, in which multiple electrodes are placed in an on the heart to measure the cardiac electrical activity intrinsic to the heart and its response to external stimulation.

Implicit Theories of Creativity in Computer Science in the United States and China

ERIC Educational Resources Information Center

Tang, Chaoying; Baer, John; Kaufman, James C.

2015-01-01

To study implicit concepts of creativity in computer science in the United States and mainland China, we first asked 308 Chinese computer scientists for adjectives that would describe a creative computer scientist. Computer scientists and non-computer scientists from China (N = 1069) and the United States (N = 971) then rated how well those…

Using spatial principles to optimize distributed computing for enabling the physical science discoveries

PubMed Central

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-01-01

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century. PMID:21444779

Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

PubMed

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-04-05

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

NASA Technical Reports Server (NTRS)

Sen, Syamal K.; Shaykhian, Gholam Ali

2011-01-01

MatLab(R) (MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many cou ntries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its re al strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbo x. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using s ymbolic operations. MatLab in its interpreter programming language fo rm (command interface) is similar with well known programming languag es such as C/C++, support data structures and cell arrays to define c lasses in object oriented programming. As such, MatLab is equipped with most ofthe essential constructs of a higher programming language. M atLab is packaged with an editor and debugging functionality useful t o perform analysis of large MatLab programs and find errors. We belie ve there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and ana lysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applicati ons. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientifi c problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabu lar format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed. The presentation will emphasize creating practIcal scripts (pro grams) that extend the basic features of MatLab TOPICS mclude (1) Ma trix and vector analysis and manipulations (2) Mathematical functions (3) Symbolic calculations & functions (4) Import/export data files (5) Program lOgic and flow control (6) Writing function and passing parameters (7) Test application programs

Fusion interfaces for tactical environments: An application of virtual reality technology

NASA Technical Reports Server (NTRS)

Haas, Michael W.

1994-01-01

The term Fusion Interface is defined as a class of interface which integrally incorporates both virtual and nonvirtual concepts and devices across the visual, auditory, and haptic sensory modalities. A fusion interface is a multisensory virtually-augmented synthetic environment. A new facility has been developed within the Human Engineering Division of the Armstrong Laboratory dedicated to exploratory development of fusion interface concepts. This new facility, the Fusion Interfaces for Tactical Environments (FITE) Facility is a specialized flight simulator enabling efficient concept development through rapid prototyping and direct experience of new fusion concepts. The FITE Facility also supports evaluation of fusion concepts by operation fighter pilots in an air combat environment. The facility is utilized by a multidisciplinary design team composed of human factors engineers, electronics engineers, computer scientists, experimental psychologists, and oeprational pilots. The FITE computational architecture is composed of twenty-five 80486-based microcomputers operating in real-time. The microcomputers generate out-the-window visuals, in-cockpit and head-mounted visuals, localized auditory presentations, haptic displays on the stick and rudder pedals, as well as executing weapons models, aerodynamic models, and threat models.

The physics of volume rendering

NASA Astrophysics Data System (ADS)

Peters, Thomas

2014-11-01

Radiation transfer is an important topic in several physical disciplines, probably most prominently in astrophysics. Computer scientists use radiation transfer, among other things, for the visualization of complex data sets with direct volume rendering. In this article, I point out the connection between physical radiation transfer and volume rendering, and I describe an implementation of direct volume rendering in the astrophysical radiation transfer code RADMC-3D. I show examples for the use of this module on analytical models and simulation data.

Scaling up to address data science challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, Joanne R.

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Scaling up to address data science challenges

DOE PAGES

Wendelberger, Joanne R.

2017-04-27

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

AccessScope project: Accessible light microscope for users with upper limb mobility or visual impairments.

PubMed

Mansoor, Awais; Ahmed, Wamiq M; Samarapungavan, Ala; Cirillo, John; Schwarte, David; Robinson, J Paul; Duerstock, Bradley S

2010-01-01

A web-based application was developed to remotely view slide specimens and control all functions of a research-level light microscopy workstation, called AccessScope. Students and scientists with upper limb mobility and visual impairments are often unable to use a light microscope by themselves and must depend on others in its operation. Users with upper limb mobility impairments and low vision were recruited to assist in the design process of the AccessScope personal computer (PC) user interface. Participants with these disabilities were evaluated in their ability to use AccessScope to perform microscopical tasks. AccessScope usage was compared with inspecting prescanned slide images by grading participants' identification and understanding of histological features and knowledge of microscope operation. With AccessScope subjects were able to independently perform common light microscopy functions through an Internet browser by employing different PC pointing devices or accessibility software according to individual abilities. Subjects answered more histology and microscope usage questions correctly after first participating in an AccessScope test session. AccessScope allowed users with upper limb or visual impairments to successfully perform light microscopy without assistance. This unprecedented capability is crucial for students and scientists with disabilities to perform laboratory coursework or microscope-based research and pursue science, technology, engineering, and mathematics fields.

Applications of the pipeline environment for visual informatics and genomics computations

PubMed Central

2011-01-01

Background Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols. Results This paper reports on the applications of the LONI Pipeline environment to address two informatics challenges - graphical management of diverse genomics tools, and the interoperability of informatics software. Specifically, this manuscript presents the concrete details of deploying general informatics suites and individual software tools to new hardware infrastructures, the design, validation and execution of new visual analysis protocols via the Pipeline graphical interface, and integration of diverse informatics tools via the Pipeline eXtensible Markup Language syntax. We demonstrate each of these processes using several established informatics packages (e.g., miBLAST, EMBOSS, mrFAST, GWASS, MAQ, SAMtools, Bowtie) for basic local sequence alignment and search, molecular biology data analysis, and genome-wide association studies. These examples demonstrate the power of the Pipeline graphical workflow environment to enable integration of bioinformatics resources which provide a well-defined syntax for dynamic specification of the input/output parameters and the run-time execution controls. Conclusions The LONI Pipeline environment http://pipeline.loni.ucla.edu provides a flexible graphical infrastructure for efficient biomedical computing and distributed informatics research. The interactive Pipeline resource manager enables the utilization and interoperability of diverse types of informatics resources. The Pipeline client-server model provides computational power to a broad spectrum of informatics investigators - experienced developers and novice users, user with or without access to advanced computational-resources (e.g., Grid, data), as well as basic and translational scientists. The open development, validation and dissemination of computational networks (pipeline workflows) facilitates the sharing of knowledge, tools, protocols and best practices, and enables the unbiased validation and replication of scientific findings by the entire community. PMID:21791102

Functional requirements document for the Earth Observing System Data and Information System (EOSDIS) Scientific Computing Facilities (SCF) of the NASA/MSFC Earth Science and Applications Division, 1992

NASA Technical Reports Server (NTRS)

Botts, Michael E.; Phillips, Ron J.; Parker, John V.; Wright, Patrick D.

1992-01-01

Five scientists at MSFC/ESAD have EOS SCF investigator status. Each SCF has unique tasks which require the establishment of a computing facility dedicated to accomplishing those tasks. A SCF Working Group was established at ESAD with the charter of defining the computing requirements of the individual SCFs and recommending options for meeting these requirements. The primary goal of the working group was to determine which computing needs can be satisfied using either shared resources or separate but compatible resources, and which needs require unique individual resources. The requirements investigated included CPU-intensive vector and scalar processing, visualization, data storage, connectivity, and I/O peripherals. A review of computer industry directions and a market survey of computing hardware provided information regarding important industry standards and candidate computing platforms. It was determined that the total SCF computing requirements might be most effectively met using a hierarchy consisting of shared and individual resources. This hierarchy is composed of five major system types: (1) a supercomputer class vector processor; (2) a high-end scalar multiprocessor workstation; (3) a file server; (4) a few medium- to high-end visualization workstations; and (5) several low- to medium-range personal graphics workstations. Specific recommendations for meeting the needs of each of these types are presented.

Dynamic Collaboration Infrastructure for Hydrologic Science

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

2016-12-01

Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the results of this proof-of-concept prototype which enabled HydroShare users to readily instantiate virtual infrastructure marshaling arbitrary combinations, varieties, and quantities of distributed data and computing infrastructure in addressing big problems in hydrology.

Exploring Two Approaches for an End-to-End Scientific Analysis Workflow

NASA Astrophysics Data System (ADS)

Dodelson, Scott; Kent, Steve; Kowalkowski, Jim; Paterno, Marc; Sehrish, Saba

2015-12-01

The scientific discovery process can be advanced by the integration of independently-developed programs run on disparate computing facilities into coherent workflows usable by scientists who are not experts in computing. For such advancement, we need a system which scientists can use to formulate analysis workflows, to integrate new components to these workflows, and to execute different components on resources that are best suited to run those components. In addition, we need to monitor the status of the workflow as components get scheduled and executed, and to access the intermediate and final output for visual exploration and analysis. Finally, it is important for scientists to be able to share their workflows with collaborators. We have explored two approaches for such an analysis framework for the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC); the first one is based on the use and extension of Galaxy, a web-based portal for biomedical research, and the second one is based on a programming language, Python. In this paper, we present a brief description of the two approaches, describe the kinds of extensions to the Galaxy system we have found necessary in order to support the wide variety of scientific analysis in the cosmology community, and discuss how similar efforts might be of benefit to the HEP community.

Visual self-images of scientists and science in Greece.

PubMed

Christidou, Vasilia; Kouvatas, Apostolos

2013-01-01

A popular and well-established image of scientists and science dominates in the public field, signifying a contradictory and multifaceted combination of stereotypes. This paper investigates crucial aspects of the visual self-image of Greek scientists and science as exposed in photographic material retrieved from relevant institutions' websites. In total 971 photos were analysed along dimensions corresponding to the image of scientists and science. Analysis demonstrates ambivalence in Greek scientists' self-images between traditional stereotypic characteristics and an intention to overcome them. Differences between the self-images of physics, chemistry and biology are determined, as well as between the "masculine" and "feminine" face of science. Implications concerning improvements in science and scientists' self-images and further research are presented.

Big Data Processing for a Central Texas Groundwater Case Study

NASA Astrophysics Data System (ADS)

Cantu, A.; Rivera, O.; Martínez, A.; Lewis, D. H.; Gentle, J. N., Jr.; Fuentes, G.; Pierce, S. A.

2016-12-01

As computational methods improve, scientists are able to expand the level and scale of experimental simulation and testing that is completed for case studies. This study presents a comparative analysis of multiple models for the Barton Springs segment of the Edwards aquifer. Several numerical simulations using state-mandated MODFLOW models ran on Stampede, a High Performance Computing system housed at the Texas Advanced Computing Center, were performed for multiple scenario testing. One goal of this multidisciplinary project aims to visualize and compare the output data of the groundwater model using the statistical programming language R to find revealing data patterns produced by different pumping scenarios. Presenting data in a friendly post-processing format is covered in this paper. Visualization of the data and creating workflows applicable to the management of the data are tasks performed after data extraction. Resulting analyses provide an example of how supercomputing can be used to accelerate evaluation of scientific uncertainty and geological knowledge in relation to policy and management decisions. Understanding the aquifer behavior helps policy makers avoid negative impact on the endangered species, environmental services and aids in maximizing the aquifer yield.

Developing the next generation of diverse computer scientists: the need for enhanced, intersectional computing identity theory

NASA Astrophysics Data System (ADS)

Rodriguez, Sarah L.; Lehman, Kathleen

2017-10-01

This theoretical paper explores the need for enhanced, intersectional computing identity theory for the purpose of developing a diverse group of computer scientists for the future. Greater theoretical understanding of the identity formation process specifically for computing is needed in order to understand how students come to understand themselves as computer scientists. To ensure that the next generation of computer scientists is diverse, this paper presents a case for examining identity development intersectionally, understanding the ways in which women and underrepresented students may have difficulty identifying as computer scientists and be systematically oppressed in their pursuit of computer science careers. Through a review of the available scholarship, this paper suggests that creating greater theoretical understanding of the computing identity development process will inform the way in which educational stakeholders consider computer science practices and policies.

A Computing Infrastructure for Supporting Climate Studies

NASA Astrophysics Data System (ADS)

Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

2011-12-01

Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

Bird song: in vivo, in vitro, in silico

NASA Astrophysics Data System (ADS)

Mukherjee, Aryesh; Mandre, Shreyas; Mahadevan, Lakshminarayan

2010-11-01

Bird song, long since an inspiration for artists, writers and poets also poses challenges for scientists interested in dissecting the mechanisms underlying the neural, motor, learning and behavioral systems behind the beak and brain, as a way to recreate and synthesize it. We use a combination of quantitative visualization experiments with physical models and computational theories to understand the simplest aspects of these complex musical boxes, focusing on using the controllable elastohydrodynamic interactions to mimic aural gestures and simple songs.

Simulating Earthquakes for Science and Society: New Earthquake Visualizations Ideal for Use in Science Communication

NASA Astrophysics Data System (ADS)

de Groot, R. M.; Benthien, M. L.

2006-12-01

The Southern California Earthquake Center (SCEC) has been developing groundbreaking computer modeling capabilities for studying earthquakes. These visualizations were initially shared within the scientific community but have recently have gained visibility via television news coverage in Southern California. These types of visualizations are becoming pervasive in the teaching and learning of concepts related to earth science. Computers have opened up a whole new world for scientists working with large data sets, and students can benefit from the same opportunities (Libarkin &Brick, 2002). Earthquakes are ideal candidates for visualization products: they cannot be predicted, are completed in a matter of seconds, occur deep in the earth, and the time between events can be on a geologic time scale. For example, the southern part of the San Andreas fault has not seen a major earthquake since about 1690, setting the stage for an earthquake as large as magnitude 7.7 -- the "big one." Since no one has experienced such an earthquake, visualizations can help people understand the scale of such an event. Accordingly, SCEC has developed a revolutionary simulation of this earthquake, with breathtaking visualizations that are now being distributed. According to Gordin and Pea (1995), theoretically visualization should make science accessible, provide means for authentic inquiry, and lay the groundwork to understand and critique scientific issues. This presentation will discuss how the new SCEC visualizations and other earthquake imagery achieve these results, how they fit within the context of major themes and study areas in science communication, and how the efficacy of these tools can be improved.

A Rotational Motion Perception Neural Network Based on Asymmetric Spatiotemporal Visual Information Processing.

PubMed

Hu, Bin; Yue, Shigang; Zhang, Zhuhong

All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion/contraction perceptions; however, little has been done in the past to create computational models for rotational motion perception. To fill this gap, we proposed a neural network that utilizes a specific spatiotemporal arrangement of asymmetric lateral inhibited direction selective neural networks (DSNNs) for rotational motion perception. The proposed neural network consists of two parts-presynaptic and postsynaptic parts. In the presynaptic part, there are a number of lateral inhibited DSNNs to extract directional visual cues. In the postsynaptic part, similar to the arrangement of the directional columns in the cerebral cortex, these direction selective neurons are arranged in a cyclic order to perceive rotational motion cues. In the postsynaptic network, the delayed excitation from each direction selective neuron is multiplied by the gathered excitation from this neuron and its unilateral counterparts depending on which rotation, clockwise (cw) or counter-cw (ccw), to perceive. Systematic experiments under various conditions and settings have been carried out and validated the robustness and reliability of the proposed neural network in detecting cw or ccw rotational motion. This research is a critical step further toward dynamic visual information processing.All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion/contraction perceptions; however, little has been done in the past to create computational models for rotational motion perception. To fill this gap, we proposed a neural network that utilizes a specific spatiotemporal arrangement of asymmetric lateral inhibited direction selective neural networks (DSNNs) for rotational motion perception. The proposed neural network consists of two parts-presynaptic and postsynaptic parts. In the presynaptic part, there are a number of lateral inhibited DSNNs to extract directional visual cues. In the postsynaptic part, similar to the arrangement of the directional columns in the cerebral cortex, these direction selective neurons are arranged in a cyclic order to perceive rotational motion cues. In the postsynaptic network, the delayed excitation from each direction selective neuron is multiplied by the gathered excitation from this neuron and its unilateral counterparts depending on which rotation, clockwise (cw) or counter-cw (ccw), to perceive. Systematic experiments under various conditions and settings have been carried out and validated the robustness and reliability of the proposed neural network in detecting cw or ccw rotational motion. This research is a critical step further toward dynamic visual information processing.

Engaging Audiences in Planetary Science Through Visualizations

NASA Astrophysics Data System (ADS)

Shupla, C. B.; Mason, T.; Peticolas, L. M.; Hauck, K.

2017-12-01

One way to share compelling stories is through visuals. The Lunar and Planetary Institute (LPI), in collaboration with Laboratory for Atmospheric and Space Physics (LASP) and Space Science Laboratory at the University of California, Berkeley, has been working with planetary scientists to reach and engage audiences in their research through the use of visualizations. We will share how images and animations have been used in multiple mediums, including the planetarium, Science on a Sphere, the hyperwall, and within apps. Our objectives are to provide a tool that planetary scientists can use to tell their stories, as well as to increase audience awareness of and interest in planetary science. While scientists are involved in the selection of topics and the development of the visuals, LPI and partners seek to increase the planetary science community's awareness of these resources and their ability to incorporate them into their own public engagement efforts. This presentation will share our own resources and efforts, as well as the input received from scientists on how education and public engagement teams can best assist them in developing and using these resources, and disseminating them to both scientists and to informal science education venues.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows

DOE PAGES

Pugmire, David; Kress, James; Choi, Jong; ...

2016-08-04

Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less

Remote visual analysis of large turbulence databases at multiple scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pulido, Jesus; Livescu, Daniel; Kanov, Kalin

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methodsmore » supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.« less

Remote visual analysis of large turbulence databases at multiple scales

DOE PAGES

Pulido, Jesus; Livescu, Daniel; Kanov, Kalin; ...

2018-06-15

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methodsmore » supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.« less

An interactive environment for agile analysis and visualization of ChIP-sequencing data.

PubMed

Lerdrup, Mads; Johansen, Jens Vilstrup; Agrawal-Singh, Shuchi; Hansen, Klaus

2016-04-01

To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.

NASA high performance computing, communications, image processing, and data visualization-potential applications to medicine.

PubMed

Kukkonen, C A

1995-06-01

High-speed information processing technologies being developed and applied by the Jet Propulsion Laboratory for NASA and Department of Defense mission needs have potential dual-uses in telemedicine and other medical applications. Fiber optic ground networks connected with microwave satellite links allow NASA to communicate with its astronauts in Earth orbit or on the moon, and with its deep space probes billions of miles away. These networks monitor the health of astronauts and or robotic spacecraft. Similar communications technology will also allow patients to communicate with doctors anywhere on Earth. NASA space missions have science as a major objective. Science sensors have become so sophisticated that they can take more data than our scientists can analyze by hand. High performance computers--workstations, supercomputer and massively parallel computers are being used to transform this data into knowledge. This is done using image processing, data visualization and other techniques to present the data--one's and zero's in forms that a human analyst can readily relate to and understand. Medical sensors have also explored in the in data output--witness CT scans, MRI, and ultrasound. This data must be presented in visual form and computers will allow routine combination of many two dimensional MRI images into three dimensional reconstructions of organs that then can be fully examined by physicians. Emerging technologies such as neural networks that are being "trained" to detect craters on planets or incoming missiles amongst decoys can be used to identify microcalcification in mammograms.

iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

PubMed Central

Sinha, Amit U.; Armstrong, Scott A.

2012-01-01

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression. PMID:22393367

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, E Wes; Brugger, Eric

Supercomputing centers are unique resources that aim to enable scientific knowledge discovery by employing large computational resources - the 'Big Iron.' Design, acquisition, installation, and management of the Big Iron are carefully planned and monitored. Because these Big Iron systems produce a tsunami of data, it's natural to colocate the visualization and analysis infrastructure. This infrastructure consists of hardware (Little Iron) and staff (Skinny Guys). Our collective experience suggests that design, acquisition, installation, and management of the Little Iron and Skinny Guys doesn't receive the same level of treatment as that of the Big Iron. This article explores the followingmore » questions about the Little Iron: How should we size the Little Iron to adequately support visualization and analysis of data coming off the Big Iron? What sort of capabilities must it have? Related questions concern the size of visualization support staff: How big should a visualization program be - that is, how many Skinny Guys should it have? What should the staff do? How much of the visualization should be provided as a support service, and how much should applications scientists be expected to do on their own?« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pugmire, David; Kress, James; Choi, Jong

Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less

Data-Proximate Analysis and Visualization in the Cloud using Cloudstream, an Open-Source Application Streaming Technology Stack

NASA Astrophysics Data System (ADS)

Fisher, W. I.

2017-12-01

The rise in cloud computing, coupled with the growth of "Big Data", has lead to a migration away from local scientific data storage. The increasing size of remote scientific data sets increase, however, makes it difficult for scientists to subject them to large-scale analysis and visualization. These large datasets can take an inordinate amount of time to download; subsetting is a potential solution, but subsetting services are not yet ubiquitous. Data providers may also pay steep prices, as many cloud providers meter data based on how much data leaves their cloud service. The solution to this problem is a deceptively simple one; move data analysis and visualization tools to the cloud, so that scientists may perform data-proximate analysis and visualization. This results in increased transfer speeds, while egress costs are lowered or completely eliminated. Moving standard desktop analysis and visualization tools to the cloud is enabled via a technique called "Application Streaming". This technology allows a program to run entirely on a remote virtual machine while still allowing for interactivity and dynamic visualizations. When coupled with containerization technology such as Docker, we are able to easily deploy legacy analysis and visualization software to the cloud whilst retaining access via a desktop, netbook, a smartphone, or the next generation of hardware, whatever it may be. Unidata has created a Docker-based solution for easily adapting legacy software for Application Streaming. This technology stack, dubbed Cloudstream, allows desktop software to run in the cloud with little-to-no effort. The docker container is configured by editing text files, and the legacy software does not need to be modified in any way. This work will discuss the underlying technologies used by Cloudstream, and outline how to use Cloudstream to run and access an existing desktop application to the cloud.

Recruitment of Foreigners in the Market for Computer Scientists in the United States

PubMed Central

Bound, John; Braga, Breno; Golden, Joseph M.

2016-01-01

We present and calibrate a dynamic model that characterizes the labor market for computer scientists. In our model, firms can recruit computer scientists from recently graduated college students, from STEM workers working in other occupations or from a pool of foreign talent. Counterfactual simulations suggest that wages for computer scientists would have been 2.8–3.8% higher, and the number of Americans employed as computers scientists would have been 7.0–13.6% higher in 2004 if firms could not hire more foreigners than they could in 1994. In contrast, total CS employment would have been 3.8–9.0% lower, and consequently output smaller. PMID:27170827

Visualizing TZVOLCANO GNSS Data with Grafana via the EarthCube Cyberinfrastructure CHORDS: an Example of Dashboard Creation for the Geosciences

NASA Astrophysics Data System (ADS)

Nguyen, T. T.; Stamps, D. S.

2017-12-01

Visualizing societally relevant data in easy to comprehend formats is necessary for making informed decisions by non-scientist stakeholders. Despite scientists' efforts to inform the public, there continues to be a disconnect in information between stakeholders and scientists. Closing the gap in knowledge requires increased communication between the two groups facilitated by models and data visualizations. In this work we use real-time streaming data from TZVOLCANO, a network of GNSS/GPS sensors that monitor the active volcano Ol Doinyo Lengai in Tanzania, as a test-case for visualizing societally relevant data. Real-time data from TZVOLCANO is streamed into the US NSF Geodesy Facility UNAVCO archive (www.unavco.org) from which data are made available through the EarthCube cyberinfrastructure CHORDS (Cloud-Hosted Real-Time Data Services for the geosciences). CHORDS uses InfluxDB to make streaming data accessible in Grafana: an open source software that specializes in the display of time series analysis. With over 350 downloadable "dashboards", Grafana serves as an emerging software for data visualizations. Creating user-friendly visualizations ("dashboards") for the TZVOLCANO GNSS/GPS data in Tanzania can help scientists and stakeholders communicate effectively so informed decisions can be made about volcanic hazards during a time-sensitive crisis. Our use of Grafana's dashboards for one specific case-study provides an example for other geoscientists to develop analogous visualizations with the objectives of increasing the knowledge of the general public and facilitating a more informed decision-making process.

Exploring Two Approaches for an End-to-End Scientific Analysis Workflow

DOE PAGES

Dodelson, Scott; Kent, Steve; Kowalkowski, Jim; ...

2015-12-23

The advance of the scientific discovery process is accomplished by the integration of independently-developed programs run on disparate computing facilities into coherent workflows usable by scientists who are not experts in computing. For such advancement, we need a system which scientists can use to formulate analysis workflows, to integrate new components to these workflows, and to execute different components on resources that are best suited to run those components. In addition, we need to monitor the status of the workflow as components get scheduled and executed, and to access the intermediate and final output for visual exploration and analysis. Finally,more » it is important for scientists to be able to share their workflows with collaborators. Moreover we have explored two approaches for such an analysis framework for the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC), the first one is based on the use and extension of Galaxy, a web-based portal for biomedical research, and the second one is based on a programming language, Python. In our paper, we present a brief description of the two approaches, describe the kinds of extensions to the Galaxy system we have found necessary in order to support the wide variety of scientific analysis in the cosmology community, and discuss how similar efforts might be of benefit to the HEP community.« less

Analysis, Mining and Visualization Service at NCSA

NASA Astrophysics Data System (ADS)

Wilhelmson, R.; Cox, D.; Welge, M.

2004-12-01

NCSA's goal is to create a balanced system that fully supports high-end computing as well as: 1) high-end data management and analysis; 2) visualization of massive, highly complex data collections; 3) large databases; 4) geographically distributed Grid computing; and 5) collaboratories, all based on a secure computational environment and driven with workflow-based services. To this end NCSA has defined a new technology path that includes the integration and provision of cyberservices in support of data analysis, mining, and visualization. NCSA has begun to develop and apply a data mining system-NCSA Data-to-Knowledge (D2K)-in conjunction with both the application and research communities. NCSA D2K will enable the formation of model-based application workflows and visual programming interfaces for rapid data analysis. The Java-based D2K framework, which integrates analytical data mining methods with data management, data transformation, and information visualization tools, will be configurable from the cyberservices (web and grid services, tools, ..) viewpoint to solve a wide range of important data mining problems. This effort will use modules, such as a new classification methods for the detection of high-risk geoscience events, and existing D2K data management, machine learning, and information visualization modules. A D2K cyberservices interface will be developed to seamlessly connect client applications with remote back-end D2K servers, providing computational resources for data mining and integration with local or remote data stores. This work is being coordinated with SDSC's data and services efforts. The new NCSA Visualization embedded workflow environment (NVIEW) will be integrated with D2K functionality to tightly couple informatics and scientific visualization with the data analysis and management services. Visualization services will access and filter disparate data sources, simplifying tasks such as fusing related data from distinct sources into a coherent visual representation. This approach enables collaboration among geographically dispersed researchers via portals and front-end clients, and the coupling with data management services enables recording associations among datasets and building annotation systems into visualization tools and portals, giving scientists a persistent, shareable, virtual lab notebook. To facilitate provision of these cyberservices to the national community, NCSA will be providing a computational environment for large-scale data assimilation, analysis, mining, and visualization. This will be initially implemented on the new 512 processor shared memory SGI's recently purchased by NCSA. In addition to standard batch capabilities, NCSA will provide on-demand capabilities for those projects requiring rapid response (e.g., development of severe weather, earthquake events) for decision makers. It will also be used for non-sequential interactive analysis of data sets where it is important have access to large data volumes over space and time.

Stackable middleware services for advanced multimedia applications. Final report for period July 14, 1999 - July 14, 2001

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Wu-chi; Crawfis, Roger, Weide, Bruce

2002-02-01

In this project, the authors propose the research, development, and distribution of a stackable component-based multimedia streaming protocol middleware service. The goals of this stackable middleware interface include: (1) The middleware service will provide application writers and scientists easy to use interfaces that support their visualization needs. (2) The middleware service will support a variety of image compression modes. Currently, many of the network adaptation protocols for video have been developed with DCT-based compression algorithms like H.261, MPEG-1, or MPEG-2 in mind. It is expected that with advanced scientific computing applications that the lossy compression of the image data willmore » be unacceptable in certain instances. The middleware service will support several in-line lossless compression modes for error-sensitive scientific visualization data. (3) The middleware service will support two different types of streaming video modes: one for interactive collaboration of scientists and a stored video streaming mode for viewing prerecorded animations. The use of two different streaming types will allow the quality of the video delivered to the user to be maximized. Most importantly, this service will happen transparently to the user (with some basic controls exported to the user for domain specific tweaking). In the spirit of layered network protocols (like ISO and TCP/IP), application writers should not have to know a large amount about lower level network details. Currently, many example video streaming players have their congestion management techniques tightly integrated into the video player itself and are, for the most part, ''one-off'' applications. As more networked multimedia and video applications are written in the future, a larger percentage of these programmers and scientist will most likely know little about the underlying networking layer. By providing a simple, powerful, and semi-transparent middleware layer, the successful completion of this project will help serve as a catalyst to support future video-based applications, particularly those of advanced scientific computing applications.« less

Communicating why land surface heterogeneity matters

NASA Astrophysics Data System (ADS)

Tague, C.; Burke, W.; Bart, R. R.; Turpin, E.; Wood, T.; Gordon, D.

2017-12-01

As hydrologic scientists, we know that land surface heterogeneity can have nuanced and sometimes dramatic impacts on the water cycle. Land surface characteristics, including the structure and composition of vegetation and soil storage and drainage properties, alter how incoming precipitation is translated into streamflow and evapotranspiration. Land surface heterogeneity can explain why this partitioning of incoming precipitation cannot always be computed by a simple water budget calculation. We also know that land surface characteristics are dynamic - vegetation grows and changes with fire, disease and human actions and these changes will alter the partitioning of water - how much so, however depends itself on other site characteristics - soil water storage and the timing and magnitude of precipitation. This complex impact of space-time dynamics on the water cycle is something we need to effectively communicate to non-experts. For example, we may want to explain why sometimes forest management practices increase water availability but sometimes they don't - or why the impacts of urbanization or fire are location specific. If we do not communicate these dependencies we risk over-simplifying and eroding scientific credibility when observed effects don't match simple generalizations. On the other hand excessive detail can overwhelm and disengage audiences. So how do we help different communities public, private landowners, other scientists, NGOs, governments to better understand the role of space-time heterogeneity. To address this issue, we present some results from ongoing work that looks at the impact of fuel treatment of forest ecohydrology. This work stem from a collaboration between an ecohydrologic modeling team, social-scientists, a visual artist and compute graphics students. We use a coupled model, validated with field measurements, to show why spatial heterogeneity matters for understanding the impact of fuel treatments on the water cycle for the Sierra Critical Zone Observatory. We summarize current findings and present initial designs for translating these science based results into interactive visualization and conceptual art installations with the goal of better communicating the different components of landscape heterogeneity and why it matters

Southern California Earthquake Center/Undergraduate Studies in Earthquake Information Technology (SCEC/UseIT): Towards the Next Generation of Internship

NASA Astrophysics Data System (ADS)

Perry, S.; Benthien, M.; Jordan, T. H.

2005-12-01

The SCEC/UseIT internship program is training the next generation of earthquake scientist, with methods that can be adapted to other disciplines. UseIT interns work collaboratively, in multi-disciplinary teams, conducting computer science research that is needed by earthquake scientists. Since 2002, the UseIT program has welcomed 64 students, in some two dozen majors, at all class levels, from schools around the nation. Each summer''s work is posed as a ``Grand Challenge.'' The students then organize themselves into project teams, decide how to proceed, and pool their diverse talents and backgrounds. They have traditional mentors, who provide advice and encouragement, but they also mentor one another, and this has proved to be a powerful relationship. Most begin with fear that their Grand Challenge is impossible, and end with excitement and pride about what they have accomplished. The 22 UseIT interns in summer, 2005, were primarily computer science and engineering majors, with others in geology, mathematics, English, digital media design, physics, history, and cinema. The 2005 Grand Challenge was to "build an earthquake monitoring system" to aid scientists who must visualize rapidly evolving earthquake sequences and convey information to emergency personnel and the public. Most UseIT interns were engaged in software engineering, bringing new datasets and functionality to SCEC-VDO (Virtual Display of Objects), a 3D visualization software that was prototyped by interns last year, using Java3D and an extensible, plug-in architecture based on the Eclipse Integrated Development Environment. Other UseIT interns used SCEC-VDO to make animated movies, and experimented with imagery in order to communicate concepts and events in earthquake science. One movie-making project included the creation of an assessment to test the effectiveness of the movie''s educational message. Finally, one intern created an interactive, multimedia presentation of the UseIT program.

Visualization at supercomputing centers: the tale of little big iron and the three skinny guys.

PubMed

Bethel, E W; van Rosendale, J; Southard, D; Gaither, K; Childs, H; Brugger, E; Ahern, S

2011-01-01

Supercomputing centers are unique resources that aim to enable scientific knowledge discovery by employing large computational resources-the "Big Iron." Design, acquisition, installation, and management of the Big Iron are carefully planned and monitored. Because these Big Iron systems produce a tsunami of data, it's natural to colocate the visualization and analysis infrastructure. This infrastructure consists of hardware (Little Iron) and staff (Skinny Guys). Our collective experience suggests that design, acquisition, installation, and management of the Little Iron and Skinny Guys doesn't receive the same level of treatment as that of the Big Iron. This article explores the following questions about the Little Iron: How should we size the Little Iron to adequately support visualization and analysis of data coming off the Big Iron? What sort of capabilities must it have? Related questions concern the size of visualization support staff: How big should a visualization program be-that is, how many Skinny Guys should it have? What should the staff do? How much of the visualization should be provided as a support service, and how much should applications scientists be expected to do on their own?

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

NASA Technical Reports Server (NTRS)

Maxwell, Thomas

2012-01-01

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Rich client data exploration and research prototyping for NOAA

NASA Astrophysics Data System (ADS)

Grossberg, Michael; Gladkova, Irina; Guch, Ingrid; Alabi, Paul; Shahriar, Fazlul; Bonev, George; Aizenman, Hannah

2009-08-01

Data from satellites and model simulations is increasing exponentially as observations and model computing power improve rapidly. Not only is technology producing more data, but it often comes from sources all over the world. Researchers and scientists who must collaborate are also located globally. This work presents a software design and technologies which will make it possible for groups of researchers to explore large data sets visually together without the need to download these data sets locally. The design will also make it possible to exploit high performance computing remotely and transparently to analyze and explore large data sets. Computer power, high quality sensing, and data storage capacity have improved at a rate that outstrips our ability to develop software applications that exploit these resources. It is impractical for NOAA scientists to download all of the satellite and model data that may be relevant to a given problem and the computing environments available to a given researcher range from supercomputers to only a web browser. The size and volume of satellite and model data are increasing exponentially. There are at least 50 multisensor satellite platforms collecting Earth science data. On the ground and in the sea there are sensor networks, as well as networks of ground based radar stations, producing a rich real-time stream of data. This new wealth of data would have limited use were it not for the arrival of large-scale high-performance computation provided by parallel computers, clusters, grids, and clouds. With these computational resources and vast archives available, it is now possible to analyze subtle relationships which are global, multi-modal and cut across many data sources. Researchers, educators, and even the general public, need tools to access, discover, and use vast data center archives and high performance computing through a simple yet flexible interface.

The Impact of Visualizations in Promoting Informed Natural Resource Decisions

ERIC Educational Resources Information Center

Turner, Sheldon

2013-01-01

The research in this dissertation was conducted in order to understand the ways in which scientific visualizations can influence the decision process of non-scientists. A wide variety of classical and novel methods were used in order to capture and analyze the decision process. Data were collected from non-scientists through role-play interviews…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drouhard, Margaret MEG G; Steed, Chad A; Hahn, Steven E

In this paper, we propose strategies and objectives for immersive data visualization with applications in materials science using the Oculus Rift virtual reality headset. We provide background on currently available analysis tools for neutron scattering data and other large-scale materials science projects. In the context of the current challenges facing scientists, we discuss immersive virtual reality visualization as a potentially powerful solution. We introduce a prototype immersive visual- ization system, developed in conjunction with materials scientists at the Spallation Neutron Source, which we have used to explore large crystal structures and neutron scattering data. Finally, we offer our perspective onmore » the greatest challenges that must be addressed to build effective and intuitive virtual reality analysis tools that will be useful for scientists in a wide range of fields.« less

A 3-D Approach for Teaching and Learning about Surface Water Systems through Computational Thinking, Data Visualization and Physical Models

NASA Astrophysics Data System (ADS)

Caplan, B.; Morrison, A.; Moore, J. C.; Berkowitz, A. R.

2017-12-01

Understanding water is central to understanding environmental challenges. Scientists use `big data' and computational models to develop knowledge about the structure and function of complex systems, and to make predictions about changes in climate, weather, hydrology, and ecology. Large environmental systems-related data sets and simulation models are difficult for high school teachers and students to access and make sense of. Comp Hydro, a collaboration across four states and multiple school districts, integrates computational thinking and data-related science practices into water systems instruction to enhance development of scientific model-based reasoning, through curriculum, assessment and teacher professional development. Comp Hydro addresses the need for 1) teaching materials for using data and physical models of hydrological phenomena, 2) building teachers' and students' comfort or familiarity with data analysis and modeling, and 3) infusing the computational knowledge and practices necessary to model and visualize hydrologic processes into instruction. Comp Hydro teams in Baltimore, MD and Fort Collins, CO are integrating teaching about surface water systems into high school courses focusing on flooding (MD) and surface water reservoirs (CO). This interactive session will highlight the successes and challenges of our physical and simulation models in helping teachers and students develop proficiency with computational thinking about surface water. We also will share insights from comparing teacher-led vs. project-led development of curriculum and our simulations.

Remote third shift EAST operation: a new paradigm

NASA Astrophysics Data System (ADS)

Schissel, D. P.; Coviello, E.; Eidietis, N.; Flanagan, S.; Garcia, F.; Humphreys, D.; Kostuk, M.; Lanctot, M.; Lee, X.; Margo, M.; Miller, D.; Parker, C.; Penaflor, B.; Qian, J. P.; Sun, X.; Tan, H.; Walker, M.; Xiao, B.; Yuan, Q.

2017-05-01

General Atomics’ (GA) scientists in the United States remotely conducted experimental operation of the experimental advanced superconducting tokamak (EAST) in China during its third shift. Scientists led these experiments in a dedicated remote control room that utilized a novel computer science hardware and software infrastructure to allow data movement, visualization, and communication on the time scale of EAST’s pulse cycle. This Fusion Science Collaboration Zone infrastructure allows the movement of large amounts of data between continents in a short time scale with a 300-fold increase in data transfer rate over that available using the traditional transmission protocol. Real-time data from control systems is moved almost instantaneously. An event system tied to the EAST pulse cycle allows automatic initiation of data transfers, resulting in bulk EAST data to be transferred to GA within minutes. The EAST data at GA is served via MDSplus to approved US collaborators avoiding multiple US clients from requesting data from EAST and competing for the long-haul network’s bandwidth. At present there are 37 approved scientists from 8 US research institutions.

Out-of-Core Streamline Visualization on Large Unstructured Meshes

NASA Technical Reports Server (NTRS)

Ueng, Shyh-Kuang; Sikorski, K.; Ma, Kwan-Liu

1997-01-01

It's advantageous for computational scientists to have the capability to perform interactive visualization on their desktop workstations. For data on large unstructured meshes, this capability is not generally available. In particular, particle tracing on unstructured grids can result in a high percentage of non-contiguous memory accesses and therefore may perform very poorly with virtual memory paging schemes. The alternative of visualizing a lower resolution of the data degrades the original high-resolution calculations. This paper presents an out-of-core approach for interactive streamline construction on large unstructured tetrahedral meshes containing millions of elements. The out-of-core algorithm uses an octree to partition and restructure the raw data into subsets stored into disk files for fast data retrieval. A memory management policy tailored to the streamline calculations is used such that during the streamline construction only a very small amount of data are brought into the main memory on demand. By carefully scheduling computation and data fetching, the overhead of reading data from the disk is significantly reduced and good memory performance results. This out-of-core algorithm makes possible interactive streamline visualization of large unstructured-grid data sets on a single mid-range workstation with relatively low main-memory capacity: 5-20 megabytes. Our test results also show that this approach is much more efficient than relying on virtual memory and operating system's paging algorithms.

Python-Based Applications for Hydrogeological Modeling

NASA Astrophysics Data System (ADS)

Khambhammettu, P.

2013-12-01

Python is a general-purpose, high-level programming language whose design philosophy emphasizes code readability. Add-on packages supporting fast array computation (numpy), plotting (matplotlib), scientific /mathematical Functions (scipy), have resulted in a powerful ecosystem for scientists interested in exploratory data analysis, high-performance computing and data visualization. Three examples are provided to demonstrate the applicability of the Python environment in hydrogeological applications. Python programs were used to model an aquifer test and estimate aquifer parameters at a Superfund site. The aquifer test conducted at a Groundwater Circulation Well was modeled with the Python/FORTRAN-based TTIM Analytic Element Code. The aquifer parameters were estimated with PEST such that a good match was produced between the simulated and observed drawdowns. Python scripts were written to interface with PEST and visualize the results. A convolution-based approach was used to estimate source concentration histories based on observed concentrations at receptor locations. Unit Response Functions (URFs) that relate the receptor concentrations to a unit release at the source were derived with the ATRANS code. The impact of any releases at the source could then be estimated by convolving the source release history with the URFs. Python scripts were written to compute and visualize receptor concentrations for user-specified source histories. The framework provided a simple and elegant way to test various hypotheses about the site. A Python/FORTRAN-based program TYPECURVEGRID-Py was developed to compute and visualize groundwater elevations and drawdown through time in response to a regional uniform hydraulic gradient and the influence of pumping wells using either the Theis solution for a fully-confined aquifer or the Hantush-Jacob solution for a leaky confined aquifer. The program supports an arbitrary number of wells that can operate according to arbitrary schedules. The python wrapper invokes the underlying FORTRAN layer to compute transient groundwater elevations and processes this information to create time-series and 2D plots.

Scientists' sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support.

PubMed

Mirel, Barbara; Görg, Carsten

2014-04-26

A common class of biomedical analysis is to explore expression data from high throughput experiments for the purpose of uncovering functional relationships that can lead to a hypothesis about mechanisms of a disease. We call this analysis expression driven, -omics hypothesizing. In it, scientists use interactive data visualizations and read deeply in the research literature. Little is known, however, about the actual flow of reasoning and behaviors (sense making) that scientists enact in this analysis, end-to-end. Understanding this flow is important because if bioinformatics tools are to be truly useful they must support it. Sense making models of visual analytics in other domains have been developed and used to inform the design of useful and usable tools. We believe they would be helpful in bioinformatics. To characterize the sense making involved in expression-driven, -omics hypothesizing, we conducted an in-depth observational study of one scientist as she engaged in this analysis over six months. From findings, we abstracted a preliminary sense making model. Here we describe its stages and suggest guidelines for developing visualization tools that we derived from this case. A single case cannot be generalized. But we offer our findings, sense making model and case-based tool guidelines as a first step toward increasing interest and further research in the bioinformatics field on scientists' analytical workflows and their implications for tool design.

ODI - Portal, Pipeline, and Archive (ODI-PPA): a web-based astronomical compute archive, visualization, and analysis service

NASA Astrophysics Data System (ADS)

Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Harbeck, Daniel R.; Boroson, Todd; Liu, Wilson; Kotulla, Ralf; Shaw, Richard; Henschel, Robert; Rajagopal, Jayadev; Stobie, Elizabeth; Knezek, Patricia; Martin, R. Pierre; Archbold, Kevin

2014-07-01

The One Degree Imager-Portal, Pipeline, and Archive (ODI-PPA) is a web science gateway that provides astronomers a modern web interface that acts as a single point of access to their data, and rich computational and visualization capabilities. Its goal is to support scientists in handling complex data sets, and to enhance WIYN Observatory's scientific productivity beyond data acquisition on its 3.5m telescope. ODI-PPA is designed, with periodic user feedback, to be a compute archive that has built-in frameworks including: (1) Collections that allow an astronomer to create logical collations of data products intended for publication, further research, instructional purposes, or to execute data processing tasks (2) Image Explorer and Source Explorer, which together enable real-time interactive visual analysis of massive astronomical data products within an HTML5 capable web browser, and overlaid standard catalog and Source Extractor-generated source markers (3) Workflow framework which enables rapid integration of data processing pipelines on an associated compute cluster and users to request such pipelines to be executed on their data via custom user interfaces. ODI-PPA is made up of several light-weight services connected by a message bus; the web portal built using Twitter/Bootstrap, AngularJS and jQuery JavaScript libraries, and backend services written in PHP (using the Zend framework) and Python; it leverages supercomputing and storage resources at Indiana University. ODI-PPA is designed to be reconfigurable for use in other science domains with large and complex datasets, including an ongoing offshoot project for electron microscopy data.

Skills and Knowledge for Data-Intensive Environmental Research

PubMed Central

Hampton, Stephanie E.; Jones, Matthew B.; Wasser, Leah A.; Schildhauer, Mark P.; Supp, Sarah R.; Brun, Julien; Hernandez, Rebecca R.; Boettiger, Carl; Collins, Scott L.; Gross, Louis J.; Fernández, Denny S.; Budden, Amber; White, Ethan P.; Teal, Tracy K.; Aukema, Juliann E.

2017-01-01

Abstract The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap. PMID:28584342

Skills and Knowledge for Data-Intensive Environmental Research.

PubMed

Hampton, Stephanie E; Jones, Matthew B; Wasser, Leah A; Schildhauer, Mark P; Supp, Sarah R; Brun, Julien; Hernandez, Rebecca R; Boettiger, Carl; Collins, Scott L; Gross, Louis J; Fernández, Denny S; Budden, Amber; White, Ethan P; Teal, Tracy K; Labou, Stephanie G; Aukema, Juliann E

2017-06-01

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

Visualizing Terrestrial and Aquatic Systems in 3D

EPA Science Inventory

The need for better visualization tools for environmental science is well documented, and the Visualization for Terrestrial and Aquatic Systems project (VISTAS) aims to both help scientists produce effective environmental science visualizations and to determine which visualizatio...

2017 ISCB Accomplishment by a Senior Scientist Award: Pavel Pevzner

PubMed Central

Fogg, Christiana N.; Kovats, Diane E.; Berger, Bonnie

2017-01-01

The International Society for Computational Biology ( ISCB) recognizes an established scientist each year with the Accomplishment by a Senior Scientist Award for significant contributions he or she has made to the field. This award honors scientists who have contributed to the advancement of computational biology and bioinformatics through their research, service, and education work. Pavel Pevzner, PhD, Ronald R. Taylor Professor of Computer Science and Director of the NIH Center for Computational Mass Spectrometry at University of California, San Diego, has been selected as the winner of the 2017 Accomplishment by a Senior Scientist Award. The ISCB awards committee, chaired by Dr. Bonnie Berger of the Massachusetts Institute of Technology, selected Pevzner as the 2017 winner. Pevzner will receive his award and deliver a keynote address at the 2017 Intelligent Systems for Molecular Biology-European Conference on Computational Biology joint meeting ( ISMB/ECCB 2017) held in Prague, Czech Republic from July 21-July 25, 2017. ISMB/ECCB is a biennial joint meeting that brings together leading scientists in computational biology and bioinformatics from around the globe. PMID:28713548

Enabling scientific workflows in virtual reality

USGS Publications Warehouse

Kreylos, O.; Bawden, G.; Bernardin, T.; Billen, M.I.; Cowgill, E.S.; Gold, R.D.; Hamann, B.; Jadamec, M.; Kellogg, L.H.; Staadt, O.G.; Sumner, D.Y.

2006-01-01

To advance research and improve the scientific return on data collection and interpretation efforts in the geosciences, we have developed methods of interactive visualization, with a special focus on immersive virtual reality (VR) environments. Earth sciences employ a strongly visual approach to the measurement and analysis of geologic data due to the spatial and temporal scales over which such data ranges, As observations and simulations increase in size and complexity, the Earth sciences are challenged to manage and interpret increasing amounts of data. Reaping the full intellectual benefits of immersive VR requires us to tailor exploratory approaches to scientific problems. These applications build on the visualization method's strengths, using both 3D perception and interaction with data and models, to take advantage of the skills and training of the geological scientists exploring their data in the VR environment. This interactive approach has enabled us to develop a suite of tools that are adaptable to a range of problems in the geosciences and beyond. Copyright ?? 2008 by the Association for Computing Machinery, Inc.

A Cloud-Based Global Flood Disaster Community Cyber-Infrastructure: Development and Demonstration

NASA Technical Reports Server (NTRS)

Wan, Zhanming; Hong, Yang; Khan, Sadiq; Gourley, Jonathan; Flamig, Zachary; Kirschbaum, Dalia; Tang, Guoqiang

2014-01-01

Flood disasters have significant impacts on the development of communities globally. This study describes a public cloud-based flood cyber-infrastructure (CyberFlood) that collects, organizes, visualizes, and manages several global flood databases for authorities and the public in real-time, providing location-based eventful visualization as well as statistical analysis and graphing capabilities. In order to expand and update the existing flood inventory, a crowdsourcing data collection methodology is employed for the public with smartphones or Internet to report new flood events, which is also intended to engage citizen-scientists so that they may become motivated and educated about the latest developments in satellite remote sensing and hydrologic modeling technologies. Our shared vision is to better serve the global water community with comprehensive flood information, aided by the state-of-the- art cloud computing and crowdsourcing technology. The CyberFlood presents an opportunity to eventually modernize the existing paradigm used to collect, manage, analyze, and visualize water-related disasters.

Pathview Web: user friendly pathway visualization and data integration

PubMed Central

Pant, Gaurav; Bhavnasi, Yeshvant K.; Blanchard, Steven G.; Brouwer, Cory

2017-01-01

Abstract Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. PMID:28482075

Eye of the Forehead and Eye of the Mind: How Engineers and Scientists See

ScienceCinema

Lienhard, John [NPR, United States

2017-12-09

Public radio host Dr. John Lienhard gives a talk titled "Eye of the Forehead and Eye of the Mind: How Engineers and Scientists See". Lienhard contends that spatial visualization is the subtlest of abilities. In his talk, he traces its evolution through the past five centuries and explains how remarkable aids to seeing may have been placing mental visualization under threat.

Biological Basis For Computer Vision: Some Perspectives

NASA Astrophysics Data System (ADS)

Gupta, Madan M.

1990-03-01

Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

The Center for Computational Biology: resources, achievements, and challenges

PubMed Central

Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

The Center for Computational Biology: resources, achievements, and challenges.

PubMed

Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2012-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

The GLOBAL Learning and Observations to Benefit the Environment (GLOBE) Data Visualization and Retrieval System. Building a robust system for scientists and students.

NASA Astrophysics Data System (ADS)

Overoye, D.; Lewis, C.; Butler, D. M.; Andersen, T. J.

2016-12-01

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is a worldwide hands-on, primary and secondary school-based science and education program founded on Earth Day 1995. Implemented in 117 countries, GLOBE promotes the teaching and learning of science, supporting students, teachers and scientists worldwide to collaborate with each other on inquiry-based investigations of the Earth system. The GLOBE Data Information System (DIS) currently supports users with the ability to enter data from over 50 different science protocols. GLOBE's Data Access and Visualization tools have been developed to accommodate the need to display and retrieve data from this large number of protocols. The community of users is also diverse, including NASA scientists, citizen scientists and grade school students. The challenge for GLOBE is to meet the needs from this diverse set of users with protocol specific displays that are simple enough for a GLOBE school to use, but also provide enough features for a NASA Scientist to retrieve data sets they are interested in. During the last 3 years, the GLOBE visualization system has evolved to meet the needs of these various users, leveraging user feedback and technological advances. Further refinements and enhancements continue. In this session we review the design and capabilities of the GLOBE visualization and data retrieval tool set, discuss the evolution of these tools, and discuss coming directions.

Robotics and Virtual Reality for Cultural Heritage Digitization and Fruition

NASA Astrophysics Data System (ADS)

Calisi, D.; Cottefoglie, F.; D'Agostini, L.; Giannone, F.; Nenci, F.; Salonia, P.; Zaratti, M.; Ziparo, V. A.

2017-05-01

In this paper we present our novel approach for acquiring and managing digital models of archaeological sites, and the visualization techniques used to showcase them. In particular, we will demonstrate two technologies: our robotic system for digitization of archaeological sites (DigiRo) result of over three years of efforts by a group of cultural heritage experts, computer scientists and roboticists, and our cloud-based archaeological information system (ARIS). Finally we describe the viewers we developed to inspect and navigate the 3D models: a viewer for the web (ROVINA Web Viewer) and an immersive viewer for Virtual Reality (ROVINA VR Viewer).

Face Recognition in Humans and Machines

NASA Astrophysics Data System (ADS)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

PubMed Central

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E.; Tkachenko, Valery; Torcivia-Rodriguez, John; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure. The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu PMID:26989153

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis.

PubMed

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E; Tkachenko, Valery; Torcivia-Rodriguez, John; Voskanian, Alin; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu. © The Author(s) 2016. Published by Oxford University Press.

Developing a Science Commons for Geosciences

NASA Astrophysics Data System (ADS)

Lenhardt, W. C.; Lander, H.

2016-12-01

Many scientific communities, recognizing the research possibilities inherent in data sets, have created domain specific archives such as the Incorporated Research Institutions for Seismology (iris.edu) and ClinicalTrials.gov. Though this is an important step forward, most scientists, including geoscientists, also use a variety of software tools and at least some amount of computation to conduct their research. While the archives make it simpler for scientists to locate the required data, provisioning disk space, compute resources, and network bandwidth can still require significant efforts. This challenge exists despite the wealth of resources available to researchers, namely lab IT resources, institutional IT resources, national compute resources (XSEDE, OSG), private clouds, public clouds, and the development of cyberinfrastructure technologies meant to facilitate use of those resources. Further tasks include obtaining and installing required tools for analysis and visualization. If the research effort is a collaboration or involves certain types of data, then the partners may well have additional non-scientific tasks such as securing the data and developing secure sharing methods for the data. These requirements motivate our investigations into the "Science Commons". This paper will present a working definition of a science commons, compare and contrast examples of existing science commons, and describe a project based at RENCI to implement a science commons for risk analytics. We will then explore what a similar tool might look like for the geosciences.

Visualizing Terrestrial and Aquatic Systems in 3D - in IEEE VisWeek 2014

EPA Science Inventory

The need for better visualization tools for environmental science is well documented, and the Visualization for Terrestrial and Aquatic Systems project (VISTAS) aims to both help scientists produce effective environmental science visualizations and to determine which visualizatio...

Advancing Water Science through Data Visualization

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T.

2014-12-01

As water scientists, we are increasingly handling larger and larger datasets with many variables, making it easy to lose ourselves in the details. Advanced data visualization will play an increasingly significant role in propelling the development of water science in research, economy, policy and education. It can enable analysis within research and further data scientists' understanding of behavior and processes and can potentially affect how the public, whom we often want to inform, understands our work. Unfortunately for water scientists, data visualization is approached in an ad hoc manner when a more formal methodology or understanding could potentially significantly improve both research within the academy and outreach to the public. Firstly to broaden and deepen scientific understanding, data visualization can allow for more analyzed targets to be processed simultaneously and can represent the variables effectively, finding patterns, trends and relationships; thus it can even explores the new research direction or branch of water science. Depending on visualization, we can detect and separate the pivotal and trivial influential factors more clearly to assume and abstract the original complex target system. Providing direct visual perception of the differences between observation data and prediction results of models, data visualization allows researchers to quickly examine the quality of models in water science. Secondly data visualization can also improve public awareness and perhaps influence behavior. Offering decision makers clearer perspectives of potential profits of water, data visualization can amplify the economic value of water science and also increase relevant employment rates. Providing policymakers compelling visuals of the role of water for social and natural systems, data visualization can advance the water management and legislation of water conservation. By building the publics' own data visualization through apps and games about water science, they can absorb the knowledge about water indirectly and incite the awareness of water problems.

Real-time visualization of magnetic flux densities for transcranial magnetic stimulation on commodity and fully immersive VR systems

NASA Astrophysics Data System (ADS)

Kalivarapu, Vijay K.; Serrate, Ciro; Hadimani, Ravi L.

2017-05-01

Transcranial Magnetic Stimulation (TMS) is a non-invasive procedure that uses time varying short pulses of magnetic fields to stimulate nerve cells in the brain. In this method, a magnetic field generator ("TMS coil") produces small electric fields in the region of the brain via electromagnetic induction. This technique can be used to excite or inhibit firing of neurons, which can then be used for treatment of various neurological disorders such as Parkinson's disease, stroke, migraine, and depression. It is however challenging to focus the induced electric field from TMS coils to smaller regions of the brain. Since electric and magnetic fields are governed by laws of electromagnetism, it is possible to numerically simulate and visualize these fields to accurately determine the site of maximum stimulation and also to develop TMS coils that can focus the fields on the targeted regions. However, current software to compute and visualize these fields are not real-time and can work for only one position/orientation of TMS coil, severely limiting their usage. This paper describes the development of an application that computes magnetic flux densities (h-fields) and visualizes their distribution for different TMS coil position/orientations in real-time using GPU shaders. The application is developed for desktop, commodity VR (HTC Vive), and fully immersive VR CAVETM systems, for use by researchers, scientists, and medical professionals to quickly and effectively view the distribution of h-fields from MRI brain scans.

Bringing the Unidata IDV to the Cloud

NASA Astrophysics Data System (ADS)

Fisher, W. I.; Oxelson Ganter, J.

2015-12-01

Maintaining software compatibility across new computing environments and the associated underlying hardware is a common problem for software engineers and scientific programmers. While traditional software engineering provides a suite of tools and methodologies which may mitigate this issue, they are typically ignored by developers lacking a background in software engineering. Causing further problems, these methodologies are best applied at the start of project; trying to apply them to an existing, mature project can require an immense effort. Visualization software is particularly vulnerable to this problem, given the inherent dependency on particular graphics hardware and software API's. As a result of these issues, there exists a large body of software which is simultaneously critical to the scientists who are dependent upon it, and yet increasingly difficult to maintain.The solution to this problem was partially provided with the advent of Cloud Computing; Application Streaming. This technology allows a program to run entirely on a remote virtual machine while still allowing for interactivity and dynamic visualizations, with little-to-no re-engineering required. When coupled with containerization technology such as Docker, we are able to easily bring the same visualization software to a desktop, a netbook, a smartphone, and the next generation of hardware, whatever it may be.Unidata has been able to harness Application Streaming to provide a tablet-compatible version of our visualization software, the Integrated Data Viewer (IDV). This work will examine the challenges associated with adapting the IDV to an application streaming platform, and include a brief discussion of the underlying technologies involved.

Instrumentation, performance visualization, and debugging tools for multiprocessors

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Fineman, Charles E.; Hontalas, Philip J.

1991-01-01

The need for computing power has forced a migration from serial computation on a single processor to parallel processing on multiprocessor architectures. However, without effective means to monitor (and visualize) program execution, debugging, and tuning parallel programs becomes intractably difficult as program complexity increases with the number of processors. Research on performance evaluation tools for multiprocessors is being carried out at ARC. Besides investigating new techniques for instrumenting, monitoring, and presenting the state of parallel program execution in a coherent and user-friendly manner, prototypes of software tools are being incorporated into the run-time environments of various hardware testbeds to evaluate their impact on user productivity. Our current tool set, the Ames Instrumentation Systems (AIMS), incorporates features from various software systems developed in academia and industry. The execution of FORTRAN programs on the Intel iPSC/860 can be automatically instrumented and monitored. Performance data collected in this manner can be displayed graphically on workstations supporting X-Windows. We have successfully compared various parallel algorithms for computational fluid dynamics (CFD) applications in collaboration with scientists from the Numerical Aerodynamic Simulation Systems Division. By performing these comparisons, we show that performance monitors and debuggers such as AIMS are practical and can illuminate the complex dynamics that occur within parallel programs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Kwan-Liu

In this project, we have developed techniques for visualizing large-scale time-varying multivariate particle and field data produced by the GPS_TTBP team. Our basic approach to particle data visualization is to provide the user with an intuitive interactive interface for exploring the data. We have designed a multivariate filtering interface for scientists to effortlessly isolate those particles of interest for revealing structures in densely packed particles as well as the temporal behaviors of selected particles. With such a visualization system, scientists on the GPS-TTBP project can validate known relationships and temporal trends, and possibly gain new insights in their simulations. Wemore » have tested the system using over several millions of particles on a single PC. We will also need to address the scalability of the system to handle billions of particles using a cluster of PCs. To visualize the field data, we choose to use direct volume rendering. Because the data provided by PPPL is on a curvilinear mesh, several processing steps have to be taken. The mesh is curvilinear in nature, following the shape of a deformed torus. Additionally, in order to properly interpolate between the given slices we cannot use simple linear interpolation in Cartesian space but instead have to interpolate along the magnetic field lines given to us by the scientists. With these limitations, building a system that can provide an accurate visualization of the dataset is quite a challenge to overcome. In the end we use a combination of deformation methods such as deformation textures in order to fit a normal torus into their deformed torus, allowing us to store the data in toroidal coordinates in order to take advantage of modern GPUs to perform the interpolation along the field lines for us. The resulting new rendering capability produces visualizations at a quality and detail level previously not available to the scientists at the PPPL. In summary, in this project we have successfully created new capabilities for the scientists to visualize their 3D data at higher accuracy and quality, enhancing their ability to evaluate the simulations and understand the modeled phenomena.« less

Implementing virtual reality interfaces for the geosciences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, W.; Jacobsen, J.; Austin, A.

1996-06-01

For the past few years, a multidisciplinary team of computer and earth scientists at Lawrence Berkeley National Laboratory has been exploring the use of advanced user interfaces, commonly called {open_quotes}Virtual Reality{close_quotes} (VR), coupled with visualization and scientific computing software. Working closely with industry, these efforts have resulted in an environment in which VR technology is coupled with existing visualization and computational tools. VR technology may be thought of as a user interface. It is useful to think of a spectrum, ranging the gamut from command-line interfaces to completely immersive environments. In the former, one uses the keyboard to enter threemore » or six-dimensional parameters. In the latter, three or six-dimensional information is provided by trackers contained either in hand-held devices or attached to the user in some fashion, e.g. attached to a head-mounted display. Rich, extensible and often complex languages are a vehicle whereby the user controls parameters to manipulate object position and location in a virtual world, but the keyboard is the obstacle in that typing is cumbersome, error-prone and typically slow. In the latter, the user can interact with these parameters by means of motor skills which are highly developed. Two specific geoscience application areas will be highlighted. In the first, we have used VR technology to manipulate three-dimensional input parameters, such as the spatial location of injection or production wells in a reservoir simulator. In the second, we demonstrate how VR technology has been used to manipulate visualization tools, such as a tool for computing streamlines via manipulation of a {open_quotes}rake.{close_quotes} The rake is presented to the user in the form of a {open_quotes}virtual well{close_quotes} icon, and provides parameters used by the streamlines algorithm.« less

Mapping of Sample Collection Data: GIS Tools for the Natural Product Researcher

PubMed Central

Oberlies, Nicholas H.; Rineer, James I.; Alali, Feras Q.; Tawaha, Khaled; Falkinham, Joseph O.; Wheaton, William D.

2009-01-01

Scientists engaged in the research of natural products often either conduct field collections themselves or collaborate with partners who do, such as botanists, mycologists, or SCUBA divers. The information gleaned from such collecting trips (e.g. longitude/latitude coordinates, geography, elevation, and a multitude of other field observations) have provided valuable data to the scientific community (e.g., biodiversity), even if it is tangential to the direct aims of the natural products research, which are often focused on drug discovery and/or chemical ecology. Geographic Information Systems (GIS) have been used to display, manage, and analyze geographic data, including collection sites for natural products. However, to the uninitiated, these tools are often beyond the financial and/or computational means of the natural product scientist. With new, free, and easy-to-use geospatial visualization tools, such as Google Earth, mapping and geographic imaging of sampling data are now within the reach of natural products scientists. The goals of the present study were to develop simple tools that are tailored for the natural products setting, thereby presenting a means to map such information, particularly via open source software like Google Earth. PMID:20161345

Visualization at Supercomputing Centers: The Tale of Little Big Iron and the Three Skinny Guys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, E. Wes; van Rosendale, John; Southard, Dale

2010-12-01

Supercomputing Centers (SC's) are unique resources that aim to enable scientific knowledge discovery through the use of large computational resources, the Big Iron. Design, acquisition, installation, and management of the Big Iron are activities that are carefully planned and monitored. Since these Big Iron systems produce a tsunami of data, it is natural to co-locate visualization and analysis infrastructure as part of the same facility. This infrastructure consists of hardware (Little Iron) and staff (Skinny Guys). Our collective experience suggests that design, acquisition, installation, and management of the Little Iron and Skinny Guys does not receive the same level ofmore » treatment as that of the Big Iron. The main focus of this article is to explore different aspects of planning, designing, fielding, and maintaining the visualization and analysis infrastructure at supercomputing centers. Some of the questions we explore in this article include:"How should the Little Iron be sized to adequately support visualization and analysis of data coming off the Big Iron?" What sort of capabilities does it need to have?" Related questions concern the size of visualization support staff:"How big should a visualization program be (number of persons) and what should the staff do?" and"How much of the visualization should be provided as a support service, and how much should applications scientists be expected to do on their own?"« less

Virtual Reality: Visualization in Three Dimensions.

ERIC Educational Resources Information Center

McLellan, Hilary

Virtual reality is a newly emerging tool for scientific visualization that makes possible multisensory, three-dimensional modeling of scientific data. While the emphasis is on visualization, the other senses are added to enhance what the scientist can visualize. Researchers are working to extend the sensory range of what can be perceived in…

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

PubMed

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

Immersive Interaction, Manipulation and Analysis of Large 3D Datasets for Planetary and Earth Sciences

NASA Astrophysics Data System (ADS)

Pariser, O.; Calef, F.; Manning, E. M.; Ardulov, V.

2017-12-01

We will present implementation and study of several use-cases of utilizing Virtual Reality (VR) for immersive display, interaction and analysis of large and complex 3D datasets. These datasets have been acquired by the instruments across several Earth, Planetary and Solar Space Robotics Missions. First, we will describe the architecture of the common application framework that was developed to input data, interface with VR display devices and program input controllers in various computing environments. Tethered and portable VR technologies will be contrasted and advantages of each highlighted. We'll proceed to presenting experimental immersive analytics visual constructs that enable augmentation of 3D datasets with 2D ones such as images and statistical and abstract data. We will conclude by presenting comparative analysis with traditional visualization applications and share the feedback provided by our users: scientists and engineers.

Virtual Reality Used to Serve the Glenn Engineering Community

NASA Technical Reports Server (NTRS)

Carney, Dorothy V.

2001-01-01

There are a variety of innovative new visualization tools available to scientists and engineers for the display and analysis of their models. At the NASA Glenn Research Center, we have an ImmersaDesk, a large, single-panel, semi-immersive display device. This versatile unit can interactively display three-dimensional images in visual stereo. Our challenge is to make this virtual reality platform accessible and useful to researchers. An example of a successful application of this computer technology is the display of blade out simulations. NASA Glenn structural dynamicists, Dr. Kelly Carney and Dr. Charles Lawrence, funded by the Ultra Safe Propulsion Project under Base R&T, are researching blade outs, when turbine engines lose a fan blade during operation. Key objectives of this research include minimizing danger to the aircraft via effective blade containment, predicting destructive loads due to the imbalance following a blade loss, and identifying safe, cost-effective designs and materials for future engines.

Colour in a larger perspective: the rebirth of Gestalt psychology.

PubMed

Spillmann, L

1997-01-01

This overview takes the reader from the classical contrast and assimilation studies of the past to today's colour research, in a broad sense, with its renewed emphasis on the phenomenological qualities of visual perception. It shows how the shift in paradigm from local to global effects in single-unit recordings prompted a reappraisal of appearance in visual experiments, not just in colour, but in the perception of motion, texture, and depth as well. Gestalt ideas placed in the context of modern concepts are shown to inspire psychophysicists, neurophysiologists, and computational vision scientists alike. Feedforward, horizontal interactions, and feedback are discussed as potential neuronal mechanisms to account for phenomena such as uniform surfaces, filling-in, and grouping arising from processes beyond the classical receptive field. A look forward towards future developments in the field of figure-ground segregation (Gestalt formation) concludes the article.

Interactive access and management for four-dimensional environmental data sets using McIDAS

NASA Technical Reports Server (NTRS)

Hibbard, William L.; Tripoli, Gregory J.

1995-01-01

This grant has fundamentally changed the way that meteorologists look at the output of their atmospheric models, through the development and wide distribution of the Vis5D system. The Vis5D system is also gaining acceptance among oceanographers and atmospheric chemists. Vis5D gives these scientists an interactive three-dimensional movie of their very large data sets that they can use to understand physical mechanisms and to trace problems to their sources. This grant has also helped to define the future direction of scientific visualization through the development of the VisAD system and its lattice data model. The VisAD system can be used to interactively steer and visualize scientific computations. A key element of this capability is the flexibility of the system's data model to adapt to a wide variety of scientific data, including the integration of several forms of scientific metadata.

The functional consequences of social distraction: Attention and memory for complex scenes.

PubMed

Doherty, Brianna Ruth; Patai, Eva Zita; Duta, Mihaela; Nobre, Anna Christina; Scerif, Gaia

2017-01-01

Cognitive scientists have long proposed that social stimuli attract visual attention even when task irrelevant, but the consequences of this privileged status for memory are unknown. To address this, we combined computational approaches, eye-tracking methodology, and individual-differences measures. Participants searched for targets in scenes containing social or non-social distractors equated for low-level visual salience. Subsequent memory precision for target locations was tested. Individual differences in autistic traits and social anxiety were also measured. Eye-tracking revealed significantly more attentional capture to social compared to non-social distractors. Critically, memory precision for target locations was poorer for social scenes. This effect was moderated by social anxiety, with anxious individuals remembering target locations better under conditions of social distraction. These findings shed further light onto the privileged attentional status of social stimuli and its functional consequences on memory across individuals. Copyright © 2016. Published by Elsevier B.V.

Science and Software

NASA Astrophysics Data System (ADS)

Zelt, C. A.

2017-12-01

Earth science attempts to understand how the earth works. This research often depends on software for modeling, processing, inverting or imaging. Freely sharing open-source software is essential to prevent reinventing the wheel and allows software to be improved and applied in ways the original author may never have envisioned. For young scientists, releasing software can increase their name ID when applying for jobs and funding, and create opportunities for collaborations when scientists who collect data want the software's creator to be involved in their project. However, we frequently hear scientists say software is a tool, it's not science. Creating software that implements a new or better way of earth modeling or geophysical processing, inverting or imaging should be viewed as earth science. Creating software for things like data visualization, format conversion, storage, or transmission, or programming to enhance computational performance, may be viewed as computer science. The former, ideally with an application to real data, can be published in earth science journals, the latter possibly in computer science journals. Citations in either case should accurately reflect the impact of the software on the community. Funding agencies need to support more software development and open-source releasing, and the community should give more high-profile awards for developing impactful open-source software. Funding support and community recognition for software development can have far reaching benefits when the software is used in foreseen and unforeseen ways, potentially for years after the original investment in the software development. For funding, an open-source release that is well documented should be required, with example input and output files. Appropriate funding will provide the incentive and time to release user-friendly software, and minimize the need for others to duplicate the effort. All funded software should be available through a single web site, ideally maintained by someone in a funded position. Perhaps the biggest challenge is the reality that researches who use software, as opposed to develop software, are more attractive university hires because they are more likely to be "big picture" scientists that publish in the highest profile journals, although sometimes the two go together.

Neural Network Machine Learning and Dimension Reduction for Data Visualization

NASA Technical Reports Server (NTRS)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

A guide to the visual analysis and communication of biomolecular structural data.

PubMed

Johnson, Graham T; Hertig, Samuel

2014-10-01

Biologists regularly face an increasingly difficult task - to effectively communicate bigger and more complex structural data using an ever-expanding suite of visualization tools. Whether presenting results to peers or educating an outreach audience, a scientist can achieve maximal impact with minimal production time by systematically identifying an audience's needs, planning solutions from a variety of visual communication techniques and then applying the most appropriate software tools. A guide to available resources that range from software tools to professional illustrators can help researchers to generate better figures and presentations tailored to any audience's needs, and enable artistically inclined scientists to create captivating outreach imagery.

Visual air quality simulation techniques

NASA Astrophysics Data System (ADS)

Molenar, John V.; Malm, William C.; Johnson, Christopher E.

Visual air quality is primarily a human perceptual phenomenon beginning with the transfer of image-forming information through an illuminated, scattering and absorbing atmosphere. Visibility, especially the visual appearance of industrial emissions or the degradation of a scenic view, is the principal atmospheric characteristic through which humans perceive air pollution, and is more sensitive to changing pollution levels than any other air pollution effect. Every attempt to quantify economic costs and benefits of air pollution has indicated that good visibility is a highly valued and desired environmental condition. Measurement programs can at best approximate the state of the ambient atmosphere at a few points in a scenic vista viewed by an observer. To fully understand the visual effect of various changes in the concentration and distribution of optically important atmospheric pollutants requires the use of aerosol and radiative transfer models. Communication of the output of these models to scientists, decision makers and the public is best done by applying modern image-processing systems to generate synthetic images representing the modeled air quality conditions. This combination of modeling techniques has been under development for the past 15 yr. Initially, visual air quality simulations were limited by a lack of computational power to simplified models depicting Gaussian plumes or uniform haze conditions. Recent explosive growth in low cost, high powered computer technology has allowed the development of sophisticated aerosol and radiative transfer models that incorporate realistic terrain, multiple scattering, non-uniform illumination, varying spatial distribution, concentration and optical properties of atmospheric constituents, and relative humidity effects on aerosol scattering properties. This paper discusses these improved models and image-processing techniques in detail. Results addressing uniform and non-uniform layered haze conditions in both urban and remote pristine areas will be presented.

Experience with Data Science as an Intern with the Jet Propulsion Laboratory

NASA Astrophysics Data System (ADS)

Whittell, J.; Mattmann, C. A.; Whitehall, K. D.; Ramirez, P.; Goodale, C. E.; Boustani, M.; Hart, A. F.; Kim, J.; Waliser, D. E.; Joyce, M. J.

2013-12-01

The Regional Climate Model Evaluation System (RCMES, http://rcmes.jpl.nasa.gov) at NASA's Jet Propulsion Laboratory seeks to improve regional climate model output by comparing past model predictions with Earth-orbiting satellite data (Mattmann et al. 2013). RCMES ingests satellite and RCM data and processes these data into a common format; as needed, the software queries the RCMES database for these datasets, on which it runs a series of statistical metrics including model-satellite comparisons. The development of the RCMES software relies on collaboration between climatologists and computer scientists, as evinced by RCMES longstanding work with CORDEX (Kim et al. 2012). Over a total of 17 weeks in 2011, 2012, and 2013, I worked as an intern at NASA's Jet Propulsion Laboratory in a supportive capacity for RCMES. A high school student, I had no formal background in either Earth science or computer technology, but was immersed in both fields. In 2011, I researched three earth-science data management projects, producing a high-level explanation of these endeavors. The following year, I studied Python, contributing a command-line user interface to the RCMES project code. In 2013, I assisted with data acquisition, wrote a file header information plugin, and the visualization tool GrADS. The experience demonstrated the importance of an interdisciplinary approach to data processing: to streamline data ingestion and processing, scientists must understand, at least on a high-level, any programs they might utilize while to best serve the needs of earth scientists, software engineers must understand the science behind the data they handle.

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

PubMed

Knapp, B; Frantal, S; Cibena, M; Schreiner, W; Bauer, P

2011-08-01

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

MatLab Programming for Engineers Having No Formal Programming Knowledge

NASA Technical Reports Server (NTRS)

Shaykhian, Linda H.; Shaykhian, Gholam Ali

2007-01-01

MatLab is one of the most widely used very high level programming languages for Scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. Also, stated are the current limitations of the MatLab, which possibly can be taken care of by Mathworks Inc. in a future version to make MatLab more versatile.

a Study on Mental Representations for Realistic Visualization the Particular Case of Ski Trail Mapping

NASA Astrophysics Data System (ADS)

Balzarini, R.; Dalmasso, A.; Murat, M.

2015-08-01

This article presents preliminary results from a research project in progress that brings together geographers, cognitive scientists, historians and computer scientists. The project investigates the evolution of a particular territorial model: ski trails maps. Ski resorts, tourist and sporting innovations for mountain economies since the 1930s, have needed cartographic representations corresponding to new practices of the space.Painter artists have been involved in producing ski maps with painting techniques and panoramic views, which are by far the most common type of map, because they allow the resorts to look impressive to potential visitors. These techniques have evolved throughout the mutations of the ski resorts. Paper ski maps no longer meet the needs of a large part of the customers; the question now arises of their adaptation to digital media. In a computerized process perspective, the early stage of the project aims to identify the artist-representations, based on conceptual and technical rules, which are handled by users-skiers to perform a task (location, wayfinding, decision-making) and can be transferred to a computer system. This article presents the experimental phase that analyzes artist and user mental representations that are at stake during the making and the reading of a paper ski map. It particularly focuses on how the invention of the artist influences map reading.

Visualization in Science and the Arts.

ERIC Educational Resources Information Center

Roth, Susan King

Visualization as a factor of intelligence includes the mental manipulation of spatial configurations and has been associated with spatial abilities, creative thinking, and conceptual problem solving. There are numerous reports of scientists and mathematicians using visualization to anticipate transformation of the external world. Artists and…

Visualizing Terrestrial and Aquatic Systems in 3-D

EPA Science Inventory

The environmental modeling community has a long-standing need for affordable, easy-to-use tools that support 3-D visualization of complex spatial and temporal model output. The Visualization of Terrestrial and Aquatic Systems project (VISTAS) aims to help scientists produce effe...

Visual Literacy in Bloom: Using Bloom's Taxonomy to Support Visual Learning Skills

ERIC Educational Resources Information Center

Arneson, Jessie B.; Offerdahl, Erika G.

2018-01-01

"Vision and Change" identifies science communication as one of the core competencies in undergraduate biology. Visual representations are an integral part of science communication, allowing ideas to be shared among and between scientists and the public. As such, development of scientific visual literacy should be a desired outcome of…

Graphical User Interface Development for Representing Air Flow Patterns

NASA Technical Reports Server (NTRS)

Chaudhary, Nilika

2004-01-01

In the Turbine Branch, scientists carry out experimental and computational work to advance the efficiency and diminish the noise production of jet engine turbines. One way to do this is by decreasing the heat that the turbine blades receive. Most of the experimental work is carried out by taking a single turbine blade and analyzing the air flow patterns around it, because this data indicates the sections of the turbine blade that are getting too hot. Since the cost of doing turbine blade air flow experiments is very high, researchers try to do computational work that fits the experimental data. The goal of computational fluid dynamics is for scientists to find a numerical way to predict the complex flow patterns around different turbine blades without physically having to perform tests or costly experiments. When visualizing flow patterns, scientists need a way to represent the flow conditions around a turbine blade. A researcher will assign specific zones that surround the turbine blade. In a two-dimensional view, the zones are usually quadrilaterals. The next step is to assign boundary conditions which define how the flow enters or exits one side of a zone. way of setting up computational zones and grids, visualizing flow patterns, and storing all the flow conditions in a file on the computer for future computation. Such a program is necessary because the only method for creating flow pattern graphs is by hand, which is tedious and time-consuming. By using a computer program to create the zones and grids, the graph would be faster to make and easier to edit. Basically, the user would run a program that is an editable graph. The user could click and drag with the mouse to form various zones and grids, then edit the locations of these grids, add flow and boundary conditions, and finally save the graph for future use and analysis. My goal this summer is to create a graphical user interface (GUI) that incorporates all of these elements. I am writing the program in Java, a language that is portable among platforms, because it can run on different operating systems such as Windows and Unix without having to be rewritten. I had no prior experience of programming in Java at the start of my internship; I am continuously learning as I create the program. I have written the part of the program that enables a user to draw several zones, edit them, and store their locations. The next phase of my project is to allow the user to click on the side of a zone and create a boundary condition for it. A previous intern wrote a program that allows the user to input boundary conditions. I can integrate the two programs to create a larger, more usable program. After that, I will develop a way for the user to save the graph for future reference. Another eventual goal is to make the GUI capable of creating three-dimensional zones as well. Researchers such as my mentor, Dr. David Ashpis, need a quick, user-friendly

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

Basic instincts

NASA Astrophysics Data System (ADS)

Hutson, Matthew

2018-05-01

In their adaptability, young children demonstrate common sense, a kind of intelligence that, so far, computer scientists have struggled to reproduce. Gary Marcus, a developmental cognitive scientist at New York University in New York City, believes the field of artificial intelligence (AI) would do well to learn lessons from young thinkers. Researchers in machine learning argue that computers trained on mountains of data can learn just about anything—including common sense—with few, if any, programmed rules. But Marcus says computer scientists are ignoring decades of work in the cognitive sciences and developmental psychology showing that humans have innate abilities—programmed instincts that appear at birth or in early childhood—that help us think abstractly and flexibly. He believes AI researchers ought to include such instincts in their programs. Yet many computer scientists, riding high on the successes of machine learning, are eagerly exploring the limits of what a naïve AI can do. Computer scientists appreciate simplicity and have an aversion to debugging complex code. Furthermore, big companies such as Facebook and Google are pushing AI in this direction. These companies are most interested in narrowly defined, near-term problems, such as web search and facial recognition, in which blank-slate AI systems can be trained on vast data sets and work remarkably well. But in the longer term, computer scientists expect AIs to take on much tougher tasks that require flexibility and common sense. They want to create chatbots that explain the news, autonomous taxis that can handle chaotic city traffic, and robots that nurse the elderly. Some computer scientists are already trying. Such efforts, researchers hope, will result in AIs that sit somewhere between pure machine learning and pure instinct. They will boot up following some embedded rules, but will also learn as they go.

A Linux Workstation for High Performance Graphics

NASA Technical Reports Server (NTRS)

Geist, Robert; Westall, James

2000-01-01

The primary goal of this effort was to provide a low-cost method of obtaining high-performance 3-D graphics using an industry standard library (OpenGL) on PC class computers. Previously, users interested in doing substantial visualization or graphical manipulation were constrained to using specialized, custom hardware most often found in computers from Silicon Graphics (SGI). We provided an alternative to expensive SGI hardware by taking advantage of third-party, 3-D graphics accelerators that have now become available at very affordable prices. To make use of this hardware our goal was to provide a free, redistributable, and fully-compatible OpenGL work-alike library so that existing bodies of code could simply be recompiled. for PC class machines running a free version of Unix. This should allow substantial cost savings while greatly expanding the population of people with access to a serious graphics development and viewing environment. This should offer a means for NASA to provide a spectrum of graphics performance to its scientists, supplying high-end specialized SGI hardware for high-performance visualization while fulfilling the requirements of medium and lower performance applications with generic, off-the-shelf components and still maintaining compatibility between the two.

Understanding human visual systems and its impact on our intelligent instruments

NASA Astrophysics Data System (ADS)

Strojnik Scholl, Marija; Páez, Gonzalo; Scholl, Michelle K.

2013-09-01

We review the evolution of machine vision and comment on the cross-fertilization from the neural sciences onto flourishing fields of neural processing, parallel processing, and associative memory in optical sciences and computing. Then we examine how the intensive efforts in mapping the human brain have been influenced by concepts in computer sciences, control theory, and electronic circuits. We discuss two neural paths that employ the input from the vision sense to determine the navigational options and object recognition. They are ventral temporal pathway for object recognition (what?) and dorsal parietal pathway for navigation (where?), respectively. We describe the reflexive and conscious decision centers in cerebral cortex involved with visual attention and gaze control. Interestingly, these require return path though the midbrain for ocular muscle control. We find that the cognitive psychologists currently study human brain employing low-spatial-resolution fMRI with temporal response on the order of a second. In recent years, the life scientists have concentrated on insect brains to study neural processes. We discuss how reflexive and conscious gaze-control decisions are made in the frontal eye field and inferior parietal lobe, constituting the fronto-parietal attention network. We note that ethical and experiential learnings impact our conscious decisions.

Curve Boxplot: Generalization of Boxplot for Ensembles of Curves.

PubMed

Mirzargar, Mahsa; Whitaker, Ross T; Kirby, Robert M

2014-12-01

In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.

Pathview Web: user friendly pathway visualization and data integration.

PubMed

Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K; Blanchard, Steven G; Brouwer, Cory

2017-07-03

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Visualization and Interaction in Research, Teaching, and Scientific Communication

NASA Astrophysics Data System (ADS)

Ammon, C. J.

2017-12-01

Modern computing provides many tools for exploring observations, numerical calculations, and theoretical relationships. The number of options is, in fact, almost overwhelming. But the choices provide those with modest programming skills opportunities to create unique views of scientific information and to develop deeper insights into their data, their computations, and the underlying theoretical data-model relationships. I present simple examples of using animation and human-computer interaction to explore scientific data and scientific-analysis approaches. I illustrate how valuable a little programming ability can free scientists from the constraints of existing tools and can facilitate the development of deeper appreciation data and models. I present examples from a suite of programming languages ranging from C to JavaScript including the Wolfram Language. JavaScript is valuable for sharing tools and insight (hopefully) with others because it is integrated into one of the most powerful communication tools in human history, the web browser. Although too much of that power is often spent on distracting advertisements, the underlying computation and graphics engines are efficient, flexible, and almost universally available in desktop and mobile computing platforms. Many are working to fulfill the browser's potential to become the most effective tool for interactive study. Open-source frameworks for visualizing everything from algorithms to data are available, but advance rapidly. One strategy for dealing with swiftly changing tools is to adopt common, open data formats that are easily adapted (often by framework or tool developers). I illustrate the use of animation and interaction in research and teaching with examples from earthquake seismology.

Facilities | Computational Science | NREL

Science.gov Websites

technology innovation by providing scientists and engineers the ability to tackle energy challenges that scientists and engineers to take full advantage of advanced computing hardware and software resources

Preservice Teachers' Images of Scientists: Do Prior Science Experiences Make a Difference?

ERIC Educational Resources Information Center

Milford, Todd M.; Tippett, Christine D.

2013-01-01

This article presents the results of a mixed methods study that used the Draw-a-Scientist Test as a visual tool for exploring preservice teachers' beliefs about scientists. A questionnaire was also administered to 165 students who were enrolled in elementary (K-8) and secondary (8-12) science methods courses. Taken as a whole, the images drawn by…

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Analytical Judgment Using Visualizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

Scientists working in a particular domain often adhere to conventional data analysis and presentation methods and this leads to familiarity with these methods over time. But does high familiarity always lead to better analytical judgment? This question is especially relevant when visualizations are used in scientific tasks, as there can be discrepancies between visualization best practices and domain conventions. However, there is little empirical evidence of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their effect on scientific judgment. To address this gap and to study these factors, we focus on the climatemore » science domain, specifically on visualizations used for comparison of model performance. We present a comprehensive user study with 47 climate scientists where we explored the following factors: i) relationships between scientists’ familiarity, their perceived levels of com- fort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

2017-05-08

Scientists often use specific data analysis and presentation methods familiar within their domain. But does high familiarity drive better analytical judgment? This question is especially relevant when familiar methods themselves can have shortcomings: many visualizations used conventionally for scientific data analysis and presentation do not follow established best practices. This necessitates new methods that might be unfamiliar yet prove to be more effective. But there is little empirical understanding of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their visual analytic judgments. To address this gap and to study these factors, we focusmore » on visualizations used for comparison of climate model performance. We report on a comprehensive survey-based user study with 47 climate scientists and present an analysis of : i) relationships among scientists’ familiarity, their perceived lev- els of comfort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

An Analysis of Computer-Mediated Communication between Middle School Students and Scientist Role Models: A Pilot Study.

ERIC Educational Resources Information Center

Murfin, Brian

1994-01-01

Reports on a study of the effectiveness of computer-mediated communication (CMC) in providing African American and female middle school students with scientist role models. Quantitative and qualitative data gathered by analyzing messages students and scientists posted on a shared electronic bulletin board showed that CMC could be an effective…

Scout: high-performance heterogeneous computing made simple

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jablin, James; Mc Cormick, Patrick; Herlihy, Maurice

2011-01-26

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focusmore » on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.« less

Fast 3D Surface Extraction 2 pages (including abstract)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sewell, Christopher Meyer; Patchett, John M.; Ahrens, James P.

Ocean scientists searching for isosurfaces and/or thresholds of interest in high resolution 3D datasets required a tedious and time-consuming interactive exploration experience. PISTON research and development activities are enabling ocean scientists to rapidly and interactively explore isosurfaces and thresholds in their large data sets using a simple slider with real time calculation and visualization of these features. Ocean Scientists can now visualize more features in less time, helping them gain a better understanding of the high resolution data sets they work with on a daily basis. Isosurface timings (512{sup 3} grid): VTK 7.7 s, Parallel VTK (48-core) 1.3 s, PISTONmore » OpenMP (48-core) 0.2 s, PISTON CUDA (Quadro 6000) 0.1 s.« less

Visualizing the Big (and Large) Data from an HPC Resource

NASA Astrophysics Data System (ADS)

Sisneros, R.

2015-10-01

Supercomputers are built to endure painfully large simulations and contend with resulting outputs. These are characteristics that scientists are all too willing to test the limits of in their quest for science at scale. The data generated during a scientist's workflow through an HPC center (large data) is the primary target for analysis and visualization. However, the hardware itself is also capable of generating volumes of diagnostic data (big data); this presents compelling opportunities to deploy analogous analytic techniques. In this paper we will provide a survey of some of the many ways in which visualization and analysis may be crammed into the scientific workflow as well as utilized on machine-specific data.

Visual Representations of DNA Replication: Middle Grades Students' Perceptions and Interpretations

ERIC Educational Resources Information Center

Patrick, Michelle D.; Carter, Glenda; Wiebe, Eric N.

2005-01-01

Visual representations play a critical role in the communication of science concepts for scientists and students alike. However, recent research suggests that novice students experience difficulty extracting relevant information from representations. This study examined students' interpretations of visual representations of DNA replication. Each…

Interactive Visualization and Analysis of Geospatial Data Sets - TrikeND-iGlobe

NASA Astrophysics Data System (ADS)

Rosebrock, Uwe; Hogan, Patrick; Chandola, Varun

2013-04-01

The visualization of scientific datasets is becoming an ever-increasing challenge as advances in computing technologies have enabled scientists to build high resolution climate models that have produced petabytes of climate data. To interrogate and analyze these large datasets in real-time is a task that pushes the boundaries of computing hardware and software. But integration of climate datasets with geospatial data requires considerable amount of effort and close familiarity of various data formats and projection systems, which has prevented widespread utilization outside of climate community. TrikeND-iGlobe is a sophisticated software tool that bridges this gap, allows easy integration of climate datasets with geospatial datasets and provides sophisticated visualization and analysis capabilities. The objective for TrikeND-iGlobe is the continued building of an open source 4D virtual globe application using NASA World Wind technology that integrates analysis of climate model outputs with remote sensing observations as well as demographic and environmental data sets. This will facilitate a better understanding of global and regional phenomenon, and the impact analysis of climate extreme events. The critical aim is real-time interactive interrogation. At the data centric level the primary aim is to enable the user to interact with the data in real-time for the purpose of analysis - locally or remotely. TrikeND-iGlobe provides the basis for the incorporation of modular tools that provide extended interactions with the data, including sub-setting, aggregation, re-shaping, time series analysis methods and animation to produce publication-quality imagery. TrikeND-iGlobe may be run locally or can be accessed via a web interface supported by high-performance visualization compute nodes placed close to the data. It supports visualizing heterogeneous data formats: traditional geospatial datasets along with scientific data sets with geographic coordinates (NetCDF, HDF, etc.). It also supports multiple data access mechanisms, including HTTP, FTP, WMS, WCS, and Thredds Data Server (for NetCDF data and for scientific data, TrikeND-iGlobe supports various visualization capabilities, including animations, vector field visualization, etc. TrikeND-iGlobe is a collaborative open-source project, contributors include NASA (ARC-PX), ORNL (Oakridge National Laboratories), Unidata, Kansas University, CSIRO CMAR Australia and Geoscience Australia.

Planetary Surface Visualization and Analytics

NASA Astrophysics Data System (ADS)

Law, E. S.; Solar System Treks Team

2018-04-01

An introduction and update of the Solar System Treks Project which provides a suite of interactive visualization and analysis tools to enable users (engineers, scientists, public) to access large amounts of mapped planetary data products.

Earth Science Datacasting v2.0

NASA Technical Reports Server (NTRS)

Bingham, Andrew W.; Deen, Robert G.; Hussey, Kevin J.; Stough, Timothy M.; McCleese, Sean W.; Toole, Nicholas T.

2012-01-01

The Datacasting software, which consists of a server and a client, has been developed as part of the Earth Science (ES) Datacasting project. The goal of ES Datacasting is to provide scientists the ability to automatically and continuously download Earth science data that meets a precise, predefined need, and then to instantaneously visualize it on a local computer. This is achieved by applying the concept of podcasting to deliver science data over the Internet using RSS (Really Simple Syndication) XML feeds. By extending the RSS specification, scientists can filter a feed and only download the files that are required for a particular application (for example, only files that contain information about a particular event, such as a hurricane or flood). The extension also provides the ability for the client to understand the format of the data and visualize the information locally. The server part enables a data provider to create and serve basic Datacasting (RSS-based) feeds. The user can subscribe to any number of feeds, view the information related to each item contained within a feed (including browse pre-made images), manually download files associated with items, and place these files in a local store. The client-server architecture enables users to: a) Subscribe and interpret multiple Datacasting feeds (same look and feel as a typical mail client), b) Maintain a list of all items within each feed, c) Enable filtering on the lists based on different metadata attributes contained within the feed (list will reference only data files of interest), d) Visualize the reference data and associated metadata, e) Download files referenced within the list, and f) Automatically download files as new items become available.

Using Interactive Visualization to Analyze Solid Earth Data and Geodynamics Models

NASA Astrophysics Data System (ADS)

Kellogg, L. H.; Kreylos, O.; Billen, M. I.; Hamann, B.; Jadamec, M. A.; Rundle, J. B.; van Aalsburg, J.; Yikilmaz, M. B.

2008-12-01

The geological sciences are challenged to manage and interpret increasing volumes of data as observations and simulations increase in size and complexity. Major projects such as EarthScope and GeoEarthScope are producing the data needed to characterize the structure and kinematics of Earth's surface and interior at unprecedented resolution. At the same time, high-performance computing enables high-precision and fine- detail simulation of geodynamics processes, complementing the observational data. To facilitate interpretation and analysis of these datasets, to evaluate models, and to drive future calculations, we have developed methods of interactive visualization with a special focus on using immersive virtual reality (VR) environments to interact with models of Earth's surface and interior. VR has traditionally been used primarily as a presentation tool allowing active navigation through data. Reaping the full intellectual benefits of immersive VR as a tool for accelerated scientific analysis requires building on the method's strengths, that is, using both 3D perception and interaction with observed or simulated data. Our approach to VR takes advantage of the specialized skills of geoscientists who are trained to interpret geological and geophysical data generated from field observations. Interactive tools allow the scientist to explore and interpret geodynamic models, tomographic models, and topographic observations, while feature extraction tools support quantitative measurement of structures that emerge from numerical simulations or field observations. The use of VR technology enables us to improve our interpretation of crust and mantle structure and of geodynamical processes. Mapping tools based on computer visualization allow virtual "field studies" in inaccessible regions, and an interactive tool allows us to construct digital fault models for use in numerical models. Using the interactive tools on a high-end platform such as an immersive virtual reality room known as a Cave Automatic Virtual Environment (CAVE), enables the scientist to stand in data three-dimensional dataset while taking measurements. The CAVE involves three or more projection surfaces arranged as walls in a room. Stereo projectors combined with a motion tracking system and immersion recreates the experience of carrying out research in the field. This high-end system provides significant advantages for scientists working with complex volumetric data. The interactive tools also work on low-cost platforms that provide stereo views and the potential for interactivity such as a Geowall or a 3D enabled TV. The Geowall is also a well-established tool for education, and in combination with the tools we have developed, enables the rapid transfer of research data and new knowledge to the classroom. The interactive visualization tools can also be used on a desktop or laptop with or without stereo capability. Further information about the Virtual Reality User Interface (VRUI), the 3DVisualizer, the Virtual mapping tools, and the LIDAR viewer, can be found on the KeckCAVES website, www.keckcaves.org.

From Both Sides, Now: Librarians Team up with Computer Scientist to Deliver Virtual Computer-Information Literacy Instruction

ERIC Educational Resources Information Center

Loesch, Martha Fallahay

2011-01-01

Two members of the library faculty at Seton Hall University teamed up with a respected professor of mathematics and computer science, in order to create an online course that introduces information literacy both from the perspectives of the computer scientist and from the instruction librarian. This collaboration is unique in that it addresses the…

The Climate-G testbed: towards a large scale data sharing environment for climate change

NASA Astrophysics Data System (ADS)

Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

2009-04-01

The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for data visualization; metadata search/discovery across several countries/institutions; open environment for climate change data sharing.

Visualizing the Heliosphere

NASA Technical Reports Server (NTRS)

Bridgman, William T.; Shirah, Greg W.; Mitchell, Horace G.

2008-01-01

Today, scientific data and models can combine with modern animation tools to produce compelling visualizations to inform and educate. The Scientific Visualization Studio at Goddard Space Flight Center merges these techniques from the very different worlds of entertainment and science to enable scientists and the general public to 'see the unseeable' in new ways.

Impact of the Columbia Supercomputer on NASA Space and Exploration Mission

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Kwak, Dochan; Kiris, Cetin; Lawrence, Scott

2006-01-01

NASA's 10,240-processor Columbia supercomputer gained worldwide recognition in 2004 for increasing the space agency's computing capability ten-fold, and enabling U.S. scientists and engineers to perform significant, breakthrough simulations. Columbia has amply demonstrated its capability to accelerate NASA's key missions, including space operations, exploration systems, science, and aeronautics. Columbia is part of an integrated high-end computing (HEC) environment comprised of massive storage and archive systems, high-speed networking, high-fidelity modeling and simulation tools, application performance optimization, and advanced data analysis and visualization. In this paper, we illustrate the impact Columbia is having on NASA's numerous space and exploration applications, such as the development of the Crew Exploration and Launch Vehicles (CEV/CLV), effects of long-duration human presence in space, and damage assessment and repair recommendations for remaining shuttle flights. We conclude by discussing HEC challenges that must be overcome to solve space-related science problems in the future.

Gravity Behaves Like That?

NASA Astrophysics Data System (ADS)

Pazmino, John

2007-02-01

Many concepts of chaotic action in astrodynamics can be appreciated through simulations with home computers and software. Many astrodynamical cases are illustrated. Although chaos theory is now applied to spaceflight trajectories, this presentation employs only inert bodies with no onboard impulse, e.g., from rockets or outgassing. Other nongravitational effects are also ignored, such as atmosphere drag, solar pressure, and radiation. The ability to simulate gravity behavior, even if not completely rigorous, on small mass-market computers allows a fuller understanding of the new approach to astrodynamics by home astronomers, scientists outside orbital mechanics, and students in middle and high school. The simulations can also help a lay audience visualize gravity behavior during press conferences, briefings, and public lectures. No review, evaluation, critique of the programs shown in this presentation is intended. The results from these simulations are not valid for - and must not be used for - making earth-colliding predictions.

USRA/RIACS

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1992-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under a cooperative agreement with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing; Advanced Methods for Scientific Computing; Learning Systems; High Performance Networks and Technology; Graphics, Visualization, and Virtual Environments.

Designing for Broad Understanding of Science.

PubMed

Hristov, Nickolay; Strohecker, Carol; Allen, Louise; Merson, Martha

2018-06-04

With the acceleration and increasing complexity of macro-scale problems such as climate change, the need for scientists to ensure that their work is understood has become urgent. As citizens and recipients of public funds for research, scientists have an obligation to communicate their findings in ways many people can understand. However, developing translations that are broadly accessible without being "dumbed down" can be challenging. Fortunately, tenets of visual literacy, combined with narrative methods, can help to convey scientific knowledge with fidelity, while sustaining viewers' interest. Here we outline strategies for such translating, with an emphasis on visual approaches. Among the examples is an innovative, NSF-funded professional development initiative in which National Park rangers use scientists' imagery to create compelling explanations for the visiting public. Thoughtful visualizations based on interpretive images, motion pictures, 3D animations and augmented, immersive experiences complement the impact of the natural resource and enhance the role of the park ranger. The visualizations become scaffolds for participatory exchanges in which the ranger transcends the traditional roles of information-holder and presenter, to facilitate provocative conversations that provide members of the public with enjoyable experiences and well-founded bases for reflection and ultimately understanding. The process of generating the supporting visualizations benefits from partnerships with design professionals, who develop opportunities for engaging the public by translating important scientific findings and messages in compelling and memorable ways.

Predicting protein structures with a multiplayer online game.

PubMed

Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran; Players, Foldit

2010-08-05

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

Enabling drug discovery project decisions with integrated computational chemistry and informatics

NASA Astrophysics Data System (ADS)

Tsui, Vickie; Ortwine, Daniel F.; Blaney, Jeffrey M.

2017-03-01

Computational chemistry/informatics scientists and software engineers in Genentech Small Molecule Drug Discovery collaborate with experimental scientists in a therapeutic project-centric environment. Our mission is to enable and improve pre-clinical drug discovery design and decisions. Our goal is to deliver timely data, analysis, and modeling to our therapeutic project teams using best-in-class software tools. We describe our strategy, the organization of our group, and our approaches to reach this goal. We conclude with a summary of the interdisciplinary skills required for computational scientists and recommendations for their training.

Preface: SciDAC 2005

NASA Astrophysics Data System (ADS)

Mezzacappa, Anthony

2005-01-01

On 26-30 June 2005 at the Grand Hyatt on Union Square in San Francisco several hundred computational scientists from around the world came together for what can certainly be described as a celebration of computational science. Scientists from the SciDAC Program and scientists from other agencies and nations were joined by applied mathematicians and computer scientists to highlight the many successes in the past year where computation has led to scientific discovery in a variety of fields: lattice quantum chromodynamics, accelerator modeling, chemistry, biology, materials science, Earth and climate science, astrophysics, and combustion and fusion energy science. Also highlighted were the advances in numerical methods and computer science, and the multidisciplinary collaboration cutting across science, mathematics, and computer science that enabled these discoveries. The SciDAC Program was conceived and funded by the US Department of Energy Office of Science. It is the Office of Science's premier computational science program founded on what is arguably the perfect formula: the priority and focus is science and scientific discovery, with the understanding that the full arsenal of `enabling technologies' in applied mathematics and computer science must be brought to bear if we are to have any hope of attacking and ultimately solving today's computational Grand Challenge problems. The SciDAC Program has been in existence for four years, and many of the computational scientists funded by this program will tell you that the program has given them the hope of addressing their scientific problems in full realism for the very first time. Many of these scientists will also tell you that SciDAC has also fundamentally changed the way they do computational science. We begin this volume with one of DOE's great traditions, and core missions: energy research. As we will see, computation has been seminal to the critical advances that have been made in this arena. Of course, to understand our world, whether it is to understand its very nature or to understand it so as to control it for practical application, will require explorations on all of its scales. Computational science has been no less an important tool in this arena than it has been in the arena of energy research. From explorations of quantum chromodynamics, the fundamental theory that describes how quarks make up the protons and neutrons of which we are composed, to explorations of the complex biomolecules that are the building blocks of life, to explorations of some of the most violent phenomena in our universe and of the Universe itself, computation has provided not only significant insight, but often the only means by which we have been able to explore these complex, multicomponent systems and by which we have been able to achieve scientific discovery and understanding. While our ultimate target remains scientific discovery, it certainly can be said that at a fundamental level the world is mathematical. Equations ultimately govern the evolution of the systems of interest to us, be they physical, chemical, or biological systems. The development and choice of discretizations of these underlying equations is often a critical deciding factor in whether or not one is able to model such systems stably, faithfully, and practically, and in turn, the algorithms to solve the resultant discrete equations are the complementary, critical ingredient in the recipe to model the natural world. The use of parallel computing platforms, especially at the TeraScale, and the trend toward even larger numbers of processors, continue to present significant challenges in the development and implementation of these algorithms. Computational scientists often speak of their `workflows'. A workflow, as the name suggests, is the sum total of all complex and interlocking tasks, from simulation set up, execution, and I/O, to visualization and scientific discovery, through which the advancement in our understanding of the natural world is realized. For the computational scientist, enabling such workflows presents myriad, signiflcant challenges, and it is computer scientists that are called upon at such times to address these challenges. Simulations are currently generating data at the staggering rate of tens of TeraBytes per simulation, over the course of days. In the next few years, these data generation rates are expected to climb exponentially to hundreds of TeraBytes per simulation, performed over the course of months. The output, management, movement, analysis, and visualization of these data will be our key to unlocking the scientific discoveries buried within the data. And there is no hope of generating such data to begin with, or of scientific discovery, without stable computing platforms and a sufficiently high and sustained performance of scientific applications codes on them. Thus, scientific discovery in the realm of computational science at the TeraScale and beyond will occur at the intersection of science, applied mathematics, and computer science. The SciDAC Program was constructed to mirror this reality, and the pages that follow are a testament to the efficacy of such an approach. We would like to acknowledge the individuals on whose talents and efforts the success of SciDAC 2005 was based. Special thanks go to Betsy Riley for her work on the SciDAC 2005 Web site and meeting agenda, for lining up our corporate sponsors, for coordinating all media communications, and for her efforts in processing the proceedings contributions, to Sherry Hempfling for coordinating the overall SciDAC 2005 meeting planning, for handling a significant share of its associated communications, and for coordinating with the ORNL Conference Center and Grand Hyatt, to Angela Harris for producing many of the documents and records on which our meeting planning was based and for her efforts in coordinating with ORNL Graphics Services, to Angie Beach of the ORNL Conference Center for her efforts in procurement and setting up and executing the contracts with the hotel, and to John Bui and John Smith for their superb wireless networking and A/V set up and support. We are grateful for the relentless efforts of all of these individuals, their remarkable talents, and for the joy of working with them during this past year. They were the cornerstones of SciDAC 2005. Thanks also go to Kymba A'Hearn and Patty Boyd for on-site registration, Brittany Hagen for administrative support, Bruce Johnston for netcast support, Tim Jones for help with the proceedings and Web site, Sherry Lamb for housing and registration, Cindy Lathum for Web site design, Carolyn Peters for on-site registration, and Dami Rich for graphic design. And we would like to express our appreciation to the Oak Ridge National Laboratory, especially Jeff Nichols, the Argonne National Laboratory, the Lawrence Berkeley National Laboratory, and to our corporate sponsors, Cray, IBM, Intel, and SGI, for their support. We would like to extend special thanks also to our plenary speakers, technical speakers, poster presenters, and panelists for all of their efforts on behalf of SciDAC 2005 and for their remarkable achievements and contributions. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas and Margaret Smith of Institute of Physics Publishing, who worked tirelessly in order to provide us with this finished volume within two months, which is nothing short of miraculous. Finally, we wish to express our heartfelt thanks to Michael Strayer, SciDAC Director, whose vision it was to focus SciDAC 2005 on scientific discovery, around which all of the excitement we experienced revolved, and to our DOE SciDAC program managers, especially Fred Johnson, for their support, input, and help throughout.

Multi-Spacecraft Analysis with Generic Visualization Tools

NASA Astrophysics Data System (ADS)

Mukherjee, J.; Vela, L.; Gonzalez, C.; Jeffers, S.

2010-12-01

To handle the needs of scientists today and in the future, software tools are going to have to take better advantage of the currently available hardware. Specifically, computing power, memory, and disk space have become cheaper, while bandwidth has become more expensive due to the explosion of online applications. To overcome these limitations, we have enhanced our Southwest Data Display and Analysis System (SDDAS) to take better advantage of the hardware by utilizing threads and data caching. Furthermore, the system was enhanced to support a framework for adding data formats and data visualization methods without costly rewrites. Visualization tools can speed analysis of many common scientific tasks and we will present a suite of tools that encompass the entire process of retrieving data from multiple data stores to common visualizations of the data. The goals for the end user are ease of use and interactivity with the data and the resulting plots. The data can be simultaneously plotted in a variety of formats and/or time and spatial resolutions. The software will allow one to slice and separate data to achieve other visualizations. Furthermore, one can interact with the data using the GUI or through an embedded language based on the Lua scripting language. The data presented will be primarily from the Cluster and Mars Express missions; however, the tools are data type agnostic and can be used for virtually any type of data.

Parallel Density-Based Clustering for Discovery of Ionospheric Phenomena

NASA Astrophysics Data System (ADS)

Pankratius, V.; Gowanlock, M.; Blair, D. M.

2015-12-01

Ionospheric total electron content maps derived from global networks of dual-frequency GPS receivers can reveal a plethora of ionospheric features in real-time and are key to space weather studies and natural hazard monitoring. However, growing data volumes from expanding sensor networks are making manual exploratory studies challenging. As the community is heading towards Big Data ionospheric science, automation and Computer-Aided Discovery become indispensable tools for scientists. One problem of machine learning methods is that they require domain-specific adaptations in order to be effective and useful for scientists. Addressing this problem, our Computer-Aided Discovery approach allows scientists to express various physical models as well as perturbation ranges for parameters. The search space is explored through an automated system and parallel processing of batched workloads, which finds corresponding matches and similarities in empirical data. We discuss density-based clustering as a particular method we employ in this process. Specifically, we adapt Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This algorithm groups geospatial data points based on density. Clusters of points can be of arbitrary shape, and the number of clusters is not predetermined by the algorithm; only two input parameters need to be specified: (1) a distance threshold, (2) a minimum number of points within that threshold. We discuss an implementation of DBSCAN for batched workloads that is amenable to parallelization on manycore architectures such as Intel's Xeon Phi accelerator with 60+ general-purpose cores. This manycore parallelization can cluster large volumes of ionospheric total electronic content data quickly. Potential applications for cluster detection include the visualization, tracing, and examination of traveling ionospheric disturbances or other propagating phenomena. Acknowledgments. We acknowledge support from NSF ACI-1442997 (PI V. Pankratius).

Advancements to Visualization Control System (VCS, part of UV-CDAT), a Visualization Package Designed for Climate Scientists

NASA Astrophysics Data System (ADS)

Lipsa, D.; Chaudhary, A.; Williams, D. N.; Doutriaux, C.; Jhaveri, S.

2017-12-01

Climate Data Analysis Tools (UV-CDAT, https://uvcdat.llnl.gov) is a data analysis and visualization software package developed at Lawrence Livermore National Laboratory and designed for climate scientists. Core components of UV-CDAT include: 1) Community Data Management System (CDMS) which provides I/O support and a data model for climate data;2) CDAT Utilities (GenUtil) that processes data using spatial and temporal averaging and statistic functions; and 3) Visualization Control System (VCS) for interactive visualization of the data. VCS is a Python visualization package primarily built for climate scientists, however, because of its generality and breadth of functionality, it can be a useful tool to other scientific applications. VCS provides 1D, 2D and 3D visualization functions such as scatter plot and line graphs for 1d data, boxfill, meshfill, isofill, isoline for 2d scalar data, vector glyphs and streamlines for 2d vector data and 3d_scalar and 3d_vector for 3d data. Specifically for climate data our plotting routines include projections, Skew-T plots and Taylor diagrams. While VCS provided a user-friendly API, the previous implementation of VCS relied on slow performing vector graphics (Cairo) backend which is suitable for smaller dataset and non-interactive graphics. LLNL and Kitware team has added a new backend to VCS that uses the Visualization Toolkit (VTK) as its visualization backend. VTK is one of the most popular open source, multi-platform scientific visualization library written in C++. Its use of OpenGL and pipeline processing architecture results in a high performant VCS library. Its multitude of available data formats and visualization algorithms results in easy adoption of new visualization methods and new data formats in VCS. In this presentation, we describe recent contributions to VCS that includes new visualization plots, continuous integration testing using Conda and CircleCI, tutorials and examples using Jupyter notebooks as well as upgrades that we are planning in the near future which will improve its ease of use and reliability and extend its capabilities.

What can scientific practice look like in a classroom? Insights from scientists' critique of high school students' climate change argumentation practice

NASA Astrophysics Data System (ADS)

Walsh, E.; McGowan, V. C.

2015-12-01

The Next Generation Science Standards promote a vision in which learners engage in authentic knowledge in practice to tackle personally consequential science problems in the classroom. However, there is not yet a clear understanding amongst researchers and educators of what authentic practice looks like in a classroom and how this can be accomplished. This study explores these questions by examining interactions between scientists and students on a social media platform during two pilot enactments of a project-based curriculum focusing on the ecological impacts of climate change. During this unit, scientists provided feedback to students on infographics, visual representations of scientific information meant to communicate to an audience about climate change. We conceptualize the feedback and student work as boundary objects co-created by students and scientists moving between the school and scientific contexts, and analyze the structure and content of the scientists' feedback. We find that when giving feedback on a particular practice (e.g. argumentation), scientists would provide avenues, critiques and questions that incorporated many other practices (e.g. data analysis, visual communication); thus, scientists encouraged students to participate systemically in practices instead of isolating one particular practice. In addition, scientists drew attention to particular habits of mind that are valued in the scientific community and noted when students' work aligned with scientific values. In this way, scientists positioned students as capable of participating "scientifically." While traditionally, incorporating scientific inquiry in a classroom has emphasized student experimentation and data generation, in this work, we found that engaging with scientists around established scientific texts and data sets provided students with a platform for developing expertise in other important scientific practices during argment construction.

Oceans of Data: In what ways can learning research inform the development of electronic interfaces and tools for use by students accessing large scientific databases?

NASA Astrophysics Data System (ADS)

Krumhansl, R. A.; Foster, J.; Peach, C. L.; Busey, A.; Baker, I.

2012-12-01

The practice of science and engineering is being revolutionized by the development of cyberinfrastructure for accessing near real-time and archived observatory data. Large cyberinfrastructure projects have the potential to transform the way science is taught in high school classrooms, making enormous quantities of scientific data available, giving students opportunities to analyze and draw conclusions from many kinds of complex data, and providing students with experiences using state-of-the-art resources and techniques for scientific investigations. However, online interfaces to scientific data are built by scientists for scientists, and their design can significantly impede broad use by novices. Knowledge relevant to the design of student interfaces to complex scientific databases is broadly dispersed among disciplines ranging from cognitive science to computer science and cartography and is not easily accessible to designers of educational interfaces. To inform efforts at bridging scientific cyberinfrastructure to the high school classroom, Education Development Center, Inc. and the Scripps Institution of Oceanography conducted an NSF-funded 2-year interdisciplinary review of literature and expert opinion pertinent to making interfaces to large scientific databases accessible to and usable by precollege learners and their teachers. Project findings are grounded in the fundamentals of Cognitive Load Theory, Visual Perception, Schemata formation and Universal Design for Learning. The Knowledge Status Report (KSR) presents cross-cutting and visualization-specific guidelines that highlight how interface design features can address/ ameliorate challenges novice high school students face as they navigate complex databases to find data, and construct and look for patterns in maps, graphs, animations and other data visualizations. The guidelines present ways to make scientific databases more broadly accessible by: 1) adjusting the cognitive load imposed by the user interface and visualizations so that it doesn't exceed the amount of information the learner can actively process; 2) drawing attention to important features and patterns; and 3) enabling customization of visualizations and tools to meet the needs of diverse learners.

Immersive Visual Analytics for Transformative Neutron Scattering Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steed, Chad A; Daniel, Jamison R; Drouhard, Margaret

The ORNL Spallation Neutron Source (SNS) provides the most intense pulsed neutron beams in the world for scientific research and development across a broad range of disciplines. SNS experiments produce large volumes of complex data that are analyzed by scientists with varying degrees of experience using 3D visualization and analysis systems. However, it is notoriously difficult to achieve proficiency with 3D visualizations. Because 3D representations are key to understanding the neutron scattering data, scientists are unable to analyze their data in a timely fashion resulting in inefficient use of the limited and expensive SNS beam time. We believe a moremore » intuitive interface for exploring neutron scattering data can be created by combining immersive virtual reality technology with high performance data analytics and human interaction. In this paper, we present our initial investigations of immersive visualization concepts as well as our vision for an immersive visual analytics framework that could lower the barriers to 3D exploratory data analysis of neutron scattering data at the SNS.« less

Invariant visual object recognition and shape processing in rats

PubMed Central

Zoccolan, Davide

2015-01-01

Invariant visual object recognition is the ability to recognize visual objects despite the vastly different images that each object can project onto the retina during natural vision, depending on its position and size within the visual field, its orientation relative to the viewer, etc. Achieving invariant recognition represents such a formidable computational challenge that is often assumed to be a unique hallmark of primate vision. Historically, this has limited the invasive investigation of its neuronal underpinnings to monkey studies, in spite of the narrow range of experimental approaches that these animal models allow. Meanwhile, rodents have been largely neglected as models of object vision, because of the widespread belief that they are incapable of advanced visual processing. However, the powerful array of experimental tools that have been developed to dissect neuronal circuits in rodents has made these species very attractive to vision scientists too, promoting a new tide of studies that have started to systematically explore visual functions in rats and mice. Rats, in particular, have been the subjects of several behavioral studies, aimed at assessing how advanced object recognition and shape processing is in this species. Here, I review these recent investigations, as well as earlier studies of rat pattern vision, to provide an historical overview and a critical summary of the status of the knowledge about rat object vision. The picture emerging from this survey is very encouraging with regard to the possibility of using rats as complementary models to monkeys in the study of higher-level vision. PMID:25561421

Provenance-Powered Automatic Workflow Generation and Composition

NASA Astrophysics Data System (ADS)

Zhang, J.; Lee, S.; Pan, L.; Lee, T. J.

2015-12-01

In recent years, scientists have learned how to codify tools into reusable software modules that can be chained into multi-step executable workflows. Existing scientific workflow tools, created by computer scientists, require domain scientists to meticulously design their multi-step experiments before analyzing data. However, this is oftentimes contradictory to a domain scientist's daily routine of conducting research and exploration. We hope to resolve this dispute. Imagine this: An Earth scientist starts her day applying NASA Jet Propulsion Laboratory (JPL) published climate data processing algorithms over ARGO deep ocean temperature and AMSRE sea surface temperature datasets. Throughout the day, she tunes the algorithm parameters to study various aspects of the data. Suddenly, she notices some interesting results. She then turns to a computer scientist and asks, "can you reproduce my results?" By tracking and reverse engineering her activities, the computer scientist creates a workflow. The Earth scientist can now rerun the workflow to validate her findings, modify the workflow to discover further variations, or publish the workflow to share the knowledge. In this way, we aim to revolutionize computer-supported Earth science. We have developed a prototyping system to realize the aforementioned vision, in the context of service-oriented science. We have studied how Earth scientists conduct service-oriented data analytics research in their daily work, developed a provenance model to record their activities, and developed a technology to automatically generate workflow starting from user behavior and adaptability and reuse of these workflows for replicating/improving scientific studies. A data-centric repository infrastructure is established to catch richer provenance to further facilitate collaboration in the science community. We have also established a Petri nets-based verification instrument for provenance-based automatic workflow generation and recommendation.

Types of Creativity and Visualization in Teams of Different Educational Specialization

ERIC Educational Resources Information Center

Blazhenkova, Olesya; Kozhevnikov, Maria

2016-01-01

This research is the first to examine different types of creativity dimensions in relation to different types of visualization on a team level, by comparing adolescences' teams of different specialization (visual artist, scientists, and humanities) during a complex creative task in an ecologically valid educational setting First, the difference…

Accommodating Scientific Illiteracy: Award-Winning Visualizations on the Covers of "Science"

ERIC Educational Resources Information Center

Gigante, Maria E.

2012-01-01

The International Science and Engineering Visualization Challenge, recently established by the National Science Foundation (NSF), is an alleged attempt at public outreach. The NSF encourages scientists to submit visualizations that would appeal to non-expert audiences by displaying their work in an annual "special feature" in "Science" magazine,…

VIPER: Virtual Intelligent Planetary Exploration Rover

NASA Technical Reports Server (NTRS)

Edwards, Laurence; Flueckiger, Lorenzo; Nguyen, Laurent; Washington, Richard

2001-01-01

Simulation and visualization of rover behavior are critical capabilities for scientists and rover operators to construct, test, and validate plans for commanding a remote rover. The VIPER system links these capabilities. using a high-fidelity virtual-reality (VR) environment. a kinematically accurate simulator, and a flexible plan executive to allow users to simulate and visualize possible execution outcomes of a plan under development. This work is part of a larger vision of a science-centered rover control environment, where a scientist may inspect and explore the environment via VR tools, specify science goals, and visualize the expected and actual behavior of the remote rover. The VIPER system is constructed from three generic systems, linked together via a minimal amount of customization into the integrated system. The complete system points out the power of combining plan execution, simulation, and visualization for envisioning rover behavior; it also demonstrates the utility of developing generic technologies. which can be combined in novel and useful ways.

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

NASA Technical Reports Server (NTRS)

Brugel, Edward W.; Domik, Gitta O.; Ayres, Thomas R.

1993-01-01

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis

PubMed Central

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. Availability http://www.cemb.edu.pk/sw.html Abbreviations RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language. PMID:23055611

AstroDance: Teaching Astrophysics Through Dance?

NASA Astrophysics Data System (ADS)

Noel-Storr, Jacob; Campanelli, M.; Bochner, J.; Warfield, T.; Bischof, H.; Zlochower, Y.; Nordhaus, J.; Watkins, G.; NSF CRPA AstroDance Team

2014-01-01

Through a collaboration involving scientists, artists and educators, members of the Center for Computational Relativity and Gravitation and the National Technical Institute for the Deaf at the Rochester Institute of Technology we developed a unique project for Communicating Research to Public Audiences. The project used dance and multi-media theater techniques to expose a broad audience, about half of which is comprised of deaf and hard-of-hearing individuals, to an aesthetic, educational performance representing the concepts of gravitational physics in astrophysical settings. Since deaf and hard-of-hearing people rely heavily on visual communication for learning and gaining access to information, dance and multi-media theater provide a kinesthetic and visual experience that is fully accessible to them, as well as hearing audience members, and help facilitate their learning and development of non-linguistic representations of concepts. Here we present the results of our research into the learning outcomes for the diverse audiences of this project in terms of both knowledge and attitudes towards science.

High-resolution digital brain atlases: a Hubble telescope for the brain.

PubMed

Jones, Edward G; Stone, James M; Karten, Harvey J

2011-05-01

We describe implementation of a method for digitizing at microscopic resolution brain tissue sections containing normal and experimental data and for making the content readily accessible online. Web-accessible brain atlases and virtual microscopes for online examination can be developed using existing computer and internet technologies. Resulting databases, made up of hierarchically organized, multiresolution images, enable rapid, seamless navigation through the vast image datasets generated by high-resolution scanning. Tools for visualization and annotation of virtual microscope slides enable remote and universal data sharing. Interactive visualization of a complete series of brain sections digitized at subneuronal levels of resolution offers fine grain and large-scale localization and quantification of many aspects of neural organization and structure. The method is straightforward and replicable; it can increase accessibility and facilitate sharing of neuroanatomical data. It provides an opportunity for capturing and preserving irreplaceable, archival neurohistological collections and making them available to all scientists in perpetuity, if resources could be obtained from hitherto uninterested agencies of scientific support. © 2011 New York Academy of Sciences.

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways.

PubMed

Beltrame, Luca; Calura, Enrica; Popovici, Razvan R; Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-08-01

Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and 'wet lab' scientists. The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X.

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter.

PubMed

Schmitt, Marco; Jäschke, Robert

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists' style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science.

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science

PubMed Central

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-01-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, “Interdisciplinary Insights into Group and Team Dynamics,” which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges. PMID:29249891

Human computers: the first pioneers of the information age.

PubMed

Grier, D A

2001-03-01

Before computers were machines, they were people. They were men and women, young and old, well educated and common. They were the workers who convinced scientists that large-scale calculation had value. Long before Presper Eckert and John Mauchly built the ENIAC at the Moore School of Electronics, Philadelphia, or Maurice Wilkes designed the EDSAC for Manchester University, human computers had created the discipline of computation. They developed numerical methodologies and proved them on practical problems. These human computers were not savants or calculating geniuses. Some knew little more than basic arithmetic. A few were near equals of the scientists they served and, in a different time or place, might have become practicing scientists had they not been barred from a scientific career by their class, education, gender or ethnicity.

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science.

PubMed

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-10-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, "Interdisciplinary Insights into Group and Team Dynamics," which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges.

Visualization and Quality Control Web Tools for CERES Products

NASA Astrophysics Data System (ADS)

Mitrescu, C.; Doelling, D. R.

2017-12-01

The NASA CERES project continues to provide the scientific communities a wide variety of satellite-derived data products such as observed TOA broadband shortwave and longwave observed fluxes, computed TOA and Surface fluxes, as well as cloud, aerosol, and other atmospheric parameters. They encompass a wide range of temporal and spatial resolutions, suited to specific applications. CERES data is used mostly by climate modeling communities but also by a wide variety of educational institutions. To better serve our users, a web-based Ordering and Visualization Tool (OVT) was developed by using Opens Source Software such as Eclipse, java, javascript, OpenLayer, Flot, Google Maps, python, and others. Due to increased demand by our own scientists, we also implemented a series of specialized functions to be used in the process of CERES Data Quality Control (QC) such as 1- and 2-D histograms, anomalies and differences, temporal and spatial averaging, side-by-side parameter comparison, and others that made the process of QC far easier and faster, but more importantly far more portable. With the integration of ground site observed surface fluxes we further facilitate the CERES project to QC the CERES computed surface fluxes. An overview of the CERES OVT basic functions using Open Source Software, as well as future steps in expanding its capabilities will be presented at the meeting.

SOURCE EXPLORER: Towards Web Browser Based Tools for Astronomical Source Visualization and Analysis

NASA Astrophysics Data System (ADS)

Young, M. D.; Hayashi, S.; Gopu, A.

2014-05-01

As a new generation of large format, high-resolution imagers come online (ODI, DECAM, LSST, etc.) we are faced with the daunting prospect of astronomical images containing upwards of hundreds of thousands of identifiable sources. Visualizing and interacting with such large datasets using traditional astronomical tools appears to be unfeasible, and a new approach is required. We present here a method for the display and analysis of arbitrarily large source datasets using dynamically scaling levels of detail, enabling scientists to rapidly move from large-scale spatial overviews down to the level of individual sources and everything in-between. Based on the recognized standards of HTML5+JavaScript, we enable observers and archival users to interact with their images and sources from any modern computer without having to install specialized software. We demonstrate the ability to produce large-scale source lists from the images themselves, as well as overlaying data from publicly available source ( 2MASS, GALEX, SDSS, etc.) or user provided source lists. A high-availability cluster of computational nodes allows us to produce these source maps on demand and customized based on user input. User-generated source lists and maps are persistent across sessions and are available for further plotting, analysis, refinement, and culling.

Building place-based collaborations to develop high school students' groundwater systems knowledge and decision-making capacity

NASA Astrophysics Data System (ADS)

Podrasky, A.; Covitt, B. A.; Woessner, W.

2017-12-01

The availability of clean water to support human uses and ecological integrity has become an urgent interest for many scientists, decision makers and citizens. Likewise, as computational capabilities increasingly revolutionize and become integral to the practice of science, technology, engineering and math (STEM) disciplines, the STEM+ Computing (STEM+C) Partnerships program seeks to integrate the use of computational approaches in K-12 STEM teaching and learning. The Comp Hydro project, funded by a STEM+C grant from the National Science Foundation, brings together a diverse team of scientists, educators, professionals and citizens at sites in Arizona, Colorado, Maryland and Montana to foster water literacy, as well as computational science literacy, by integrating authentic, place- and data- based learning using physical, mathematical, computational and conceptual models. This multi-state project is currently engaging four teams of six teachers who work during two academic years with educators and scientists at each site. Teams work to develop instructional units specific to their region that integrate hydrologic science and computational modeling. The units, currently being piloted in high school earth and environmental science classes, provide a classroom context to investigate student understanding of how computation is used in Earth systems science. To develop effective science instruction that is rich in place- and data- based learning, effective collaborations between researchers, educators, scientists, professionals and citizens are crucial. In this poster, we focus on project implementation in Montana, where an instructional unit has been developed and is being tested through collaboration among University scientists, researchers and educators, high school teachers and agency and industry scientists and engineers. In particular, we discuss three characteristics of effective collaborative science education design for developing and implementing place- and data- based science education to support students in developing socio-scientific and computational literacy sufficient for making decisions about real world issues such as groundwater contamination. These characteristics include that science education experiences are real, responsive/accessible and rigorous.

Magnifying Students' Interest in Science

ERIC Educational Resources Information Center

Frazier, Wendy

2006-01-01

While some textbooks still teach students that there is one scientific process that must be rigidly followed, this stagnant portrayal of the process of science can lead students to think that science and scientists are quite boring. Through integrating visual art and microscopy, students learn about the creativity of scientists and begin to…

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals.

PubMed

Betts, Aislinn M; McGoldrick, Matthew T; Dethlefs, Christopher R; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W M

2017-04-25

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings.

In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations.

PubMed

Dutta, Soumya; Chen, Chun-Ming; Heinlein, Gregory; Shen, Han-Wei; Chen, Jen-Ping

2017-01-01

Study of flow instability in turbine engine compressors is crucial to understand the inception and evolution of engine stall. Aerodynamics experts have been working on detecting the early signs of stall in order to devise novel stall suppression technologies. A state-of-the-art Navier-Stokes based, time-accurate computational fluid dynamics simulator, TURBO, has been developed in NASA to enhance the understanding of flow phenomena undergoing rotating stall. Despite the proven high modeling accuracy of TURBO, the excessive simulation data prohibits post-hoc analysis in both storage and I/O time. To address these issues and allow the expert to perform scalable stall analysis, we have designed an in situ distribution guided stall analysis technique. Our method summarizes statistics of important properties of the simulation data in situ using a probabilistic data modeling scheme. This data summarization enables statistical anomaly detection for flow instability in post analysis, which reveals the spatiotemporal trends of rotating stall for the expert to conceive new hypotheses. Furthermore, the verification of the hypotheses and exploratory visualization using the summarized data are realized using probabilistic visualization techniques such as uncertain isocontouring. Positive feedback from the domain scientist has indicated the efficacy of our system in exploratory stall analysis.

SPICE Supports Planetary Science Observation Geometry

NASA Astrophysics Data System (ADS)

Hall Acton, Charles; Bachman, Nathaniel J.; Semenov, Boris V.; Wright, Edward D.

2015-11-01

"SPICE" is an information system, comprising both data and software, providing scientists with the observation geometry needed to plan observations from instruments aboard robotic spacecraft, and to subsequently help in analyzing the data returned from those observations. The SPICE system has been used on the majority of worldwide planetary exploration missions since the time of NASA's Galileo mission to Jupiter. Along with its "free" price tag, portability and the absence of licensing and export restrictions, its stable, enduring qualities help make it a popular choice. But stability does not imply rigidity-improvements and new capabilities are regularly added. This poster highlights recent additions that could be of interest to planetary scientists.Geometry Finder allows one to find all the times or time intervals when a particular geometric condition exists (e.g. occultation) or when a particular geometric parameter is within a given range or has reached a maximum or minimum.Digital Shape Kernel (DSK) provides means to compute observation geometry using accurately modeled target bodies: a tessellated plate model for irregular bodies and a digital elevation model for large, regular bodies.WebGeocalc (WGC) provides a graphical user interface (GUI) to a SPICE "geometry engine" installed at a mission operations facility, such as the one operated by NAIF. A WGC user need have only a computer with a web browser to access this geometry engine. Using traditional GUI widgets-drop-down menus, check boxes, radio buttons and fill-in boxes-the user inputs the data to be used, the kind of calculation wanted, and the details of that calculation. The WGC server makes the specified calculations and returns results to the user's browser.Cosmographia is a mission visualization program. This tool provides 3D visualization of solar system (target) bodies, spacecraft trajectory and orientation, instrument field-of-view "cones" and footprints, and more.The research described in this publication was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Analysis of Sea Level Rise in Action

NASA Astrophysics Data System (ADS)

Gill, K. M.; Huang, T.; Quach, N. T.; Boening, C.

2016-12-01

NASA's Sea Level Change Portal provides scientists and the general public with "one-stop" source for current sea level change information and data. Sea Level Rise research is a multidisciplinary research and in order to understand its causes, scientists must be able to access different measurements and to be able to compare them. The portal includes an interactive tool, called the Data Analysis Tool (DAT), for accessing, visualizing, and analyzing observations and models relevant to the study of Sea Level Rise. Using NEXUS, an open source, big data analytic technology developed at the Jet Propulsion Laboratory, the DAT is able provide user on-the-fly data analysis on all relevant parameters. DAT is composed of three major components: A dedicated instance of OnEarth (a WMTS service), NEXUS deep data analytic platform, and the JPL Common Mapping Client (CMC) for web browser based user interface (UI). Utilizing the global imagery, a user is capable of browsing the data in a visual manner and isolate areas of interest for further study. The interfaces "Analysis" tool provides tools for area or point selection, single and/or comparative dataset selection, and a range of options, algorithms, and plotting. This analysis component utilizes the Nexus cloud computing platform to provide on-demand processing of the data within the user-selected parameters and immediate display of the results. A RESTful web API is exposed for users comfortable with other interfaces and who may want to take advantage of the cloud computing capabilities. This talk discuss how DAT enables on-the-fly sea level research. The talk will introduce the DAT with an end-to-end tour of the tool with exploration and animating of available imagery, a demonstration of comparative analysis and plotting, and how to share and export data along with images for use in publications/presentations. The session will cover what kind of data is available, what kind of analysis is possible, and what are the outputs.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

ERIC Educational Resources Information Center

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors…

Effects of Direct Instruction of Visual Literacy Skills on Science Achievement When Integrated into Inquiry Learning

ERIC Educational Resources Information Center

Galyas, Lesley Crowell

2016-01-01

Understanding of visual representations is a pivotal skill necessary in science. These visual, verbal, and numeric representations are the crux of science discourses "by scientists, with students and the general public" (Pauwels, 2006, p.viii). Those who lack the understanding of these representations see it as a foreign language, one…

Modeling human comprehension of data visualizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matzen, Laura E.; Haass, Michael Joseph; Divis, Kristin Marie

This project was inspired by two needs. The first is a need for tools to help scientists and engineers to design effective data visualizations for communicating information, whether to the user of a system, an analyst who must make decisions based on complex data, or in the context of a technical report or publication. Most scientists and engineers are not trained in visualization design, and they could benefit from simple metrics to assess how well their visualization's design conveys the intended message. In other words, will the most important information draw the viewer's attention? The second is the need formore » cognition-based metrics for evaluating new types of visualizations created by researchers in the information visualization and visual analytics communities. Evaluating visualizations is difficult even for experts. However, all visualization methods and techniques are intended to exploit the properties of the human visual system to convey information efficiently to a viewer. Thus, developing evaluation methods that are rooted in the scientific knowledge of the human visual system could be a useful approach. In this project, we conducted fundamental research on how humans make sense of abstract data visualizations, and how this process is influenced by their goals and prior experience. We then used that research to develop a new model, the Data Visualization Saliency Model, that can make accurate predictions about which features in an abstract visualization will draw a viewer's attention. The model is an evaluation tool that can address both of the needs described above, supporting both visualization research and Sandia mission needs.« less

Message from the ISCB: 2015 ISCB Accomplishment by a Senior Scientist Award: Cyrus Chothia.

PubMed

Fogg, Christiana N; Kovats, Diane E

2015-07-01

The International Society for Computational Biology (ISCB; http://www.iscb.org) honors a senior scientist annually for his or her outstanding achievements with the ISCB Accomplishment by a Senior Scientist Award. This award recognizes a leader in the field of computational biology for his or her significant contributions to the community through research, service and education. Cyrus Chothia, an emeritus scientist at the Medical Research Council Laboratory of Molecular Biology and emeritus fellow of Wolfson College at Cambridge University, England, is the 2015 ISCB Accomplishment by a Senior Scientist Award winner.Chothia was selected by the Awards Committee, which is chaired by Dr Bonnie Berger of the Massachusetts Institute of Technology. He will receive his award and deliver a keynote presentation at 2015 Intelligent Systems for Molecular Biology/European Conference on Computational Biology in Dublin, Ireland, in July 2015. dkovats@iscb.org. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Enabling Earth Science: The Facilities and People of the NCCS

NASA Technical Reports Server (NTRS)

2002-01-01

The NCCS's mass data storage system allows scientists to store and manage the vast amounts of data generated by these computations, and its high-speed network connections allow the data to be accessed quickly from the NCCS archives. Some NCCS users perform studies that are directly related to their ability to run computationally expensive and data-intensive simulations. Because the number and type of questions scientists research often are limited by computing power, the NCCS continually pursues the latest technologies in computing, mass storage, and networking technologies. Just as important as the processors, tapes, and routers of the NCCS are the personnel who administer this hardware, create and manage accounts, maintain security, and assist the scientists, often working one on one with them.

Landsat Science: 40 Years of Innovation and Opportunity

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Irons, James R.; Masek, Jeffrey G.; Loveland, Thomas R.

2012-01-01

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Big Data: An Opportunity for Collaboration with Computer Scientists on Data-Driven Science

NASA Astrophysics Data System (ADS)

Baru, C.

2014-12-01

Big data technologies are evolving rapidly, driven by the need to manage ever increasing amounts of historical data; process relentless streams of human and machine-generated data; and integrate data of heterogeneous structure from extremely heterogeneous sources of information. Big data is inherently an application-driven problem. Developing the right technologies requires an understanding of the applications domain. Though, an intriguing aspect of this phenomenon is that the availability of the data itself enables new applications not previously conceived of! In this talk, we will discuss how the big data phenomenon creates an imperative for collaboration among domain scientists (in this case, geoscientists) and computer scientists. Domain scientists provide the application requirements as well as insights about the data involved, while computer scientists help assess whether problems can be solved with currently available technologies or require adaptaion of existing technologies and/or development of new technologies. The synergy can create vibrant collaborations potentially leading to new science insights as well as development of new data technologies and systems. The area of interface between geosciences and computer science, also referred to as geoinformatics is, we believe, a fertile area for interdisciplinary research.

CREASE 6.0 Catalog of Resources for Education in Ada and Software Engineering

DTIC Science & Technology

1992-02-01

Programming Software Engineering Strong Typing Tasking Audene . Computer Scientists Terbook(s): Barnes, J. Programming in Ada, 3rd ed. Addison-Wesley...Ada. Concept: Abstract Data Types Management Overview Package Real-Time Programming Tasking Audene Computer Scientists Textbook(s): Barnes, J

Parallel computing in genomic research: advances and applications

PubMed Central

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today’s genomic experiments have to process the so-called “biological big data” that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. PMID:26604801

Parallel computing in genomic research: advances and applications.

PubMed

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

Development of 3D interactive visual objects using the Scripps Institution of Oceanography's Visualization Center

NASA Astrophysics Data System (ADS)

Kilb, D.; Reif, C.; Peach, C.; Keen, C. S.; Smith, B.; Mellors, R. J.

2003-12-01

Within the last year scientists and educators at the Scripps Institution of Oceanography (SIO), the Birch Aquarium at Scripps and San Diego State University have collaborated with education specialists to develop 3D interactive graphic teaching modules for use in the classroom and in teacher workshops at the SIO Visualization center (http://siovizcenter.ucsd.edu). The unique aspect of the SIO Visualization center is that the center is designed around a 120 degree curved Panoram floor-to-ceiling screen (8'6" by 28'4") that immerses viewers in a virtual environment. The center is powered by an SGI 3400 Onyx computer that is more powerful, by an order of magnitude in both speed and memory, than typical base systems currently used for education and outreach presentations. This technology allows us to display multiple 3D data layers (e.g., seismicity, high resolution topography, seismic reflectivity, draped interferometric synthetic aperture radar (InSAR) images, etc.) simultaneously, render them in 3D stereo, and take a virtual flight through the data as dictated on the spot by the user. This system can also render snapshots, images and movies that are too big for other systems, and then export smaller size end-products to more commonly used computer systems. Since early 2002, we have explored various ways to provide informal education and outreach focusing on current research presented directly by the researchers doing the work. The Center currently provides a centerpiece for instruction on southern California seismology for K-12 students and teachers for various Scripps education endeavors. Future plans are in place to use the Visualization Center at Scripps for extended K-12 and college educational programs. In particular, we will be identifying K-12 curriculum needs, assisting with teacher education, developing assessments of our programs and products, producing web-accessible teaching modules and facilitating the development of appropriate teaching tools to be used directly by classroom teachers.

American and Greek Children's Visual Images of Scientists

NASA Astrophysics Data System (ADS)

Christidou, Vasilia; Bonoti, Fotini; Kontopoulou, Argiro

2016-08-01

This study explores American and Greek primary pupils' visual images of scientists by means of two nonverbal data collection tasks to identify possible convergences and divergences. Specifically, it aims to investigate whether their images of scientists vary according to the data collection instrument used and to gender. To this end, 91 third-grade American ( N = 46) and Greek ( N = 45) pupils were examined. Data collection was conducted through a drawing task based on Chambers (1983) `Draw-A-Scientist-Test' (DAST) and a picture selection task during which the children selected between 14 pairs of illustrations those that were most probable to represent scientists. Analysis focused on stereotype indicators related with scientists' appearance and work setting. Results showed that the two groups' performance varied significantly across the tasks used to explore their stereotypic perceptions, although the overall stereotypy was not differentiated according to participants' ethnic group. Moreover, boys were found to use more stereotypic indicators than girls, while the picture selection task elicited more stereotypic responses than the drawing task. In general, data collected by the two instruments revealed convergences and divergences concerning the stereotypic indicators preferred. Similarities and differences between national groups point to the influence of a globalized popular culture on the one hand and of the different sociocultural contexts underlying science curricula and their implementation on the other. Implications for science education are discussed.

A blueprint for computational analysis of acoustical scattering from orchestral panel arrays

NASA Astrophysics Data System (ADS)

Burns, Thomas

2005-09-01

Orchestral panel arrays have been a topic of interest to acousticians, and it is reasonable to expect optimal design criteria to result from a combination of musician surveys, on-stage empirical data, and computational modeling of various configurations. Preparing a musicians survey to identify specific mechanisms of perception and sound quality is best suited for a clinically experienced hearing scientist. Measuring acoustical scattering from a panel array and discerning the effects from various boundaries is best suited for the experienced researcher in engineering acoustics. Analyzing a numerical model of the panel arrays is best suited for the tools typically used in computational engineering analysis. Toward this end, a streamlined process will be described using PROENGINEER to define a panel array geometry in 3-D, a commercial mesher to numerically discretize this geometry, SYSNOISE to solve the associated boundary element integral equations, and MATLAB to visualize the results. The model was run (background priority) on an SGI Altix (Linux) server with 12 CPUs, 24 Gbytes of RAM, and 1 Tbyte of disk space. These computational resources are available to research teams interested in this topic and willing to write and pursue grants.

GeoBrain Computational Cyber-laboratory for Earth Science Studies

NASA Astrophysics Data System (ADS)

Deng, M.; di, L.

2009-12-01

Computational approaches (e.g., computer-based data visualization, analysis and modeling) are critical for conducting increasingly data-intensive Earth science (ES) studies to understand functions and changes of the Earth system. However, currently Earth scientists, educators, and students have met two major barriers that prevent them from being effectively using computational approaches in their learning, research and application activities. The two barriers are: 1) difficulties in finding, obtaining, and using multi-source ES data; and 2) lack of analytic functions and computing resources (e.g., analysis software, computing models, and high performance computing systems) to analyze the data. Taking advantages of recent advances in cyberinfrastructure, Web service, and geospatial interoperability technologies, GeoBrain, a project funded by NASA, has developed a prototype computational cyber-laboratory to effectively remove the two barriers. The cyber-laboratory makes ES data and computational resources at large organizations in distributed locations available to and easily usable by the Earth science community through 1) enabling seamless discovery, access and retrieval of distributed data, 2) federating and enhancing data discovery with a catalogue federation service and a semantically-augmented catalogue service, 3) customizing data access and retrieval at user request with interoperable, personalized, and on-demand data access and services, 4) automating or semi-automating multi-source geospatial data integration, 5) developing a large number of analytic functions as value-added, interoperable, and dynamically chainable geospatial Web services and deploying them in high-performance computing facilities, 6) enabling the online geospatial process modeling and execution, and 7) building a user-friendly extensible web portal for users to access the cyber-laboratory resources. Users can interactively discover the needed data and perform on-demand data analysis and modeling through the web portal. The GeoBrain cyber-laboratory provides solutions to meet common needs of ES research and education, such as, distributed data access and analysis services, easy access to and use of ES data, and enhanced geoprocessing and geospatial modeling capability. It greatly facilitates ES research, education, and applications. The development of the cyber-laboratory provides insights, lessons-learned, and technology readiness to build more capable computing infrastructure for ES studies, which can meet wide-range needs of current and future generations of scientists, researchers, educators, and students for their formal or informal educational training, research projects, career development, and lifelong learning.

Strategies for Interactive Visualization of Large Scale Climate Simulations

NASA Astrophysics Data System (ADS)

Xie, J.; Chen, C.; Ma, K.; Parvis

2011-12-01

With the advances in computational methods and supercomputing technology, climate scientists are able to perform large-scale simulations at unprecedented resolutions. These simulations produce data that are time-varying, multivariate, and volumetric, and the data may contain thousands of time steps with each time step having billions of voxels and each voxel recording dozens of variables. Visualizing such time-varying 3D data to examine correlations between different variables thus becomes a daunting task. We have been developing strategies for interactive visualization and correlation analysis of multivariate data. The primary task is to find connection and correlation among data. Given the many complex interactions among the Earth's oceans, atmosphere, land, ice and biogeochemistry, and the sheer size of observational and climate model data sets, interactive exploration helps identify which processes matter most for a particular climate phenomenon. We may consider time-varying data as a set of samples (e.g., voxels or blocks), each of which is associated with a vector of representative or collective values over time. We refer to such a vector as a temporal curve. Correlation analysis thus operates on temporal curves of data samples. A temporal curve can be treated as a two-dimensional function where the two dimensions are time and data value. It can also be treated as a point in the high-dimensional space. In this case, to facilitate effective analysis, it is often necessary to transform temporal curve data from the original space to a space of lower dimensionality. Clustering and segmentation of temporal curve data in the original or transformed space provides us a way to categorize and visualize data of different patterns, which reveals connection or correlation of data among different variables or at different spatial locations. We have employed the power of GPU to enable interactive correlation visualization for studying the variability and correlations of a single or a pair of variables. It is desired to create a succinct volume classification that summarizes the connection among all correlation volumes with respect to various reference locations. Providing a reference location must correspond to a voxel position, the number of correlation volumes equals the total number of voxels. A brute-force solution takes all correlation volumes as the input and classifies their corresponding voxels according to their correlation volumes' distance. For large-scale time-varying multivariate data, calculating all these correlation volumes on-the-fly and analyzing the relationships among them is not feasible. We have developed a sampling-based approach for volume classification in order to reduce the computation cost of computing the correlation volumes. Users are able to employ their domain knowledge in selecting important samples. The result is a static view that captures the essence of correlation relationships; i.e., for all voxels in the same cluster, their corresponding correlation volumes are similar. This sampling-based approach enables us to obtain an approximation of correlation relations in a cost-effective manner, thus leading to a scalable solution to investigate large-scale data sets. These techniques empower climate scientists to study large data from their simulations.

An economic and financial exploratory

NASA Astrophysics Data System (ADS)

Cincotti, S.; Sornette, D.; Treleaven, P.; Battiston, S.; Caldarelli, G.; Hommes, C.; Kirman, A.

2012-11-01

This paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs.

Award-Winning Animation Helps Scientists See Nature at Work | News | NREL

Science.gov Websites

Scientists See Nature at Work August 8, 2008 A computer-aided image combines a photo of a man with a three -dimensional, computer-generated image. The man has long brown hair and a long beard. He is wearing a blue - simultaneously. "It is very difficult to parallelize the process to run even on a huge computer,"

Optimizing Scientist Time through In Situ Visualization and Analysis.

PubMed

Patchett, John; Ahrens, James

2018-01-01

In situ processing produces reduced size persistent representations of a simulations state while the simulation is running. The need for in situ visualization and data analysis is usually described in terms of supercomputer size and performance in relation to available storage size.

From Years of Work in Psychology and Computer Science, Scientists Build Theories of Thinking and Learning.

ERIC Educational Resources Information Center

Wheeler, David L.

1988-01-01

Scientists feel that progress in artificial intelligence and the availability of thousands of experimental results make this the right time to build and test theories on how people think and learn, using the computer to model minds. (MSE)

Bay in Flux: Marine Climate Impacts, Art and Tablet App Design

NASA Astrophysics Data System (ADS)

Kintisch, E. S.

2012-12-01

Bay in Flux is a year-long experimental effort to design and develop interactive tablet computer apps exploring the marine impacts of climate change. The goal is to convey, visualize and enliven scientific ideas around this topic, while engaging a broad audience through the design of interactive content. Pioneering new models of scientist-artist collaborations are a central part of the effort as well. The project begins with an innovative studio class at the Rhode Island School of Design (RISD) called Bay in Flux, taught in the Fall 2012 semester. Its three instructor team includes two artist-designers and one science reporter, with active collaborations from affiliated marine scientists. The subject matter focus is the Narragansett Bay, which has shown physical, chemical and ecological impacts of climate change, along with the ongoing efforts of researchers to explain and characterize it. In exploring this rich story, we intend to innovate pioneering means of handling narrative material on interactive e-books, enable data collection by citizen scientists or devise game-like simulations to enable audiences to explore and understand complex natural systems. The lessons we seek to learn in this project include: how to effectively encourage collaborations between scientists and designers around digital design; how to pioneer new and compelling ways to tell science-based nonfiction stories on tablets; and how art and design students with no scientific training can engage with complex scientific content effectively. The project will also challenge us to think about the tablet computer not only as a data output device -- in which the user reads, watches, or interacts with provided content -- but also as a dynamic and ideal tool for mobile data input, enabling citizen science projects and novel connections between working researchers and the public. The intended audience could include high school students or older audiences who currently eschew science journalism. HTML5 is the likely language of choice, with the iPad being the initial intended platform. Following the fall class, a spring 2013 effort will involve developing a prototype app. Partners in the Bay in Flux project are the Knight Science Journalism program at MIT, RISD and the National Science Foundation's Rhode Island Experimental Program to Stimulate Competitive Research. Ultimately, the goal is to foster new ways for artists and designers to collaborate with scientists in the environmental field while reaching broad audiences.

Thirteen ways to say nothing with scientific visualization

NASA Technical Reports Server (NTRS)

Globus, AL; Raible, E.

1992-01-01

Scientific visualization can be used to produce very beautiful images. Frequently, users and others not properly initiated into mysteries of visualization research fail to appreciate the artistic qualities of these images. Scientists will frequently use our work to needlessly understand the data from which it is derived. This paper describes a number of effective techniques to confound such pernicious activity.

Interfaces Visualize Data for Airline Safety, Efficiency

NASA Technical Reports Server (NTRS)

2014-01-01

As the A-Train Constellation orbits Earth to gather data, NASA scientists and partners visualize, analyze, and communicate the information. To this end, Langley Research Center awarded SBIR funding to Fairfax, Virginia-based WxAnalyst Ltd. to refine the company's existing user interface for Google Earth to visualize data. Hawaiian Airlines is now using the technology to help manage its flights.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaskey, Alexander J.

Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.

ScyFlow: An Environment for the Visual Specification and Execution of Scientific Workflows

NASA Technical Reports Server (NTRS)

McCann, Karen M.; Yarrow, Maurice; DeVivo, Adrian; Mehrotra, Piyush

2004-01-01

With the advent of grid technologies, scientists and engineers are building more and more complex applications to utilize distributed grid resources. The core grid services provide a path for accessing and utilizing these resources in a secure and seamless fashion. However what the scientists need is an environment that will allow them to specify their application runs at a high organizational level, and then support efficient execution across any given set or sets of resources. We have been designing and implementing ScyFlow, a dual-interface architecture (both GUT and APT) that addresses this problem. The scientist/user specifies the application tasks along with the necessary control and data flow, and monitors and manages the execution of the resulting workflow across the distributed resources. In this paper, we utilize two scenarios to provide the details of the two modules of the project, the visual editor and the runtime workflow engine.

Analyzing task-based user study data to determine colormap efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ashton, Zoe Charon Maria; Wendelberger, Joanne Roth; Ticknor, Lawrence O.

2015-07-23

Domain scientists need colormaps to visualize their data and are especially useful for identifying areas of interest, like in ocean data to identify eddies or characterize currents. However, traditional Rainbow colormap performs poorly for understanding details, because of the small perceptual range. In order to assist domain scientists in recognizing and identifying important details in their data, different colormaps need to be applied to allow higher perceptual definition. Visual artist Francesca Samsel used her understanding of color theory to create new colormaps to improve perception. While domain scientists find the new colormaps to be useful, we implemented a rigorous andmore » quantitative study to determine whether or not the new colormaps have perceptually more colors. Color count data from one of these studies will be analyzed in depth in order to determine whether or not the new colormaps have more perceivable colors and what affects the number of perceivable colors.« less

Neural network based visualization of collaborations in a citizen science project

NASA Astrophysics Data System (ADS)

Morais, Alessandra M. M.; Santos, Rafael D. C.; Raddick, M. Jordan

2014-05-01

Citizen science projects are those in which volunteers are asked to collaborate in scientific projects, usually by volunteering idle computer time for distributed data processing efforts or by actively labeling or classifying information - shapes of galaxies, whale sounds, historical records are all examples of citizen science projects in which users access a data collecting system to label or classify images and sounds. In order to be successful, a citizen science project must captivate users and keep them interested on the project and on the science behind it, increasing therefore the time the users spend collaborating with the project. Understanding behavior of citizen scientists and their interaction with the data collection systems may help increase the involvement of the users, categorize them accordingly to different parameters, facilitate their collaboration with the systems, design better user interfaces, and allow better planning and deployment of similar projects and systems. Users behavior can be actively monitored or derived from their interaction with the data collection systems. Records of the interactions can be analyzed using visualization techniques to identify patterns and outliers. In this paper we present some results on the visualization of more than 80 million interactions of almost 150 thousand users with the Galaxy Zoo I citizen science project. Visualization of the attributes extracted from their behaviors was done with a clustering neural network (the Self-Organizing Map) and a selection of icon- and pixel-based techniques. These techniques allows the visual identification of groups of similar behavior in several different ways.

Scientists’ sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support

PubMed Central

2014-01-01

A common class of biomedical analysis is to explore expression data from high throughput experiments for the purpose of uncovering functional relationships that can lead to a hypothesis about mechanisms of a disease. We call this analysis expression driven, -omics hypothesizing. In it, scientists use interactive data visualizations and read deeply in the research literature. Little is known, however, about the actual flow of reasoning and behaviors (sense making) that scientists enact in this analysis, end-to-end. Understanding this flow is important because if bioinformatics tools are to be truly useful they must support it. Sense making models of visual analytics in other domains have been developed and used to inform the design of useful and usable tools. We believe they would be helpful in bioinformatics. To characterize the sense making involved in expression-driven, -omics hypothesizing, we conducted an in-depth observational study of one scientist as she engaged in this analysis over six months. From findings, we abstracted a preliminary sense making model. Here we describe its stages and suggest guidelines for developing visualization tools that we derived from this case. A single case cannot be generalized. But we offer our findings, sense making model and case-based tool guidelines as a first step toward increasing interest and further research in the bioinformatics field on scientists’ analytical workflows and their implications for tool design. PMID:24766796

"Ask Argonne" - Charlie Catlett, Computer Scientist, Part 2

ScienceCinema

Catlett, Charlie

2018-02-14

A few weeks back, computer scientist Charlie Catlett talked a bit about the work he does and invited questions from the public during Part 1 of his "Ask Argonne" video set (http://bit.ly/1joBtzk). In Part 2, he answers some of the questions that were submitted. Enjoy!

"Ask Argonne" - Charlie Catlett, Computer Scientist, Part 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Catlett, Charlie

2014-06-17

A few weeks back, computer scientist Charlie Catlett talked a bit about the work he does and invited questions from the public during Part 1 of his "Ask Argonne" video set (http://bit.ly/1joBtzk). In Part 2, he answers some of the questions that were submitted. Enjoy!

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research.

PubMed

Mader, Malte; Simon, Ronald; Kurtz, Stefan

2014-03-31

A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle.

Science & Art in Motion: Visualizing the X-ray Universe

NASA Astrophysics Data System (ADS)

Hobart, A. J.; Arcand, K. K.; Edmonds, P. D.; Tucker, W. H.

2005-12-01

Since its launch in 1999, the Chandra X-ray Observatory has probed regions around black holes, traced the debris of exploded stars, and helped to elucidate the formation of galaxy clusters, the largest bound structures in the Universe. Conveying Chandra's exciting, though often complicated, high-energy results to the public and the media poses certain visual challenges, such as photon-starved observational data, spectra, and esoteric concepts. This poster will demonstrate some of the techniques developed to present visuals by way of motion graphics in X-ray astronomy. Some tricks of the trade will be highlighted, including establishing texture libraries, using particle or paint effects, and modeling stock objects. Topics unique to animating scientific concepts for public consumption will also be discussed, such as addressing public perception versus scientists' findings, keeping a high standard of accuracy while leaving room for visual excitement, communicating with scientists for revisions, and creative ways to interact with and educate the public. Developed with funding from NASA under Contract NAS8-39073.

VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA

PubMed Central

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.

2010-01-01

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org. PMID:20007449

From Lived Experiences to Game Creation: How Scaffolding Supports Elementary School Students Learning Computer Science Principles in an After School Setting

ERIC Educational Resources Information Center

Her Many Horses, Ian

2016-01-01

The world, and especially our own country, is in dire need of a larger and more diverse population of computer scientists. While many organizations have approached this problem of too few computer scientists in various ways, a promising, and I believe necessary, path is to expose elementary students to authentic practices of the discipline.…

An Active Vision Approach to Understanding and Improving Visual Training in the Geosciences

NASA Astrophysics Data System (ADS)

Voronov, J.; Tarduno, J. A.; Jacobs, R. A.; Pelz, J. B.; Rosen, M. R.

2009-12-01

Experience in the field is a fundamental aspect of geologic training, and its effectiveness is largely unchallenged because of anecdotal evidence of its success among expert geologists. However, there have been only a few quantitative studies based on large data collection efforts to investigate how Earth Scientists learn in the field. In a recent collaboration between Earth scientists, Cognitive scientists and experts in Imaging science at the University of Rochester and Rochester Institute of Technology, we are investigating such a study. Within Cognitive Science, one school of thought, referred to as the Active Vision approach, emphasizes that visual perception is an active process requiring us to move our eyes to acquire new information about our environment. The Active Vision approach indicates the perceptual skills which experts possess and which novices will need to acquire to achieve expert performance. We describe data collection efforts using portable eye-trackers to assess how novice and expert geologists acquire visual knowledge in the field. We also discuss our efforts to collect images for use in a semi-immersive classroom environment, useful for further testing of novices and experts using eye-tracking technologies.

Visualization techniques to aid in the analysis of multispectral astrophysical data sets

NASA Technical Reports Server (NTRS)

Brugel, E. W.; Domik, Gitta O.; Ayres, T. R.

1993-01-01

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report.

National Fusion Collaboratory: Grid Computing for Simulations and Experiments

NASA Astrophysics Data System (ADS)

Greenwald, Martin

2004-05-01

The National Fusion Collaboratory Project is creating a computational grid designed to advance scientific understanding and innovation in magnetic fusion research by facilitating collaborations, enabling more effective integration of experiments, theory and modeling and allowing more efficient use of experimental facilities. The philosophy of FusionGrid is that data, codes, analysis routines, visualization tools, and communication tools should be thought of as network available services, easily used by the fusion scientist. In such an environment, access to services is stressed rather than portability. By building on a foundation of established computer science toolkits, deployment time can be minimized. These services all share the same basic infrastructure that allows for secure authentication and resource authorization which allows stakeholders to control their own resources such as computers, data and experiments. Code developers can control intellectual property, and fair use of shared resources can be demonstrated and controlled. A key goal is to shield scientific users from the implementation details such that transparency and ease-of-use are maximized. The first FusionGrid service deployed was the TRANSP code, a widely used tool for transport analysis. Tools for run preparation, submission, monitoring and management have been developed and shared among a wide user base. This approach saves user sites from the laborious effort of maintaining such a large and complex code while at the same time reducing the burden on the development team by avoiding the need to support a large number of heterogeneous installations. Shared visualization and A/V tools are being developed and deployed to enhance long-distance collaborations. These include desktop versions of the Access Grid, a highly capable multi-point remote conferencing tool and capabilities for sharing displays and analysis tools over local and wide-area networks.

Google Earth Engine

NASA Astrophysics Data System (ADS)

Gorelick, Noel

2013-04-01

The Google Earth Engine platform is a system designed to enable petabyte-scale, scientific analysis and visualization of geospatial datasets. Earth Engine provides a consolidated environment including a massive data catalog co-located with thousands of computers for analysis. The user-friendly front-end provides a workbench environment to allow interactive data and algorithm development and exploration and provides a convenient mechanism for scientists to share data, visualizations and analytic algorithms via URLs. The Earth Engine data catalog contains a wide variety of popular, curated datasets, including the world's largest online collection of Landsat scenes (> 2.0M), numerous MODIS collections, and many vector-based data sets. The platform provides a uniform access mechanism to a variety of data types, independent of their bands, projection, bit-depth, resolution, etc..., facilitating easy multi-sensor analysis. Additionally, a user is able to add and curate their own data and collections. Using a just-in-time, distributed computation model, Earth Engine can rapidly process enormous quantities of geo-spatial data. All computation is performed lazily; nothing is computed until it's required either for output or as input to another step. This model allows real-time feedback and preview during algorithm development, supporting a rapid algorithm development, test, and improvement cycle that scales seamlessly to large-scale production data processing. Through integration with a variety of other services, Earth Engine is able to bring to bear considerable analytic and technical firepower in a transparent fashion, including: AI-based classification via integration with Google's machine learning infrastructure, publishing and distribution at Google scale through integration with the Google Maps API, Maps Engine and Google Earth, and support for in-the-field activities such as validation, ground-truthing, crowd-sourcing and citizen science though the Android Open Data Kit.

Google Earth Engine

NASA Astrophysics Data System (ADS)

Gorelick, N.

2012-12-01

The Google Earth Engine platform is a system designed to enable petabyte-scale, scientific analysis and visualization of geospatial datasets. Earth Engine provides a consolidated environment including a massive data catalog co-located with thousands of computers for analysis. The user-friendly front-end provides a workbench environment to allow interactive data and algorithm development and exploration and provides a convenient mechanism for scientists to share data, visualizations and analytic algorithms via URLs. The Earth Engine data catalog contains a wide variety of popular, curated datasets, including the world's largest online collection of Landsat scenes (> 2.0M), numerous MODIS collections, and many vector-based data sets. The platform provides a uniform access mechanism to a variety of data types, independent of their bands, projection, bit-depth, resolution, etc..., facilitating easy multi-sensor analysis. Additionally, a user is able to add and curate their own data and collections. Using a just-in-time, distributed computation model, Earth Engine can rapidly process enormous quantities of geo-spatial data. All computation is performed lazily; nothing is computed until it's required either for output or as input to another step. This model allows real-time feedback and preview during algorithm development, supporting a rapid algorithm development, test, and improvement cycle that scales seamlessly to large-scale production data processing. Through integration with a variety of other services, Earth Engine is able to bring to bear considerable analytic and technical firepower in a transparent fashion, including: AI-based classification via integration with Google's machine learning infrastructure, publishing and distribution at Google scale through integration with the Google Maps API, Maps Engine and Google Earth, and support for in-the-field activities such as validation, ground-truthing, crowd-sourcing and citizen science though the Android Open Data Kit.

High-Performance Computing and Visualization | Energy Systems Integration

Science.gov Websites

Facility | NREL High-Performance Computing and Visualization High-Performance Computing and Visualization High-performance computing (HPC) and visualization at NREL propel technology innovation as a . Capabilities High-Performance Computing NREL is home to Peregrine-the largest high-performance computing system

Visual Environments for CFD Research

NASA Technical Reports Server (NTRS)

Watson, Val; George, Michael W. (Technical Monitor)

1994-01-01

This viewgraph presentation gives an overview of the visual environments for computational fluid dynamics (CFD) research. It includes details on critical needs from the future computer environment, features needed to attain this environment, prospects for changes in and the impact of the visualization revolution on the human-computer interface, human processing capabilities, limits of personal environment and the extension of that environment with computers. Information is given on the need for more 'visual' thinking (including instances of visual thinking), an evaluation of the alternate approaches for and levels of interactive computer graphics, a visual analysis of computational fluid dynamics, and an analysis of visualization software.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ayer, Vidya M.; Miguez, Sheila; Toby, Brian H.

Scientists have been central to the historical development of the computer industry, but the importance of software only continues to grow for all areas of scientific research and in particular for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. The article introduces the three types of programming languages and why scripting languages are now preferred for scientists. Of them, the authors assert Python is the most useful and easiest to learn. Python is introduced. Also presented is an overview to a few of the many add-on packages available to extend the capabilitiesmore » of Python, for example, for numerical computations, scientific graphics and graphical user interface programming.« less

Intelligent Systems: Terrestrial Observation and Prediction Using Remote Sensing Data

NASA Technical Reports Server (NTRS)

Coughlan, Joseph C.

2005-01-01

NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.

Comparing art-science collaboration efforts to highlight changes in the marine environment of Arctic Alaska

NASA Astrophysics Data System (ADS)

Lee, O. A.

2016-12-01

Significant changes to the Arctic marine environment is anticipated as a result of decreasing sea ice and increasing anthropogenic activity that may occur with increasing access to ice-free waters. Two different collaboration efforts between scientists and artists on projects related to changes in the Alaskan Arctic waters are compared to present different outcomes from two collaboration strategies. The first collaboration involved a funded project to develop visualizations of change on the North Slope as part of an outreach effort for the North Slope Science Initiative Scenarios project. The second collaboration was a voluntary art-science collaboration to develop artwork about changing sea ice habitat for walrus as one contribution to a featured art show during the 2016 Arctic Science Summit Week. Both collaboration opportunities resulted in compelling visualizations. However the funded collaboration provided for more iterative discussions between the scientist and the collaborators for the film and animation products throughout the duration of the project. This ensured that the science remained an important focal point. In contrast, the product of the voluntary collaboration effort was primarily driven by the artist's perspective, although the discussions with the scientist played a role in connecting the content of the three panels in the final art and sculpture piece. This comparison of different levels of scientist-involvement and resources used to develop the visualizations highlights the importance of defining the intended audience and expectations for all collaborators early.

Long live the Data Scientist, but can he/she persist?

NASA Astrophysics Data System (ADS)

Wyborn, L. A.

2011-12-01

In recent years the fourth paradigm of data intensive science has slowly taken hold as the increased capacity of instruments and an increasing number of instruments (in particular sensor networks) have changed how fundamental research is undertaken. Most modern scientific research is about digital capture of data direct from instruments, processing it by computers, storing the results on computers and only publishing a small fraction of data in hard copy publications. At the same time, the rapid increase in capacity of supercomputers, particularly at petascale, means that far larger data sets can be analysed and to greater resolution than previously possible. The new cloud computing paradigm which allows distributed data, software and compute resources to be linked by seamless workflows, is creating new opportunities in processing of high volumes of data to an increasingly larger number of researchers. However, to take full advantage of these compute resources, data sets for analysis have to be aggregated from multiple sources to create high performance data sets. These new technology developments require that scientists must become more skilled in data management and/or have a higher degree of computer literacy. In almost every science discipline there is now an X-informatics branch and a computational X branch (eg, Geoinformatics and Computational Geoscience): both require a new breed of researcher that has skills in both the science fundamentals and also knowledge of some ICT aspects (computer programming, data base design and development, data curation, software engineering). People that can operate in both science and ICT are increasingly known as 'data scientists'. Data scientists are a critical element of many large scale earth and space science informatics projects, particularly those that are tackling current grand challenges at an international level on issues such as climate change, hazard prediction and sustainable development of our natural resources. These projects by their very nature require the integration of multiple digital data sets from multiple sources. Often the preparation of the data for computational analysis can take months and requires painstaking attention to detail to ensure that anomalies identified are real and are not just artefacts of the data preparation and/or the computational analysis. Although data scientists are increasingly vital to successful data intensive earth and space science projects, unless they are recognised for their capabilities in both the science and the computational domains they are likely to migrate to either a science role or an ICT role as their career advances. Most reward and recognition systems do not recognise those with skills in both, hence, getting trained data scientists to persist beyond one or two projects can be challenge. Those data scientists that persist in the profession are characteristically committed and enthusiastic people who have the support of their organisations to take on this role. They also tend to be people who share developments and are critical to the success of the open source software movement. However, the fact remains that survival of the data scientist as a species is being threatened unless something is done to recognise their invaluable contributions to the new fourth paradigm of science.

Climate Discovery: Integrating Research With Exhibit, Public Tours, K-12, and Web-based EPO Resources

NASA Astrophysics Data System (ADS)

Foster, S. Q.; Carbone, L.; Gardiner, L.; Johnson, R.; Russell, R.; Advisory Committee, S.; Ammann, C.; Lu, G.; Richmond, A.; Maute, A.; Haller, D.; Conery, C.; Bintner, G.

2005-12-01

The Climate Discovery Exhibit at the National Center for Atmospheric Research (NCAR) Mesa Lab provides an exciting conceptual outline for the integration of several EPO activities with other well-established NCAR educational resources and programs. The exhibit is organized into four topic areas intended to build understanding among NCAR's 80,000 annual visitors, including 10,000 school children, about Earth system processes and scientific methods contributing to a growing body of knowledge about climate and global change. These topics include: 'Sun-Earth Connections,' 'Climate Now,' 'Climate Past,' and 'Climate Future.' Exhibit text, graphics, film and electronic media, and interactives are developed and updated through collaborations between NCAR's climate research scientists and staff in the Office of Education and Outreach (EO) at the University Corporation for Atmospheric Research (UCAR). With funding from NCAR, paleoclimatologists have contributed data and ideas for a new exhibit Teachers' Guide unit about 'Climate Past.' This collection of middle-school level, standards-aligned lessons are intended to help students gain understanding about how scientists use proxy data and direct observations to describe past climates. Two NASA EPO's have funded the development of 'Sun-Earth Connection' lessons, visual media, and tips for scientists and teachers. Integrated with related content and activities from the NASA-funded Windows to the Universe web site, these products have been adapted to form a second unit in the Climate Discovery Teachers' Guide about the Sun's influence on Earth's climate. Other lesson plans, previously developed by on-going efforts of EO staff and NSF's previously-funded Project Learn program are providing content for a third Teachers' Guide unit on 'Climate Now' - the dynamic atmospheric and geological processes that regulate Earth's climate. EO has plans to collaborate with NCAR climatologists and computer modelers in the next year to develop lessons and ancillary exhibit interactives and visualizations for the final Teachers' Guide unit about 'Climate Future.' Units developed so far are available in downloadable format on the NCAR EO and Windows to the Universe web sites for dissemination to educators and the general public public. Those web sites are, respectively, (http://eo.ucar.edu/educators/ClimateDiscovery) and (http://www.windows.ucar.edu). Encouragement from funding agencies to integrate and relate resources and growing pressure to implement efficiencies in educational programs have created excellent opportunities which will be described from the viewpoints of EO staff and scientists'. Challenges related to public and student perceptions about climate and global change, the scientific endeavor, and how to establish successful dialogues between educators and scientists will also be discussed.

Novel Visualization Approaches in Environmental Mineralogy

NASA Astrophysics Data System (ADS)

Anderson, C. D.; Lopano, C. L.; Hummer, D. R.; Heaney, P. J.; Post, J. E.; Kubicki, J. D.; Sofo, J. O.

2006-05-01

Communicating the complexities of atomic scale reactions between minerals and fluids is fraught with intrinsic challenges. For example, an increasing number of techniques are now available for the interrogation of dynamical processes at the mineral-fluid interface. However, the time-dependent behavior of atomic interactions between a solid and a liquid is often not adequately captured by two-dimensional line drawings or images. At the same time, the necessity for describing these reactions to general audiences is growing more urgent, as funding agencies are amplifying their encouragement to scientists to reach across disciplines and to justify their studies to public audiences. To overcome the shortcomings of traditional graphical representations, the Center for Environmental Kinetics Analysis is creating three-dimensional visualizations of experimental and simulated mineral reactions. These visualizations are then displayed on a stereo 3D projection system called the GeoWall. Made possible (and affordable) by recent improvements in computer and data projector technology, the GeoWall system uses a combination of computer software and hardware, polarizing filters and polarizing glasses, to present visualizations in true 3D. The three-dimensional views greatly improve comprehension of complex multidimensional data, and animations of time series foster better understanding of the underlying processes. The visualizations also offer an effective means to communicate the complexities of environmental mineralogy to colleagues, students and the public. Here we present three different kinds of datasets that demonstrate the effectiveness of the GeoWall in clarifying complex environmental reactions at the atomic scale. First, a time-resolved series of diffraction patterns obtained during the hydrothermal synthesis of metal oxide phases from precursor solutions can be viewed as a surface with interactive controls for peak scaling and color mapping. Second, the results of Rietveld analysis of cation exchange reactions in Mn oxides has provided three-dimensional difference Fourier maps. When stitched together in a temporal series, these offer an animated view of changes in atomic configurations during the process of exchange. Finally, molecular dynamical simulations are visualized as three-dimensional reactions between vibrating atoms in both the solid and the aqueous phases.

Policy summary: visualization and communication track

NASA Astrophysics Data System (ADS)

Gates, Harvey M.

1994-03-01

The goal of visualization and graphics oriented scientists, engineers, and educators is to electronically share their products with colleagues around the United States and the world. Thus, these specialists have dubbed their communication requirement as `100 megabits (per second) to the desktop.' This simply means that these high technology specialists would like to transmit and receive visual products in real-time, unimpeded by the network speed and interconnection protocols.

The Role of Visual Representations in Scientific Practices: From Conceptual Understanding and Knowledge Generation to 'Seeing' How Science Works

ERIC Educational Resources Information Center

Evagorou, Maria; Erduran, Sibel; Mäntylä, Terhi

2015-01-01

Background: The use of visual representations (i.e., photographs, diagrams, models) has been part of science, and their use makes it possible for scientists to interact with and represent complex phenomena, not observable in other ways. Despite a wealth of research in science education on visual representations, the emphasis of such research has…

Preservice Teachers' Images of Scientists: Do Prior Science Experiences Make a Difference?

NASA Astrophysics Data System (ADS)

Milford, Todd M.; Tippett, Christine D.

2013-06-01

This article presents the results of a mixed methods study that used the Draw-a-Scientist Test as a visual tool for exploring preservice teachers' beliefs about scientists. A questionnaire was also administered to 165 students who were enrolled in elementary (K-8) and secondary (8-12) science methods courses. Taken as a whole, the images drawn by preservice teachers reflected the stereotype of a scientist as a man with a wild hairdo who wears a lab coat and glasses while working in a laboratory setting. However, results indicated statistically significant differences in stereotypical components of representations of scientists depending on preservice teachers' program and previous science experiences. Post degree students in secondary science methods courses created images of scientists with fewer stereotypical elements than drawings created by students in the regular elementary program.

How to Cloud for Earth Scientists: An Introduction

NASA Technical Reports Server (NTRS)

Lynnes, Chris

2018-01-01

This presentation is a tutorial on getting started with cloud computing for the purposes of Earth Observation datasets. We first discuss some of the main advantages that cloud computing can provide for the Earth scientist: copious processing power, immense and affordable data storage, and rapid startup time. We also talk about some of the challenges of getting the most out of cloud computing: re-organizing the way data are analyzed, handling node failures and attending.

MEVA--An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices.

PubMed

Helbig, Carolin; Bilke, Lars; Bauer, Hans-Stefan; Böttinger, Michael; Kolditz, Olaf

2015-01-01

To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work. Instead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results.

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

PubMed Central

Helbig, Carolin; Bilke, Lars; Bauer, Hans-Stefan; Böttinger, Michael; Kolditz, Olaf

2015-01-01

Background To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work. Methods and Results Instead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results. PMID:25915061

Integrated Data Visualization and Virtual Reality Tool

NASA Technical Reports Server (NTRS)

Dryer, David A.

1998-01-01

The Integrated Data Visualization and Virtual Reality Tool (IDVVRT) Phase II effort was for the design and development of an innovative Data Visualization Environment Tool (DVET) for NASA engineers and scientists, enabling them to visualize complex multidimensional and multivariate data in a virtual environment. The objectives of the project were to: (1) demonstrate the transfer and manipulation of standard engineering data in a virtual world; (2) demonstrate the effects of design and changes using finite element analysis tools; and (3) determine the training and engineering design and analysis effectiveness of the visualization system.

PLOT3D/AMES, SGI IRIS VERSION (WITHOUT TURB3D)

NASA Technical Reports Server (NTRS)

Buning, P.

1994-01-01

PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into five groups: 1) Grid Functions for grids, grid-checking, etc.; 2) Scalar Functions for contour or carpet plots of density, pressure, temperature, Mach number, vorticity magnitude, helicity, etc.; 3) Vector Functions for vector plots of velocity, vorticity, momentum, and density gradient, etc.; 4) Particle Trace Functions for rake-like plots of particle flow or vortex lines; and 5) Shock locations based on pressure gradient. TURB3D is a modification of PLOT3D which is used for viewing CFD simulations of incompressible turbulent flow. Input flow data consists of pressure, velocity and vorticity. Typical quantities to plot include local fluctuations in flow quantities and turbulent production terms, plotted in physical or wall units. PLOT3D/TURB3D includes both TURB3D and PLOT3D because the operation of TURB3D is identical to PLOT3D, and there is no additional sample data or printed documentation for TURB3D. Graphical capabilities of PLOT3D version 3.6b+ vary among the implementations available through COSMIC. Customers are encouraged to purchase and carefully review the PLOT3D manual before ordering the program for a specific computer and graphics library. There is only one manual for use with all implementations of PLOT3D, and although this manual generally assumes that the Silicon Graphics Iris implementation is being used, informative comments concerning other implementations appear throughout the text. With all implementations, the visual representation of the object and flow field created by PLOT3D consists of points, lines, and polygons. Points can be represented with dots or symbols, color can be used to denote data values, and perspective is used to show depth. Differences among implementations impact the program's ability to use graphical features that are based on 3D polygons, the user's ability to manipulate the graphical displays, and the user's ability to obtain alternate forms of output. In each of these areas, the IRIS implementation of PLOT3D offers advanced features which aid visualization efforts. Shading and hidden line/surface removal can be used to enhance depth perception and other aspects of the graphical displays. A mouse can be used to translate, rotate, or zoom in on views. Files for several types of output can be produced. Two animation options are even offered: creation of simple animation sequences without the need for other software; and, creation of files for use in GAS (Graphics Animation System, ARC-12379), an IRIS program which offers more complex rendering and animation capabilities and can record images to digital disk, video tape, or 16-mm film. The version 3.6b+ SGI implementations of PLOT3D (ARC-12783) and PLOT3D/TURB3D (ARC-12782) were developed for use on Silicon Graphics IRIS 2xxx/3xxx or IRIS 4D workstations. These programs are each distributed on one .25 inch magnetic tape cartridge in IRIS TAR format. Customers purchasing one implementation version of PLOT3D or PLOT3D/TURB3D will be given a $200 discount on each additional implementation version ordered at the same time. Version 3.6b+ of PLOT3D and PLOT3D/TURB3D are also supported for the following computers and graphics libraries: (1) generic UNIX Supercomputer and IRIS, suitable for CRAY 2/UNICOS, CONVEX, and Alliant with remote IRIS 2xxx/3xxx or IRIS 4D (ARC-12779, ARC-12784); (2) VAX computers running VMS Version 5.0 and DISSPLA Version 11.0 (ARC-12777,ARC-12781); (3) generic UNIX and DISSPLA Version 11.0 (ARC-12788, ARC-12778); and (4) Apollo computers running UNIX and GMR3D Version 2.0 (ARC-12789, ARC-12785 which have no capabilities to put text on plots). Silicon Graphics Iris, IRIS 4D, and IRIS 2xxx/3xxx are trademarks of Silicon Graphics Incorporated. VAX and VMS are trademarks of Digital Electronics Corporation. DISSPLA is a trademark of Computer Associates. CRAY 2 and UNICOS are trademarks of CRAY Research, Incorporated. CONVEX is a trademark of Convex Computer Corporation. Alliant is a trademark of Alliant. Apollo and GMR3D are trademarks of Hewlett-Packard, Incorporated. UNIX is a registered trademark of AT&T.

PLOT3D/AMES, SGI IRIS VERSION (WITH TURB3D)

NASA Technical Reports Server (NTRS)

Buning, P.

1994-01-01

PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into five groups: 1) Grid Functions for grids, grid-checking, etc.; 2) Scalar Functions for contour or carpet plots of density, pressure, temperature, Mach number, vorticity magnitude, helicity, etc.; 3) Vector Functions for vector plots of velocity, vorticity, momentum, and density gradient, etc.; 4) Particle Trace Functions for rake-like plots of particle flow or vortex lines; and 5) Shock locations based on pressure gradient. TURB3D is a modification of PLOT3D which is used for viewing CFD simulations of incompressible turbulent flow. Input flow data consists of pressure, velocity and vorticity. Typical quantities to plot include local fluctuations in flow quantities and turbulent production terms, plotted in physical or wall units. PLOT3D/TURB3D includes both TURB3D and PLOT3D because the operation of TURB3D is identical to PLOT3D, and there is no additional sample data or printed documentation for TURB3D. Graphical capabilities of PLOT3D version 3.6b+ vary among the implementations available through COSMIC. Customers are encouraged to purchase and carefully review the PLOT3D manual before ordering the program for a specific computer and graphics library. There is only one manual for use with all implementations of PLOT3D, and although this manual generally assumes that the Silicon Graphics Iris implementation is being used, informative comments concerning other implementations appear throughout the text. With all implementations, the visual representation of the object and flow field created by PLOT3D consists of points, lines, and polygons. Points can be represented with dots or symbols, color can be used to denote data values, and perspective is used to show depth. Differences among implementations impact the program's ability to use graphical features that are based on 3D polygons, the user's ability to manipulate the graphical displays, and the user's ability to obtain alternate forms of output. In each of these areas, the IRIS implementation of PLOT3D offers advanced features which aid visualization efforts. Shading and hidden line/surface removal can be used to enhance depth perception and other aspects of the graphical displays. A mouse can be used to translate, rotate, or zoom in on views. Files for several types of output can be produced. Two animation options are even offered: creation of simple animation sequences without the need for other software; and, creation of files for use in GAS (Graphics Animation System, ARC-12379), an IRIS program which offers more complex rendering and animation capabilities and can record images to digital disk, video tape, or 16-mm film. The version 3.6b+ SGI implementations of PLOT3D (ARC-12783) and PLOT3D/TURB3D (ARC-12782) were developed for use on Silicon Graphics IRIS 2xxx/3xxx or IRIS 4D workstations. These programs are each distributed on one .25 inch magnetic tape cartridge in IRIS TAR format. Customers purchasing one implementation version of PLOT3D or PLOT3D/TURB3D will be given a $200 discount on each additional implementation version ordered at the same time. Version 3.6b+ of PLOT3D and PLOT3D/TURB3D are also supported for the following computers and graphics libraries: (1) generic UNIX Supercomputer and IRIS, suitable for CRAY 2/UNICOS, CONVEX, and Alliant with remote IRIS 2xxx/3xxx or IRIS 4D (ARC-12779, ARC-12784); (2) VAX computers running VMS Version 5.0 and DISSPLA Version 11.0 (ARC-12777,ARC-12781); (3) generic UNIX and DISSPLA Version 11.0 (ARC-12788, ARC-12778); and (4) Apollo computers running UNIX and GMR3D Version 2.0 (ARC-12789, ARC-12785 which have no capabilities to put text on plots). Silicon Graphics Iris, IRIS 4D, and IRIS 2xxx/3xxx are trademarks of Silicon Graphics Incorporated. VAX and VMS are trademarks of Digital Electronics Corporation. DISSPLA is a trademark of Computer Associates. CRAY 2 and UNICOS are trademarks of CRAY Research, Incorporated. CONVEX is a trademark of Convex Computer Corporation. Alliant is a trademark of Alliant. Apollo and GMR3D are trademarks of Hewlett-Packard, Incorporated. UNIX is a registered trademark of AT&T.

Slycat™ User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crossno, Patricia J.; Gittinger, Jaxon; Hunt, Warren L.

Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features acrossmore » the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.« less

In situ visualization for large-scale combustion simulations.

PubMed

Yu, Hongfeng; Wang, Chaoli; Grout, Ray W; Chen, Jacqueline H; Ma, Kwan-Liu

2010-01-01

As scientific supercomputing moves toward petascale and exascale levels, in situ visualization stands out as a scalable way for scientists to view the data their simulations generate. This full picture is crucial particularly for capturing and understanding highly intermittent transient phenomena, such as ignition and extinction events in turbulent combustion.

The Language of Visualisation

NASA Astrophysics Data System (ADS)

Wyatt, R.

2014-01-01

There is a visual language present in all images and this article explores the meaning of these languages, their importance, and what it means for the visualisation of science. Do we, as science communicators, confuse and confound our audiences by assuming the visual vernacular of the scientist or isolate our scientific audience by ignoring it?

Analyzing Task-Based User Study Data to Determine Colormap Efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ashton, Zoe Charon Maria; Wendelberger, Joanne Roth; Ticknor, Lawrence O.

2015-07-23

Domain scientists use colormaps to visualize their data. These are useful for identifying areas of interest including Eddy Identification and Characterizing Currents. New colormaps have been designed by visual artist Francesca Samsel. User studies have been implemented to determine whether or not these colormaps are an improvement.

Histochemical Seeing: Scientific Visualization and Art Education

ERIC Educational Resources Information Center

Knochel, Aaron

2013-01-01

What are the capacities of visual arts curricula to engage learning within narrow frameworks of overly "scientistic" standards (Lather, 2007)? With growing emphasis in schools under STEM initiatives and evidence-based standards, the possible cross-pollination of effects that art education may have on a science-centric education may be a…

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

[To explain is to narrate. How to visualize scientific data].

PubMed

Hawtin, Nigel

2014-01-01

When you try to appeal a vast ranging audience, as it occurs at the New Scientist that addresses scientists as well as the general public, your scientific visual explainer must be succinct, clear, accurate and easily understandable. In order to reach this goal, your message should provide only the main data, the ones that allow you to balance information and clarity: information should be put into context and all the extra details should be cut down. It is very important, then, to know well both your audience and the subject you are going to describe, as graphic masters of the past, like William Playfair and Charles Minard, have taught us. Moreover, you should try to engage your reader connecting the storytelling power of words and the driving force of the graphics: colours, visual elements, typography. To be effective, in fact, an infographic should not only be truthful and functional, but also elegant, having style and legibility.

A Virtual Rock Physics Laboratory Through Visualized and Interactive Experiments

NASA Astrophysics Data System (ADS)

Vanorio, T.; Di Bonito, C.; Clark, A. C.

2014-12-01

As new scientific challenges demand more comprehensive and multidisciplinary investigations, laboratory experiments are not expected to become simpler and/or faster. Experimental investigation is an indispensable element of scientific inquiry and must play a central role in the way current and future generations of scientist make decisions. To turn the complexity of laboratory work (and that of rocks!) into dexterity, engagement, and expanded learning opportunities, we are building an interactive, virtual laboratory reproducing in form and function the Stanford Rock Physics Laboratory, at Stanford University. The objective is to combine lectures on laboratory techniques and an online repository of visualized experiments consisting of interactive, 3-D renderings of equipment used to measure properties central to the study of rock physics (e.g., how to saturate rocks, how to measure porosity, permeability, and elastic wave velocity). We use a game creation system together with 3-D computer graphics, and a narrative voice to guide the user through the different phases of the experimental protocol. The main advantage gained in employing computer graphics over video footage is that students can virtually open the instrument, single out its components, and assemble it. Most importantly, it helps describe the processes occurring within the rock. These latter cannot be tracked while simply recording the physical experiment, but computer animation can efficiently illustrate what happens inside rock samples (e.g., describing acoustic waves, and/or fluid flow through a porous rock under pressure within an opaque core-holder - Figure 1). The repository of visualized experiments will complement lectures on laboratory techniques and constitute an on-line course offered through the EdX platform at Stanford. This will provide a virtual laboratory for anyone, anywhere to facilitate teaching/learning of introductory laboratory classes in Geophysics and expand the number of courses that can be offered for curricula in Earth Sciences. The primary goal is to open up a research laboratory such as the one available at Stanford to promising students worldwide who are currently left out of such educational resources.

Modality-Driven Classification and Visualization of Ensemble Variance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no informationmore » about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.« less

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals

PubMed Central

Dethlefs, Christopher R.; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W. M.

2017-01-01

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings. PMID:28518066

A Distributed Laboratory for Event-Driven Coastal Prediction and Hazard Planning

NASA Astrophysics Data System (ADS)

Bogden, P.; Allen, G.; MacLaren, J.; Creager, G. J.; Flournoy, L.; Sheng, Y. P.; Graber, H.; Graves, S.; Conover, H.; Luettich, R.; Perrie, W.; Ramakrishnan, L.; Reed, D. A.; Wang, H. V.

2006-12-01

The 2005 Atlantic hurricane season was the most active in recorded history. Collectively, 2005 hurricanes caused more than 2,280 deaths and record damages of over 100 billion dollars. Of the storms that made landfall, Dennis, Emily, Katrina, Rita, and Wilma caused most of the destruction. Accurate predictions of storm-driven surge, wave height, and inundation can save lives and help keep recovery costs down, provided the information gets to emergency response managers in time. The information must be available well in advance of landfall so that responders can weigh the costs of unnecessary evacuation against the costs of inadequate preparation. The SURA Coastal Ocean Observing and Prediction (SCOOP) Program is a multi-institution collaboration implementing a modular, distributed service-oriented architecture for real time prediction and visualization of the impacts of extreme atmospheric events. The modular infrastructure enables real-time prediction of multi- scale, multi-model, dynamic, data-driven applications. SURA institutions are working together to create a virtual and distributed laboratory integrating coastal models, simulation data, and observations with computational resources and high speed networks. The loosely coupled architecture allows teams of computer and coastal scientists at multiple institutions to innovate complex system components that are interconnected with relatively stable interfaces. The operational system standardizes at the interface level to enable substantial innovation by complementary communities of coastal and computer scientists. This architectural philosophy solves a long-standing problem associated with the transition from research to operations. The SCOOP Program thereby implements a prototype laboratory consistent with the vision of a national, multi-agency initiative called the Integrated Ocean Observing System (IOOS). Several service- oriented components of the SCOOP enterprise architecture have already been designed and implemented, including data archive and transport services, metadata registry and retrieval (catalog), resource management, and portal interfaces. SCOOP partners are integrating these at the service level and implementing reconfigurable workflows for several kinds of user scenarios, and are working with resource providers to prototype new policies and technologies for on-demand computing.

NASA Opportunities in Visualization, Art, and Science (NOVAS)

NASA Astrophysics Data System (ADS)

Fillingim, M. O.; Zevin, D.; Croft, S.; Thrall, L.; Raftery, C. L.; Shackelford, R. L., III

2014-12-01

Led by members of UC Berkeley's Multiverse education team at the Space Sciences Laboratory (http://multiverse.ssl.berkeley.edu/), in partnership with UC Berkeley Astronomy, NASA Opportunities in Visualization, Art and Science (NOVAS) is a NASA-funded program mainly for high school students that explores NASA science through art and highlights the need for and uses of art and visualizations in science. The project's aim is to motivate more diverse young people (especially African Americans) to consider Science, Technology, Engineering, and Mathematics (STEM) careers. The program offers intensive summer workshops at community youth centers, afterschool workshops at a local high school, a year-round internship for those who have taken part in one or more of our workshops, public and school outreach, and educator professional development workshops. By adding art (and multimedia) to STEM learning, we wanted to try a unique "STEAM" approach, highlighting how scientists and artists often collaborate, and why scientists need visualization experts. The program values the rise of the STEAM teaching concept, particularly that art and multimedia projects can help communicate science concepts more effectively. We also promote the fact that art and visualization skills can lead to jobs and broader participation in science, and we frequently work with and showcase scientific illustrators and other science visualization professionals.

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

PubMed Central

Kanwal, Nadia; Bostanci, Erkan; Currie, Keith; Clark, Adrian F.

2015-01-01

For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect's infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately. PMID:27057135

The Genome Portal of the Department of Energy Joint Genome Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nordberg, Henrik; Cantor, Michael; Dushekyo, Serge

2014-03-14

The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. Genome Portal in the past 2 years was significantly updated, with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI. A critical aspect of handling big data in genomics is the development of visualization and analysis tools that allow scientists to derive meaning from what are otherwise terrabases ofmore » inert sequence. An interactive visualization tool developed in the group allows us to explore contigs resulting from a single metagenome assembly. Implemented with modern web technologies that take advantage of the power of the computer's graphical processing unit (gpu), the tool allows the user to easily navigate over a 100,000 data points in multiple dimensions, among many biologically meaningful parameters of a dataset such as relative abundance, contig length, and G+C content.« less

Reverse Asteroids: Searching for an Effective Tool to Combat Asteroid Belt Misconceptions

NASA Astrophysics Data System (ADS)

Summers, F.; Eisenhamer, B.

2014-12-01

The public 'knows' that asteroid belts are densely packed and dangerous for spaceships to cross. Visuals from "Star Wars" to, unfortunately, the recent "Cosmos" TV series have firmly established this astronomical misconception. However, even scientifically correct graphics, such as the Minor Planet Center's plot of the inner solar system, reinforces that view. Each pixel in the image is more than a million kilometers in width, making an accurate representation of the object density impossible.To address this widespread misconception, we are investigating an educational exercise built around a computer interactive that we call "Reverse Asteroids". In the arcade classic video game, the asteroids came to the player's spaceship. For our reverse implementation, we consider an inquiry-based activity in which the spaceship must go hunting for the asteroids, using a database of real objects in our solar system. Both 3D data visualization and basic statistical analysis play crucial roles in bringing out the true space density within the asteroid belt, and perhaps a reconciliation between imagination and reality. We also emphasize that a partnership of scientists and educators is fundamental to the success of such projects.

Using Rose and Compass for Authentication

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, G

2009-07-09

Many recent non-proliferation software projects include a software authentication component. In this context, 'authentication' is defined as determining that a software package performs only its intended purpose and performs that purpose correctly and reliably over many years. In addition to visual inspection by knowledgeable computer scientists, automated tools are needed to highlight suspicious code constructs both to aid the visual inspection and to guide program development. While many commercial tools are available for portions of the authentication task, they are proprietary, and have limited extensibility. An open-source, extensible tool can be customized to the unique needs of each project. ROSEmore » is an LLNL-developed robust source-to-source analysis and optimization infrastructure currently addressing large, million-line DOE applications in C, C++, and FORTRAN. It continues to be extended to support the automated analysis of binaries (x86, ARM, and PowerPC). We continue to extend ROSE to address a number of security specific requirements and apply it to software authentication for non-proliferation projects. We will give an update on the status of our work.« less

Exploratory visualization software for reporting environmental survey results.

PubMed

Fisher, P; Arnot, C; Bastin, L; Dykes, J

2001-08-01

Environmental surveys yield three principal products: maps, a set of data tables, and a textual report. The relationships between these three elements, however, are often cumbersome to present, making full use of all the information in an integrated and systematic sense difficult. The published paper report is only a partial solution. Modern developments in computing, particularly in cartography, GIS, and hypertext, mean that it is increasingly possible to conceive of an easier and more interactive approach to the presentation of such survey results. Here, we present such an approach which links map and tabular datasets arising from a vegetation survey, allowing users ready access to a complex dataset using dynamic mapping techniques. Multimedia datasets equipped with software like this provide an exciting means of quick and easy visual data exploration and comparison. These techniques are gaining popularity across the sciences as scientists and decision-makers are presented with increasing amounts of diverse digital data. We believe that the software environment actively encourages users to make complex interrogations of the survey information, providing a new vehicle for the reader of an environmental survey report.

The IT in Secondary Science Book. A Compendium of Ideas for Using Computers and Teaching Science.

ERIC Educational Resources Information Center

Frost, Roger

Scientists need to measure and communicate, to handle information, and model ideas. In essence, they need to process information. Young scientists have the same needs. Computers have become a tremendously important addition to the processing of information through database use, graphing and modeling and also in the collection of information…

75 FR 64996 - Takes of Marine Mammals Incidental to Specified Activities; Marine Geophysical Survey in the...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-21

... cruises. A laptop computer is located on the observer platform for ease of data entry. The computer is... lines, the receiving systems will receive the returning acoustic signals. The study (e.g., equipment...-board assistance by the scientists who have proposed the study. The Chief Scientist is Dr. Franco...

eButterfly: Leveraging Massive Online Citizen Science for Butterfly Conservation

PubMed Central

Prudic, Kathleen L.; McFarland, Kent P.; Oliver, Jeffrey C.; Hutchinson, Rebecca A.; Long, Elizabeth C.; Kerr, Jeremy T.; Larrivée, Maxim

2017-01-01

Data collection, storage, analysis, visualization, and dissemination are changing rapidly due to advances in new technologies driven by computer science and universal access to the internet. These technologies and web connections place human observers front and center in citizen science-driven research and are critical in generating new discoveries and innovation in such fields as astronomy, biodiversity, and meteorology. Research projects utilizing a citizen science approach address scientific problems at regional, continental, and even global scales otherwise impossible for a single lab or even a small collection of academic researchers. Here we describe eButterfly an integrative checklist-based butterfly monitoring and database web-platform that leverages the skills and knowledge of recreational butterfly enthusiasts to create a globally accessible unified database of butterfly observations across North America. Citizen scientists, conservationists, policy makers, and scientists are using eButterfly data to better understand the biological patterns of butterfly species diversity and how environmental conditions shape these patterns in space and time. eButterfly in collaboration with thousands of butterfly enthusiasts has created a near real-time butterfly data resource producing tens of thousands of observations per year open to all to share and explore. PMID:28524117

Passengers on Voyages of Exploration: The Beautiful and Surprising Work Amateurs Can do with Raw Image Data from Planetary Missions

NASA Astrophysics Data System (ADS)

Lakdawalla, E. S.

2008-11-01

Many recent planetary science missions, including the Mars Exploration Rovers, Cassini-Huygens, and New Horizons, have instituted a policy of the rapid release of ``raw'' images to the Internet within days or even hours of their acquisition. The availability of these data, along with the increasing power of home computers and availability of high-bandwidth Internet connections, have stimulated the development of a worldwide community of armchair planetary scientists, who are able to participate in the everyday drama of exploratory missions' encounters with new worlds and new landscapes. Far from passive onlookers, many of these enthusiasts have taught themselves image processing techniques and have even written software to perform automated processing and mosaicking of these raw data sets. They rapidly produce stunning visualizations and then post them to their own blogs or online forums, where they also engage in discussing scientific observations and inferences about the data sets, broadening missions' public outreach efforts beyond their direct reach. These amateur space scientists feel a deep sense of involvement in and connection to space missions, which makes them enthusiastic (and occasionally demanding) supporters of space exploration.

A Web service-based architecture for real-time hydrologic sensor networks

NASA Astrophysics Data System (ADS)

Wong, B. P.; Zhao, Y.; Kerkez, B.

2014-12-01

Recent advances in web services and cloud computing provide new means by which to process and respond to real-time data. This is particularly true of platforms built for the Internet of Things (IoT). These enterprise-scale platforms have been designed to exploit the IP-connectivity of sensors and actuators, providing a robust means by which to route real-time data feeds and respond to events of interest. While powerful and scalable, these platforms have yet to be adopted by the hydrologic community, where the value of real-time data impacts both scientists and decision makers. We discuss the use of one such IoT platform for the purpose of large-scale hydrologic measurements, showing how rapid deployment and ease-of-use allows scientists to focus on their experiment rather than software development. The platform is hardware agnostic, requiring only IP-connectivity of field devices to capture, store, process, and visualize data in real-time. We demonstrate the benefits of real-time data through a real-world use case by showing how our architecture enables the remote control of sensor nodes, thereby permitting the nodes to adaptively change sampling strategies to capture major hydrologic events of interest.

eButterfly: Leveraging Massive Online Citizen Science for Butterfly Consevation.

PubMed

Prudic, Kathleen L; McFarland, Kent P; Oliver, Jeffrey C; Hutchinson, Rebecca A; Long, Elizabeth C; Kerr, Jeremy T; Larrivée, Maxim

2017-05-18

Data collection, storage, analysis, visualization, and dissemination are changing rapidly due to advances in new technologies driven by computer science and universal access to the internet. These technologies and web connections place human observers front and center in citizen science-driven research and are critical in generating new discoveries and innovation in such fields as astronomy, biodiversity, and meteorology. Research projects utilizing a citizen science approach address scientific problems at regional, continental, and even global scales otherwise impossible for a single lab or even a small collection of academic researchers. Here we describe eButterfly an integrative checklist-based butterfly monitoring and database web-platform that leverages the skills and knowledge of recreational butterfly enthusiasts to create a globally accessible unified database of butterfly observations across North America. Citizen scientists, conservationists, policy makers, and scientists are using eButterfly data to better understand the biological patterns of butterfly species diversity and how environmental conditions shape these patterns in space and time. eButterfly in collaboration with thousands of butterfly enthusiasts has created a near real-time butterfly data resource producing tens of thousands of observations per year open to all to share and explore.

FATES: a flexible analysis toolkit for the exploration of single-particle mass spectrometer data

NASA Astrophysics Data System (ADS)

Sultana, Camille M.; Cornwell, Gavin C.; Rodriguez, Paul; Prather, Kimberly A.

2017-04-01

Single-particle mass spectrometer (SPMS) analysis of aerosols has become increasingly popular since its invention in the 1990s. Today many iterations of commercial and lab-built SPMSs are in use worldwide. However, supporting analysis toolkits for these powerful instruments are outdated, have limited functionality, or are versions that are not available to the scientific community at large. In an effort to advance this field and allow better communication and collaboration between scientists, we have developed FATES (Flexible Analysis Toolkit for the Exploration of SPMS data), a MATLAB toolkit easily extensible to an array of SPMS designs and data formats. FATES was developed to minimize the computational demands of working with large data sets while still allowing easy maintenance, modification, and utilization by novice programmers. FATES permits scientists to explore, without constraint, complex SPMS data with simple scripts in a language popular for scientific numerical analysis. In addition FATES contains an array of data visualization graphic user interfaces (GUIs) which can aid both novice and expert users in calibration of raw data; exploration of the dependence of mass spectral characteristics on size, time, and peak intensity; and investigations of clustered data sets.

Familiarity Vs Trust: A Comparative Study of Domain Scientists' Trust in Visual Analytics and Conventional Analysis Methods.

PubMed

Dasgupta, Aritra; Lee, Joon-Yong; Wilson, Ryan; Lafrance, Robert A; Cramer, Nick; Cook, Kristin; Payne, Samuel

2017-01-01

Combining interactive visualization with automated analytical methods like statistics and data mining facilitates data-driven discovery. These visual analytic methods are beginning to be instantiated within mixed-initiative systems, where humans and machines collaboratively influence evidence-gathering and decision-making. But an open research question is that, when domain experts analyze their data, can they completely trust the outputs and operations on the machine-side? Visualization potentially leads to a transparent analysis process, but do domain experts always trust what they see? To address these questions, we present results from the design and evaluation of a mixed-initiative, visual analytics system for biologists, focusing on analyzing the relationships between familiarity of an analysis medium and domain experts' trust. We propose a trust-augmented design of the visual analytics system, that explicitly takes into account domain-specific tasks, conventions, and preferences. For evaluating the system, we present the results of a controlled user study with 34 biologists where we compare the variation of the level of trust across conventional and visual analytic mediums and explore the influence of familiarity and task complexity on trust. We find that despite being unfamiliar with a visual analytic medium, scientists seem to have an average level of trust that is comparable with the same in conventional analysis medium. In fact, for complex sense-making tasks, we find that the visual analytic system is able to inspire greater trust than other mediums. We summarize the implications of our findings with directions for future research on trustworthiness of visual analytic systems.

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research

PubMed Central

2014-01-01

Background A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. Results We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. Conclusions The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle. PMID:24684958

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter

PubMed Central

Schmitt, Marco

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science. PMID:28636619

Analysis of severe storm data

NASA Technical Reports Server (NTRS)

Hickey, J. S.

1983-01-01

The Mesoscale Analysis and Space Sensor (MASS) Data Management and Analysis System developed by Atsuko Computing International (ACI) on the MASS HP-1000 Computer System within the Systems Dynamics Laboratory of the Marshall Space Flight Center is described. The MASS Data Management and Analysis System was successfully implemented and utilized daily by atmospheric scientists to graphically display and analyze large volumes of conventional and satellite derived meteorological data. The scientists can process interactively various atmospheric data (Sounding, Single Level, Gird, and Image) by utilizing the MASS (AVE80) share common data and user inputs, thereby reducing overhead, optimizing execution time, and thus enhancing user flexibility, useability, and understandability of the total system/software capabilities. In addition ACI installed eight APPLE III graphics/imaging computer terminals in individual scientist offices and integrated them into the MASS HP-1000 Computer System thus providing significant enhancement to the overall research environment.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 19: Computer and information technology and aerospace knowledge diffusion

NASA Technical Reports Server (NTRS)

Pinelli, Thomas E.; Kennedy, John M.; Barclay, Rebecca O.; Bishop, Ann P.

1992-01-01

To remain a world leader in aerospace, the US must improve and maintain the professional competency of its engineers and scientists, increase the research and development (R&D) knowledge base, improve productivity, and maximize the integration of recent technological developments into the R&D process. How well these objectives are met, and at what cost, depends on a variety of factors, but largely on the ability of US aerospace engineers and scientists to acquire and process the results of federally funded R&D. The Federal Government's commitment to high speed computing and networking systems presupposes that computer and information technology will play a major role in the aerospace knowledge diffusion process. However, we know little about information technology needs, uses, and problems within the aerospace knowledge diffusion process. The use of computer and information technology by US aerospace engineers and scientists in academia, government, and industry is reported.

Introduction to the Space Physics Analysis Network (SPAN)

NASA Technical Reports Server (NTRS)

Green, J. L. (Editor); Peters, D. J. (Editor)

1985-01-01

The Space Physics Analysis Network or SPAN is emerging as a viable method for solving an immediate communication problem for the space scientist. SPAN provides low-rate communication capability with co-investigators and colleagues, and access to space science data bases and computational facilities. The SPAN utilizes up-to-date hardware and software for computer-to-computer communications allowing binary file transfer and remote log-on capability to over 25 nationwide space science computer systems. SPAN is not discipline or mission dependent with participation from scientists in such fields as magnetospheric, ionospheric, planetary, and solar physics. Basic information on the network and its use are provided. It is anticipated that SPAN will grow rapidly over the next few years, not only from the standpoint of more network nodes, but as scientists become more proficient in the use of telescience, more capability will be needed to satisfy the demands.

Study on identifying deciduous forest by the method of feature space transformation

NASA Astrophysics Data System (ADS)

Zhang, Xuexia; Wu, Pengfei

2009-10-01

The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

Big Data Ecosystems Enable Scientific Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Critchlow, Terence J.; Kleese van Dam, Kerstin

Over the past 5 years, advances in experimental, sensor and computational technologies have driven the exponential growth in the volumes, acquisition rates, variety and complexity of scientific data. As noted by Hey et al in their 2009 e-book The Fourth Paradigm, this availability of large-quantities of scientifically meaningful data has given rise to a new scientific methodology - data intensive science. Data intensive science is the ability to formulate and evaluate hypotheses using data and analysis to extend, complement and, at times, replace experimentation, theory, or simulation. This new approach to science no longer requires scientists to interact directly withmore » the objects of their research; instead they can utilize digitally captured, reduced, calibrated, analyzed, synthesized and visualized results - allowing them carry out 'experiments' in data.« less

Synergy Between Archives, VO, and the Grid at ESAC

NASA Astrophysics Data System (ADS)

Arviset, C.; Alvarez, R.; Gabriel, C.; Osuna, P.; Ott, S.

2011-07-01

Over the years, in support to the Science Operations Centers at ESAC, we have set up two Grid infrastructures. These have been built: 1) to facilitate daily research for scientists at ESAC, 2) to provide high computing capabilities for project data processing pipelines (e.g., Herschel), 3) to support science operations activities (e.g., calibration monitoring). Furthermore, closer collaboration between the science archives, the Virtual Observatory (VO) and data processing activities has led to an other Grid use case: the Remote Interface to XMM-Newton SAS Analysis (RISA). This web service-based system allows users to launch SAS tasks transparently to the GRID, save results on http-based storage and visualize them through VO tools. This paper presents real and operational use cases of Grid usages in these contexts

Oceanography for the Visually Impaired

ERIC Educational Resources Information Center

Fraser, Kate

2008-01-01

Amy Bower is a physical oceanographer and senior scientist at the Woods Hole Oceanographic Institution (WHOI) in Woods Hole, Massachusetts--she has also been legally blind for 14 years. Through her partnership with the Perkins School for the Blind in Watertown, Massachusetts, the oldest K-12 school for the visually impaired in the United States,…

How Visualizing Ecosystem Land Management Assessments (VELMA) modeling quantifies co-benefits and tradeoffs in Community Forest management

EPA Science Inventory

The Northwest Community Forest Coalition invited EPA-WED Research Scientist Bob McKane to present the Keynote Address for the 2018 Northwest Community Forest Forum on May 9‐11 in Astoria, OR. His address will describe "How Visualizing Ecosystem Land Management Assessme...

Visually Determined Soil Disturbance Classes Used as Indices of Forest Harvesting Disturbance

Treesearch

W. Michael Aust; James A. Burger; Emily A. Carter; David P. Preston; Steven C. Patterson

1998-01-01

Visual estimates of soil and site disturbances are used by foresters, soil scientists, logging supervisors. and machinery operators to minimize harvest disturbances to forest sites, to evaluate compliance with forestry Best Management Practices (BMPs), and to determine the need for ameliorative practices such as tnechanical site preparation. Although estimates are...

Development and methods for an open-sourced data visualization tool

USDA-ARS?s Scientific Manuscript database

This paper presents an open source on-demand web tool, which is specifically addressed to scientists and researchers that are non-expert in converting time series data into a time surface visualization. Similar to a GIS environment the time surface shows time on two axes; time of day vs. day of year...

KML-Based Access and Visualization of High Resolution LiDAR Topography

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Blair, J. L.; Nandigam, V.; Memon, A.; Baru, C.; Arrowsmith, J. R.

2008-12-01

Over the past decade, there has been dramatic growth in the acquisition of LiDAR (Light Detection And Ranging) high-resolution topographic data for earth science studies. Capable of providing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LiDAR data allow earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible yet essential for their appropriate representation. These datasets also have significant implications for earth science education and outreach because they provide an accurate representation of landforms and geologic hazards. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To make these data available to a larger user community, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to provide access to LiDAR data products and visualizations. LiDAR digital elevation models are typically delivered in a tiled format that lends itself well to a KML-based distribution system. For LiDAR datasets hosted in the GEON OpenTopography Portal (www.opentopography.org) we have developed KML files that show the extent of available LiDAR DEMs and provide direct access to the data products. Users interact with these KML files to explore the extent of the available data and are able to select DEMs that correspond to their area of interest. Selection of a tile loads a download that the user can then save locally for analysis in their software of choice. The GEON topography system also has tools available that allow users to generate custom DEMs from LiDAR point cloud data. This system is powerful because it enables users to access massive volumes of raw LiDAR data and to produce DEM products that are optimized to their science applications. We have developed a web service that converts the custom DEM models produced by the system to a hillshade that is delivered to the user as a KML groundoverlay. The KML product enables users to quickly and easily visualize the DEMs in Google Earth. By combining internet-based LiDAR data processing with KML visualization products, users are able to execute computationally intensive data sub-setting, processing and visualization without having local access to computing resources, GIS software, or data processing expertise. Finally, GEON has partnered with the US Geological Survey to generate region-dependant network linked KML visualizations for large volumes of LiDAR derived hillshades of the Northern San Andreas fault system. These data, acquired by the NSF-funded GeoEarthScope project, offer an unprecedented look at active faults in the northern portion of the San Andreas system. Through the region-dependant network linked KML, users can seamlessly access 1 meter hillshades (both 315 and 45 degree sun angles) for the full 1400 square kilometer dataset, without downloading huge volumes of data. This type of data access has great utility for users ranging from earthquake scientists to K-12 educators who wish to introduce cutting edge real world data into their earth science lessons.

Exploring Visual Evidence of Human Impact on the Environment with Planetary-Scale Zoomable Timelapse Video

NASA Astrophysics Data System (ADS)

Sargent, R.; Egge, M.; Dille, P. S.; O'Donnell, G. D.; Herwig, C.

2016-12-01

Visual evidence ignites curiosity and inspires advocacy. Zoomable imagery and video on a planetary scale provides compelling evidence of human impact on the environment. Earth Timelapse places the observable impact of 30+ years of human activity into the hands of policy makers, scientists, and advocates, with fluidity and speed that supports inquiry and exploration. Zoomability enables compelling narratives and ready apprehension of environmental changes, connecting human-scale evidence to regional and ecosystem-wide trends and changes. Leveraging the power of Google Earth Engine, join us to explore 30+ years of Landset 30m RGB imagery showing glacial retreat, agricultural deforestation, irrigation expansion, and the disappearance of lakes. These narratives are enriched with datasets showing planetary forest gain/loss, annual cycles of agricultural fires, global changes in the health of coral reefs, trends in resource extraction, and of renewable energy development. We demonstrate the intuitive and inquiry-enabling power of these planetary visualizations, and provide instruction on how scientists and advocates can create and share or contribute visualizations of their own research or topics of interest.

Visualisation methods for large provenance collections in data-intensive collaborative platforms

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Fligueira, Rosa; Atkinson, Malcolm; Gemuend, Andre

2016-04-01

This work investigates improving the methods of visually representing provenance information in the context of modern data-driven scientific research. It explores scenarios where data-intensive workflows systems are serving communities of researchers within collaborative environments, supporting the sharing of data and methods, and offering a variety of computation facilities, including HPC, HTC and Cloud. It focuses on the exploration of big-data visualization techniques aiming at producing comprehensive and interactive views on top of large and heterogeneous provenance data. The same approach is applicable to control-flow and data-flow workflows or to combinations of the two. This flexibility is achieved using the W3C-PROV recommendation as a reference model, especially its workflow oriented profiles such as D-PROV (Messier et al. 2013). Our implementation is based on the provenance records produced by the dispel4py data-intensive processing library (Filgueira et al. 2015). dispel4py is an open-source Python framework for describing abstract stream-based workflows for distributed data-intensive applications, developed during the VERCE project. dispel4py enables scientists to develop their scientific methods and applications on their laptop and then run them at scale on a wide range of e-Infrastructures (Cloud, Cluster, etc.) without making changes. Users can therefore focus on designing their workflows at an abstract level, describing actions, input and output streams, and how they are connected. The dispel4py system then maps these descriptions to the enactment platforms, such as MPI, Storm, multiprocessing. It provides a mechanism which allows users to determine the provenance information to be collected and to analyze it at runtime. For this work we consider alternative visualisation methods for provenance data, from infinite lists and localised interactive graphs, to radial-views. The latter technique has been positively explored in many fields, from text data visualisation to genomics and social networking analysis. Its adoption for provenance has been presented in literature (Borkin et al. 2013) in the context of parent-child relationships across processes, constructed from control-flow information. Computer graphics research has focused on the advantage of this radial distribution of interlinked information and on ways to improve the visual efficiency and tunability of such representations, like the Hierarchical Edge Bundles visualisation method, (Holten et al. 2006), which aims at reducing visual clutter of highly connected structures via the generation of bundles. Our approach explores the potential of the combination of these methods. It serves environments where the size of the provenance collection, coupled with the diversity of the infrastructures and the domain metadata, make the extrapolation of usage trends extremely challenging. Applications of such visualisation systems can engage groups of scientists, data providers and computational engineers, by serving visual snapshots that highlight relationships between an item and its connected processes. We will present examples of comprehensive views on the distribution of processing and data transfers during a workflow's execution in HPC, as well as cross workflows interactions and internal dynamics. The latter in the context of faceted searches on domain metadata values-range. These are obtained from the analysis of real provenance data generated by the processing of seismic traces performed through the VERCE platform.

Picturing the Earth: Geoscience in Public Art Abstract for AGU 2013: Geoscience through the Lens of Art. Author: Stacy Levy, Sere Ltd., Spring Mills, PA (Invited)

NASA Astrophysics Data System (ADS)

Levy, S.

2013-12-01

Public places such as parks, urban plazas, transportation centers and educational institutions offer the opportunity to reach many people in the course of daily life. Yet these public spaces are often devoid of any substantive information about the local environment and natural processes that have shaped it. Art is a particularly effective means to visualize environmental phenomena. Art has the ability to translate the processes of nature into visual information that communicates with clarity and beauty. People often have no connection to the world through which they walk: no sense of their place in the local watershed or where the rainwater goes once it hits the ground. Creating an awareness of place is critical first step for people to understand the changes in their world. Art can be a gateway for understanding geo-scientific concepts that are not frequently made accessible in a visual manner And art requires scientific knowledge to inform an accurate visualization of nature. Artists must collaborate with scientists in order to create art that informs the public about environmental processes. There is a new current in the design world that combines art and technology to create artful solutions to site issues such as storm water runoff, periodic flooding and habitat destruction. Instead of being considered functionless, art is now given a chance to do some real work on the site. This new combination of function and aesthetic concerns will have a major impact on how site issues are perceived. Site concerns that were once considered obstacles can become opportunities to visualize and celebrate how problems can be solved. This sort of artful solutions requires teamwork across many disciplines. In my presentation I will speak about various ways of I have visualized the invisible processes of the natural world in my projects. I will share eight of my permanent and temporary art commissions that are collaborations with scientists and engineers. These works reveal wetland habitats, tides, prevailing winds, rain and microorganisms, and water pollution. In examining each project I will detail the essential collaborations with scientists and engineers that brought the projects to fruition. I will discuss how the cross-discipline approach of scientists, engineers and designers made effective and artful solutions to site issues, and created visually stimulating and educational places. I will also look at the role of truth and metaphor in art and compare how accuracy and data collection have differing thresholds in art and in science.

Measurement of cognitive performance in computer programming concept acquisition: interactive effects of visual metaphors and the cognitive style construct.

PubMed

McKay, E

2000-01-01

An innovative research program was devised to investigate the interactive effect of instructional strategies enhanced with text-plus-textual metaphors or text-plus-graphical metaphors, and cognitive style on the acquisition of programming concepts. The Cognitive Styles Analysis (CSA) program (Riding,1991) was used to establish the participants' cognitive style. The QUEST Interactive Test Analysis System (Adams and Khoo,1996) provided the cognitive performance measuring tool, which ensured an absence of error measurement in the programming knowledge testing instruments. Therefore, reliability of the instrumentation was assured through the calibration techniques utilized by the QUEST estimate; providing predictability of the research design. A means analysis of the QUEST data, using the Cohen (1977) approach to size effect and statistical power further quantified the significance of the findings. The experimental methodology adopted for this research links the disciplines of instructional science, cognitive psychology, and objective measurement to provide reliable mechanisms for beneficial use in the evaluation of cognitive performance by the education, training and development sectors. Furthermore, the research outcomes will be of interest to educators, cognitive psychologists, communications engineers, and computer scientists specializing in computer-human interactions.

Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible

DOE Office of Scientific and Technical Information (OSTI.GOV)

Venkatakrishnan, S. V.; Mohan, K. Aditya; Beattie, Keith

2016-02-14

Synchrotrons such as the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory are known as user facilities. They are sources of extremely bright X-ray beams, and scientists come from all over the world to perform experiments that require these beams. As the complexity of experiments has increased, and the size and rates of data sets has exploded, managing, analyzing and presenting the data collected at synchrotrons has been an increasing challenge. The ALS has partnered with high performance computing, fast networking, and applied mathematics groups to create a"super-facility", giving users simultaneous access to the experimental, computational, and algorithmic resourcesmore » to overcome this challenge. This combination forms an efficient closed loop, where data despite its high rate and volume is transferred and processed, in many cases immediately and automatically, on appropriate compute resources, and results are extracted, visualized, and presented to users or to the experimental control system, both to provide immediate insight and to guide decisions about subsequent experiments during beam-time. In this paper, We will present work done on advanced tomographic reconstruction algorithms to support users of the 3D micron-scale imaging instrument (Beamline 8.3.2, hard X-ray micro-tomography).« less

Most Social Scientists Shun Free Use of Supercomputers.

ERIC Educational Resources Information Center

Kiernan, Vincent

1998-01-01

Social scientists, who frequently complain that the federal government spends too little on them, are passing up what scholars in the physical and natural sciences see as the government's best give-aways: free access to supercomputers. Some social scientists say the supercomputers are difficult to use; others find desktop computers provide…

The Unified English Braille Code: Examination by Science, Mathematics, and Computer Science Technical Expert Braille Readers

ERIC Educational Resources Information Center

Holbrook, M. Cay; MacCuspie, P. Ann

2010-01-01

Braille-reading mathematicians, scientists, and computer scientists were asked to examine the usability of the Unified English Braille Code (UEB) for technical materials. They had little knowledge of the code prior to the study. The research included two reading tasks, a short tutorial about UEB, and a focus group. The results indicated that the…

Integrating and Visualizing Tropical Cyclone Data Using the Real Time Mission Monitor

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Blakeslee, Richard; Conover, Helen; Hall, John; He, Yubin; Regner, Kathryn

2009-01-01

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the NASA Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM is extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, scientists, and managers appreciate the contributions that RTMM makes to their flight projects. A broad spectrum of interdisciplinary scientists used RTMM during field campaigns including the hurricane-focused 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 NOAA-NASA Aerosonde Hurricane Noel flight, 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), plus a soil moisture (SMAP-VEX) and two arctic research experiments (ARCTAS) in 2008. Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated "on the fly". The resultant flight plan is then immediately posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and subsequently compare it to the actual real time flight progress. We are planning additional capabilities to RTMM including collaborations with the Jet Propulsion Laboratory in the joint development of a Tropical Cyclone Integrated Data Exchange and Analysis System (TC IDEAS) which will serve as a web portal for access to tropical cyclone data, visualizations and model output.

The global lambda visualization facility: An international ultra-high-definition wide-area visualization collaboratory

USGS Publications Warehouse

Leigh, J.; Renambot, L.; Johnson, Aaron H.; Jeong, B.; Jagodic, R.; Schwarz, N.; Svistula, D.; Singh, R.; Aguilera, J.; Wang, X.; Vishwanath, V.; Lopez, B.; Sandin, D.; Peterka, T.; Girado, J.; Kooima, R.; Ge, J.; Long, L.; Verlo, A.; DeFanti, T.A.; Brown, M.; Cox, D.; Patterson, R.; Dorn, P.; Wefel, P.; Levy, S.; Talandis, J.; Reitzer, J.; Prudhomme, T.; Coffin, T.; Davis, B.; Wielinga, P.; Stolk, B.; Bum, Koo G.; Kim, J.; Han, S.; Corrie, B.; Zimmerman, T.; Boulanger, P.; Garcia, M.

2006-01-01

The research outlined in this paper marks an initial global cooperative effort between visualization and collaboration researchers to build a persistent virtual visualization facility linked by ultra-high-speed optical networks. The goal is to enable the comprehensive and synergistic research and development of the necessary hardware, software and interaction techniques to realize the next generation of end-user tools for scientists to collaborate on the global Lambda Grid. This paper outlines some of the visualization research projects that were demonstrated at the iGrid 2005 workshop in San Diego, California.

Science Opportunity Analyzer (SOA) Version 8

NASA Technical Reports Server (NTRS)

Witoff, Robert J.; Polanskey, Carol A.; Aguinaldo, Anna Marie A.; Liu, Ning; Hofstadter, Mark D.

2013-01-01

SOA allows scientists to plan spacecraft observations. It facilitates the identification of geometrically interesting times in a spacecraft s orbit that a user can use to plan observations or instrument-driven spacecraft maneuvers. These observations can then be visualized multiple ways in both two- and three-dimensional views. When observations have been optimized within a spacecraft's flight rules, the resulting plans can be output for use by other JPL uplink tools. Now in its eighth major version, SOA improves on these capabilities in a modern and integrated fashion. SOA consists of five major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, and Data Output. Opportunity Search is a GUI-driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last-minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily assess the cost to science if flight rule changes occur. Data Output allows the user to compute ancillary data related to an observation or to a given position of the spacecraft along its trajectory. The data can be saved as a tab-delimited text file or viewed as a graph. SOA combines science planning functionality unique to both JPL and the sponsoring spacecraft. SOA is able to ingest JPL SPICE Kernels that are used to drive the tool and its computations. A Percy search engine is then included that identifies interesting time periods for the user to build observations. When observations are then built, flight-like orientation algorithms replicate spacecraft dynamics to closely simulate the flight spacecraft s dynamics. SOA v8 represents large steps forward from SOA v7 in terms of quality, reliability, maintainability, efficiency, and user experience. A tailored agile development environment has been built around SOA that provides automated unit testing, continuous build and integration, a consolidated Web-based code and documentation storage environment, modern Java enhancements, and a focus on usability

Trend-Centric Motion Visualization: Designing and Applying a New Strategy for Analyzing Scientific Motion Collections.

PubMed

Schroeder, David; Korsakov, Fedor; Knipe, Carissa Mai-Ping; Thorson, Lauren; Ellingson, Arin M; Nuckley, David; Carlis, John; Keefe, Daniel F

2014-12-01

In biomechanics studies, researchers collect, via experiments or simulations, datasets with hundreds or thousands of trials, each describing the same type of motion (e.g., a neck flexion-extension exercise) but under different conditions (e.g., different patients, different disease states, pre- and post-treatment). Analyzing similarities and differences across all of the trials in these collections is a major challenge. Visualizing a single trial at a time does not work, and the typical alternative of juxtaposing multiple trials in a single visual display leads to complex, difficult-to-interpret visualizations. We address this problem via a new strategy that organizes the analysis around motion trends rather than trials. This new strategy matches the cognitive approach that scientists would like to take when analyzing motion collections. We introduce several technical innovations making trend-centric motion visualization possible. First, an algorithm detects a motion collection's trends via time-dependent clustering. Second, a 2D graphical technique visualizes how trials leave and join trends. Third, a 3D graphical technique, using a median 3D motion plus a visual variance indicator, visualizes the biomechanics of the set of trials within each trend. These innovations are combined to create an interactive exploratory visualization tool, which we designed through an iterative process in collaboration with both domain scientists and a traditionally-trained graphic designer. We report on insights generated during this design process and demonstrate the tool's effectiveness via a validation study with synthetic data and feedback from expert musculoskeletal biomechanics researchers who used the tool to analyze the effects of disc degeneration on human spinal kinematics.

Meet EPA Scientist Valerie Zartarian, Ph.D.

EPA Pesticide Factsheets

Senior exposure scientist and research environmental engineer Valerie Zartarian, Ph.D. helps build computer models and other tools that advance our understanding of how people interact with chemicals.

Hot, Hot, Hot Computer Careers.

ERIC Educational Resources Information Center

Basta, Nicholas

1988-01-01

Discusses the increasing need for electrical, electronic, and computer engineers; and scientists. Provides current status of the computer industry and average salaries. Considers computer chip manufacture and the current chip shortage. (MVL)

SAVS: A Space and Atmospheric Visualization Science system

NASA Technical Reports Server (NTRS)

Szuszczewicz, E. P.; Mankofsky, A.; Blanchard, P.; Goodrich, C.; McNabb, D.; Kamins, D.

1995-01-01

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Effects of VR system fidelity on analyzing isosurface visualization of volume datasets.

PubMed

Laha, Bireswar; Bowman, Doug A; Socha, John J

2014-04-01

Volume visualization is an important technique for analyzing datasets from a variety of different scientific domains. Volume data analysis is inherently difficult because volumes are three-dimensional, dense, and unfamiliar, requiring scientists to precisely control the viewpoint and to make precise spatial judgments. Researchers have proposed that more immersive (higher fidelity) VR systems might improve task performance with volume datasets, and significant results tied to different components of display fidelity have been reported. However, more information is needed to generalize these results to different task types, domains, and rendering styles. We visualized isosurfaces extracted from synchrotron microscopic computed tomography (SR-μCT) scans of beetles, in a CAVE-like display. We ran a controlled experiment evaluating the effects of three components of system fidelity (field of regard, stereoscopy, and head tracking) on a variety of abstract task categories that are applicable to various scientific domains, and also compared our results with those from our prior experiment using 3D texture-based rendering. We report many significant findings. For example, for search and spatial judgment tasks with isosurface visualization, a stereoscopic display provides better performance, but for tasks with 3D texture-based rendering, displays with higher field of regard were more effective, independent of the levels of the other display components. We also found that systems with high field of regard and head tracking improve performance in spatial judgment tasks. Our results extend existing knowledge and produce new guidelines for designing VR systems to improve the effectiveness of volume data analysis.

Of the Helmholtz Club, South-Californian seedbed for visual and cognitive neuroscience, and its patron Francis Crick

PubMed Central

Aicardi, Christine

2014-01-01

Taking up the view that semi-institutional gatherings such as clubs, societies, research schools, have been instrumental in creating sheltered spaces from which many a 20th-century project-driven interdisciplinary research programme could develop and become established within the institutions of science, the paper explores the history of one such gathering from its inception in the early 1980s into the 2000s, the Helmholtz Club, which brought together scientists from such various research fields as neuroanatomy, neurophysiology, psychophysics, computer science and engineering, who all had an interest in the study of the visual system and of higher cognitive functions relying on visual perception such as visual consciousness. It argues that British molecular biologist turned South Californian neuroscientist Francis Crick had an early and lasting influence over the Helmholtz Club of which he was a founding pillar, and that from its inception, the club served as a constitutive element in his long-term plans for a neuroscience of vision and of cognition. Further, it argues that in this role, the Helmholtz Club served many purposes, the primary of which was to be a social forum for interdisciplinary discussion, where ‘discussion’ was not mere talk but was imbued with an epistemic value and as such, carefully cultivated. Finally, it questions what counts as ‘doing science’ and in turn, definitions of success and failure—and provides some material evidence towards re-appraising the successfulness of Crick’s contribution to the neurosciences. PMID:24384229

Harnessing vision for computation.

PubMed

Changizi, Mark

2008-01-01

Might it be possible to harness the visual system to carry out artificial computations, somewhat akin to how DNA has been harnessed to carry out computation? I provide the beginnings of a research programme attempting to do this. In particular, new techniques are described for building 'visual circuits' (or 'visual software') using wire, NOT, OR, and AND gates in a visual 6modality such that our visual system acts as 'visual hardware' computing the circuit, and generating a resultant perception which is the output.

Cognitive and psychological science insights to improve climate change data visualization

NASA Astrophysics Data System (ADS)

Harold, Jordan; Lorenzoni, Irene; Shipley, Thomas F.; Coventry, Kenny R.

2016-12-01

Visualization of climate data plays an integral role in the communication of climate change findings to both expert and non-expert audiences. The cognitive and psychological sciences can provide valuable insights into how to improve visualization of climate data based on knowledge of how the human brain processes visual and linguistic information. We review four key research areas to demonstrate their potential to make data more accessible to diverse audiences: directing visual attention, visual complexity, making inferences from visuals, and the mapping between visuals and language. We present evidence-informed guidelines to help climate scientists increase the accessibility of graphics to non-experts, and illustrate how the guidelines can work in practice in the context of Intergovernmental Panel on Climate Change graphics.

Building effective learning experiences around visualizations: NASA Eyes on the Solar System and Infiniscope

NASA Astrophysics Data System (ADS)

Tamer, A. J. J.; Anbar, A. D.; Elkins-Tanton, L. T.; Klug Boonstra, S.; Mead, C.; Swann, J. L.; Hunsley, D.

2017-12-01

Advances in scientific visualization and public access to data have transformed science outreach and communication, but have yet to realize their potential impacts in the realm of education. Computer-based learning is a clear bridge between visualization and education, but creating high-quality learning experiences that leverage existing visualizations requires close partnerships among scientists, technologists, and educators. The Infiniscope project is working to foster such partnerships in order to produce exploration-driven learning experiences around NASA SMD data and images, leveraging the principles of ETX (Education Through eXploration). The visualizations inspire curiosity, while the learning design promotes improved reasoning skills and increases understanding of space science concepts. Infiniscope includes both a web portal to host these digital learning experiences, as well as a teaching network of educators using and modifying these experiences. Our initial efforts to enable student discovery through active exploration of the concepts associated with Small Worlds, Kepler's Laws, and Exoplanets led us to develop our own visualizations at Arizona State University. Other projects focused on Astrobiology and Mars geology led us to incorporate an immersive Virtual Field Trip platform into the Infiniscope portal in support of virtual exploration of scientifically significant locations. Looking to apply ETX design practices with other visualizations, our team at Arizona State partnered with the Jet Propulsion Lab to integrate the web-based version of NASA Eyes on the Eclipse within Smart Sparrow's digital learning platform in a proof-of-concept focused on the 2017 Eclipse. This goes a step beyond the standard features of "Eyes" by wrapping guided exploration, focused on a specific learning goal into standards-aligned lesson built around the visualization, as well as its distribution through Infiniscope and it's digital teaching network. Experience from this development effort has laid the groundwork to explore future integrations with JPL and other NASA partners.

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

SciFlo: Semantically-Enabled Grid Workflow for Collaborative Science

NASA Astrophysics Data System (ADS)

Yunck, T.; Wilson, B. D.; Raskin, R.; Manipon, G.

2005-12-01

SciFlo is a system for Scientific Knowledge Creation on the Grid using a Semantically-Enabled Dataflow Execution Environment. SciFlo leverages Simple Object Access Protocol (SOAP) Web Services and the Grid Computing standards (WS-* standards and the Globus Alliance toolkits), and enables scientists to do multi-instrument Earth Science by assembling reusable SOAP Services, native executables, local command-line scripts, and python codes into a distributed computing flow (a graph of operators). SciFlo's XML dataflow documents can be a mixture of concrete operators (fully bound operations) and abstract template operators (late binding via semantic lookup). All data objects and operators can be both simply typed (simple and complex types in XML schema) and semantically typed using controlled vocabularies (linked to OWL ontologies such as SWEET). By exploiting ontology-enhanced search and inference, one can discover (and automatically invoke) Web Services and operators that have been semantically labeled as performing the desired transformation, and adapt a particular invocation to the proper interface (number, types, and meaning of inputs and outputs). The SciFlo client & server engines optimize the execution of such distributed data flows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The scientist injects a distributed computation into the Grid by simply filling out an HTML form or directly authoring the underlying XML dataflow document, and results are returned directly to the scientist's desktop. A Visual Programming tool is also being developed, but it is not required. Once an analysis has been specified for a granule or day of data, it can be easily repeated with different control parameters and over months or years of data. SciFlo uses and preserves semantics, and also generates and infers new semantic annotations. Specifically, the SciFlo engine uses semantic metadata to understand (infer) what it is doing and potentially improve the data flow; preserves semantics by saving links to the semantics of (metadata describing) the input datasets, related datasets, and the data transformations (algorithms) used to generate downstream products; generates new metadata by allowing the user to add semantic annotations to the generated data products (or simply accept automatically generated provenance annotations); and infers new semantic metadata by understanding and applying logic to the semantics of the data and the transformations performed. Much ontology development still needs to be done but, nevertheless, SciFlo documents provide a substrate for using and preserving more semantics as ontologies develop. We will give a live demonstration of the growing SciFlo network using an example dataflow in which atmospheric temperature and water vapor profiles from three Earth Observing System (EOS) instruments are retrieved using SOAP (geo-location query & data access) services, co-registered, and visually & statistically compared on demand (see http://sciflo.jpl.nasa.gov for more information).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankar, Arjun

Computer scientist Arjun Shankar is director of the Compute and Data Environment for Science (CADES), ORNL’s multidisciplinary big data computing center. CADES offers computing, networking and data analytics to facilitate workflows for both ORNL and external research projects.

Jungle Computing: Distributed Supercomputing Beyond Clusters, Grids, and Clouds

NASA Astrophysics Data System (ADS)

Seinstra, Frank J.; Maassen, Jason; van Nieuwpoort, Rob V.; Drost, Niels; van Kessel, Timo; van Werkhoven, Ben; Urbani, Jacopo; Jacobs, Ceriel; Kielmann, Thilo; Bal, Henri E.

In recent years, the application of high-performance and distributed computing in scientific practice has become increasingly wide spread. Among the most widely available platforms to scientists are clusters, grids, and cloud systems. Such infrastructures currently are undergoing revolutionary change due to the integration of many-core technologies, providing orders-of-magnitude speed improvements for selected compute kernels. With high-performance and distributed computing systems thus becoming more heterogeneous and hierarchical, programming complexity is vastly increased. Further complexities arise because urgent desire for scalability and issues including data distribution, software heterogeneity, and ad hoc hardware availability commonly force scientists into simultaneous use of multiple platforms (e.g., clusters, grids, and clouds used concurrently). A true computing jungle.

Data-Intensive Scientific Management, Analysis and Visualization

NASA Astrophysics Data System (ADS)

Goranova, Mariana; Shishedjiev, Bogdan; Juliana Georgieva, Juliana

2012-11-01

The proposed integrated system provides a suite of services for data-intensive sciences that enables scientists to describe, manage, analyze and visualize data from experiments and numerical simulations in distributed and heterogeneous environment. This paper describes the advisor and the converter services and presents an example from the monitoring of the slant column content of atmospheric minor gases.

Applying Dataflow Architecture and Visualization Tools to In Vitro Pharmacology Data Automation.

PubMed

Pechter, David; Xu, Serena; Kurtz, Marc; Williams, Steven; Sonatore, Lisa; Villafania, Artjohn; Agrawal, Sony

2016-12-01

The pace and complexity of modern drug discovery places ever-increasing demands on scientists for data analysis and interpretation. Data flow programming and modern visualization tools address these demands directly. Three different requirements-one for allosteric modulator analysis, one for a specialized clotting analysis, and one for enzyme global progress curve analysis-are reviewed, and their execution in a combined data flow/visualization environment is outlined. © 2016 Society for Laboratory Automation and Screening.

`Let your data tell a story:' climate change experts and students navigating disciplinary argumentation in the classroom

NASA Astrophysics Data System (ADS)

Walsh, Elizabeth Mary; McGowan, Veronica Cassone

2017-01-01

Science education trends promote student engagement in authentic knowledge in practice to tackle personally consequential problems. This study explored how partnering scientists and students on a social media platform supported students' development of disciplinary practice knowledge through practice-based learning with experts during two pilot enactments of a project-based curriculum focusing on the ecological impacts of climate change. Through the online platform, scientists provided feedback on students' infographics, visual argumentation artifacts that use data to communicate about climate change science. We conceptualize the infographics and professional data sets as boundary objects that supported authentic argumentation practices across classroom and professional contexts, but found that student generated data was not robust enough to cross these boundaries. Analysis of the structure and content of the scientists' feedback revealed that when critiquing argumentation, scientists initiated engagement in multiple scientific practices, supporting a holistic rather than discrete model of practice-based learning. While traditional classroom inquiry has emphasized student experimentation, we found that engagement with existing professional data sets provided students with a platform for developing expertise in systemic scientific practices during argument construction. We further found that many students increased the complexity and improved the visual presentation of their arguments after feedback.

Sonification of Climate Data

NASA Astrophysics Data System (ADS)

Vogt, Katharina; Visda, Goudarzi

2013-04-01

Sonification is the acoustic analogue of data visualization and takes advantage of human perceptual and cognitive capabilities. The amount of data being processed today is steadily increasing, and both scientists and society need new ways to understand scientific data and their implications. Sonification is especially suited to the preliminary exploration of complex, dynamic, and multidimensional data sets, as can be found in climate science. In the research project SysSon (https://sysson.kug.ac.at/), we apply a systematic approach to design sonifications to climate data. In collaboration with the Wegener Center for Climate and Global Change (http://www.wegcenter.at/) we assessed the metaphors climate scientists use and their typical workflows, and chose data sets where sonification has high potential revealing new phenomena. This background will be used to develop an audio interface which is directly linked to the visualization interfaces for data analysis the scientists use today. The protoype will be evaluated according to its functionality, intuitivity for climate scientists, and aesthetic criteria. In the current stage of the project, conceptual links between climate science and sound have been elaborated and first sonification designs have been developed. The research is mainly carried out at the Institute of Electronic Music and Acoustics (http://iem.kug.ac.at/), which has extensive experience in interactive sonification with multidimensional data sets.

Supporting the scientific lifecycle through cloud services

NASA Astrophysics Data System (ADS)

Gensch, S.; Klump, J. F.; Bertelmann, R.; Braune, C.

2014-12-01

Cloud computing has made resources and applications available for numerous use cases ranging from business processes in the private sector to scientific applications. Developers have created tools for data management, collaborative writing, social networking, data access and visualization, project management and many more; either for free or as paid premium services with additional or extended features. Scientists have begun to incorporate tools that fit their needs into their daily work. To satisfy specialized needs, some cloud applications specifically address the needs of scientists for sharing research data, literature search, laboratory documentation, or data visualization. Cloud services may vary in extent, user coverage, and inter-service integration and are also at risk of being abandonend or changed by the service providers making changes to their business model, or leaving the field entirely.Within the project Academic Enterprise Cloud we examine cloud based services that support the research lifecycle, using feature models to describe key properties in the areas of infrastructure and service provision, compliance to legal regulations, and data curation. Emphasis is put on the term Enterprise as to establish an academic cloud service provider infrastructure that satisfies demands of the research community through continious provision across the whole cloud stack. This could enable the research community to be independent from service providers regarding changes to terms of service and ensuring full control of its extent and usage. This shift towards a self-empowered scientific cloud provider infrastructure and its community raises implications about feasability of provision and overall costs. Legal aspects and licensing issues have to be considered, when moving data into cloud services, especially when personal data is involved.Educating researchers about cloud based tools is important to help in the transition towards effective and safe use. Scientists can benefit from the provision of standard services, like weblog and website creation, virtual machine deployments, and groupware provision using cloud based app store-like portals. And, other than in an industrial environment, researchers will want to keep their existing user profile when moving from one institution to another.

Developing a strategy for computational lab skills training through Software and Data Carpentry: Experiences from the ELIXIR Pilot action

PubMed Central

Pawlik, Aleksandra; van Gelder, Celia W.G.; Nenadic, Aleksandra; Palagi, Patricia M.; Korpelainen, Eija; Lijnzaad, Philip; Marek, Diana; Sansone, Susanna-Assunta; Hancock, John; Goble, Carole

2017-01-01

Quality training in computational skills for life scientists is essential to allow them to deliver robust, reproducible and cutting-edge research. A pan-European bioinformatics programme, ELIXIR, has adopted a well-established and progressive programme of computational lab and data skills training from Software and Data Carpentry, aimed at increasing the number of skilled life scientists and building a sustainable training community in this field. This article describes the Pilot action, which introduced the Carpentry training model to the ELIXIR community. PMID:28781745

Developing a strategy for computational lab skills training through Software and Data Carpentry: Experiences from the ELIXIR Pilot action.

PubMed

Pawlik, Aleksandra; van Gelder, Celia W G; Nenadic, Aleksandra; Palagi, Patricia M; Korpelainen, Eija; Lijnzaad, Philip; Marek, Diana; Sansone, Susanna-Assunta; Hancock, John; Goble, Carole

2017-01-01

Quality training in computational skills for life scientists is essential to allow them to deliver robust, reproducible and cutting-edge research. A pan-European bioinformatics programme, ELIXIR, has adopted a well-established and progressive programme of computational lab and data skills training from Software and Data Carpentry, aimed at increasing the number of skilled life scientists and building a sustainable training community in this field. This article describes the Pilot action, which introduced the Carpentry training model to the ELIXIR community.

Media and the making of scientists

NASA Astrophysics Data System (ADS)

O'Keeffe, Moira

This dissertation explores how scientists and science students respond to fictional, visual media about science. I consider how scientists think about images of science in relation to their own career paths from childhood onwards. I am especially interested in the possibility that entertainment media can inspire young people to learn about science. Such inspiration is badly needed, as schools are failing to provide it. Science education in the United States is in a state of crisis. Studies repeatedly find low levels of science literacy in the U.S. This bleak situation exists during a boom in the popularity of science-oriented television shows and science fiction movies. How might entertainment media play a role in helping young people engage with science? To grapple with these questions, I interviewed a total of fifty scientists and students interested in science careers, representing a variety of scientific fields and demographic backgrounds, and with varying levels of interest in science fiction. Most respondents described becoming attracted to the sciences at a young age, and many were able to identify specific sources for this interest. The fact that interest in the sciences begins early in life, demonstrates a potentially important role for fictional media in the process of inspiration, perhaps especially for children without access to real-life scientists. One key aspect to the appeal of fiction about science is how scientists are portrayed as characters. Scientists from groups traditionally under-represented in the sciences often sought out fictional characters with whom they could identify, and viewers from all backgrounds preferred well-rounded characters to the extreme stereotypes of mad or dorky scientists. Genre is another aspect of appeal. Some respondents identified a specific role for science fiction: conveying a sense of wonder. Visual media introduce viewers to the beauty of science. Special effects, in particular, allow viewers to explore the unknown. Advocates of informal science learning initiatives suggest that media can be used as a tool for teaching science content. The potential of entertainment media to provide a sense of wonder is a powerful aspect of its potential to inspire the next generation of scientists.

Explore Earth Science Datasets for STEM with the NASA GES DISC Online Visualization and Analysis Tool, GIOVANNI

NASA Astrophysics Data System (ADS)

Liu, Z.; Acker, J. G.; Kempler, S. J.

2016-12-01

The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is one of twelve NASA Science Mission Directorate (SMD) Data Centers that provide Earth science data, information, and services to research scientists, applications scientists, applications users, and students around the world. The GES DISC is the home (archive) of NASA Precipitation and Hydrology, as well as Atmospheric Composition and Dynamics remote sensing data and information. To facilitate Earth science data access, the GES DISC has been developing user-friendly data services for users at different levels. Among them, the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (GIOVANNI, http://giovanni.gsfc.nasa.gov/) allows users to explore satellite-based data using sophisticated analyses and visualizations without downloading data and software, which is particularly suitable for novices to use NASA datasets in STEM activities. In this presentation, we will briefly introduce GIOVANNI and recommend datasets for STEM. Examples of using these datasets in STEM activities will be presented as well.

Explore Earth Science Datasets for STEM with the NASA GES DISC Online Visualization and Analysis Tool, Giovanni

NASA Technical Reports Server (NTRS)

Liu, Z.; Acker, J.; Kempler, S.

2016-01-01

The NASA Goddard Earth Sciences (GES) Data and Information Services Center(DISC) is one of twelve NASA Science Mission Directorate (SMD) Data Centers that provide Earth science data, information, and services to users around the world including research and application scientists, students, citizen scientists, etc. The GESDISC is the home (archive) of remote sensing datasets for NASA Precipitation and Hydrology, Atmospheric Composition and Dynamics, etc. To facilitate Earth science data access, the GES DISC has been developing user-friendly data services for users at different levels in different countries. Among them, the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni, http:giovanni.gsfc.nasa.gov) allows users to explore satellite-based datasets using sophisticated analyses and visualization without downloading data and software, which is particularly suitable for novices (such as students) to use NASA datasets in STEM (science, technology, engineering and mathematics) activities. In this presentation, we will briefly introduce Giovanni along with examples for STEM activities.

Collaborative WorkBench (cwb): Enabling Experiment Execution, Analysis and Visualization with Increased Scientific Productivity

NASA Astrophysics Data System (ADS)

Maskey, Manil; Ramachandran, Rahul; Kuo, Kwo-Sen

2015-04-01

The Collaborative WorkBench (CWB) has been successfully developed to support collaborative science algorithm development. It incorporates many features that enable and enhance science collaboration, including the support for both asynchronous and synchronous modes of interactions in collaborations. With the former, members in a team can share a full range of research artifacts, e.g. data, code, visualizations, and even virtual machine images. With the latter, they can engage in dynamic interactions such as notification, instant messaging, file exchange, and, most notably, collaborative programming. CWB also implements behind-the-scene provenance capture as well as version control to relieve scientists of these chores. Furthermore, it has achieved a seamless integration between researchers' local compute environments and those of the Cloud. CWB has also been successfully extended to support instrument verification and validation. Adopted by almost every researcher, the current practice of downloading data to local compute resources for analysis results in much duplication and inefficiency. CWB leverages Cloud infrastructure to provide a central location for data used by an entire science team, thereby eliminating much of this duplication and waste. Furthermore, use of CWB in concert with this same Cloud infrastructure enables co-located analysis with data where opportunities of data-parallelism can be better exploited, thereby further improving efficiency. With its collaboration-enabling features apposite to steps throughout the scientific process, we expect CWB to fundamentally transform research collaboration and realize maximum science productivity.

PeptideNavigator: An interactive tool for exploring large and complex data sets generated during peptide-based drug design projects.

PubMed

Diller, Kyle I; Bayden, Alexander S; Audie, Joseph; Diller, David J

2018-01-01

There is growing interest in peptide-based drug design and discovery. Due to their relatively large size, polymeric nature, and chemical complexity, the design of peptide-based drugs presents an interesting "big data" challenge. Here, we describe an interactive computational environment, PeptideNavigator, for naturally exploring the tremendous amount of information generated during a peptide drug design project. The purpose of PeptideNavigator is the presentation of large and complex experimental and computational data sets, particularly 3D data, so as to enable multidisciplinary scientists to make optimal decisions during a peptide drug discovery project. PeptideNavigator provides users with numerous viewing options, such as scatter plots, sequence views, and sequence frequency diagrams. These views allow for the collective visualization and exploration of many peptides and their properties, ultimately enabling the user to focus on a small number of peptides of interest. To drill down into the details of individual peptides, PeptideNavigator provides users with a Ramachandran plot viewer and a fully featured 3D visualization tool. Each view is linked, allowing the user to seamlessly navigate from collective views of large peptide data sets to the details of individual peptides with promising property profiles. Two case studies, based on MHC-1A activating peptides and MDM2 scaffold design, are presented to demonstrate the utility of PeptideNavigator in the context of disparate peptide-design projects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real Science, Real Learning: Bridging the Gap Between Scientists, Educators and Students

NASA Astrophysics Data System (ADS)

Lewis, Y.

2006-05-01

Today as never before, America needs its citizens to be literate in science and technology. Not only must we only inspire a new generation of scientists and engineers and technologists, we must foster a society capable of meeting complex, 21st-century challenges. Unfortunately, the need for creative, flexible thinkers is growing at a time when our young students are lagging in science interest and performance. Over the past 17 years, the JASON Project has worked to link real science and scientists to the classroom. This link provide viable pipeline to creating the next generation scientists and researchers. Ultimately, JASON's mission is to improve the way science is taught by enabling students to learn directly from leading scientists. Through partnerships with agencies such as NOAA and NASA, JASON creates multimedia classroom products based on current scientific research. Broadcasts of science expeditions, hosted by leading researchers, are coupled with classroom materials that include interactive computer-based simulations, video- on-demand, inquiry-based experiments and activities, and print materials for students and teachers. A "gated" Web site hosts online resources and provides a secure platform to network with scientists and other classrooms in a nationwide community of learners. Each curriculum is organized around a specific theme for a comprehensive learning experience. It may be taught as a complete package, or individual components can be selected to teach specific, standards-based concepts. Such thematic units include: Disappearing Wetlands, Mysteries of Earth and Mars, and Monster Storms. All JASON curriculum units are grounded in "inquiry-based learning." The highly interactive curriculum will enable students to access current, real-world scientific research and employ the scientific method through reflection, investigation, identification of problems, sharing of data, and forming and testing hypotheses. JASON specializes in effectively applying technology in science education by designing animated interactive visualizations that promote student understanding of complex scientific concepts and systems (Rieber, 1990, 1996). JASON's experience in utilizing the power of simulation technology has been widely recognized for its effectiveness in exciting and engaging students in science learning by independent evaluations of JASON's multimedia science curriculum (Ba et al., 2001; Goldenberg et al., 2003). The data collected indicates that JASON's science products have had a positive impact on students' science learning, have positively influenced their perceptions of scientists and of becoming scientists, and have helped diverse students grasp a deeper understanding of complex scientific content, concepts and technologies.

Web servers and services for electrostatics calculations with APBS and PDB2PQR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unni, Samir; Huang, Yong; Hanson, Robert M.

APBS and PDB2PQR are widely utilized free software packages for biomolecular electrostatics calculations. Using the Opal toolkit, we have developed a web services framework for these software packages that enables the use of APBS and PDB2PQR by users who do not have local access to the necessary amount of computational capabilities. This not only increases accessibility of the software to a wider range of scientists, educators, and students but it also increases the availability of electrostatics calculations on portable computing platforms. Users can access this new functionality in two ways. First, an Opal-enabled version of APBS is provided in currentmore » distributions, available freely on the web. Second, we have extended the PDB2PQR web server to provide an interface for the setup, execution, and visualization electrostatics potentials as calculated by APBS. This web interface also uses the Opal framework which ensures the scalability needed to support the large APBS user community. Both of these resources are available from the APBS/PDB2PQR website: http://www.poissonboltzmann.org/.« less

IEEE International Symposium on Biomedical Imaging.

PubMed

2017-01-01

The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2018 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are requested containing original contributions to the topics of interest including image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological, and statistical modeling. Accepted 4-page regular papers will be published in the symposium proceedings published by IEEE and included in IEEE Xplore. To encourage attendance by a broader audience of imaging scientists and offer additional presentation opportunities, ISBI 2018 will continue to have a second track featuring posters selected from 1-page abstract submissions without subsequent archival publication.

Web servers and services for electrostatics calculations with APBS and PDB2PQR

PubMed Central

Unni, Samir; Huang, Yong; Hanson, Robert; Tobias, Malcolm; Krishnan, Sriram; Li, Wilfred W.; Nielsen, Jens E.; Baker, Nathan A.

2011-01-01

APBS and PDB2PQR are widely utilized free software packages for biomolecular electrostatics calculations. Using the Opal toolkit, we have developed a Web services framework for these software packages that enables the use of APBS and PDB2PQR by users who do not have local access to the necessary amount of computational capabilities. This not only increases accessibility of the software to a wider range of scientists, educators, and students but it also increases the availability of electrostatics calculations on portable computing platforms. Users can access this new functionality in two ways. First, an Opal-enabled version of APBS is provided in current distributions, available freely on the web. Second, we have extended the PDB2PQR web server to provide an interface for the setup, execution, and visualization electrostatics potentials as calculated by APBS. This web interface also uses the Opal framework which ensures the scalability needed to support the large APBS user community. Both of these resources are available from the APBS/PDB2PQR website: http://www.poissonboltzmann.org/. PMID:21425296

Terascale direct numerical simulations of turbulent combustion using S3D

NASA Astrophysics Data System (ADS)

Chen, J. H.; Choudhary, A.; de Supinski, B.; DeVries, M.; Hawkes, E. R.; Klasky, S.; Liao, W. K.; Ma, K. L.; Mellor-Crummey, J.; Podhorszki, N.; Sankaran, R.; Shende, S.; Yoo, C. S.

2009-01-01

Computational science is paramount to the understanding of underlying processes in internal combustion engines of the future that will utilize non-petroleum-based alternative fuels, including carbon-neutral biofuels, and burn in new combustion regimes that will attain high efficiency while minimizing emissions of particulates and nitrogen oxides. Next-generation engines will likely operate at higher pressures, with greater amounts of dilution and utilize alternative fuels that exhibit a wide range of chemical and physical properties. Therefore, there is a significant role for high-fidelity simulations, direct numerical simulations (DNS), specifically designed to capture key turbulence-chemistry interactions in these relatively uncharted combustion regimes, and in particular, that can discriminate the effects of differences in fuel properties. In DNS, all of the relevant turbulence and flame scales are resolved numerically using high-order accurate numerical algorithms. As a consequence terascale DNS are computationally intensive, require massive amounts of computing power and generate tens of terabytes of data. Recent results from terascale DNS of turbulent flames are presented here, illustrating its role in elucidating flame stabilization mechanisms in a lifted turbulent hydrogen/air jet flame in a hot air coflow, and the flame structure of a fuel-lean turbulent premixed jet flame. Computing at this scale requires close collaborations between computer and combustion scientists to provide optimized scaleable algorithms and software for terascale simulations, efficient collective parallel I/O, tools for volume visualization of multiscale, multivariate data and automating the combustion workflow. The enabling computer science, applied to combustion science, is also required in many other terascale physics and engineering simulations. In particular, performance monitoring is used to identify the performance of key kernels in the DNS code, S3D and especially memory intensive loops in the code. Through the careful application of loop transformations, data reuse in cache is exploited thereby reducing memory bandwidth needs, and hence, improving S3D's nodal performance. To enhance collective parallel I/O in S3D, an MPI-I/O caching design is used to construct a two-stage write-behind method for improving the performance of write-only operations. The simulations generate tens of terabytes of data requiring analysis. Interactive exploration of the simulation data is enabled by multivariate time-varying volume visualization. The visualization highlights spatial and temporal correlations between multiple reactive scalar fields using an intuitive user interface based on parallel coordinates and time histogram. Finally, an automated combustion workflow is designed using Kepler to manage large-scale data movement, data morphing, and archival and to provide a graphical display of run-time diagnostics.

Trend-Centric Motion Visualization: Designing and Applying a new Strategy for Analyzing Scientific Motion Collections

PubMed Central

Schroeder, David; Korsakov, Fedor; Knipe, Carissa Mai-Ping; Thorson, Lauren; Ellingson, Arin M.; Nuckley, David; Carlis, John; Keefe, Daniel F

2017-01-01

In biomechanics studies, researchers collect, via experiments or simulations, datasets with hundreds or thousands of trials, each describing the same type of motion (e.g., a neck flexion-extension exercise) but under different conditions (e.g., different patients, different disease states, pre- and post-treatment). Analyzing similarities and differences across all of the trials in these collections is a major challenge. Visualizing a single trial at a time does not work, and the typical alternative of juxtaposing multiple trials in a single visual display leads to complex, difficult-to-interpret visualizations. We address this problem via a new strategy that organizes the analysis around motion trends rather than trials. This new strategy matches the cognitive approach that scientists would like to take when analyzing motion collections. We introduce several technical innovations making trend-centric motion visualization possible. First, an algorithm detects a motion collection’s trends via time-dependent clustering. Second, a 2D graphical technique visualizes how trials leave and join trends. Third, a 3D graphical technique, using a median 3D motion plus a visual variance indicator, visualizes the biomechanics of the set of trials within each trend. These innovations are combined to create an interactive exploratory visualization tool, which we designed through an iterative process in collaboration with both domain scientists and a traditionally-trained graphic designer. We report on insights generated during this design process and demonstrate the tool’s effectiveness via a validation study with synthetic data and feedback from expert musculoskeletal biomechanics researchers who used the tool to analyze the effects of disc degeneration on human spinal kinematics. PMID:26356978

Genetic Constructor: An Online DNA Design Platform.

PubMed

Bates, Maxwell; Lachoff, Joe; Meech, Duncan; Zulkower, Valentin; Moisy, Anaïs; Luo, Yisha; Tekotte, Hille; Franziska Scheitz, Cornelia Johanna; Khilari, Rupal; Mazzoldi, Florencio; Chandran, Deepak; Groban, Eli

2017-12-15

Genetic Constructor is a cloud Computer Aided Design (CAD) application developed to support synthetic biologists from design intent through DNA fabrication and experiment iteration. The platform allows users to design, manage, and navigate complex DNA constructs and libraries, using a new visual language that focuses on functional parts abstracted from sequence. Features like combinatorial libraries and automated primer design allow the user to separate design from construction by focusing on functional intent, and design constraints aid iterative refinement of designs. A plugin architecture enables contributions from scientists and coders to leverage existing powerful software and connect to DNA foundries. The software is easily accessible and platform agnostic, free for academics, and available in an open-source community edition. Genetic Constructor seeks to democratize DNA design, manufacture, and access to tools and services from the synthetic biology community.

NUCLEAR ESPIONAGE: Report Details Spying on Touring Scientists.

PubMed

Malakoff, D

2000-06-30

A congressional report released this week details dozens of sometimes clumsy attempts by foreign agents to obtain nuclear secrets from U.S. nuclear scientists traveling abroad, ranging from offering scientists prostitutes to prying off the backs of their laptop computers. The report highlights the need to better prepare traveling researchers to safeguard secrets and resist such temptations, say the two lawmakers who requested the report and officials at the Department of Energy, which employs the scientists.

Distributed GPU Computing in GIScience

NASA Astrophysics Data System (ADS)

Jiang, Y.; Yang, C.; Huang, Q.; Li, J.; Sun, M.

2013-12-01

Geoscientists strived to discover potential principles and patterns hidden inside ever-growing Big Data for scientific discoveries. To better achieve this objective, more capable computing resources are required to process, analyze and visualize Big Data (Ferreira et al., 2003; Li et al., 2013). Current CPU-based computing techniques cannot promptly meet the computing challenges caused by increasing amount of datasets from different domains, such as social media, earth observation, environmental sensing (Li et al., 2013). Meanwhile CPU-based computing resources structured as cluster or supercomputer is costly. In the past several years with GPU-based technology matured in both the capability and performance, GPU-based computing has emerged as a new computing paradigm. Compare to traditional computing microprocessor, the modern GPU, as a compelling alternative microprocessor, has outstanding high parallel processing capability with cost-effectiveness and efficiency(Owens et al., 2008), although it is initially designed for graphical rendering in visualization pipe. This presentation reports a distributed GPU computing framework for integrating GPU-based computing within distributed environment. Within this framework, 1) for each single computer, computing resources of both GPU-based and CPU-based can be fully utilized to improve the performance of visualizing and processing Big Data; 2) within a network environment, a variety of computers can be used to build up a virtual super computer to support CPU-based and GPU-based computing in distributed computing environment; 3) GPUs, as a specific graphic targeted device, are used to greatly improve the rendering efficiency in distributed geo-visualization, especially for 3D/4D visualization. Key words: Geovisualization, GIScience, Spatiotemporal Studies Reference : 1. Ferreira de Oliveira, M. C., & Levkowitz, H. (2003). From visual data exploration to visual data mining: A survey. Visualization and Computer Graphics, IEEE Transactions on, 9(3), 378-394. 2. Li, J., Jiang, Y., Yang, C., Huang, Q., & Rice, M. (2013). Visualizing 3D/4D Environmental Data Using Many-core Graphics Processing Units (GPUs) and Multi-core Central Processing Units (CPUs). Computers & Geosciences, 59(9), 78-89. 3. Owens, J. D., Houston, M., Luebke, D., Green, S., Stone, J. E., & Phillips, J. C. (2008). GPU computing. Proceedings of the IEEE, 96(5), 879-899.

Keeping an Eye on the Prize

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hazi, A U

2007-02-06

Setting performance goals is part of the business plan for almost every company. The same is true in the world of supercomputers. Ten years ago, the Department of Energy (DOE) launched the Accelerated Strategic Computing Initiative (ASCI) to help ensure the safety and reliability of the nation's nuclear weapons stockpile without nuclear testing. ASCI, which is now called the Advanced Simulation and Computing (ASC) Program and is managed by DOE's National Nuclear Security Administration (NNSA), set an initial 10-year goal to obtain computers that could process up to 100 trillion floating-point operations per second (teraflops). Many computer experts thought themore » goal was overly ambitious, but the program's results have proved them wrong. Last November, a Livermore-IBM team received the 2005 Gordon Bell Prize for achieving more than 100 teraflops while modeling the pressure-induced solidification of molten metal. The prestigious prize, which is named for a founding father of supercomputing, is awarded each year at the Supercomputing Conference to innovators who advance high-performance computing. Recipients for the 2005 prize included six Livermore scientists--physicists Fred Streitz, James Glosli, and Mehul Patel and computer scientists Bor Chan, Robert Yates, and Bronis de Supinski--as well as IBM researchers James Sexton and John Gunnels. This team produced the first atomic-scale model of metal solidification from the liquid phase with results that were independent of system size. The record-setting calculation used Livermore's domain decomposition molecular-dynamics (ddcMD) code running on BlueGene/L, a supercomputer developed by IBM in partnership with the ASC Program. BlueGene/L reached 280.6 teraflops on the Linpack benchmark, the industry standard used to measure computing speed. As a result, it ranks first on the list of Top500 Supercomputer Sites released in November 2005. To evaluate the performance of nuclear weapons systems, scientists must understand how materials behave under extreme conditions. Because experiments at high pressures and temperatures are often difficult or impossible to conduct, scientists rely on computer models that have been validated with obtainable data. Of particular interest to weapons scientists is the solidification of metals. ''To predict the performance of aging nuclear weapons, we need detailed information on a material's phase transitions'', says Streitz, who leads the Livermore-IBM team. For example, scientists want to know what happens to a metal as it changes from molten liquid to a solid and how that transition affects the material's characteristics, such as its strength.« less

Visual ergonomics and computer work--is it all about computer glasses?

PubMed

Jonsson, Christina

2012-01-01

The Swedish Provisions on Work with Display Screen Equipment and the EU Directive on the minimum safety and health requirements for work with display screen equipment cover several important visual ergonomics aspects. But a review of cases and questions to the Swedish Work Environment Authority clearly shows that most attention is given to the demands for eyesight tests and special computer glasses. Other important visual ergonomics factors are at risk of being neglected. Today computers are used everywhere, both at work and at home. Computers can be laptops, PDA's, tablet computers, smart phones, etc. The demands on eyesight tests and computer glasses still apply but the visual demands and the visual ergonomics conditions are quite different compared to the use of a stationary computer. Based on this review, we raise the question if the demand on the employer to provide the employees with computer glasses is outdated.

Final Report. Center for Scalable Application Development Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mellor-Crummey, John

2014-10-26

The Center for Scalable Application Development Software (CScADS) was established as a part- nership between Rice University, Argonne National Laboratory, University of California Berkeley, University of Tennessee – Knoxville, and University of Wisconsin – Madison. CScADS pursued an integrated set of activities with the aim of increasing the productivity of DOE computational scientists by catalyzing the development of systems software, libraries, compilers, and tools for leadership computing platforms. Principal Center activities were workshops to engage the research community in the challenges of leadership computing, research and development of open-source software, and work with computational scientists to help them develop codesmore » for leadership computing platforms. This final report summarizes CScADS activities at Rice University in these areas.« less

Characterization of real-time computers

NASA Technical Reports Server (NTRS)

Shin, K. G.; Krishna, C. M.

1984-01-01

A real-time system consists of a computer controller and controlled processes. Despite the synergistic relationship between these two components, they have been traditionally designed and analyzed independently of and separately from each other; namely, computer controllers by computer scientists/engineers and controlled processes by control scientists. As a remedy for this problem, in this report real-time computers are characterized by performance measures based on computer controller response time that are: (1) congruent to the real-time applications, (2) able to offer an objective comparison of rival computer systems, and (3) experimentally measurable/determinable. These measures, unlike others, provide the real-time computer controller with a natural link to controlled processes. In order to demonstrate their utility and power, these measures are first determined for example controlled processes on the basis of control performance functionals. They are then used for two important real-time multiprocessor design applications - the number-power tradeoff and fault-masking and synchronization.

Visualizing Distributions from Multi-Return Lidar Data to Understand Forest Structure

NASA Technical Reports Server (NTRS)

Kao, David L.; Kramer, Marc; Luo, Alison; Dungan, Jennifer; Pang, Alex

2004-01-01

Spatially distributed probability density functions (pdfs) are becoming relevant to the Earth scientists and ecologists because of stochastic models and new sensors that provide numerous realizations or data points per unit area. One source of these data is from multi-return airborne lidar, a type of laser that records multiple returns for each pulse of light sent towards the ground. Data from multi-return lidar is a vital tool in helping us understand the structure of forest canopies over large extents. This paper presents several new visualization tools that allow scientists to rapidly explore, interpret and discover characteristic distributions within the entire spatial field. The major contribution from-this work is a paradigm shift which allows ecologists to think of and analyze their data in terms of the distribution. This provides a way to reveal information on the modality and shape of the distribution previously not possible. The tools allow the scientists to depart from traditional parametric statistical analyses and to associate multimodal distribution characteristics to forest structures. Examples are given using data from High Island, southeast Alaska.

Exploring Vaccine Hesitancy Through an Artist-Scientist Collaboration : Visualizing Vaccine-Critical Parents' Health Beliefs.

PubMed

Koski, Kaisu; Holst, Johan

2017-09-01

This project explores vaccine hesitancy through an artist-scientist collaboration. It aims to create better understanding of vaccine hesitant parents' health beliefs and how these influence their vaccine-critical decisions. The project interviews vaccine-hesitant parents in the Netherlands and Finland and develops experimental visual-narrative means to analyse the interview data. Vaccine-hesitant parents' health beliefs are, in this study, expressed through stories, and they are paralleled with so-called illness narratives. The study explores the following four main health beliefs originating from the parents' interviews: (1) perceived benefits of illness, (2) belief in the body's intelligence and self-healing capacity, (3) beliefs about the "inside-outside" flow of substances in the body, and (4) view of death as a natural part of life. These beliefs are interpreted through arts-based diagrammatic representations. These diagrams, merging multiple aspects of the parents' narratives, are subsequently used in a collaborative meaning-making dialogue between the artist and the scientist. The resulting dialogue contrasts the health beliefs behind vaccine hesitancy with scientific knowledge, as well as the authors' personal, and differing, attitudes toward these.

Innovative Visualizations Shed Light on Avian Nocturnal Migration

PubMed Central

Farnsworth, Andrew; Aelterman, Bart; Alves, Jose A.; Azijn, Kevin; Bernstein, Garrett; Branco, Sérgio; Desmet, Peter; Dokter, Adriaan M.; Horton, Kyle; Kelling, Steve; Kelly, Jeffrey F.; Leijnse, Hidde; Rong, Jingjing; Sheldon, Daniel; Van den Broeck, Wouter; Van Den Meersche, Jan Klaas; Van Doren, Benjamin Mark; van Gasteren, Hans

2016-01-01

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals’ life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human–wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement. PMID:27557096

Innovative Visualizations Shed Light on Avian Nocturnal Migration.

PubMed

Shamoun-Baranes, Judy; Farnsworth, Andrew; Aelterman, Bart; Alves, Jose A; Azijn, Kevin; Bernstein, Garrett; Branco, Sérgio; Desmet, Peter; Dokter, Adriaan M; Horton, Kyle; Kelling, Steve; Kelly, Jeffrey F; Leijnse, Hidde; Rong, Jingjing; Sheldon, Daniel; Van den Broeck, Wouter; Van Den Meersche, Jan Klaas; Van Doren, Benjamin Mark; van Gasteren, Hans

2016-01-01

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals' life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human-wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement.

Experimenter's Laboratory for Visualized Interactive Science

NASA Technical Reports Server (NTRS)

Hansen, Elaine R.; Rodier, Daniel R.; Klemp, Marjorie K.

1994-01-01

ELVIS (Experimenter's Laboratory for Visualized Interactive Science) is an interactive visualization environment that enables scientists, students, and educators to visualize and analyze large, complex, and diverse sets of scientific data. It accomplishes this by presenting the data sets as 2-D, 3-D, color, stereo, and graphic images with movable and multiple light sources combined with displays of solid-surface, contours, wire-frame, and transparency. By simultaneously rendering diverse data sets acquired from multiple sources, formats, and resolutions and by interacting with the data through an intuitive, direct-manipulation interface, ELVIS provides an interactive and responsive environment for exploratory data analysis.

EDITORIAL: Focus on Visualization in Physics FOCUS ON VISUALIZATION IN PHYSICS

NASA Astrophysics Data System (ADS)

Sanders, Barry C.; Senden, Tim; Springel, Volker

2008-12-01

Advances in physics are intimately connected with developments in a new technology, the telescope, precision clocks, even the computer all have heralded a shift in thinking. These landmark developments open new opportunities accelerating research and in turn new scientific directions. These technological drivers often correspond to new instruments, but equally might just as well flag a new mathematical tool, an algorithm or even means to visualize physics in a new way. Early on in this twenty-first century, scientific communities are just starting to explore the potential of digital visualization. Whether visualization is used to represent and communicate complex concepts, or to understand and interpret experimental data, or to visualize solutions to complex dynamical equations, the basic tools of visualization are shared in each of these applications and implementations. High-performance computing exemplifies the integration of visualization with leading research. Visualization is an indispensable tool for analyzing and interpreting complex three-dimensional dynamics as well as to diagnose numerical problems in intricate parallel calculation algorithms. The effectiveness of visualization arises by exploiting the unmatched capability of the human eye and visual cortex to process the large information content of images. In a brief glance, we recognize patterns or identify subtle features even in noisy data, something that is difficult or impossible to achieve with more traditional forms of data analysis. Importantly, visualizations guide the intuition of researchers and help to comprehend physical phenomena that lie far outside of direct experience. In fact, visualizations literally allow us to see what would otherwise remain completely invisible. For example, artificial imagery created to visualize the distribution of dark matter in the Universe has been instrumental to develop the notion of a cosmic web, and for helping to establish the current standard model of cosmology wherein this (in principle invisible) dark matter dominates the cosmic matter content. The advantages of visualization found for simulated data also hold for real world data as well. With the application of computerized acquisition many scientific disciplines are witnessing exponential growth rates of the volume of accumulated raw data, which often makes it daunting to condense the information into a manageable form, a challenge that can be addressed by modern visualization techniques. Such visualizations are also often an enticing way to communicate scientific results to the general public. This need for visualization is especially true in basic science, with its reliance on a benevolent and interested general public that drives the need for high-quality visualizations. Despite the widespread use of visualization, this technology has suffered from a lack of the unifying influence of shared common experiences. As with any emerging technology practitioners have often independently found solutions to similar problems. It is the aim of this focus issue to celebrate the importance of visualization, report on its growing use by the broad community of physicists, including biophysics, chemical physics, geophysics, astrophysics, and medical physics, and provide an opportunity for the diverse community of scientists using visualization to share work in one issue of a journal that itself is in the vanguard of supporting visualization and multimedia. A remarkable breadth and diversity of visualization in physics is to be found in this issue spanning fundamental aspects of relativity theory to computational fluid dynamics. The topics span length scales that are as small as quantum phenomena to the entire observable Universe. We have been impressed by the quality of the submissions and hope that this snap-shot will introduce, inform, motivate and maybe even help to unify visualization in physics. Readers are also directed to the December issue of Physics World which includes the following features highlighting work in this collection and other novel uses of visualization techniques: 'A feast of visualization' Physics World December 2008 pp 20 23 'Seeing the quantum world' by Barry Sanders Physics World December 2008 pp 24 27 'A picture of the cosmos' by Mark SubbaRao and Miguel Aragon-Calvo Physics World December 2008 pp 29 32 'Thinking outside the cube' by César A Hidalgo Physics World December 2008 pp 34 37 Focus on Visualization in Physics Contents Visualization of spiral and scroll waves in simulated and experimental cardiac tissue E M Cherry and F H Fenton Visualization of large scale structure from the Sloan Digital Sky Survey M U SubbaRao, M A Aragón-Calvo, H W Chen, J M Quashnock, A S Szalay and D G York How computers can help us in creating an intuitive access to relativity Hanns Ruder, Daniel Weiskopf, Hans-Peter Nollert and Thomas Müller Lagrangian particle tracking in three dimensions via single-camera in-line digital holography Jiang Lu, Jacob P Fugal, Hansen Nordsiek, Ewe Wei Saw, Raymond A Shaw and Weidong Yang Quantifying spatial heterogeneity from images Andrew E Pomerantz and Yi-Qiao Song Disaggregation and scientific visualization of earthscapes considering trends and spatial dependence structures S Grunwald Strength through structure: visualization and local assessment of the trabecular bone structure C Räth, R Monetti, J Bauer, I Sidorenko, D Müller, M Matsuura, E-M Lochmüller, P Zysset and F Eckstein Thermonuclear supernovae: a multi-scale astrophysical problem challenging numerical simulations and visualization F K Röpke and R Bruckschen Visualization needs and techniques for astrophysical simulations W Kapferer and T Riser Flow visualization and field line advection in computational fluid dynamics: application to magnetic fields and turbulent flows Pablo Mininni, Ed Lee, Alan Norton and John Clyne Splotch: visualizing cosmological simulations K Dolag, M Reinecke, C Gheller and S Imboden Visualizing a silicon quantum computer Barry C Sanders, Lloyd C L Hollenberg, Darran Edmundson and Andrew Edmundson Colliding galaxies, rotating neutron stars and merging black holes—visualizing high dimensional datasets on arbitrary meshes Werner Benger A low complexity visualization tool that helps to perform complex systems analysis M G Beiró, J I Alvarez-Hamelin and J R Busch Visualizing astrophysical N-body systems John Dubinski

Computer Vision Syndrome.

PubMed

Randolph, Susan A

2017-07-01

With the increased use of electronic devices with visual displays, computer vision syndrome is becoming a major public health issue. Improving the visual status of workers using computers results in greater productivity in the workplace and improved visual comfort.

Integrating Research and Education at the National Center for Atmospheric Research at the Interface of Formal and Informal Education

NASA Astrophysics Data System (ADS)

Johnson, R.; Foster, S.

2005-12-01

The National Center for Atmospheric Research (NCAR) in Boulder, Colorado, is a leading institution in scientific research, education and service associated with exploring and understanding our atmosphere and its interactions with the Sun, the oceans, the biosphere, and human society. NCAR draws thousands of public and scientific visitors from around the world to its Mesa Laboratory facility annually for educational as well as research purposes. Public visitors include adult visitors, clubs, and families on an informal visit to NCAR and its exhibits, as well as classroom and summer camp groups. Additionally, NCAR provides extensive computational and visualization services, which can be used not only for scientific, but also public informational purposes. As such, NCAR's audience provides an opportunity to address both formal and informal education through the programs that we offer. The University Corporation for Atmospheric Research (UCAR) Office of Education and Outreach works with NCAR to develop and implement a highly-integrated strategy for reaching both formal and informal audiences through programs that range from events and exhibits to professional development (for scientists and educators) and bilingual distance learning. The hallmarks of our program include close collaboration with scientists, multi-purposing resources where appropriate for maximum efficiency, and a commitment to engage populations historically underrepresented in science in the geosciences.

Public Computer Assisted Learning Facilities for Children with Visual Impairment: Universal Design for Inclusive Learning

ERIC Educational Resources Information Center

Siu, Kin Wai Michael; Lam, Mei Seung

2012-01-01

Although computer assisted learning (CAL) is becoming increasingly popular, people with visual impairment face greater difficulty in accessing computer-assisted learning facilities. This is primarily because most of the current CAL facilities are not visually impaired friendly. People with visual impairment also do not normally have access to…

Computer Skill Acquisition and Retention: The Effects of Computer-Aided Self-Explanation

ERIC Educational Resources Information Center

Chi, Tai-Yin

2016-01-01

This research presents an experimental study to determine to what extent computer skill learners can benefit from generating self-explanation with the aid of different computer-based visualization technologies. Self-explanation was stimulated with dynamic visualization (Screencast), static visualization (Screenshot), or verbal instructions only,…

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways

PubMed Central

Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-01-01

Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and ‘wet lab’ scientists. Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X. Contact: duccio.cavalieri@unifi.it; sorin@wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21653523

Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants

PubMed Central

Wahabzada, Mirwaes; Mahlein, Anne-Katrin; Bauckhage, Christian; Steiner, Ulrike; Oerke, Erich-Christian; Kersting, Kristian

2016-01-01

Modern phenotyping and plant disease detection methods, based on optical sensors and information technology, provide promising approaches to plant research and precision farming. In particular, hyperspectral imaging have been found to reveal physiological and structural characteristics in plants and to allow for tracking physiological dynamics due to environmental effects. In this work, we present an approach to plant phenotyping that integrates non-invasive sensors, computer vision, as well as data mining techniques and allows for monitoring how plants respond to stress. To uncover latent hyperspectral characteristics of diseased plants reliably and in an easy-to-understand way, we “wordify” the hyperspectral images, i.e., we turn the images into a corpus of text documents. Then, we apply probabilistic topic models, a well-established natural language processing technique that identifies content and topics of documents. Based on recent regularized topic models, we demonstrate that one can track automatically the development of three foliar diseases of barley. We also present a visualization of the topics that provides plant scientists an intuitive tool for hyperspectral imaging. In short, our analysis and visualization of characteristic topics found during symptom development and disease progress reveal the hyperspectral language of plant diseases. PMID:26957018

The Fermilab Connection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fermilab

More than 4,000 scientists in 53 countries use Fermilab and its particle accelerators, detectors and computers for their research. That includes about 2,500 scientists from 223 U.S. institutions in 42 states, plus the District of Columbia and Puerto Rico.

EdGCM: Research Tools for Training the Climate Change Generation

NASA Astrophysics Data System (ADS)

Chandler, M. A.; Sohl, L. E.; Zhou, J.; Sieber, R.

2011-12-01

Climate scientists employ complex computer simulations of the Earth's physical systems to prepare climate change forecasts, study the physical mechanisms of climate, and to test scientific hypotheses and computer parameterizations. The Intergovernmental Panel on Climate Change 4th Assessment Report (2007) demonstrates unequivocally that policy makers rely heavily on such Global Climate Models (GCMs) to assess the impacts of potential economic and emissions scenarios. However, true climate modeling capabilities are not disseminated to the majority of world governments or U.S. researchers - let alone to the educators who will be training the students who are about to be presented with a world full of climate change stakeholders. The goal is not entirely quixotic; in fact, by the mid-1990's prominent climate scientists were predicting with certainty that schools and politicians would "soon" be running GCMs on laptops [Randall, 1996]. For a variety of reasons this goal was never achieved (nor even really attempted). However, around the same time NASA and the National Science Foundation supported a small pilot project at Columbia University to show the potential of putting sophisticated computer climate models - not just "demos" or "toy models" - into the hands of non-specialists. The Educational Global Climate Modeling Project (EdGCM) gave users access to a real global climate model and provided them with the opportunity to experience the details of climate model setup, model operation, post-processing and scientific visualization. EdGCM was designed for use in both research and education - it is a full-blown research GCM, but the ultimate goal is to develop a capability to embed these crucial technologies across disciplines, networks, platforms, and even across academia and industry. With this capability in place we can begin training the skilled workforce that is necessary to deal with the multitude of climate impacts that will occur over the coming decades. To further increase the educational potential of climate models, the EdGCM project has also created "EZgcm". Through a joint venture of NASA, Columbia University and McGill University EZgcm moves the focus toward a greater use of Web 1.0 and Web 2.0-based technologies. It shifts the educational objectives towards a greater emphasis on teaching students how science is conducted and what role science plays in assessing climate change. That is, students learn about the steps of the scientific process as conveyed by climate modeling research: constructing a hypothesis, designing an experiment, running a computer model, using scientific visualization to support analysis, communicating the results of that analysis, and role playing the scientific peer review process. This is in stark contrast to what they learn from the political debate over climate change, which they often confuse with a scientific debate.

Visualizing Moon Data and Imagery with Google Earth

NASA Astrophysics Data System (ADS)

Weiss-Malik, M.; Scharff, T.; Nefian, A.; Moratto, Z.; Kolb, E.; Lundy, M.; Hancher, M.; Gorelick, N.; Broxton, M.; Beyer, R. A.

2009-12-01

There is a vast store of planetary geospatial data that has been collected by NASA but is difficult to access and visualize. Virtual globes have revolutionized the way we visualize and understand the Earth, but other planetary bodies including Mars and the Moon can be visualized in similar ways. Extraterrestrial virtual globes are poised to revolutionize planetary science, bring an exciting new dimension to science education, and allow ordinary users to explore imagery being sent back to Earth by planetary science satellites. The original Google Moon Web site was a limited series of maps and Apollo content. The new Moon in Google Earth feature provides a similar virtual planet experience for the Moon as we have for the Earth and Mars. We incorporated existing Clementine and Lunar Orbiter imagery for the basemaps and a combination of Kaguya LALT topography and some terrain created from Apollo Metric and Panoramic images. We also have information about the Apollo landings and other robotic landers on the surface, as well as historic maps and charts, and guided tours. Some of the first-released LROC imagery of the Apollo landing sites has been put in place, and we look forward to incorporating more data as it is released from LRO, Chandraayan-1, and Kaguya. These capabilities have obvious public outreach and education benefits, but the potential benefits of allowing planetary scientists to rapidly explore these large and varied data collections — in geological context and within a single user interface — are also becoming evident. Because anyone can produce additional KML content for use in Google Earth, scientists can customize the environment to their needs as well as publish their own processed data and results for others to use. Many scientists and organizations have begun to do this already, resulting in a useful and growing collection of planetary-science-oriented Google Earth layers. Screen shot of Moon in Google Earth, a freely downloadable application for visualizing Moon imagery and data.

2008 ALCF annual report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drugan, C.

2009-12-07

The word 'breakthrough' aptly describes the transformational science and milestones achieved at the Argonne Leadership Computing Facility (ALCF) throughout 2008. The number of research endeavors undertaken at the ALCF through the U.S. Department of Energy's (DOE) Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program grew from 9 in 2007 to 20 in 2008. The allocation of computer time awarded to researchers on the Blue Gene/P also spiked significantly - from nearly 10 million processor hours in 2007 to 111 million in 2008. To support this research, we expanded the capabilities of Intrepid, an IBM Blue Gene/P systemmore » at the ALCF, to 557 teraflops (TF) for production use. Furthermore, we enabled breakthrough levels of productivity and capability in visualization and data analysis with Eureka, a powerful installation of NVIDIA Quadro Plex S4 external graphics processing units. Eureka delivered a quantum leap in visual compute density, providing more than 111 TF and more than 3.2 terabytes of RAM. On April 21, 2008, the dedication of the ALCF realized DOE's vision to bring the power of the Department's high performance computing to open scientific research. In June, the IBM Blue Gene/P supercomputer at the ALCF debuted as the world's fastest for open science and third fastest overall. No question that the science benefited from this growth and system improvement. Four research projects spearheaded by Argonne National Laboratory computer scientists and ALCF users were named to the list of top ten scientific accomplishments supported by DOE's Advanced Scientific Computing Research (ASCR) program. Three of the top ten projects used extensive grants of computing time on the ALCF's Blue Gene/P to model the molecular basis of Parkinson's disease, design proteins at atomic scale, and create enzymes. As the year came to a close, the ALCF was recognized with several prestigious awards at SC08 in November. We provided resources for Linear Scaling Divide-and-Conquer Electronic Structure Calculations for Thousand Atom Nanostructures, a collaborative effort between Argonne, Lawrence Berkeley National Laboratory, and Oak Ridge National Laboratory that received the ACM Gordon Bell Prize Special Award for Algorithmic Innovation. The ALCF also was named a winner in two of the four categories in the HPC Challenge best performance benchmark competition.« less

Effects of ensemble and summary displays on interpretations of geospatial uncertainty data.

PubMed

Padilla, Lace M; Ruginski, Ian T; Creem-Regehr, Sarah H

2017-01-01

Ensemble and summary displays are two widely used methods to represent visual-spatial uncertainty; however, there is disagreement about which is the most effective technique to communicate uncertainty to the general public. Visualization scientists create ensemble displays by plotting multiple data points on the same Cartesian coordinate plane. Despite their use in scientific practice, it is more common in public presentations to use visualizations of summary displays, which scientists create by plotting statistical parameters of the ensemble members. While prior work has demonstrated that viewers make different decisions when viewing summary and ensemble displays, it is unclear what components of the displays lead to diverging judgments. This study aims to compare the salience of visual features - or visual elements that attract bottom-up attention - as one possible source of diverging judgments made with ensemble and summary displays in the context of hurricane track forecasts. We report that salient visual features of both ensemble and summary displays influence participant judgment. Specifically, we find that salient features of summary displays of geospatial uncertainty can be misunderstood as displaying size information. Further, salient features of ensemble displays evoke judgments that are indicative of accurate interpretations of the underlying probability distribution of the ensemble data. However, when participants use ensemble displays to make point-based judgments, they may overweight individual ensemble members in their decision-making process. We propose that ensemble displays are a promising alternative to summary displays in a geospatial context but that decisions about visualization methods should be informed by the viewer's task.

NASA Opportunities in Visualization, Art, and Science (NOVAS)

NASA Astrophysics Data System (ADS)

Fillingim, M. O.; Zevin, D.; Croft, S.; Thrall, L.; Shackelford, R. L., III

2015-12-01

Led by members of UC Berkeley's Multiverse education team at the Space Sciences Laboratory (http://multiverse.ssl.berkeley.edu/), in partnership with UC Berkeley Astronomy, NASA Opportunities in Visualization, Art and Science (NOVAS) is a NASA-funded program mainly for high school students that explores NASA science through art and highlights the need for and uses of art and visualizations in science. The project's aim is to motivate more diverse young people (especially African Americans) to consider Science, Technology, Engineering, and Mathematics (STEM) careers. The program offers intensive summer workshops at community youth centers, afterschool workshops at a local high school, a year-round internship for those who have taken part in one or more of our workshops, public and school outreach, and educator professional development workshops. By adding Art (fine art, graphic art, multimedia, design, and "maker/tinkering" approaches) to STEM learning, we wanted to try a unique combination of what's often now called the "STEAM movement" in STEM education. We've paid particular attention to highlighting how scientists and artists/tinkerers often collaborate, and why scientists need visualization and design experts. The program values the rise of the STEAM teaching concept, particularly that art, multimedia, design, and maker projects can help communicate science concepts more effectively. We also promote the fact that art, design, and visualization skills can lead to jobs and broader participation in science, and we frequently work with and showcase scientific illustrators and other science visualization professionals. This presentation will highlight the significant findings from our multi-year program.

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

The Second SIAM Conference on Computational Science and Engineering was held in San Diego from February 10-12, 2003. Total conference attendance was 553. This is a 23% increase in attendance over the first conference. The focus of this conference was to draw attention to the tremendous range of major computational efforts on large problems in science and engineering, to promote the interdisciplinary culture required to meet these large-scale challenges, and to encourage the training of the next generation of computational scientists. Computational Science & Engineering (CS&E) is now widely accepted, along with theory and experiment, as a crucial third modemore » of scientific investigation and engineering design. Aerospace, automotive, biological, chemical, semiconductor, and other industrial sectors now rely on simulation for technical decision support. For federal agencies also, CS&E has become an essential support for decisions on resources, transportation, and defense. CS&E is, by nature, interdisciplinary. It grows out of physical applications and it depends on computer architecture, but at its heart are powerful numerical algorithms and sophisticated computer science techniques. From an applied mathematics perspective, much of CS&E has involved analysis, but the future surely includes optimization and design, especially in the presence of uncertainty. Another mathematical frontier is the assimilation of very large data sets through such techniques as adaptive multi-resolution, automated feature search, and low-dimensional parameterization. The themes of the 2003 conference included, but were not limited to: Advanced Discretization Methods; Computational Biology and Bioinformatics; Computational Chemistry and Chemical Engineering; Computational Earth and Atmospheric Sciences; Computational Electromagnetics; Computational Fluid Dynamics; Computational Medicine and Bioengineering; Computational Physics and Astrophysics; Computational Solid Mechanics and Materials; CS&E Education; Meshing and Adaptivity; Multiscale and Multiphysics Problems; Numerical Algorithms for CS&E; Discrete and Combinatorial Algorithms for CS&E; Inverse Problems; Optimal Design, Optimal Control, and Inverse Problems; Parallel and Distributed Computing; Problem-Solving Environments; Software and Wddleware Systems; Uncertainty Estimation and Sensitivity Analysis; and Visualization and Computer Graphics.« less

SciDAC's Earth System Grid Center for Enabling Technologies Semiannual Progress Report October 1, 2010 through March 31, 2011

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Dean N.

2011-04-02

This report summarizes work carried out by the Earth System Grid Center for Enabling Technologies (ESG-CET) from October 1, 2010 through March 31, 2011. It discusses ESG-CET highlights for the reporting period, overall progress, period goals, and collaborations, and lists papers and presentations. To learn more about our project and to find previous reports, please visit the ESG-CET Web sites: http://esg-pcmdi.llnl.gov/ and/or https://wiki.ucar.edu/display/esgcet/Home. This report will be forwarded to managers in the Department of Energy (DOE) Scientific Discovery through Advanced Computing (SciDAC) program and the Office of Biological and Environmental Research (OBER), as well as national and international collaborators andmore » stakeholders (e.g., those involved in the Coupled Model Intercomparison Project, phase 5 (CMIP5) for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5); the Community Earth System Model (CESM); the Climate Science Computational End Station (CCES); SciDAC II: A Scalable and Extensible Earth System Model for Climate Change Science; the North American Regional Climate Change Assessment Program (NARCCAP); the Atmospheric Radiation Measurement (ARM) program; the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA)), and also to researchers working on a variety of other climate model and observation evaluation activities. The ESG-CET executive committee consists of Dean N. Williams, Lawrence Livermore National Laboratory (LLNL); Ian Foster, Argonne National Laboratory (ANL); and Don Middleton, National Center for Atmospheric Research (NCAR). The ESG-CET team is a group of researchers and scientists with diverse domain knowledge, whose home institutions include eight laboratories and two universities: ANL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), LLNL, NASA/Jet Propulsion Laboratory (JPL), NCAR, Oak Ridge National Laboratory (ORNL), Pacific Marine Environmental Laboratory (PMEL)/NOAA, Rensselaer Polytechnic Institute (RPI), and University of Southern California, Information Sciences Institute (USC/ISI). All ESG-CET work is accomplished under DOE open-source guidelines and in close collaboration with the project's stakeholders, domain researchers, and scientists. Through the ESG project, the ESG-CET team has developed and delivered a production environment for climate data from multiple climate model sources (e.g., CMIP (IPCC), CESM, ocean model data (e.g., Parallel Ocean Program), observation data (e.g., Atmospheric Infrared Sounder, Microwave Limb Sounder), and analysis and visualization tools) that serves a worldwide climate research community. Data holdings are distributed across multiple sites including LANL, LBNL, LLNL, NCAR, and ORNL as well as unfunded partners sites such as the Australian National University (ANU) National Computational Infrastructure (NCI), the British Atmospheric Data Center (BADC), the Geophysical Fluid Dynamics Laboratory/NOAA, the Max Planck Institute for Meteorology (MPI-M), the German Climate Computing Centre (DKRZ), and NASA/JPL. As we transition from development activities to production and operations, the ESG-CET team is tasked with making data available to all users who want to understand it, process it, extract value from it, visualize it, and/or communicate it to others. This ongoing effort is extremely large and complex, but it will be incredibly valuable for building 'science gateways' to critical climate resources (such as CESM, CMIP5, ARM, NARCCAP, Atmospheric Infrared Sounder (AIRS), etc.) for processing the next IPCC assessment report. Continued ESG progress will result in a production-scale system that will empower scientists to attempt new and exciting data exchanges, which could ultimately lead to breakthrough climate science discoveries.« less

Image communication scheme based on dynamic visual cryptography and computer generated holography

NASA Astrophysics Data System (ADS)

Palevicius, Paulius; Ragulskis, Minvydas

2015-01-01

Computer generated holograms are often exploited to implement optical encryption schemes. This paper proposes the integration of dynamic visual cryptography (an optical technique based on the interplay of visual cryptography and time-averaging geometric moiré) with Gerchberg-Saxton algorithm. A stochastic moiré grating is used to embed the secret into a single cover image. The secret can be visually decoded by a naked eye if only the amplitude of harmonic oscillations corresponds to an accurately preselected value. The proposed visual image encryption scheme is based on computer generated holography, optical time-averaging moiré and principles of dynamic visual cryptography. Dynamic visual cryptography is used both for the initial encryption of the secret image and for the final decryption. Phase data of the encrypted image are computed by using Gerchberg-Saxton algorithm. The optical image is decrypted using the computationally reconstructed field of amplitudes.

PLOT3D/AMES, GENERIC UNIX VERSION USING DISSPLA (WITH TURB3D)

NASA Technical Reports Server (NTRS)

Buning, P.

1994-01-01

PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into five groups: 1) Grid Functions for grids, grid-checking, etc.; 2) Scalar Functions for contour or carpet plots of density, pressure, temperature, Mach number, vorticity magnitude, helicity, etc.; 3) Vector Functions for vector plots of velocity, vorticity, momentum, and density gradient, etc.; 4) Particle Trace Functions for rake-like plots of particle flow or vortex lines; and 5) Shock locations based on pressure gradient. TURB3D is a modification of PLOT3D which is used for viewing CFD simulations of incompressible turbulent flow. Input flow data consists of pressure, velocity and vorticity. Typical quantities to plot include local fluctuations in flow quantities and turbulent production terms, plotted in physical or wall units. PLOT3D/TURB3D includes both TURB3D and PLOT3D because the operation of TURB3D is identical to PLOT3D, and there is no additional sample data or printed documentation for TURB3D. Graphical capabilities of PLOT3D version 3.6b+ vary among the implementations available through COSMIC. Customers are encouraged to purchase and carefully review the PLOT3D manual before ordering the program for a specific computer and graphics library. There is only one manual for use with all implementations of PLOT3D, and although this manual generally assumes that the Silicon Graphics Iris implementation is being used, informative comments concerning other implementations appear throughout the text. With all implementations, the visual representation of the object and flow field created by PLOT3D consists of points, lines, and polygons. Points can be represented with dots or symbols, color can be used to denote data values, and perspective is used to show depth. Differences among implementations impact the program's ability to use graphical features that are based on 3D polygons, the user's ability to manipulate the graphical displays, and the user's ability to obtain alternate forms of output. The UNIX/DISSPLA implementation of PLOT3D supports 2-D polygons as well as 2-D and 3-D lines, but does not support graphics features requiring 3-D polygons (shading and hidden line removal, for example). Views can be manipulated using keyboard commands. This version of PLOT3D is potentially able to produce files for a variety of output devices; however, site-specific capabilities will vary depending on the device drivers supplied with the user's DISSPLA library. The version 3.6b+ UNIX/DISSPLA implementations of PLOT3D (ARC-12788) and PLOT3D/TURB3D (ARC-12778) were developed for use on computers running UNIX SYSTEM 5 with BSD 4.3 extensions. The standard distribution media for each ofthese programs is a 9track, 6250 bpi magnetic tape in TAR format. Customers purchasing one implementation version of PLOT3D or PLOT3D/TURB3D will be given a $200 discount on each additional implementation version ordered at the same time. Version 3.6b+ of PLOT3D and PLOT3D/TURB3D are also supported for the following computers and graphics libraries: (1) generic UNIX Supercomputer and IRIS, suitable for CRAY 2/UNICOS, CONVEX, Alliant with remote IRIS 2xxx/3xxx or IRIS 4D (ARC-12779, ARC-12784); (2) Silicon Graphics IRIS 2xxx/3xxx or IRIS 4D (ARC-12783, ARC-12782); (3) VAX computers running VMS Version 5.0 and DISSPLA Version 11.0 (ARC-12777, ARC-12781); and (4) Apollo computers running UNIX and GMR3D Version 2.0 (ARC-12789, ARC-12785 which have no capabilities to put text on plots). Silicon Graphics Iris, IRIS 4D, and IRIS 2xxx/3xxx are trademarks of Silicon Graphics Incorporated. VAX and VMS are trademarks of Digital Electronics Corporation. DISSPLA is a trademark of Computer Associates. CRAY 2 and UNICOS are trademarks of CRAY Research, Incorporated. CONVEX is a trademark of Convex Computer Corporation. Alliant is a trademark of Alliant. Apollo and GMR3D are trademarks of Hewlett-Packard, Incorporated. System 5 is a trademark of Bell Labs, Incorporated. BSD4.3 is a trademark of the University of California at Berkeley. UNIX is a registered trademark of AT&T.

PLOT3D/AMES, GENERIC UNIX VERSION USING DISSPLA (WITHOUT TURB3D)

NASA Technical Reports Server (NTRS)

Buning, P.

1994-01-01

PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into five groups: 1) Grid Functions for grids, grid-checking, etc.; 2) Scalar Functions for contour or carpet plots of density, pressure, temperature, Mach number, vorticity magnitude, helicity, etc.; 3) Vector Functions for vector plots of velocity, vorticity, momentum, and density gradient, etc.; 4) Particle Trace Functions for rake-like plots of particle flow or vortex lines; and 5) Shock locations based on pressure gradient. TURB3D is a modification of PLOT3D which is used for viewing CFD simulations of incompressible turbulent flow. Input flow data consists of pressure, velocity and vorticity. Typical quantities to plot include local fluctuations in flow quantities and turbulent production terms, plotted in physical or wall units. PLOT3D/TURB3D includes both TURB3D and PLOT3D because the operation of TURB3D is identical to PLOT3D, and there is no additional sample data or printed documentation for TURB3D. Graphical capabilities of PLOT3D version 3.6b+ vary among the implementations available through COSMIC. Customers are encouraged to purchase and carefully review the PLOT3D manual before ordering the program for a specific computer and graphics library. There is only one manual for use with all implementations of PLOT3D, and although this manual generally assumes that the Silicon Graphics Iris implementation is being used, informative comments concerning other implementations appear throughout the text. With all implementations, the visual representation of the object and flow field created by PLOT3D consists of points, lines, and polygons. Points can be represented with dots or symbols, color can be used to denote data values, and perspective is used to show depth. Differences among implementations impact the program's ability to use graphical features that are based on 3D polygons, the user's ability to manipulate the graphical displays, and the user's ability to obtain alternate forms of output. The UNIX/DISSPLA implementation of PLOT3D supports 2-D polygons as well as 2-D and 3-D lines, but does not support graphics features requiring 3-D polygons (shading and hidden line removal, for example). Views can be manipulated using keyboard commands. This version of PLOT3D is potentially able to produce files for a variety of output devices; however, site-specific capabilities will vary depending on the device drivers supplied with the user's DISSPLA library. The version 3.6b+ UNIX/DISSPLA implementations of PLOT3D (ARC-12788) and PLOT3D/TURB3D (ARC-12778) were developed for use on computers running UNIX SYSTEM 5 with BSD 4.3 extensions. The standard distribution media for each ofthese programs is a 9track, 6250 bpi magnetic tape in TAR format. Customers purchasing one implementation version of PLOT3D or PLOT3D/TURB3D will be given a $200 discount on each additional implementation version ordered at the same time. Version 3.6b+ of PLOT3D and PLOT3D/TURB3D are also supported for the following computers and graphics libraries: (1) generic UNIX Supercomputer and IRIS, suitable for CRAY 2/UNICOS, CONVEX, Alliant with remote IRIS 2xxx/3xxx or IRIS 4D (ARC-12779, ARC-12784); (2) Silicon Graphics IRIS 2xxx/3xxx or IRIS 4D (ARC-12783, ARC-12782); (3) VAX computers running VMS Version 5.0 and DISSPLA Version 11.0 (ARC-12777, ARC-12781); and (4) Apollo computers running UNIX and GMR3D Version 2.0 (ARC-12789, ARC-12785 which have no capabilities to put text on plots). Silicon Graphics Iris, IRIS 4D, and IRIS 2xxx/3xxx are trademarks of Silicon Graphics Incorporated. VAX and VMS are trademarks of Digital Electronics Corporation. DISSPLA is a trademark of Computer Associates. CRAY 2 and UNICOS are trademarks of CRAY Research, Incorporated. CONVEX is a trademark of Convex Computer Corporation. Alliant is a trademark of Alliant. Apollo and GMR3D are trademarks of Hewlett-Packard, Incorporated. System 5 is a trademark of Bell Labs, Incorporated. BSD4.3 is a trademark of the University of California at Berkeley. UNIX is a registered trademark of AT&T.

The Computational Science Education Reference Desk: A tool for increasing inquiry based learning in the science classroom

NASA Astrophysics Data System (ADS)

Joiner, D. A.; Stevenson, D. E.; Panoff, R. M.

2000-12-01

The Computational Science Reference Desk is an online tool designed to provide educators in math, physics, astronomy, biology, chemistry, and engineering with information on how to use computational science to enhance inquiry based learning in the undergraduate and pre college classroom. The Reference Desk features a showcase of original content exploration activities, including lesson plans and background materials; a catalog of websites which contain models, lesson plans, software, and instructional resources; and a forum to allow educators to communicate their ideas. Many of the recent advances in astronomy rely on the use of computer simulation, and tools are being developed by CSERD to allow students to experiment with some of the models that have guided scientific discovery. One of these models allows students to study how scientists use spectral information to determine the makeup of the interstellar medium by modeling the interstellar extinction curve using spherical grains of silicate, amorphous carbon, or graphite. Students can directly compare their model to the average interstellar extinction curve, and experiment with how small changes in their model alter the shape of the interstellar extinction curve. A simpler model allows students to visualize spatial relationships between the Earth, Moon, and Sun to understand the cause of the phases of the moon. A report on the usefulness of these models in two classes, the Computational Astrophysics workshop at The Shodor Education Foundation and the Conceptual Astronomy class at the University of North Carolina at Greensboro, will be presented.

Of the Helmholtz Club, South-Californian seedbed for visual and cognitive neuroscience, and its patron Francis Crick.

PubMed

Aicardi, Christine

2014-03-01

Taking up the view that semi-institutional gatherings such as clubs, societies, research schools, have been instrumental in creating sheltered spaces from which many a 20th-century project-driven interdisciplinary research programme could develop and become established within the institutions of science, the paper explores the history of one such gathering from its inception in the early 1980s into the 2000s, the Helmholtz Club, which brought together scientists from such various research fields as neuroanatomy, neurophysiology, psychophysics, computer science and engineering, who all had an interest in the study of the visual system and of higher cognitive functions relying on visual perception such as visual consciousness. It argues that British molecular biologist turned South Californian neuroscientist Francis Crick had an early and lasting influence over the Helmholtz Club of which he was a founding pillar, and that from its inception, the club served as a constitutive element in his long-term plans for a neuroscience of vision and of cognition. Further, it argues that in this role, the Helmholtz Club served many purposes, the primary of which was to be a social forum for interdisciplinary discussion, where 'discussion' was not mere talk but was imbued with an epistemic value and as such, carefully cultivated. Finally, it questions what counts as 'doing science' and in turn, definitions of success and failure-and provides some material evidence towards re-appraising the successfulness of Crick's contribution to the neurosciences. Copyright © 2013 The Author. Published by Elsevier Ltd.. All rights reserved.

Volunteer Clouds and Citizen Cyberscience for LHC Physics

NASA Astrophysics Data System (ADS)

Aguado Sanchez, Carlos; Blomer, Jakob; Buncic, Predrag; Chen, Gang; Ellis, John; Garcia Quintas, David; Harutyunyan, Artem; Grey, Francois; Lombrana Gonzalez, Daniel; Marquina, Miguel; Mato, Pere; Rantala, Jarno; Schulz, Holger; Segal, Ben; Sharma, Archana; Skands, Peter; Weir, David; Wu, Jie; Wu, Wenjing; Yadav, Rohit

2011-12-01

Computing for the LHC, and for HEP more generally, is traditionally viewed as requiring specialized infrastructure and software environments, and therefore not compatible with the recent trend in "volunteer computing", where volunteers supply free processing time on ordinary PCs and laptops via standard Internet connections. In this paper, we demonstrate that with the use of virtual machine technology, at least some standard LHC computing tasks can be tackled with volunteer computing resources. Specifically, by presenting volunteer computing resources to HEP scientists as a "volunteer cloud", essentially identical to a Grid or dedicated cluster from a job submission perspective, LHC simulations can be processed effectively. This article outlines both the technical steps required for such a solution and the implications for LHC computing as well as for LHC public outreach and for participation by scientists from developing regions in LHC research.

Computer-based communication in support of scientific and technical work. [conferences on management information systems used by scientists of NASA programs

NASA Technical Reports Server (NTRS)

Vallee, J.; Wilson, T.

1976-01-01

Results are reported of the first experiments for a computer conference management information system at the National Aeronautics and Space Administration. Between August 1975 and March 1976, two NASA projects with geographically separated participants (NASA scientists) used the PLANET computer conferencing system for portions of their work. The first project was a technology assessment of future transportation systems. The second project involved experiments with the Communication Technology Satellite. As part of this project, pre- and postlaunch operations were discussed in a computer conference. These conferences also provided the context for an analysis of the cost of computer conferencing. In particular, six cost components were identified: (1) terminal equipment, (2) communication with a network port, (3) network connection, (4) computer utilization, (5) data storage and (6) administrative overhead.

Know Your Discipline: Teaching the Philosophy of Computer Science

ERIC Educational Resources Information Center

Tedre, Matti

2007-01-01

The diversity and interdisciplinarity of computer science and the multiplicity of its uses in other sciences make it hard to define computer science and to prescribe how computer science should be carried out. The diversity of computer science also causes friction between computer scientists from different branches. Computer science curricula, as…

PLANETarium Pilot: visualizing PLANET Earth inside-out on the planetarium's full-dome

NASA Astrophysics Data System (ADS)

Ballmer, Maxim; Wiethoff, Tobias

2016-04-01

In the past decade, projection systems in most planetariums, traditional sites of outreach and education, have advanced from interfaces that can display the motion of stars as moving beam spots to systems that are able to visualize multicolor, high-resolution, immersive full-dome videos or images. These extraordinary capabilities are ideally suited for visualization of global processes occurring on the surface and within the interior of the Earth, a spherical body just as the full dome. So far, however, our community has largely ignored this wonderful interface for outreach and education, and any previous geo-shows have mostly been limited to cartoon-style animations. Thus, we here propose a framework to convey recent scientific results on the origin and evolution of our PLANET to the >100 million per-year worldwide audience of planetariums, making the traditionally astronomy-focussed interface a true PLANETarium. In order to do this most efficiently, we intend to show "inside-out" visualizations of scientific datasets and models, as if the audience was positioned in the Earth's core. Such visualizations are expected to be renderable to the dome with little or no effort. For example, showing global geophysical datasets (e.g., gravity, air temperature), or horizontal slices of seismic-tomography images and spherical computer models requires no rendering at all. Rendering of 3D Cartesian datasets or models may further be achieved using standard techiques. Here, we show several example pilot animations. These animations rendered for the full dome are projected back to 2D for visualization on the flatscreen. Present-day science visualizations are typically as intuitive as cartoon-style animations, yet more appealing visually, and clearly with a higher level of detail. In addition to e.g. climate change and natural hazards, themes for any future geo-shows may include the coupled evolution of the Earth's interior and life, from the accretion of our planet to the evolution of mantle convection as well as the sustainment of a magnetic field and habitable conditions. We believe that high-quality tax-funded science visualizations should not exclusively be used for communication among scientists, but also recycled to raise the public's awareness and appreciation of the Geosciences.

PLANETarium Pilot: visualizing PLANET Earth inside-out on the planetarium's full-dome

NASA Astrophysics Data System (ADS)

Ballmer, M. D.; Wiethoff, T.

2014-12-01

In the past decade, projection systems in most planetariums, traditional sites of outreach and education, have advanced from interfaces that can display the motion of stars as moving beam spots to systems that are able to visualize multicolor, high-resolution, immersive full-dome videos or images. These extraordinary capabilities are ideally suited for visualization of global processes occurring on the surface and within the interior of the Earth, a spherical body just as the full dome. So far, however, our community has largely ignored this wonderful interface for outreach and education, and any previous geo-shows have mostly been limited to cartoon-style animations. Thus, we here propose a framework to convey recent scientific results on the origin and evolution of our PLANET to the >100 million per-year worldwide audience of planetariums, making the traditionally astronomy-focussed interface a true PLANETarium. In order to do this most efficiently, we intend to show „inside-out" visualizations of scientific datasets and models, as if the audience was positioned in the Earth's inner core. Such visualizations are expected to be renderable to the dome with little or no effort. For example, showing global geophysical datasets (e.g., gravity, air temperature), or horizontal slices of seismic-tomography images and spherical computer models requires no rendering at all. Rendering of 3D Cartesian datasets or models may further be achieved using standard techiques. Here, we show several example pilot animations. These animations rendered for the full dome are projected back to 2D for visualization on a flatscreen. Present-day science visualizations are typically as intuitive as cartoon-style animations, yet more appealing visually, and clearly with a higher level of detail. In addition to e.g. climate change and natural hazards, themes for any future geo-shows may include the coupled evolution of the Earth's interior and life, from the accretion of our planet to the evolution of mantle convection as well as the sustainment of a magnetic field and habitable conditions. We believe that high-quality tax-funded science visualizations should not exclusively be used for communication among scientists, but also recycled to raise the public's awareness and appreciation of the geosciences.

Science information systems: Visualization

NASA Technical Reports Server (NTRS)

Wall, Ray J.

1991-01-01

Future programs in earth science, planetary science, and astrophysics will involve complex instruments that produce data at unprecedented rates and volumes. Current methods for data display, exploration, and discovery are inadequate. Visualization technology offers a means for the user to comprehend, explore, and examine complex data sets. The goal of this program is to increase the effectiveness and efficiency of scientists in extracting scientific information from large volumes of instrument data.

Popularization and Teaching of the Relationship between Visual Arts and Natural Sciences: Historical, Philosophical and Didactical Dimensions of the Problem

ERIC Educational Resources Information Center

Arapaki, Xenia; Koliopoulos, Dimitris

2011-01-01

The need for a convergence of the visual arts and the natural sciences within the framework of both formal (schools, universities) and non-formal education (museum) at the level of dissemination and popularization of this knowledge is something that has preoccupied the communities of artists, scientists and educators. In the present work we aim to…

A fish on the hunt, observed neuron by neuron

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2010-01-01

This three-dimensional microscopy image reveals an output neuron of the optic tectum lighting up in response to visual information from the retina. The scientists used this state-of-the-art imaging technology to learn how neurons in the optic tectum take visual information and convert it into an output that drives action. More information: http://newscenter.lbl.gov/feature-stories/2010/10/29/zebrafish-vision/

Computerized Writing and Reading Instruction for Students in Grades 4 to 9 With Specific Learning Disabilities Affecting Written Language

PubMed Central

Tanimoto, Steven; Thompson, Rob; Berninger, Virginia W.; Nagy, William; Abbott, Robert D.

2015-01-01

Computer scientists and educational researchers evaluated effectiveness of computerized instruction tailored to evidence-based impairments in specific learning disabilities (SLDs) in students in grades 4 to 9 with persisting SLDs despite prior extra help. Following comprehensive, evidence-based differential diagnosis for dysgraphia (impaired handwriting), dyslexia (impaired word reading and spelling), and oral and written language learning disability (OWL LD), students completed 18 sessions of computerized instruction over about 3 months. The 11 students taught letter formation with sequential, numbered, colored arrow cues with full contours who wrote letters on lines added to iPAD screen showed more and stronger treatment effects than the 21 students taught using only visual motion cues for letter formation who wrote on an unlined computer monitor. Teaching to all levels of language in multiple functional language systems (by ear, eye, mouth, and hand) close in time resulted in significant gains in reading and writing skills for the group and in diagnosed SLD hallmark impairments for individuals; also, performance on computerized learning activities correlated with treatment gains. Results are discussed in reference to need for both accommodations and explicit instruction for persisting SLDs and the potential for computers to teach handwriting, morphophonemic orthographies, comprehension, and composition. PMID:26858470

Computer-Based Tutoring of Visual Concepts: From Novice to Experts.

ERIC Educational Resources Information Center

Sharples, Mike

1991-01-01

Description of ways in which computers might be used to teach visual concepts discusses hypermedia systems; describes computer-generated tutorials; explains the use of computers to create learning aids such as concept maps, feature spaces, and structural models; and gives examples of visual concept teaching in medical education. (10 references)…

Deep hierarchies in the primate visual cortex: what can we learn for computer vision?

PubMed

Krüger, Norbert; Janssen, Peter; Kalkan, Sinan; Lappe, Markus; Leonardis, Ales; Piater, Justus; Rodríguez-Sánchez, Antonio J; Wiskott, Laurenz

2013-08-01

Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Organized for a computer vision audience, we present functional principles of the processing hierarchies present in the primate visual system considering recent discoveries in neurophysiology. The hierarchical processing in the primate visual system is characterized by a sequence of different levels of processing (on the order of 10) that constitute a deep hierarchy in contrast to the flat vision architectures predominantly used in today's mainstream computer vision. We hope that the functional description of the deep hierarchies realized in the primate visual system provides valuable insights for the design of computer vision algorithms, fostering increasingly productive interaction between biological and computer vision research.

"What's A Geoscientist Do?": A Student Recruitment And Education Tool

NASA Astrophysics Data System (ADS)

Hughes, C. G.

2015-12-01

Student perception of science, particularly the earth sciences, is not based on actual science jobs. Students have difficulty envisioning themselves as scientists, or in understanding the role of science in their lives as a result. Not all students can envision themselves as scientists when first enrolling in college. While student recruitment into geoscience programs starts before college enrollment at many universities, general education science requirements can act as a gateway into these majors as well. By providing students in general education science classes with more accurate insights into the scientific process and what it means to be a scientist, these classes can help students envision themselves as scientists. A short module, to be embedded within lectures, has been developed to improve recruitment from Clarion University's Introductory Earth Science classes entitled "What's A Geoscientist Do?". As this module aims to help students visualize themselves as geoscientists through examples, diversity of the examples is critical to recruiting students from underrepresented groups. Images and subjects within these modules are carefully selected to emphasize the fact that the geosciences are not, and should not be, the exclusive province of the stereotypical older, white, male scientist. Noteworthy individuals (e.g. John Wesley Powell, Roger Arliner Young) may be highlighted, or the discussion may focus on a particular career path (e.g. hydrologist) relevant to that day's material. While some students are initially attracted to the geosciences due to a love of the outdoors, many students have never spent a night outdoors, and do not find this aspect of the geosciences particularly appealing. "What's A Geoscientist Do?" has been designed to expose these students to the breadth of the field, including a number of geoscience jobs focused on laboratory (e.g. geochemistry) or computer (e.g. GIS, remote sensing, scientific illustration) work instead of focusing exclusively on fieldwork. As Clarion University students tend to be very job-oriented, information on careers includes average starting salaries with the hope of improving student's opinions of the position as possible future employment - helping students (and their families) realize they can support themselves in a geoscience career.

50 Years of renal physiology from one man and the perfused tubule: Maurice B. Burg.

PubMed

Hamilton, Kirk L; Moore, Antoni B

2016-08-01

Technical advancements in research techniques in science are made in slow increments. Even so, large advances from insight and hard work of an individual with a single technique can have astonishing ramifications. Here, we examine the impact of Dr. Maurice B. Burg and the isolated perfused renal tubule technique and celebrate the 50th anniversary of the publication by Dr. Burg and his colleagues of their landmark paper in the American Journal of Physiology in 1966. In this study, we have taken a scientific visualization approach to study the scientific contributions of Dr. Burg and the isolated perfused tubule preparation as determining research impact by the number of research students, postdoctoral fellows, visiting scientists, and national and international collaborators. Additionally, we have examined the research collaborations (first and second generation scientists), established the migrational visualization of the first generation scientists who worked directly with Dr. Burg, quantified the metrics indices, identified and quantified the network of coauthorship of the first generation scientists with their second generation links, and determined the citations analyses of outputs of Dr. Burg and/or his first generation collaborators as coauthors. We also review the major advances in kidney physiology that have been made with the isolated perfused tubule technique. Finally, we are all waiting for the discoveries that the isolated perfused preparation technique will bring during the next 50 years. Copyright © 2016 the American Physiological Society.

Benefits of Exchange Between Computer Scientists and Perceptual Scientists: A Panel Discussion

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Null, Cynthia H. (Technical Monitor)

1995-01-01

We have established several major goals for this panel: 1) Introduce the computer graphics community to some specific leaders in the use of perceptual psychology relating to computer graphics; 2) Enumerate the major results that are known, and provide a set of resources for finding others; 3) Identify research areas where knowledge of perceptual psychology can help computer system designers improve their systems; and 4) Provide advice to researchers on how they can establish collaborations in their own research programs. We believe this will be a very important panel. In addition to generating lively discussion, we hope to point out some of the fundamental issues that occur at the boundary between computer science and perception, and possibly help researchers avoid some of the common pitfalls.

Visual Memories Bypass Normalization.

PubMed

Bloem, Ilona M; Watanabe, Yurika L; Kibbe, Melissa M; Ling, Sam

2018-05-01

How distinct are visual memory representations from visual perception? Although evidence suggests that briefly remembered stimuli are represented within early visual cortices, the degree to which these memory traces resemble true visual representations remains something of a mystery. Here, we tested whether both visual memory and perception succumb to a seemingly ubiquitous neural computation: normalization. Observers were asked to remember the contrast of visual stimuli, which were pitted against each other to promote normalization either in perception or in visual memory. Our results revealed robust normalization between visual representations in perception, yet no signature of normalization occurring between working memory stores-neither between representations in memory nor between memory representations and visual inputs. These results provide unique insight into the nature of visual memory representations, illustrating that visual memory representations follow a different set of computational rules, bypassing normalization, a canonical visual computation.

Visual Memories Bypass Normalization

PubMed Central

Bloem, Ilona M.; Watanabe, Yurika L.; Kibbe, Melissa M.; Ling, Sam

2018-01-01

How distinct are visual memory representations from visual perception? Although evidence suggests that briefly remembered stimuli are represented within early visual cortices, the degree to which these memory traces resemble true visual representations remains something of a mystery. Here, we tested whether both visual memory and perception succumb to a seemingly ubiquitous neural computation: normalization. Observers were asked to remember the contrast of visual stimuli, which were pitted against each other to promote normalization either in perception or in visual memory. Our results revealed robust normalization between visual representations in perception, yet no signature of normalization occurring between working memory stores—neither between representations in memory nor between memory representations and visual inputs. These results provide unique insight into the nature of visual memory representations, illustrating that visual memory representations follow a different set of computational rules, bypassing normalization, a canonical visual computation. PMID:29596038

Boom. Bust. Build.

ERIC Educational Resources Information Center

Kite, Vance; Park, Soonhye

2018-01-01

In 2006 Jeanette Wing, a professor of computer science at Carnegie Mellon University, proposed computational thinking (CT) as a literacy just as important as reading, writing, and mathematics. Wing defined CT as a set of skills and strategies computer scientists use to solve complex, computational problems (Wing 2006). The computer science and…

Software applications to three-dimensional visualization of forest landscapes -- A case study demontrating the use of visual nature studio (VNS) in visualizing fire spread in forest landscapes

Treesearch

Brian J. Williams; Bo Song; Chou Chiao-Ying; Thomas M. Williams; John Hom

2010-01-01

Three-dimensional (3D) visualization is a useful tool that depicts virtual forest landscapes on computer. Previous studies in visualization have required high end computer hardware and specialized technical skills. A virtual forest landscape can be used to show different effects of disturbances and management scenarios on a computer, which allows observation of forest...

Workforce Retention Study in Support of the U.S. Army Aberdeen Test Center Human Capital Management Strategy

DTIC Science & Technology

2016-09-01

Sciences Group 6% 1550s Computer Scientists Group 5% Other 1500s ORSAa, Mathematics, & Statistics Group 3% 1600s Equipment & Facilities Group 4...Employee removal based on misconduct, delinquency , suitability, unsatisfactory performance, or failure to qualify for conversion to a career appointment...average of 10.4% in many areas, but over double the average for the 1550s (Computer Scientists) and other 1500s (ORSA, Mathematics, and Statistics ). Also

Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

1999-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2000-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations

PubMed Central

Sun, Peng; Zhou, Haoyin; Ha, Seongmin; Hartaigh, Bríain ó; Truong, Quynh A.; Min, James K.

2016-01-01

In clinical cardiology, both anatomy and physiology are needed to diagnose cardiac pathologies. CT imaging and computer simulations provide valuable and complementary data for this purpose. However, it remains challenging to gain useful information from the large amount of high-dimensional diverse data. The current tools are not adequately integrated to visualize anatomic and physiologic data from a complete yet focused perspective. We introduce a new computer-aided diagnosis framework, which allows for comprehensive modeling and visualization of cardiac anatomy and physiology from CT imaging data and computer simulations, with a primary focus on ischemic heart disease. The following visual information is presented: (1) Anatomy from CT imaging: geometric modeling and visualization of cardiac anatomy, including four heart chambers, left and right ventricular outflow tracts, and coronary arteries; (2) Function from CT imaging: motion modeling, strain calculation, and visualization of four heart chambers; (3) Physiology from CT imaging: quantification and visualization of myocardial perfusion and contextual integration with coronary artery anatomy; (4) Physiology from computer simulation: computation and visualization of hemodynamics (e.g., coronary blood velocity, pressure, shear stress, and fluid forces on the vessel wall). Substantially, feedback from cardiologists have confirmed the practical utility of integrating these features for the purpose of computer-aided diagnosis of ischemic heart disease. PMID:26863663

Scientific Visualization and Computational Science: Natural Partners

NASA Technical Reports Server (NTRS)

Uselton, Samuel P.; Lasinski, T. A. (Technical Monitor)

1995-01-01

Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization research because the results vary so widely and include things that have no known appearance. The amount of data creates additional challenges for both hardware and software systems. Evaluations of visualization should ultimately reflect the insight gained into the scientific phenomena. So making good visualizations requires consideration of characteristics of the user and the purpose of the visualization. Knowledge about human perception and graphic design is also relevant. It is this breadth of knowledge that stimulates proposals for multidisciplinary visualization teams and intelligent visualization assistant software. Visualization is an immature field, but computational science is stimulating research on a broad front.

Visual problems in young adults due to computer use.

PubMed

Moschos, M M; Chatziralli, I P; Siasou, G; Papazisis, L

2012-04-01

Computer use can cause visual problems. The purpose of our study was to evaluate visual problems due to computer use in young adults. Participants in our study were 87 adults, 48 male and 39 female, mean aged 31.3 years old (SD 7.6). All the participants completed a questionnaire regarding visual problems detected after computer use. The mean daily use of computers was 3.2 hours (SD 2.7). 65.5 % of the participants complained for dry eye, mainly after more than 2.5 hours of computer use. 32 persons (36.8 %) had a foreign body sensation in their eyes, while 15 participants (17.2 %) complained for blurred vision which caused difficulties in driving, after 3.25 hours of continuous computer use. 10.3 % of the participants sought medical advice for their problem. There was a statistically significant correlation between the frequency of visual problems and the duration of computer use (p = 0.021). 79.3 % of the participants use artificial tears during or after long use of computers, so as not to feel any ocular discomfort. The main symptom after computer use in young adults was dry eye. All visual problems associated with the duration of computer use. Artificial tears play an important role in the treatment of ocular discomfort after computer use. © Georg Thieme Verlag KG Stuttgart · New York.

Recent Advances and Issues in Computers. Oryx Frontiers of Science Series.

ERIC Educational Resources Information Center

Gay, Martin K.

Discussing recent issues in computer science, this book contains 11 chapters covering: (1) developments that have the potential for changing the way computers operate, including microprocessors, mass storage systems, and computing environments; (2) the national computational grid for high-bandwidth, high-speed collaboration among scientists, and…

Visualization Tools for Teaching Computer Security

ERIC Educational Resources Information Center

Yuan, Xiaohong; Vega, Percy; Qadah, Yaseen; Archer, Ricky; Yu, Huiming; Xu, Jinsheng

2010-01-01

Using animated visualization tools has been an important teaching approach in computer science education. We have developed three visualization and animation tools that demonstrate various information security concepts and actively engage learners. The information security concepts illustrated include: packet sniffer and related computer network…

Preface: SciDAC 2006

NASA Astrophysics Data System (ADS)

Tang, William M., Dr.

2006-01-01

The second annual Scientific Discovery through Advanced Computing (SciDAC) Conference was held from June 25-29, 2006 at the new Hyatt Regency Hotel in Denver, Colorado. This conference showcased outstanding SciDAC-sponsored computational science results achieved during the past year across many scientific domains, with an emphasis on science at scale. Exciting computational science that has been accomplished outside of the SciDAC program both nationally and internationally was also featured to help foster communication between SciDAC computational scientists and those funded by other agencies. This was illustrated by many compelling examples of how domain scientists collaborated productively with applied mathematicians and computer scientists to effectively take advantage of terascale computers (capable of performing trillions of calculations per second) not only to accelerate progress in scientific discovery in a variety of fields but also to show great promise for being able to utilize the exciting petascale capabilities in the near future. The SciDAC program was originally conceived as an interdisciplinary computational science program based on the guiding principle that strong collaborative alliances between domain scientists, applied mathematicians, and computer scientists are vital to accelerated progress and associated discovery on the world's most challenging scientific problems. Associated verification and validation are essential in this successful program, which was funded by the US Department of Energy Office of Science (DOE OS) five years ago. As is made clear in many of the papers in these proceedings, SciDAC has fundamentally changed the way that computational science is now carried out in response to the exciting challenge of making the best use of the rapid progress in the emergence of more and more powerful computational platforms. In this regard, Dr. Raymond Orbach, Energy Undersecretary for Science at the DOE and Director of the OS has stated: `SciDAC has strengthened the role of high-end computing in furthering science. It is defining whole new fields for discovery.' (SciDAC Review, Spring 2006, p8). Application domains within the SciDAC 2006 conference agenda encompassed a broad range of science including: (i) the DOE core mission of energy research involving combustion studies relevant to fuel efficiency and pollution issues faced today and magnetic fusion investigations impacting prospects for future energy sources; (ii) fundamental explorations into the building blocks of matter, ranging from quantum chromodynamics - the basic theory that describes how quarks make up the protons and neutrons of all matter - to the design of modern high-energy accelerators; (iii) the formidable challenges of predicting and controlling the behavior of molecules in quantum chemistry and the complex biomolecules determining the evolution of biological systems; (iv) studies of exploding stars for insights into the nature of the universe; and (v) integrated climate modeling to enable realistic analysis of earth's changing climate. Associated research has made it quite clear that advanced computation is often the only means by which timely progress is feasible when dealing with these complex, multi-component physical, chemical, and biological systems operating over huge ranges of temporal and spatial scales. Working with the domain scientists, applied mathematicians and computer scientists have continued to develop the discretizations of the underlying equations and the complementary algorithms to enable improvements in solutions on modern parallel computing platforms as they evolve from the terascale toward the petascale regime. Moreover, the associated tremendous growth of data generated from the terabyte to the petabyte range demands not only the advanced data analysis and visualization methods to harvest the scientific information but also the development of efficient workflow strategies which can deal with the data input/output, management, movement, and storage challenges. If scientific discovery is expected to keep apace with the continuing progression from tera- to petascale platforms, the vital alliance between domain scientists, applied mathematicians, and computer scientists will be even more crucial. During the SciDAC 2006 Conference, some of the future challenges and opportunities in interdisciplinary computational science were emphasized in the Advanced Architectures Panel and by Dr. Victor Reis, Senior Advisor to the Secretary of Energy, who gave a featured presentation on `Simulation, Computation, and the Global Nuclear Energy Partnership.' Overall, the conference provided an excellent opportunity to highlight the rising importance of computational science in the scientific enterprise and to motivate future investment in this area. As Michael Strayer, SciDAC Program Director, has noted: `While SciDAC may have started out as a specific program, Scientific Discovery through Advanced Computing has become a powerful concept for addressing some of the biggest challenges facing our nation and our world.' Looking forward to next year, the SciDAC 2007 Conference will be held from June 24-28 at the Westin Copley Plaza in Boston, Massachusetts. Chairman: David Keyes, Columbia University. The Organizing Committee for the SciDAC 2006 Conference would like to acknowledge the individuals whose talents and efforts were essential to the success of the meeting. Special thanks go to Betsy Riley for her leadership in building the infrastructure support for the conference, for identifying and then obtaining contributions from our corporate sponsors, for coordinating all media communications, and for her efforts in organizing and preparing the conference proceedings for publication; to Tim Jones for handling the hotel scouting, subcontracts, and exhibits and stage production; to Angela Harris for handling supplies, shipping, and tracking, poster sessions set-up, and for her efforts in coordinating and scheduling the promotional activities that took place during the conference; to John Bui and John Smith for their superb wireless networking and A/V set-up and support; to Cindy Latham for Web site design, graphic design, and quality control of proceedings submissions; and to Pamelia Nixon-Hartje of Ambassador for budget and quality control of catering. We are grateful for the highly professional dedicated efforts of all of these individuals, who were the cornerstones of the SciDAC 2006 Conference. Thanks also go to Angela Beach of the ORNL Conference Center for her efforts in executing the contracts with the hotel, Carolyn James of Colorado State for on-site registration supervision, Lora Wolfe and Brittany Hagen for administrative support at ORNL, and Dami Rich and Andrew Sproles for graphic design and production. We are also most grateful to the Oak Ridge National Laboratory, especially Jeff Nichols, and to our corporate sponsors, Data Direct Networks, Cray, IBM, SGI, and Institute of Physics Publishing for their support. We especially express our gratitude to the featured speakers, invited oral speakers, invited poster presenters, session chairs, and advanced architecture panelists and chair for their excellent contributions on behalf of SciDAC 2006. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas, Margaret Smith, and the production team of Institute of Physics Publishing, who worked tirelessly to publish the final conference proceedings in a timely manner. Finally, heartfelt thanks are extended to Michael Strayer, Associate Director for OASCR and SciDAC Director, and to the DOE program managers associated with SciDAC for their continuing enthusiasm and strong support for the annual SciDAC Conferences as a special venue to showcase the exciting scientific discovery achievements enabled by the interdisciplinary collaborations championed by the SciDAC program.

PLOT3D/AMES, APOLLO UNIX VERSION USING GMR3D (WITHOUT TURB3D)

NASA Technical Reports Server (NTRS)

Buning, P.

1994-01-01

PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into five groups: 1) Grid Functions for grids, grid-checking, etc.; 2) Scalar Functions for contour or carpet plots of density, pressure, temperature, Mach number, vorticity magnitude, helicity, etc.; 3) Vector Functions for vector plots of velocity, vorticity, momentum, and density gradient, etc.; 4) Particle Trace Functions for rake-like plots of particle flow or vortex lines; and 5) Shock locations based on pressure gradient. TURB3D is a modification of PLOT3D which is used for viewing CFD simulations of incompressible turbulent flow. Input flow data consists of pressure, velocity and vorticity. Typical quantities to plot include local fluctuations in flow quantities and turbulent production terms, plotted in physical or wall units. PLOT3D/TURB3D includes both TURB3D and PLOT3D because the operation of TURB3D is identical to PLOT3D, and there is no additional sample data or printed documentation for TURB3D. Graphical capabilities of PLOT3D version 3.6b+ vary among the implementations available through COSMIC. Customers are encouraged to purchase and carefully review the PLOT3D manual before ordering the program for a specific computer and graphics library. There is only one manual for use with all implementations of PLOT3D, and although this manual generally assumes that the Silicon Graphics Iris implementation is being used, informative comments concerning other implementations appear throughout the text. With all implementations, the visual representation of the object and flow field created by PLOT3D consists of points, lines, and polygons. Points can be represented with dots or symbols, color can be used to denote data values, and perspective is used to show depth. Differences among implementations impact the program's ability to use graphical features that are based on 3D polygons, the user's ability to manipulate the graphical displays, and the user's ability to obtain alternate forms of output. The Apollo implementation of PLOT3D uses some of the capabilities of Apollo's 3-dimensional graphics hardware, but does not take advantage of the shading and hidden line/surface removal capabilities of the Apollo DN10000. Although this implementation does not offer a capability for putting text on plots, it does support the use of a mouse to translate, rotate, or zoom in on views. The version 3.6b+ Apollo implementations of PLOT3D (ARC-12789) and PLOT3D/TURB3D (ARC-12785) were developed for use on Apollo computers running UNIX System V with BSD 4.3 extensions and the graphics library GMR3D Version 2.0. The standard distribution media for each of these programs is a 9-track, 6250 bpi magnetic tape in TAR format. Customers purchasing one implementation version of PLOT3D or PLOT3D/TURB3D will be given a $200 discount on each additional implementation version ordered at the same time. Version 3.6b+ of PLOT3D and PLOT3D/TURB3D are also supported for the following computers and graphics libraries: 1) generic UNIX Supercomputer and IRIS, suitable for CRAY 2/UNICOS, CONVEX, and Alliant with remote IRIS 2xxx/3xxx or IRIS 4D (ARC-12779, ARC-12784); 2) VAX computers running VMS Version 5.0 and DISSPLA Version 11.0 (ARC-12777, ARC-12781); 3) generic UNIX and DISSPLA Version 11.0 (ARC-12788, ARC-12778); and (4) Silicon Graphics IRIS 2xxx/3xxx or IRIS 4D workstations (ARC-12783, ARC-12782). Silicon Graphics Iris, IRIS 4D, and IRIS 2xxx/3xxx are trademarks of Silicon Graphics Incorporated. VAX and VMS are trademarks of Digital Electronics Corporation. DISSPLA is a trademark of Computer Associates. CRAY 2 and UNICOS are trademarks of CRAY Research, Incorporated. CONVEX is a trademark of Convex Computer Corporation. Alliant is a trademark of Alliant. Apollo and GMR3D are trademarks of Hewlett-Packard, Incorporated. UNIX is a registered trademark of AT&T.

PLOT3D/AMES, APOLLO UNIX VERSION USING GMR3D (WITH TURB3D)

NASA Technical Reports Server (NTRS)

Buning, P.

1994-01-01

PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into five groups: 1) Grid Functions for grids, grid-checking, etc.; 2) Scalar Functions for contour or carpet plots of density, pressure, temperature, Mach number, vorticity magnitude, helicity, etc.; 3) Vector Functions for vector plots of velocity, vorticity, momentum, and density gradient, etc.; 4) Particle Trace Functions for rake-like plots of particle flow or vortex lines; and 5) Shock locations based on pressure gradient. TURB3D is a modification of PLOT3D which is used for viewing CFD simulations of incompressible turbulent flow. Input flow data consists of pressure, velocity and vorticity. Typical quantities to plot include local fluctuations in flow quantities and turbulent production terms, plotted in physical or wall units. PLOT3D/TURB3D includes both TURB3D and PLOT3D because the operation of TURB3D is identical to PLOT3D, and there is no additional sample data or printed documentation for TURB3D. Graphical capabilities of PLOT3D version 3.6b+ vary among the implementations available through COSMIC. Customers are encouraged to purchase and carefully review the PLOT3D manual before ordering the program for a specific computer and graphics library. There is only one manual for use with all implementations of PLOT3D, and although this manual generally assumes that the Silicon Graphics Iris implementation is being used, informative comments concerning other implementations appear throughout the text. With all implementations, the visual representation of the object and flow field created by PLOT3D consists of points, lines, and polygons. Points can be represented with dots or symbols, color can be used to denote data values, and perspective is used to show depth. Differences among implementations impact the program's ability to use graphical features that are based on 3D polygons, the user's ability to manipulate the graphical displays, and the user's ability to obtain alternate forms of output. The Apollo implementation of PLOT3D uses some of the capabilities of Apollo's 3-dimensional graphics hardware, but does not take advantage of the shading and hidden line/surface removal capabilities of the Apollo DN10000. Although this implementation does not offer a capability for putting text on plots, it does support the use of a mouse to translate, rotate, or zoom in on views. The version 3.6b+ Apollo implementations of PLOT3D (ARC-12789) and PLOT3D/TURB3D (ARC-12785) were developed for use on Apollo computers running UNIX System V with BSD 4.3 extensions and the graphics library GMR3D Version 2.0. The standard distribution media for each of these programs is a 9-track, 6250 bpi magnetic tape in TAR format. Customers purchasing one implementation version of PLOT3D or PLOT3D/TURB3D will be given a $200 discount on each additional implementation version ordered at the same time. Version 3.6b+ of PLOT3D and PLOT3D/TURB3D are also supported for the following computers and graphics libraries: 1) generic UNIX Supercomputer and IRIS, suitable for CRAY 2/UNICOS, CONVEX, and Alliant with remote IRIS 2xxx/3xxx or IRIS 4D (ARC-12779, ARC-12784); 2) VAX computers running VMS Version 5.0 and DISSPLA Version 11.0 (ARC-12777, ARC-12781); 3) generic UNIX and DISSPLA Version 11.0 (ARC-12788, ARC-12778); and (4) Silicon Graphics IRIS 2xxx/3xxx or IRIS 4D workstations (ARC-12783, ARC-12782). Silicon Graphics Iris, IRIS 4D, and IRIS 2xxx/3xxx are trademarks of Silicon Graphics Incorporated. VAX and VMS are trademarks of Digital Electronics Corporation. DISSPLA is a trademark of Computer Associates. CRAY 2 and UNICOS are trademarks of CRAY Research, Incorporated. CONVEX is a trademark of Convex Computer Corporation. Alliant is a trademark of Alliant. Apollo and GMR3D are trademarks of Hewlett-Packard, Incorporated. UNIX is a registered trademark of AT&T.

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

NASA Astrophysics Data System (ADS)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs, and web browsers. The framework is designed to be scalable to large datasets, yet easy to use and familiar to scientists using previous tools. Integration in the ACME overall user interface facilitates data publication, further analysis, and quick feedback to model developers and scientists making component or coupled model runs.

IT Tools for Teachers and Scientists, Created by Undergraduate Researchers

NASA Astrophysics Data System (ADS)

Millar, A. Z.; Perry, S.

2007-12-01

Interns in the Southern California Earthquake Center/Undergraduate Studies in Earthquake Information Technology (SCEC/UseIT) program conduct computer science research for the benefit of earthquake scientists and have created products in growing use within the SCEC education and research communities. SCEC/UseIT comprises some twenty undergraduates who combine their varied talents and academic backgrounds to achieve a Grand Challenge that is formulated around needs of SCEC scientists and educators and that reflects the value SCEC places on the integration of computer science and the geosciences. In meeting the challenge, students learn to work on multidisciplinary teams and to tackle complex problems with no guaranteed solutions. Meantime, their efforts bring fresh perspectives and insight to the professionals with whom they collaborate, and consistently produces innovative, useful tools for research and education. The 2007 Grand Challenge was to design and prototype serious games to communicate important earthquake science concepts. Interns broke themselves into four game teams, the Educational Game, the Training Game, the Mitigation Game and the Decision-Making Game, and created four diverse games with topics from elementary plate tectonics to earthquake risk mitigation, with intended players ranging from elementary students to city planners. The games were designed to be versatile, to accommodate variation in the knowledge base of the player; and extensible, to accommodate future additions. The games are played on a web browser or from within SCEC-VDO (Virtual Display of Objects). SCEC-VDO, also engineered by UseIT interns, is a 4D, interactive, visualization software that enables integration and exploration of datasets and models such as faults, earthquake hypocenters and ruptures, digital elevation models, satellite imagery, global isochrons, and earthquake prediction schemes. SCEC-VDO enables the user to create animated movies during a session, and is now part of a multi-media, general education curriculum at University of Southern California. Throughout this meeting, at the SCEC booth, UseIT interns will be demonstrating both the serious games and SCEC-VDO. SCEC/UseIT is a National Science Foundation Research Experience for Undergraduates site.

Data Prospecting Framework - a new approach to explore "big data" in Earth Science

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Rushing, J.; Lin, A.; Kuo, K.

2012-12-01

Due to advances in sensors, computation and storage, cost and effort required to produce large datasets have been significantly reduced. As a result, we are seeing a proliferation of large-scale data sets being assembled in almost every science field, especially in geosciences. Opportunities to exploit the "big data" are enormous as new hypotheses can be generated by combining and analyzing large amounts of data. However, such a data-driven approach to science discovery assumes that scientists can find and isolate relevant subsets from vast amounts of available data. Current Earth Science data systems only provide data discovery through simple metadata and keyword-based searches and are not designed to support data exploration capabilities based on the actual content. Consequently, scientists often find themselves downloading large volumes of data, struggling with large amounts of storage and learning new analysis technologies that will help them separate the wheat from the chaff. New mechanisms of data exploration are needed to help scientists discover the relevant subsets We present data prospecting, a new content-based data analysis paradigm to support data-intensive science. Data prospecting allows the researchers to explore big data in determining and isolating data subsets for further analysis. This is akin to geo-prospecting in which mineral sites of interest are determined over the landscape through screening methods. The resulting "data prospects" only provide an interaction with and feel for the data through first-look analytics; the researchers would still have to download the relevant datasets and analyze them deeply using their favorite analytical tools to determine if the datasets will yield new hypotheses. Data prospecting combines two traditional categories of data analysis, data exploration and data mining within the discovery step. Data exploration utilizes manual/interactive methods for data analysis such as standard statistical analysis and visualization, usually on small datasets. On the other hand, data mining utilizes automated algorithms to extract useful information. Humans guide these automated algorithms and specify algorithm parameters (training samples, clustering size, etc.). Data Prospecting combines these two approaches using high performance computing and the new techniques for efficient distributed file access.

Building Virtual Mars

NASA Astrophysics Data System (ADS)

Abercrombie, S. P.; Menzies, A.; Goddard, C.

2017-12-01

Virtual and augmented reality enable scientists to visualize environments that are very difficult, or even impossible to visit, such as the surface of Mars. A useful immersive visualization begins with a high quality reconstruction of the environment under study. This presentation will discuss a photogrammetry pipeline developed at the Jet Propulsion Laboratory to reconstruct 3D models of the surface of Mars using stereo images sent back to Earth by the Curiosity Mars rover. The resulting models are used to support a virtual reality tool (OnSight) that allows scientists and engineers to visualize the surface of Mars as if they were standing on the red planet. Images of Mars present challenges to existing scene reconstruction solutions. Surface images of Mars are sparse with minimal overlap, and are often taken from extremely different viewpoints. In addition, the specialized cameras used by Mars rovers are significantly different than consumer cameras, and GPS localization data is not available on Mars. This presentation will discuss scene reconstruction with an emphasis on coping with limited input data, and on creating models suitable for rendering in virtual reality at high frame rate.

Advanced Techniques for Simulating the Behavior of Sand

NASA Astrophysics Data System (ADS)

Clothier, M.; Bailey, M.

2009-12-01

Computer graphics and visualization techniques continue to provide untapped research opportunities, particularly when working with earth science disciplines. Through collaboration with the Oregon Space Grant and IGERT Ecosystem Informatics programs we are developing new techniques for simulating sand. In addition, through collaboration with the Oregon Space Grant, we’ve been communicating with the Jet Propulsion Laboratory (JPL) to exchange ideas and gain feedback on our work. More specifically, JPL’s DARTS Laboratory specializes in planetary vehicle simulation, such as the Mars rovers. This simulation utilizes a virtual "sand box" to test how planetary rovers respond to different terrains while traversing them. Unfortunately, this simulation is unable to fully mimic the harsh, sandy environments of those found on Mars. Ideally, these simulations should allow a rover to interact with the sand beneath it, particularly for different sand granularities and densities. In particular, there may be situations where a rover may become stuck in sand due to lack of friction between the sand and wheels. In fact, in May 2009, the Spirit rover became stuck in the Martian sand and has provided additional motivation for this research. In order to develop a new sand simulation model, high performance computing will play a very important role in this work. More specifically, graphics processing units (GPUs) are useful due to their ability to run general purpose algorithms and ability to perform massively parallel computations. In prior research, simulating vast quantities of sand has been difficult to compute in real-time due to the computational complexity of many colliding particles. With the use of GPUs however, each particle collision will be parallelized, allowing for a dramatic performance increase. In addition, spatial partitioning will also provide a speed boost as this will help limit the number of particle collision calculations. However, since the goal of this research is to simulate the look and behavior of sand, this work will go beyond simple particle collision. In particular, we can continue to use our parallel algorithms not only on single particles but on particle “clumps” that consist of multiple combined particles. Since sand is typically not spherical in nature, these particle “clumps” help to simulate the coarse nature of sand. In a simulation environment, multiple combined particles could be used to simulate the polygonal and granular nature of sand grains. Thus, a diversity of sand particles can be generated. The interaction between these particles can then be parallelized using GPU hardware. As such, this research will investigate different graphics and physics techniques and determine the tradeoffs in performance and visual quality for sand simulation. An enhanced sand model through the use of high performance computing and GPUs has great potential to impact research for both earth and space scientists. Interaction with JPL has provided an opportunity for us to refine our simulation techniques that can ultimately be used for their vehicle simulator. As an added benefit of this work, advancements in simulating sand can also benefit scientists here on earth, especially in regard to understanding landslides and debris flows.

Help for the Visually Impaired

NASA Technical Reports Server (NTRS)

1995-01-01

The Low Vision Enhancement System (LVES) is a video headset that offers people with low vision a view of their surroundings equivalent to the image on a five-foot television screen four feet from the viewer. It will not make the blind see but for many people with low vision, it eases everyday activities such as reading, watching TV and shopping. LVES was developed over almost a decade of cooperation between Stennis Space Center, the Wilmer Eye Institute of the Johns Hopkins Medical Institutions, the Department of Veteran Affairs, and Visionics Corporation. With the aid of Stennis scientists, Wilmer researchers used NASA technology for computer processing of satellite images and head-mounted vision enhancement systems originally intended for the space station. The unit consists of a head-mounted video display, three video cameras, and a control unit for the cameras. The cameras feed images to the video display in the headset.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Richen; Guo, Hanqi; Yuan, Xiaoru

Most of the existing approaches to visualize vector field ensembles are to reveal the uncertainty of individual variables, for example, statistics, variability, etc. However, a user-defined derived feature like vortex or air mass is also quite significant, since they make more sense to domain scientists. In this paper, we present a new framework to extract user-defined derived features from different simulation runs. Specially, we use a detail-to-overview searching scheme to help extract vortex with a user-defined shape. We further compute the geometry information including the size, the geo-spatial location of the extracted vortexes. We also design some linked views tomore » compare them between different runs. At last, the temporal information such as the occurrence time of the feature is further estimated and compared. Results show that our method is capable of extracting the features across different runs and comparing them spatially and temporally.« less

Analysis of recurrent patterns in toroidal magnetic fields.

PubMed

Sanderson, Allen R; Chen, Guoning; Tricoche, Xavier; Pugmire, David; Kruger, Scott; Breslau, Joshua

2010-01-01

In the development of magnetic confinement fusion which will potentially be a future source for low cost power, physicists must be able to analyze the magnetic field that confines the burning plasma. While the magnetic field can be described as a vector field, traditional techniques for analyzing the field's topology cannot be used because of its Hamiltonian nature. In this paper we describe a technique developed as a collaboration between physicists and computer scientists that determines the topology of a toroidal magnetic field using fieldlines with near minimal lengths. More specifically, we analyze the Poincaré map of the sampled fieldlines in a Poincaré section including identifying critical points and other topological features of interest to physicists. The technique has been deployed into an interactive parallel visualization tool which physicists are using to gain new insight into simulations of magnetically confined burning plasmas.

Molecular expressions: exploring the world of optics and microscopy. http://microscopy.fsu.edu.

PubMed

Eliceiri, Kevin W

2004-08-01

Our knowledge of the structure, dynamics and physiology of a cell has increased significantly in the last ten years through the emergence of new optical imaging modalities such as optical sectioning microscopy, computer- enhanced video microscopy and laser-scanning microscopy. These techniques together with the use of genetically engineered fluorophores have helped scientists visualize the 3-dimensional dynamic processes of living cells. However as powerful as these imaging tools are, they can often be difficult to understand and fully utilize. Below I will discuss my favorite website: The Molecular Expressions Web Site that endeavors to present the power of microscopy to its visitors. The Molecular Expressions group does a remarkable job of not only clearly presenting the principles behind these techniques in a manner approachable by lay and scientific audiences alike but also provides representative data from each as well.

How previous experience shapes perception in different sensory modalities

PubMed Central

Snyder, Joel S.; Schwiedrzik, Caspar M.; Vitela, A. Davi; Melloni, Lucia

2015-01-01

What has transpired immediately before has a strong influence on how sensory stimuli are processed and perceived. In particular, temporal context can have contrastive effects, repelling perception away from the interpretation of the context stimulus, and attractive effects (TCEs), whereby perception repeats upon successive presentations of the same stimulus. For decades, scientists have documented contrastive and attractive temporal context effects mostly with simple visual stimuli. But both types of effects also occur in other modalities, e.g., audition and touch, and for stimuli of varying complexity, raising the possibility that context effects reflect general computational principles of sensory systems. Neuroimaging shows that contrastive and attractive context effects arise from neural processes in different areas of the cerebral cortex, suggesting two separate operations with distinct functional roles. Bayesian models can provide a functional account of both context effects, whereby prior experience adjusts sensory systems to optimize perception of future stimuli. PMID:26582982

MatLab Script and Functional Programming

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

MatLab Script and Functional Programming: MatLab is one of the most widely used very high level programming languages for scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. The MatLab seminar covers the functional and script programming aspect of MatLab language. Specific expectations are: a) Recognize MatLab commands, script and function. b) Create, and run a MatLab function. c) Read, recognize, and describe MatLab syntax. d) Recognize decisions, loops and matrix operators. e) Evaluate scope among multiple files, and multiple functions within a file. f) Declare, define and use scalar variables, vectors and matrices.

An Overview of R in Health Decision Sciences.

PubMed

Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam

2017-10-01

As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.

Electronic Ecosystem.

ERIC Educational Resources Information Center

Travis, John

1991-01-01

A discipline in which scientists seek to simulate and synthesize lifelike behaviors within computers, chemical mixtures, and other media is discussed. A computer program with self-replicating digital "organisms" that evolve as they compete for computer time and memory is described. (KR)

Argonne Leadership Computing Facility 2011 annual report : Shaping future supercomputing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papka, M.; Messina, P.; Coffey, R.

The ALCF's Early Science Program aims to prepare key applications for the architecture and scale of Mira and to solidify libraries and infrastructure that will pave the way for other future production applications. Two billion core-hours have been allocated to 16 Early Science projects on Mira. The projects, in addition to promising delivery of exciting new science, are all based on state-of-the-art, petascale, parallel applications. The project teams, in collaboration with ALCF staff and IBM, have undertaken intensive efforts to adapt their software to take advantage of Mira's Blue Gene/Q architecture, which, in a number of ways, is a precursormore » to future high-performance-computing architecture. The Argonne Leadership Computing Facility (ALCF) enables transformative science that solves some of the most difficult challenges in biology, chemistry, energy, climate, materials, physics, and other scientific realms. Users partnering with ALCF staff have reached research milestones previously unattainable, due to the ALCF's world-class supercomputing resources and expertise in computation science. In 2011, the ALCF's commitment to providing outstanding science and leadership-class resources was honored with several prestigious awards. Research on multiscale brain blood flow simulations was named a Gordon Bell Prize finalist. Intrepid, the ALCF's BG/P system, ranked No. 1 on the Graph 500 list for the second consecutive year. The next-generation BG/Q prototype again topped the Green500 list. Skilled experts at the ALCF enable researchers to conduct breakthrough science on the Blue Gene system in key ways. The Catalyst Team matches project PIs with experienced computational scientists to maximize and accelerate research in their specific scientific domains. The Performance Engineering Team facilitates the effective use of applications on the Blue Gene system by assessing and improving the algorithms used by applications and the techniques used to implement those algorithms. The Data Analytics and Visualization Team lends expertise in tools and methods for high-performance, post-processing of large datasets, interactive data exploration, batch visualization, and production visualization. The Operations Team ensures that system hardware and software work reliably and optimally; system tools are matched to the unique system architectures and scale of ALCF resources; the entire system software stack works smoothly together; and I/O performance issues, bug fixes, and requests for system software are addressed. The User Services and Outreach Team offers frontline services and support to existing and potential ALCF users. The team also provides marketing and outreach to users, DOE, and the broader community.« less

Chemistry Research

NASA Technical Reports Server (NTRS)

1987-01-01

Philip Morris research center scientists use a computer program called CECTRP, for Chemical Equilibrium Composition and Transport Properties, to gain insight into the behavior of atoms as they progress along the reaction pathway. Use of the program lets the scientist accurately predict the behavior of a given molecule or group of molecules. Computer generated data must be checked by laboratory experiment, but the use of CECTRP saves the researchers hundreds of hours of laboratory time since experiments must run only to validate the computer's prediction. Philip Morris estimates that had CECTRP not been available, at least two man years would have been required to develop a program to perform similar free energy calculations.

Developing an online programme in computational biology.

PubMed

Vincent, Heather M; Page, Christopher

2013-11-01

Much has been written about the need for continuing education and training to enable life scientists and computer scientists to manage and exploit the different types of biological data now becoming available. Here we describe the development of an online programme that combines short training courses, so that those who require an educational programme can progress to complete a formal qualification. Although this flexible approach fits the needs of course participants, it does not fit easily within the organizational structures of a campus-based university.

Scientific Visualization: The Modern Oscilloscope for "Seeing the Unseeable" (LBNL Summer Lecture Series)

ScienceCinema

Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division and Scientific Visualization Group

2018-05-07

Summer Lecture Series 2008: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

The Medical Hazards of Flame-Suppressant Atmospheres

DTIC Science & Technology

1991-04-19

the external and middle earcavities. Graph B shows inward distension of the may need to be interrupted or slowed to eardrum produced by higher...experiments were performed by mental function, muscular coordination, military scientists (see ACKNOW- night vision, visual contrast sensitivity, LEDGEMENTS) in...task of muscular posure to change any of the visual coordination was slightly function tests (Luria & Knight, degraded during the first 4 h of 1987). the

System biology of gene regulation.

PubMed

Baitaluk, Michael

2009-01-01

A famous joke story that exhibits the traditionally awkward alliance between theory and experiment and showing the differences between experimental biologists and theoretical modelers is when a University sends a biologist, a mathematician, a physicist, and a computer scientist to a walking trip in an attempt to stimulate interdisciplinary research. During a break, they watch a cow in a field nearby and the leader of the group asks, "I wonder how one could decide on the size of a cow?" Since a cow is a biological object, the biologist responded first: "I have seen many cows in this area and know it is a big cow." The mathematician argued, "The true volume is determined by integrating the mathematical function that describes the outer surface of the cow's body." The physicist suggested: "Let's assume the cow is a sphere...." Finally the computer scientist became nervous and said that he didn't bring his computer because there is no Internet connection up there on the hill. In this humorous but explanatory story suggestions proposed by theorists can be taken to reflect the view of many experimental biologists that computer scientists and theorists are too far removed from biological reality and therefore their theories and approaches are not of much immediate usefulness. Conversely, the statement of the biologist mirrors the view of many traditional theoretical and computational scientists that biological experiments are for the most part simply descriptive, lack rigor, and that much of the resulting biological data are of questionable functional relevance. One of the goals of current biology as a multidisciplinary science is to bring people from different scientific areas together on the same "hill" and teach them to speak the same "language." In fact, of course, when presenting their data, most experimentalist biologists do provide an interpretation and explanation for the results, and many theorists/computer scientists aim to answer (or at least to fully describe) questions of biological relevance. Thus systems biology could be treated as such a socioscientific phenomenon and a new approach to both experiments and theory that is defined by the strategy of pursuing integration of complex data about the interactions in biological systems from diverse experimental sources using interdisciplinary tools and personnel.

Clustervision: Visual Supervision of Unsupervised Clustering.

PubMed

Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam

2018-01-01

Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

Visual Form Perception Can Be a Cognitive Correlate of Lower Level Math Categories for Teenagers.

PubMed

Cui, Jiaxin; Zhang, Yiyun; Cheng, Dazhi; Li, Dawei; Zhou, Xinlin

2017-01-01

Numerous studies have assessed the cognitive correlates of performance in mathematics, but little research has been conducted to systematically examine the relations between visual perception as the starting point of visuospatial processing and typical mathematical performance. In the current study, we recruited 223 seventh graders to perform a visual form perception task (figure matching), numerosity comparison, digit comparison, exact computation, approximate computation, and curriculum-based mathematical achievement tests. Results showed that, after controlling for gender, age, and five general cognitive processes (choice reaction time, visual tracing, mental rotation, spatial working memory, and non-verbal matrices reasoning), visual form perception had unique contributions to numerosity comparison, digit comparison, and exact computation, but had no significant relation with approximate computation or curriculum-based mathematical achievement. These results suggest that visual form perception is an important independent cognitive correlate of lower level math categories, including the approximate number system, digit comparison, and exact computation.

A workflow for the 3D visualization of meteorological data

NASA Astrophysics Data System (ADS)

Helbig, Carolin; Rink, Karsten

2014-05-01

In the future, climate change will strongly influence our environment and living conditions. To predict possible changes, climate models that include basic and process conditions have been developed and big data sets are produced as a result of simulations. The combination of various variables of climate models with spatial data from different sources helps to identify correlations and to study key processes. For our case study we use results of the weather research and forecasting (WRF) model of two regions at different scales that include various landscapes in Northern Central Europe and Baden-Württemberg. We visualize these simulation results in combination with observation data and geographic data, such as river networks, to evaluate processes and analyze if the model represents the atmospheric system sufficiently. For this purpose, a continuous workflow that leads from the integration of heterogeneous raw data to visualization using open source software (e.g. OpenGeoSys Data Explorer, ParaView) is developed. These visualizations can be displayed on a desktop computer or in an interactive virtual reality environment. We established a concept that includes recommended 3D representations and a color scheme for the variables of the data based on existing guidelines and established traditions in the specific domain. To examine changes over time in observation and simulation data, we added the temporal dimension to the visualization. In a first step of the analysis, the visualizations are used to get an overview of the data and detect areas of interest such as regions of convection or wind turbulences. Then, subsets of data sets are extracted and the included variables can be examined in detail. An evaluation by experts from the domains of visualization and atmospheric sciences establish if they are self-explanatory and clearly arranged. These easy-to-understand visualizations of complex data sets are the basis for scientific communication. In addition, they have become an essential medium for the evaluation and verification of models. Particularly in interdisciplinary research projects, they support the scientists in discussions and help to set a general level of knowledge.

NASA's Earth Observatory: 16 Years of Communicating with and for Scientists

NASA Astrophysics Data System (ADS)

Ward, K.; Carlowicz, M. J.; Allen, J.; Voiland, A.; Przyborski, P.; Hansen, K.; Stevens, J.

2015-12-01

For the past 16 years NASA's Earth Observatory website has featured stories that are driven by strong visualization and in-depth reporting and storytelling. The Earth Observatory Image of the Day is published 365 days a year and is a syndication staple for major news outlets, science-related publications, blogs and social media outlets. The daily publication pace requires that we cover a wide range of topics within NASA's portfolio of Earth science research. To meet our deadlines, and to do so competently and with the authority that a NASA-branded publication warrants, we have developed relationships with scientists from throughout the agency who both provide us with ideas for stories and review our content for accuracy. This symbiotic relationship insures that the Earth Observatory has a quality product that is syndicated, repurposed and sourced throughout popular media, resulting in science content reaching the public that might not otherwise be reported. We will discuss how we have developed our relationships and processes over the years, how we work with scientists to see the potential stories in their data, and how we package and promote these stories and visualizations for maximum exposure and reuse.

Argonne Out Loud: Computation, Big Data, and the Future of Cities

ScienceCinema

Catlett, Charlie

2018-01-16

Charlie Catlett, a Senior Computer Scientist at Argonne and Director of the Urban Center for Computation and Data at the Computation Institute of the University of Chicago and Argonne, talks about how he and his colleagues are using high-performance computing, data analytics, and embedded systems to better understand and design cities.

Using Real-Life Experiences to Teach Computer Concepts

ERIC Educational Resources Information Center

Read, Alexis

2012-01-01

Teaching computer concepts to individuals with visual impairments (that is, those who are blind or visually impaired) presents some unique challenges. Students often have difficulty remembering to perform certain steps or have difficulty remembering specific keystrokes when using computers. Many cannot visualize the way in which complex computing…

Computer Visualizations for K-8 Science Teachers: One Component of Professional Development Workshops at the Planetary Science Institute

NASA Astrophysics Data System (ADS)

Kortenkamp, S.; Baldridge, A. M.; Bleamaster, L. F.; Buxner, S.; Canizo, T.; Crown, D. A.; Lebofsky, L. A.

2012-12-01

The Planetary Science Institute (PSI), in partnership with the Tucson Regional Science Center, offers a series of professional development workshops targeting K-8 science teachers in southern Arizona. Using NASA data sets, research results, and a team of PSI scientists and educators, our workshops provide teachers with in-depth content knowledge of fundamental concepts in astronomy, geology, and planetary science. Current workshops are: The Earth-Moon System, Exploring the Terrestrial Planets, Impact Cratering, The Asteroid-Meteorite Connection, Volcanoes of the Solar System, Deserts of the Solar System, and Astrobiology and the Search for Extrasolar Planets. Several workshops incorporate customized computer visualizations developed at PSI. These visualizations are designed to help teachers overcome the common misconceptions students have in fundamental areas of space science. For example, the simple geometric relationship between the sun, the moon, and Earth is a concept that is rife with misconceptions. How can the arrangement of these objects account for the constantly changing phases of the moon as well as the occasional eclipses of the sun and moon? Students at all levels often struggle to understand the explanation for phases and eclipses even after repeated instruction over many years. Traditional classroom techniques have proven to be insufficient at rooting out entrenched misconceptions. One problem stems from the difficulty of developing an accurate mental picture of the Earth-Moon system in space when a student's perspective has always been firmly planted on the ground. To address this problem our visualizations take the viewers on a journey beyond Earth, giving them a so-called "god's eye" view of how the Earth-Moon system would look from a distance. To make this journey as realistic as possible we use ray-tracing software, incorporate NASA mission images, and accurately portray rotational and orbital motion. During a workshop our visualizations are used in conjunction with more traditional classroom techniques. This combination instills a greater confidence in teachers' understanding of the concepts and therefore increases their ability to teach their students. To date we have produced over 100 unique visualizations to demonstrate many different fundamental concepts in the Earth and space sciences. Participants in each workshop are provided with digital copies of the visualizations in a variety of file formats. They also receive Keynote and PowerPoint templates pre-embedded with the visualizations to facility straightforward use on Macs or PCs in their classrooms. A measure of the success of PSI's workshops is that nearly 50% of our teachers have attended multiple workshops, and teachers often cite the visualizations as one of the top benefits of their experience. Details of our workshops as well as downloadable examples of some visualizations can be found at: www.psi.edu/epo. This work is supported by NASA EPOESS award NNX10AE56G: Workshops in Science Education and Resources (WISER): Planetary Perspectives.

The CAVE (TM) automatic virtual environment: Characteristics and applications

NASA Technical Reports Server (NTRS)

Kenyon, Robert V.

1995-01-01

Virtual reality may best be defined as the wide-field presentation of computer-generated, multi-sensory information that tracks a user in real time. In addition to the more well-known modes of virtual reality -- head-mounted displays and boom-mounted displays -- the Electronic Visualization Laboratory at the University of Illinois at Chicago recently introduced a third mode: a room constructed from large screens on which the graphics are projected on to three walls and the floor. The CAVE is a multi-person, room sized, high resolution, 3D video and audio environment. Graphics are rear projected in stereo onto three walls and the floor, and viewed with stereo glasses. As a viewer wearing a location sensor moves within its display boundaries, the correct perspective and stereo projections of the environment are updated, and the image moves with and surrounds the viewer. The other viewers in the CAVE are like passengers in a bus, along for the ride. 'CAVE,' the name selected for the virtual reality theater, is both a recursive acronym (Cave Automatic Virtual Environment) and a reference to 'The Simile of the Cave' found in Plato's 'Republic,' in which the philosopher explores the ideas of perception, reality, and illusion. Plato used the analogy of a person facing the back of a cave alive with shadows that are his/her only basis for ideas of what real objects are. Rather than having evolved from video games or flight simulation, the CAVE has its motivation rooted in scientific visualization and the SIGGRAPH 92 Showcase effort. The CAVE was designed to be a useful tool for scientific visualization. The Showcase event was an experiment; the Showcase chair and committee advocated an environment for computational scientists to interactively present their research at a major professional conference in a one-to-many format on high-end workstations attached to large projection screens. The CAVE was developed as a 'virtual reality theater' with scientific content and projection that met the criteria of Showcase.

Visualizing Matrix Multiplication

ERIC Educational Resources Information Center

Daugulis, Peteris; Sondore, Anita

2018-01-01

Efficient visualizations of computational algorithms are important tools for students, educators, and researchers. In this article, we point out an innovative visualization technique for matrix multiplication. This method differs from the standard, formal approach by using block matrices to make computations more visual. We find this method a…

Journey to the centre of the cell: Virtual reality immersion into scientific data.

PubMed

Johnston, Angus P R; Rae, James; Ariotti, Nicholas; Bailey, Benjamin; Lilja, Andrew; Webb, Robyn; Ferguson, Charles; Maher, Sheryl; Davis, Thomas P; Webb, Richard I; McGhee, John; Parton, Robert G

2018-02-01

Visualization of scientific data is crucial not only for scientific discovery but also to communicate science and medicine to both experts and a general audience. Until recently, we have been limited to visualizing the three-dimensional (3D) world of biology in 2 dimensions. Renderings of 3D cells are still traditionally displayed using two-dimensional (2D) media, such as on a computer screen or paper. However, the advent of consumer grade virtual reality (VR) headsets such as Oculus Rift and HTC Vive means it is now possible to visualize and interact with scientific data in a 3D virtual world. In addition, new microscopic methods provide an unprecedented opportunity to obtain new 3D data sets. In this perspective article, we highlight how we have used cutting edge imaging techniques to build a 3D virtual model of a cell from serial block-face scanning electron microscope (SBEM) imaging data. This model allows scientists, students and members of the public to explore and interact with a "real" cell. Early testing of this immersive environment indicates a significant improvement in students' understanding of cellular processes and points to a new future of learning and public engagement. In addition, we speculate that VR can become a new tool for researchers studying cellular architecture and processes by populating VR models with molecular data. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

RIACS FY2002 Annual Report

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

2002-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

Exascale computing and what it means for shock physics

NASA Astrophysics Data System (ADS)

Germann, Timothy

2015-06-01

The U.S. Department of Energy is preparing to launch an Exascale Computing Initiative, to address the myriad challenges required to deploy and effectively utilize an exascale-class supercomputer (i.e., one capable of performing 1018 operations per second) in the 2023 timeframe. Since physical (power dissipation) requirements limit clock rates to at most a few GHz, this will necessitate the coordination of on the order of a billion concurrent operations, requiring sophisticated system and application software, and underlying mathematical algorithms, that may differ radically from traditional approaches. Even at the smaller workstation or cluster level of computation, the massive concurrency and heterogeneity within each processor will impact computational scientists. Through the multi-institutional, multi-disciplinary Exascale Co-design Center for Materials in Extreme Environments (ExMatEx), we have initiated an early and deep collaboration between domain (computational materials) scientists, applied mathematicians, computer scientists, and hardware architects, in order to establish the relationships between algorithms, software stacks, and architectures needed to enable exascale-ready materials science application codes within the next decade. In my talk, I will discuss these challenges, and what it will mean for exascale-era electronic structure, molecular dynamics, and engineering-scale simulations of shock-compressed condensed matter. In particular, we anticipate that the emerging hierarchical, heterogeneous architectures can be exploited to achieve higher physical fidelity simulations using adaptive physics refinement. This work is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research.

CESDIS

NASA Technical Reports Server (NTRS)

1994-01-01

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Five scientists at Johns Hopkins in the modern evolution of neuroscience.

PubMed

Harrison, T S

2000-08-01

Neuroscience's evolution at Johns Hopkins, from neurophysiology to the new field of neurobiology, though unplanned, was rapid and important. Beginning in 1933 when Philip Bard became professor of physiology at Johns Hopkins, members of his department concentrated initially on neuroanatomical control of placing reactions and sexual activity. Vernon Mountcastle, extending available techniques, discovered vertical somato-sensory columns in the 1950's. Stephen Kuffler, who arrived at Hopkins in 1947, was a pioneer in single unit microelectrode recording techniques. He soon attracted scientists from all over the world to his laboratory. Among them, Torsten Wiesel and David Hubel discovered vertical neuronal columns in the visual cortex. During several decades at Johns Hopkins, these five scientists set extremely high scientific standards and established a climate of inquiry in which ideas were shared and young scientists encouraged. They contributed significantly to the emerging discipline of neuroscience.

Computational Thinking: A Digital Age Skill for Everyone

ERIC Educational Resources Information Center

Barr, David; Harrison, John; Conery, Leslie

2011-01-01

In a seminal article published in 2006, Jeanette Wing described computational thinking (CT) as a way of "solving problems, designing systems, and understanding human behavior by drawing on the concepts fundamental to computer science." Wing's article gave rise to an often controversial discussion and debate among computer scientists,…

Scientific Visualization, Seeing the Unseeable

ScienceCinema

LBNL

2017-12-09

June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in bo... June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

Computer-aided light sheet flow visualization using photogrammetry

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1994-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and a visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) results, was chosen to interactively display the reconstructed light sheet images with the numerical surface geometry for the model or aircraft under study. The photogrammetric reconstruction technique and the image processing and computer graphics techniques and equipment are described. Results of the computer-aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images with CFD solutions in the same graphics environment is also demonstrated.

Computer-Aided Light Sheet Flow Visualization

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1993-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.

Computer-aided light sheet flow visualization

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1993-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.

Bringing 3D Printing to Geophysical Science Education

NASA Astrophysics Data System (ADS)

Boghosian, A.; Turrin, M.; Porter, D. F.

2014-12-01

3D printing technology has been embraced by many technical fields, and is rapidly making its way into peoples' homes and schools. While there is a growing educational and hobbyist community engaged in the STEM focused technical and intellectual challenges associated with 3D printing, there is unrealized potential for the earth science community to use 3D printing to communicate scientific research to the public. Moreover, 3D printing offers scientists the opportunity to connect students and the public with novel visualizations of real data. As opposed to introducing terrestrial measurements through the use of colormaps and gradients, scientists can represent 3D concepts with 3D models, offering a more intuitive education tool. Furthermore, the tactile aspect of models make geophysical concepts accessible to a wide range of learning styles like kinesthetic or tactile, and learners including both visually impaired and color-blind students.We present a workflow whereby scientists, students, and the general public will be able to 3D print their own versions of geophysical datasets, even adding time through layering to include a 4th dimension, for a "4D" print. This will enable scientists with unique and expert insights into the data to easily create the tools they need to communicate their research. It will allow educators to quickly produce teaching aids for their students. Most importantly, it will enable the students themselves to translate the 2D representation of geophysical data into a 3D representation of that same data, reinforcing spatial reasoning.

Utility of predicting group membership and the role of spatial visualization in becoming an engineer, physical scientist, or artist.

PubMed

Humphreys, L G; Lubinski, D; Yao, G

1993-04-01

This article has two themes: First, we explicate how the prediction of group membership can augment test validation designs restricted to prediction of individual differences in criterion performance. Second, we illustrate the utility of this methodology by documenting the importance of spatial visualization for becoming an engineer, physical scientist, or artist. This involved various longitudinal analyses on a sample of 400,000 high school students tracked after 11 years following their high school graduation. The predictive validities of Spatial-Math and Verbal-Math ability composites were established by successfully differentiating a variety of educational and occupational groups. One implication of our findings is that physical science and engineering disciplines appear to be losing many talented persons by restricting assessment to conventional mathematical and verbal abilities, such as those of the Scholastic Aptitude Test (SAT) and the Graduate Record Examination (GRE).

Information processing, computation, and cognition.

PubMed

Piccinini, Gualtiero; Scarantino, Andrea

2011-01-01

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently. Yet different cognitive scientists use 'computation' and 'information processing' to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates' empirical aspects.

Scientists at Work. Final Report.

ERIC Educational Resources Information Center

Education Turnkey Systems, Inc., Falls Church, VA.

This report summarizes activities related to the development, field testing, evaluation, and marketing of the "Scientists at Work" program which combines computer assisted instruction with database tools to aid cognitively impaired middle and early high school children in learning and applying thinking skills to science. The brief report reviews…

Neural networks in astronomy.

PubMed

Tagliaferri, Roberto; Longo, Giuseppe; Milano, Leopoldo; Acernese, Fausto; Barone, Fabrizio; Ciaramella, Angelo; De Rosa, Rosario; Donalek, Ciro; Eleuteri, Antonio; Raiconi, Giancarlo; Sessa, Salvatore; Staiano, Antonino; Volpicelli, Alfredo

2003-01-01

In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large astronomical databases which is foreseen in the framework of the astrophysical virtual observatory and national virtual observatory projects, is, however, posing unprecedented data mining and visualization problems which will find a rather natural and user friendly answer in artificial intelligence tools based on NNs, fuzzy sets or genetic algorithms. This review is aimed to both astronomers (who often have little knowledge of the methodological background) and computer scientists (who often know little about potentially interesting applications), and therefore will be structured as follows: after giving a short introduction to the subject, we shall summarize the methodological background and focus our attention on some of the most interesting fields of application, namely: object extraction and classification, time series analysis, noise identification, and data mining. Most of the original work described in the paper has been performed in the framework of the AstroNeural collaboration (Napoli-Salerno).

Artificial grammar learning meets formal language theory: an overview

PubMed Central

Fitch, W. Tecumseh; Friederici, Angela D.

2012-01-01

Formal language theory (FLT), part of the broader mathematical theory of computation, provides a systematic terminology and set of conventions for describing rules and the structures they generate, along with a rich body of discoveries and theorems concerning generative rule systems. Despite its name, FLT is not limited to human language, but is equally applicable to computer programs, music, visual patterns, animal vocalizations, RNA structure and even dance. In the last decade, this theory has been profitably used to frame hypotheses and to design brain imaging and animal-learning experiments, mostly using the ‘artificial grammar-learning’ paradigm. We offer a brief, non-technical introduction to FLT and then a more detailed analysis of empirical research based on this theory. We suggest that progress has been hampered by a pervasive conflation of distinct issues, including hierarchy, dependency, complexity and recursion. We offer clarifications of several relevant hypotheses and the experimental designs necessary to test them. We finally review the recent brain imaging literature, using formal languages, identifying areas of convergence and outstanding debates. We conclude that FLT has much to offer scientists who are interested in rigorous empirical investigations of human cognition from a neuroscientific and comparative perspective. PMID:22688631

Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers.

PubMed

Sochat, Vanessa V; Prybol, Cameron J; Kurtzer, Gregory M

2017-01-01

Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub's primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers.

Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers

PubMed Central

Prybol, Cameron J.; Kurtzer, Gregory M.

2017-01-01

Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub’s primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers. PMID:29186161

Addition of a Hydrological Cycle to the EPIC Jupiter Model

NASA Astrophysics Data System (ADS)

Dowling, T. E.; Palotai, C. J.

2002-09-01

We present a progress report on the development of the EPIC atmospheric model to include clouds, moist convection, and precipitation. Two major goals are: i) to study the influence that convective water clouds have on Jupiter's jets and vortices, such as those to the northwest of the Great Red Spot, and ii) to predict ammonia-cloud evolution for direct comparison to visual images (instead of relying on surrogates for clouds like potential vorticity). Data structures in the model are now set up to handle the vapor, liquid, and solid phases of the most common chemical species in planetary atmospheres. We have adapted the Prather conservation of second-order moments advection scheme to the model, which yields high accuracy for dealing with cloud edges. In collaboration with computer scientists H. Dietz and T. Mattox at the U. Kentucky, we have built a dedicated 40-node parallel computer that achieves 34 Gflops (double precision) at 74 cents per Mflop, and have updated the EPIC-model code to use cache-aware memory layouts and other modern optimizations. The latest test-case results of cloud evolution in the model will be presented. This research is funded by NASA's Planetary Atmospheres and EPSCoR programs.

Helmet-mounted display systems for flight simulation

NASA Technical Reports Server (NTRS)

Haworth, Loren A.; Bucher, Nancy M.

1989-01-01

Simulation scientists are continually improving simulation technology with the goal of more closely replicating the physical environment of the real world. The presentation or display of visual information is one area in which recent technical improvements have been made that are fundamental to conducting simulated operations close to the terrain. Detailed and appropriate visual information is especially critical for nap-of-the-earth helicopter flight simulation where the pilot maintains an 'eyes-out' orientation to avoid obstructions and terrain. This paper describes visually coupled wide field of view helmet-mounted display (WFOVHMD) system technology as a viable visual presentation system for helicopter simulation. Tradeoffs associated with this mode of presentation as well as research and training applications are discussed.