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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1991

Science information systems: Visualization

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.

Wall, Ray J.↗
NASA NTRS1994

The VIS-AD data model: Integrating metadata and polymorphic display with a scientific programming language

The VIS-AD data model integrates metadata about the precision of values, including missing data indicators and the way that arrays sample continuous functions, with the data objects of a scientific programming language. The data objects of this data model form a lattice, ordered by the precision with which they approximate mathematical objects. We define a similar lattice of displays and study visualization processes as functions from data lattices to display lattices. Such functions can be applied to visualize data objects of all data types and are thus polymorphic.

Hibbard, William L.↗
NASA NTRS1996

Software Aids Visualization Of Mars Pathfinder Mission

Report describes Simulator for Imager for Mars Pathfinder (SIMP) computer program. SIMP generates "virtual reality" display of view through video camera on Mars lander spacecraft of Mars Pathfinder mission, along with display of pertinent textual and graphical data, for use by scientific investigators in planning sequences of activities for mission.

Weidner, Richard J.↗
NASA NTRS2005

Visualization of Space-Time Ambiguities to be Explored by the NASA GEC Mission with a Critique of Synthesized Measurements for Different GEC Mission Scenarios

The objective of this grant was to study how a multi-satellite mission configuration can be optimized for maximum exploratory scientific return. NASA's Solar Terrestrial Probe (STP) concept mission Geospace Electrodynamic Connections (GEC) was the target mission for this pilot study. GEC prime mission characteristics were two fold: (i) a series of three satellites in the same orbit plane with differential spacing, and (ii) a deep-dipping phase in which these satellites could dip to altitudes as low as 130 km to explore the lower ionosphere and thermosphere. Each satellite would carry a full suite of plasma and neutral in-situ sensors and have the same dipping capability. This latter aspect would be envisaged as a series, up to 10, of deep-dipping campaigns, each lasting 10 days during which the perigee would be lowered to the desired probing depth. The challenge in optimization is to establish the scientific problems that can best be addressed by varying or selecting satellite spacing during a two-year mission while also interspersing, in this two year time frame, the deep-dipping campaigns. Although this sounds like a straightforward trade-off situation, it is complicated by the orbit precession in local time, the location of perigee, and that even the dipping campaigns will have preferred satellite spacing requirements.

Sojka, Jan J.↗
NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗
NASA NTRS2001

Discovering Communicable Scientific Knowledge from Spatio-Temporal Data

This paper describes how we used regression rules to improve upon a result previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be understandable and communicable. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial nature of the data. We also report how evaluating the learned models across time let us discover an error in the data.

Schwabacher, Mark↗
NASA NTRS2002

Discovering Communicable Models from Earth Science Data

This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be understandable and communicable. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial nature of the data. We also report how evaluating the learned models across time let us discover an error in the data.

Schwabacher, Mark↗
NASA NTRS2003

The Astrobiology Matrix and the "Drake Matrix" in Education

We organized astrobiology lectures in the Eotvos Lorand University of Sciences and the Polaris Observatory in 2002. We present here the "Drake matrix" for the comparison of the astrobiological potential of different bodies [1], and astrobiology matrix for the visualization of the interdisciplinary connections between different fields of astrobiology. Conclusion: In Hungary it is difficult to integrate astrobiology in the education system but the great advantage is that it can connect different scientific fields and improve the view of students. We would like to get in contact with persons and organizations who already have experience in the education of astrobiology.

Mizser, A.↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, whole organism, behavior; tabular, imagery). Open Science is the concept that the more people have access to scientifically curated data, the more knowledge will be gained. This led NASA to start the development of GeneLab in 2015. GeneLab houses spaceflight and space-analog multi-omics datasets from plant, rodent, small animal, and microbial experiments. The success and knowledge gained from GeneLab led to a new alliance of NASA “Open Science Data Repositories” (OSDR), which include the Ames Life Sciences Data Archive (ALSDA) and the NASA Biological Institutional Scientific Collection (NBISC). Both are adopting the GeneLab data system, so data are more findable, accessible, interoperable, and reusable (FAIR). OSDR systems provide users the ability to upload, download, search, share, analyze, and visualize. Open Science also needs strong confidence in the data, which is gained through building science communities. With ~400 current members, GeneLab and ALSDA formed Analysis Working Groups (AWGs) to provide feedback on processing pipelines, metadata curation standards (for ‘omics and phenotypic-physiological-behavioral assays), and to collaborate in effectively reusing data. The AWG also led to the development of the Radiation Biology Ontology (RBO), ensuring radiation metadata are efficiently captured, connected, and interoperable. Feedback from the AWG provided design input toward the new single point-of-entry data submission portal for all investigators to submit, curate, and share their research data. Space biological data is now maximally open access, collected-curated with rich metadata, and formatted for interoperability to enable systems biology, meta-analysis, knowledge graphs, machine learning, modeling, and other reuse approaches. With potential for further federation of OSDR for data mining with traditional biological and medical databases (NIH, NCI, EBI, etc.), a new era for space biology has begun to support the knowledge discovery necessary for Lunar and Martian missions.

Ryan T Scott↗
NASA NTRSDate not supplied

Spaceflight Environmental-Telemetry Data for Biological Science

There is a critical need for better access and visualization of spaceflight environmental telemetry and mission hardware data from sensors including relative humidity, carbon dioxide, oxygen, radiation, airflow, temperature, acceleration, and acoustics. Under the stewardship of the Ames Life Sciences Data Archive (ALSDA) and GeneLab, an effort is underway to consolidate, normalize and provide accessibility of archived mission environmental data and hardware information, with the purpose of providing important context to biological data. This effort is necessary to provide scientific context of its impact upon biological and biomedical data from spaceflight missions and experiments (genomic, metagenomic, gene expression, proteomic, metabolomic, physiological, phenomics, behavioral; tabular, imaging, video). Environmental spaceflight data is derived from dozens of sources, with various formats, and in the past year a pipeline is in development to collect, curate and present this data efficiently. In the upcoming year, a new Data Visualization Portal will utilize the standardized pipeline data to provide easy user access to compare parameters and environmental conditions between missions, locations, subjects, and durations. Environmental and hardware data enables broad accessibility and analytics, without the need for advanced data informatic expertise. Familiarity with the capabilities and limitations of a variety of existing hardware/tools is a strength that could be applied to creation of improved hardware for future ecosystems on the Moon and Mars. The intention is to make biological and environmental telemetry data maximally open-access and FAIR (findable, accessible, interoperable, reusable) for data mining-informatic approaches to support knowledge discovery necessary for low Earth orbit, cis-Lunar, Mars transit, and Mars surface missions.

Danielle K. Lopez↗
NASA NTRS1975

Geophysical studies of floating ice by remote sensing

This paper presents an overview of recent remote-sensing techniques as applied to geophysical studies of floating ice. The current increase in scientific interest in floating ice has occurred during a time of rapid evolution of both remote-sensing platforms and sensors. Mesoscale and macroscale studies of floating ice are discussed under three sensor categories: visual, passive microwave, and active microwave. The specific studies that are reviewed primarily investigate ice drift and deformation, and ice type and ice roughness identification and distribution.

Campbell, W. J.↗
NASA NTRS1989

An interactive, discipline-independent data visualization system

The data visualization techniques used by National Space Science Data Center Graphics System are discussed. The system includes a self-describing data abstraction for the storage and manipulation of multidimensional data for discipline-independent scientific applications. The system's data format and graphics display are described. Consideration is given to techniques developed for the rapid display and manipulation of large, complex data sets and for manipulating algorithms with portable implementations which can operate on any data object or geometry. The processes of operating the system are given and examples are presented from applying the system to various types of data, including TOMS data, data from the International Satellite Cloud Climatology Project, and IRAS data.

Treinish, Lloyd A.↗
NASA NTRS2016

Why an Eye Limiting Display Resolution Matters and How to Achieve It

Many factors affect the suitability of an out-the-window simulator visual system. Contrast, brightness, resolution, field-of-view, update rate, scene content and a number of other criteria are common factors often used to define requirements for simulator visual systems. Since 2008, NASA has worked with the USAF on the Operational Based Vision Assessment Program. The purpose of this program has been to provide the USAF School of Aerospace Medicine with a scientific testing laboratory to study human vision and testing standards in an operationally relevant environment. It was determined early in the design that current commercial and military training systems weren't well suited for the available budget as well as the highly research oriented requirements. During various design review meetings, it was determined the OBVA requirements were best met by using commercial-off-the-shelf equipment to minimize technical risk and costs. In this paper we will describe how the simulator specifications were developed in order to meet the research objectives and the resulting architecture and design considerations. In particular we will discuss the image generator architecture, database developments to meet eye limited resolution, and future reusablity in other projects.

flight simulator↗
NASA NTRS2014

Concepts to Support HRP Integration Using Publications and Modeling

Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.

Mindock, J.↗
NASA NTRSDate not supplied

GeneLab: The NASA System Biology Platform for Space Omics Repository, Analysis and Visualization

NASA’s GeneLab includes an open-access repository of some 250+ omics datasets generated by biological experiments relevant to spaceflight including simulated cosmic radiation and microgravity. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics background, GeneLab has become a knowledgebase platform converting raw genetic and proteomic signatures found in flight samples into biological and physiological meanings. A large community of more than 100 scientists has rallied behind GeneLab and organized into four Analysis Working Groups (AWGs: Animal, Plant, Microbe, and Multi-Omics). Together, the AWGs have gained scientific recognition worldwide by establishing a consortium in charge of adopting new complex standards for data analysis workflows and omics sample processing in a rapidly evolving field. We will demonstrate the usage of the repository with smart search capability, an online controlled-access toolshed "Galaxy" to process user data with vetted standard workflows, a workspace for data sharing and a data submission portal with ontology control for better metadata curation. The GeneLab visualization portal will also be demonstrated, showing how anyone without formal training in bioinformatics can now browse the space biology omics data to discover new biology and potential solutions to improve life in space.

GeneLab↗
NASA NTRS2015

Unified User Interface to Support Effective and Intuitive Data Discovery, Dissemination, and Analysis at NASA GES DISC

Goddard Earth Sciences Data and Information Services Center (GES DISC) has been providing access to scientific data sets since 1990s. Beginning as one of the first Earth Observing System Data and Information System (EOSDIS) archive centers, GES DISC has evolved to offer a wide range of science-enabling services. With a growing understanding of needs and goals of its science users, GES DISC continues to improve and expand on its broad set of data discovery and access tools, sub-setting services, and visualization tools. Nonetheless, the multitude of the available tools, a partial overlap of functionality, and independent and uncoupled interfaces employed by these tools often leave the end users confused as of what tools or services are the most appropriate for a task at hand. As a result, some the services remain underutilized or largely unknown to the users, significantly reducing the availability of the data and leading to a great loss of scientific productivity. In order to improve the accessibility of GES DISC tools and services, we have designed and implemented UUI, the Unified User Interface. UUI seeks to provide a simple, unified, and intuitive one-stop shop experience for the key services available at GES DISC, including sub-setting (Simple Subset Wizard), granule file search (Mirador), plotting (Giovanni), and other services. In this poster, we will discuss the main lessons, obstacles, and insights encountered while designing the UUI experience. We will also present the architecture and technology behind UUI, including NodeJS, Angular, and Mongo DB, as well as speculate on the future of the tool at GES DISC as well as in a broader context of the Space Science Informatics.

web portal↗
NASA NTRS1983

International Halley watch amateur observers' manual for scientific comet studies. Part 1: Methods

The International Halley Watch is described as well as comets and observing techniques. Information on periodic Comet Halley's apparition for its 1986 perihelion passage is provided. Instructions are given for observation projects valuable to the International Halley Watch in six areas of study: (1) visual observations; (2) photography; (3) astrometry; (4) spectroscopic observations; (5) photoelectric photometry; and (6) meteor observations.

Edberg, S. J.↗
NASA NTRS1983

A Shuttle Imaging Spectrometer Experiment for the late 1980's

The Shuttle Imaging Spectrometer Experiment (SISEX), proposed as a next experimental step in the development of advanced earth remote sensing technology, is capable of imaging the earth's surface simultaneously in 128 spectral bands covering the range from 0.4 to 2.5 micrometers. Laboratory and field measurements have suggested the utility of high-spectral-resolution remote sensing, and an aircraft-borne precursor to the SISEX has demonstrated the ability to distinguish among differing vegetation and rock types - in certain cases making unique identifications. The SISEX instrument utilizes an area-array focal plane, populated by visual- and infrared-sensitive detectors, to acquire simultaneous spatial and spectral information on a line-by-line basis. The spectrum is dispersed by means of a prism spectrometer. The performance analysis indicates that the scientific requirements for radiometric precision can be achieved using optics with an effective circular aperture of 11 cm.

Wellman, J. B.↗