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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Data visualization methods, data visualization devices, data visualization apparatuses, and articles of manufacture

Data visualization methods, data visualization devices, data visualization apparatuses, and articles of manufacture are described according to some aspects. In one aspect, a data visualization method includes accessing a plurality of initial documents at a first moment in time, first processing the initial documents providing processed initial documents, first identifying a plurality of first associations of the initial documents using the processed initial documents, generating a first visualization depicting the first associations, accessing a plurality of additional documents at a second moment in time after the first moment in time, second processing the additional documents providing processed additional documents, second identifying a plurality of second associations of the additional documents and at least some of the initial documents, wherein the second identifying comprises identifying using the processed initial documents and the processed additional documents, and generating a second visualization depicting the second associations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

An Introduction to Data Visualization

Data visualization can be used to present findings, explore data, and use the human eye to find patterns that a computer would struggle to locate. Borrowing tools from art, storytelling, data analytics and software development, data visualization is an indispensable part of the analysis process. While data visualization usage spans across multiple disciplines and sectors, most never receive formal training in the subject. As such, this tutorial will introduce key data visualization building blocks and how to best use those building blocks for different scenarios and audiences. We will also go over tips on accessibility, design and interactive elements. While this will by no means be a complete overview of the data visualization field, by building a foundation and introducing some rules of thumb, attendees will be better equipped for communicating their findings to their audience.

data visualization↗
DOE OSTI2018

Systems and methods of generating a plurality of data visualizations in a data visualization region

An exemplary method of generating a plurality of data visualizations comprises displaying a graphical user interface that includes a schema information region and a data visualization region. The method further includes receiving user actions to associate first, second, and third fields included in the schema information region with a plurality of shelves of the data visualization region. The method further includes generating a plurality of data visualizations in the data visualization region in accordance with the received user actions, each data visualization includes a plurality of data marks corresponding to a respective retrieved tuple of data having the first, second, and third fields. Moreover, each of the data marks has an x-position and y-position defined according to data for the first and second fields, respectively. In addition, each of the data visualizations corresponds to a respective unique value of the third field, and is displayed in a respective pane.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Visual Data Comm: A Tool for Visualizing Data Communication in the Multi Sector Planner Study

Data comm is a new technology proposed in future air transport system as a potential tool to provide comprehensive data connectivity. It is a key enabler to manage 4D trajectory digitally, potentially resulting in improved flight times and increased throughput. Future concepts with data comm integration have been tested in a number of human-in-the-loop studies but analyzing the results has proven to be particularly challenging because future traffic environment in which data comm is fully enabled has assumed high traffic density, resulting in data set with large amount of information. This paper describes the motivation, design, current and potential future application of Visual Data Comm (VDC), a tool for visualizing data developed in Java using Processing library which is a tool package designed for interactive visualization programming. This paper includes an example of an application of VDC on data pertaining to the most recent Multi Sector Planner study, conducted at NASA s Airspace Operations Laboratory in 2009, in which VDC was used to visualize and interpret data comm activities

Lee, Hwasoo Eric↗
DOE OSTI2017

Interactive Data Visualization

Interactive data visualization leverages human visual perception and cognition to improve the accuracy and effectiveness of data analysis. When combined with automated data analytics, data visualization systems orchestrate the strengths of humans with the computational power of machines to solve problems neither approach can manage in isolation. In the intelligent transportation system domain, such systems are necessary to support decision making in large and complex data streams. In this chapter, we provide an introduction to several key topics related to the design of data visualization systems. In addition to an overview of key techniques and strategies, we will describe practical design principles. The chapter is concluded with a detailed case study involving the design of a multivariate visualization tool.

information visualization↗
DOE OSTI2017

Web-based visual data exploration for improved radiological source detection

Radiation detection can provide a reliable means of detecting radiological material. Such capabilities can help to prevent nuclear and/or radiological attacks, but reliable detection in uncontrolled surroundings requires algorithms that account for environmental background radiation. The Berkeley Data Cloud (BDC) facilitates the development of such methods by providing a framework to capture, store, analyze, and share data sets. In the era of big data, both the size and variety of data make it difficult to explore and find data sets of interest and manage the data. Thus, in the context of big data, visualization is critical for checking data consistency and validity, identifying gaps in data coverage, searching for data relevant to an analyst's use cases, and choosing input parameters for analysis. Downloading the data and exploring it on an analyst's desktop using traditional tools are no longer feasible due to the size of the data. This study describes the design and implementation of a visualization system that addresses the problems associated with data exploration within the context of the BDC. Finally, the visualization system is based on a JavaScript front end communicating via REST with a back end web server.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2012

Why High Performance Visual Data Analytics is both Relevant and Difficult

Data visualization, as well as data analysis and data analytics, are all an integral part of the scientific process. Collectively, these technologies provide the means to gain insight into data of ever-increasing size and complexity. Over the past two decades, a substantial amount of visualization, analysis, and analytics R&D has focused on the challenges posed by increasing data size and complexity, as well as on the increasing complexity of a rapidly changing computational platform landscape. While some of this research focuses on solely on technologies, such as indexing and searching or novel analysis or visualization algorithms, other R&D projects focus on applying technological advances to specific application problems. Some of the most interesting and productive results occur when these two activities R&D and application are conducted in a collaborative fashion, where application needs drive R&D, and R&D results are immediately applicable to real world problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Xi-cam : a versatile interface for data visualization and analysis

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam 's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam 's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

Pandolfi, Ronald J. (ORCID:0000000308248548)↗
DOE OSTI2018

Real Time Streaming Data visualization tooling (RTS Data Vis App)

NREL's RTS Data Vis App contains the following sub-projects: (1) Conditioner: A tool to resample high-rate data from the relay for low-rate visualization and (2) Chart: A tool to plot the data from the relay, including a specialized copy of the Conditioner. The Conditioner is a command-line tool for reading ADMS data from ZMQ, resampling, and exporting over a websocket. The Chart is an example of a charting tool for ADMS applications, using a ZMQ message bus.

Wunder, Nicholas↗
DOE OSTI2021

NeuralCubes: Deep Representations for Visual Data Exploration

Visual exploration of large multi-dimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are some of the most promising approaches. However, these techniques usually require a large memory footprint for large datasets. To tackle this problem, we present NeuralCubes: neural networks that predict results for aggregate queries, similar to data cubes. NeuralCubes learns a function that takes as input a given query, for instance, a geographic region and temporal interval, and outputs the result of the query. The learned function serves as a real-time, low-memory approximator for aggregation queries. Our models are small enough to be sent to the client side (e.g. the web browser for a web-based application) for evaluation, enabling data exploration of large datasets without database/network connection. Here, we demonstrate the effectiveness of NeuralCubes through extensive experiments on a variety of datasets and discuss how NeuralCubes opens up opportunities for new types of visualization and interaction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Visual Data Analysis for Satellites

The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

Lau, Yee↗
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 NTRS2009

DSN Data Visualization Suite

The DSN Data Visualization Suite is a set of computer programs and reusable Application Programming Interfaces (APIs) that assist in the visualization and analysis of Deep Space Network (DSN) spacecraft-tracking data, which can include predicted and actual values of downlink frequencies, uplink frequencies, and antenna-pointing angles in various formats that can include tables of values and polynomial coefficients. The data can also include lists of antenna-pointing events, lists of antenna- limit events, and schedules of tracking activities. To date, analysis and correlation of these intricately related data before and after tracking have been difficult and time-consuming. The DSN Data Visualization Suite enables operators to quickly diagnose tracking-data problems before, during, and after tracking. The Suite provides interpolation on demand and plotting of DSN tracking data, correlation of all data on a given temporal point, and display of data with color coding configurable by users. The suite thereby enables rapid analysis of the data prior to transmission of the data to DSN control centers. At the control centers, the same suite enables operators to validate the data before committing the data to DSN subsystems. This software is also Web-enabled to afford its capabilities to international space agencies.

Bui, Bach X.↗