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All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

National Aeronautics and Space Administration fundamental research program. Information utilization and evaluation

In the second half of the 1980's NASA can expect to face difficult choices among alternative fundamental and applied research, and development projects that could potentially lead to improvements in the information systems used to manage renewable resources. The working group on information utilization and evaluation believes that effective choices cannot be made without a better understanding of the current and prospective problems and opportunities involved in the application of remote sensing to improve renewable research information systems. A renewable resources information system is defined in a broad context to include a flow of data/information from: acquisition through processing, storage, integration with other data, analysis, graphic presentation, decision making, and assessment of the affects of those decisions.

Estes, J. E.↗
NASA NTRS1990

Practical applications of remote sensing technology

Land managers increasingly are becoming dependent upon remote sensing and automated analysis techniques for information gathering and synthesis. Remote sensing and geographic information system (GIS) techniques provide quick and economical information gathering for large areas. The outputs of remote sensing classification and analysis are most effective when combined with a total natural resources data base within the capabilities of a computerized GIS. Some examples are presented of the successes, as well as the problems, in integrating remote sensing and geographic information systems. The need to exploit remotely sensed data and the potential that geographic information systems offer for managing and analyzing such data continues to grow. New microcomputers with vastly enlarged memory, multi-fold increases in operating speed and storage capacity that was previously available only on mainframe computers are a reality. Improved raster GIS software systems have been developed for these high performance microcomputers. Vector GIS systems previously reserved for mini and mainframe systems are available to operate on these enhanced microcomputers. One of the more exciting areas that is beginning to emerge is the integration of both raster and vector formats on a single computer screen. This technology will allow satellite imagery or digital aerial photography to be presented as a background to a vector display.

Whitmore, Roy A., Jr.↗
NASA NTRS1997

Managing Data in a GIS Environment

A Geographic Information System (GIS) is a computer-based system that enables capture, modeling, manipulation, retrieval, analysis and presentation of geographically referenced data. A GIS operates in a dynamic environment of spatial and temporal information. This information is held in a database like any other information system, but performance is more of an issue for a geographic database than a traditional database due to the nature of the data. What distinguishes a GIS from other information systems is the spatial and temporal dimensions of the data and the volume of data (several gigabytes). Most traditional information systems are usually based around tables and textual reports, whereas GIS requires the use of cartographic forms and other visualization techniques. Much of the data can be represented using computer graphics, but a GIS is not a graphics database. A graphical system is concerned with the manipulation and presentation of graphical objects whereas a GIS handles geographic objects that have not only spatial dimensions but non-visual, i e., attribute and components. Furthermore, the nature of the data on which a GIS operates makes the traditional relational database approach inadequate for retrieving data and answering queries that reference spatial data. The purpose of this paper is to describe the efficiency issues behind storage and retrieval of data within a GIS database. Section 2 gives a general background on GIS, and describes the issues involved in custom vs. commercial and hybrid vs. integrated geographic information systems. Section 3 describes the efficiency issues concerning the management of data within a GIS environment. The paper ends with a summary of the main concerns of this paper.

Beltran, Maria↗
NASA NTRS1980

An information adaptive system study report and development plan

The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines.

Ataras, W. S.↗
NASA NTRS1984

Evaluation methodologies for an advanced information processing system

The system concept and requirements for an Advanced Information Processing System (AIPS) are briefly described, but the emphasis of this paper is on the evaluation methodologies being developed and utilized in the AIPS program. The evaluation tasks include hardware reliability, maintainability and availability, software reliability, performance, and performability. Hardware RMA and software reliability are addressed with Markov modeling techniques. The performance analysis for AIPS is based on queueing theory. Performability is a measure of merit which combines system reliability and performance measures. The probability laws of the performance measures are obtained from the Markov reliability models. Scalar functions of this law such as the mean and variance provide measures of merit in the AIPS performability evaluations.

Schabowsky, R. S., Jr.↗
NASA NTRS2019

Collecting and Processing Earth Science Data Metrics at NASA ESDIS

Since the launch of Terra satellite in 1999, the number of Earth Science remote sensing data products created and distributed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS) has increased from a few hundred to nearly ten thousand. NASA's Earth Science Data and Information System (ESDIS) Metrics System (EMS) collects metrics on data ingest, archive, and distribution by its Distributed Active Archive Centers (DAACs) and the Science Investigator-led Systems (SIPS), known as Data Providers. These metrics are critical in helping NASA management as well as data producers in resource planning and gaining a wide range of knowledge of data users and data usage.EMS receives flat files, or log files of data archive, ingest, and distribution either in their raw format, such as Apache web logs, or text files of log records formatted by the Data Providers. Tens of millions of records are processed each day to extract metrics on data products, user information, distribution protocols and services, and so on. The metrics are then made available to designated parties.This presentation provides an overview of the EMS processing workflow and improvement efforts made in recent years to handle ever-increasing number of data records and new metrics requirements, discusses several key steps including mapping log records to data products and identifying user communities along with geo-distribution, and demonstrates typical metrics capabilities produced by the EMS system. Challenges and potential approaches to improve the system are also discussed.

Pan, Jianfu↗
DOE OSTI2020

GIS Visualization of Transportation Energy Consumption

Transportation is witnessing unprecedented transformation, where emerging technologies are disrupting the way we travel. Be it sharing economy, or micro-mobility, the landscape of urban transportation is undergoing a much-needed paradigm shift. In order to capture and model these shifts, researchers need to be agile in their studies of the current and future transportation landscape. The need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration. " need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1975

Detailed requirements document for common software of shuttle program information management system

Common software was investigated as a method for minimizing development and maintenance cost of the shuttle program information management system (SPIMS) applications while reducing the time-frame of their development. Those requirements satisfying these criteria are presented along with the stand-alone modules which may be used directly by applications. The SPIMS applications operating on the CYBER 74 computer, are specialized information management systems which use System 2000 as a data base manager. Common software provides the features to support user interactions on a CRT terminal using form input and command response capabilities. These features are available as subroutines to the applications.

Everette, J. M.↗
NASA NTRS1991

Information logistics: A production-line approach to information services

Logistics can be defined as the process of strategically managing the acquisition, movement, and storage of materials, parts, and finished inventory (and the related information flow) through the organization and its marketing channels in a cost effective manner. It is concerned with delivering the right product to the right customer in the right place at the right time. The logistics function is composed of inventory management, facilities management, communications unitization, transportation, materials management, and production scheduling. The relationship between logistics and information systems is clear. Systems such as Electronic Data Interchange (EDI), Point of Sale (POS) systems, and Just in Time (JIT) inventory management systems are important elements in the management of product development and delivery. With improved access to market demand figures, logisticians can decrease inventory sizes and better service customer demand. However, without accurate, timely information, little, if any, of this would be feasible in today's global markets. Information systems specialists can learn from logisticians. In a manner similar to logistics management, information logistics is concerned with the delivery of the right data, to the ring customer, at the right time. As such, information systems are integral components of the information logistics system charged with providing customers with accurate, timely, cost-effective, and useful information. Information logistics is a management style and is composed of elements similar to those associated with the traditional logistics activity: inventory management (data resource management), facilities management (distributed, centralized and decentralized information systems), communications (participative design and joint application development methodologies), unitization (input/output system design, i.e., packaging or formatting of the information), transportations (voice, data, image, and video communication systems), materials management (data acquisition, e.g., EDI, POS, external data bases, data entry) and production scheduling (job, staff, and project scheduling).

Adams, Dennis↗
NASA NTRS1991

Analysis of methods

Information is one of an organization's most important assets. For this reason the development and maintenance of an integrated information system environment is one of the most important functions within a large organization. The Integrated Information Systems Evolution Environment (IISEE) project has as one of its primary goals a computerized solution to the difficulties involved in the development of integrated information systems. To develop such an environment a thorough understanding of the enterprise's information needs and requirements is of paramount importance. This document is the current release of the research performed by the Integrated Development Support Environment (IDSE) Research Team in support of the IISEE project. Research indicates that an integral part of any information system environment would be multiple modeling methods to support the management of the organization's information. Automated tool support for these methods is necessary to facilitate their use in an integrated environment. An integrated environment makes it necessary to maintain an integrated database which contains the different kinds of models developed under the various methodologies. In addition, to speed the process of development of models, a procedure or technique is needed to allow automatic translation from one methodology's representation to another while maintaining the integrity of both. The purpose for the analysis of the modeling methods included in this document is to examine these methods with the goal being to include them in an integrated development support environment. To accomplish this and to develop a method for allowing intra-methodology and inter-methodology model element reuse, a thorough understanding of multiple modeling methodologies is necessary. Currently the IDSE Research Team is investigating the family of Integrated Computer Aided Manufacturing (ICAM) DEFinition (IDEF) languages IDEF(0), IDEF(1), and IDEF(1x), as well as ENALIM, Entity Relationship, Data Flow Diagrams, and Structure Charts, for inclusion in an integrated development support environment.

Mayer, Richard J.↗
NASA NTRS1991

Advanced space transportation systems

Information is given in viewgraph form relative to the advanced space transportation systems of the Space Station Freedom. Topics covered include heavy lift launch vehicle needs, requirements, and options; future launch vehicle concepts; modifications to the external tank; the Cargo Transfer Vehicle concept; lunar transportation options, Mars transportation options; the Assured Crew Return Vehicle (ACRV) baseline concept; Space Exploration Initiative (SEI) nodes options; and committee recommendations.

Davies, Robert J.↗
NASA NTRS1994

Panel to review EOSDIS plans

Formed in Jan. 1992, the Panel to Review EOSDIS Plans was charged with advising NASA on its plans for developing the Earth Observing System (EOS) Data and Information System (EOSDIS). Specifically, the panel was asked to do the following: assess the validity of the engineering and technical underpinnings of the EOSDIS; assess its potential value to scientific users; suggest how technical risk can be minimized; and assess whether current plans are sufficiently resilient to be adaptable to changing technology and requirements such as budget environments, data volumes, new users, and new databases. The panel completed an interim report (Addendum A) and transmitted it to NASA and other interested parties in the government on 9 Apr. 1992. Because of a delay in NASA's plans to select the contractor for EOSDIS, the panel was not able to complete its review of the program according to the original government request. With the issuance of a letter report (Addendum B) on 28 Sep. 1992, the panel became inactive until such time as NASA could release the details of the contractor's proposed architecture, schedule, and costs for developing EOSDIS. In early 1993, NASA awarded the contract for the EOSDIS Core System (ECS). On 20 Apr. 1993, NASA asked the panel to reconvene to do the following: ( 1) complete its review of NASA's approach to the EOSDIS architecture and implementation; (2) appraise NASA's responses to the panel's previous recommendations; and (3) review the planning for EOSDIS in the context of NASA's role in the Global Change Data and Information System (GCDIS) implementation plan. To respond to the NASA charge, the panel met three times in 1993 including sessions with NASA officials and the EOSDIS contractor. In addition, several of the panel members visited individual Distributed Active Archive Centers (DAAC's) to obtain additional views of EOSDIS. The panel has now obtained substantial information on the EOSDIS budget, contractor work program, and current baseline architecture that was not previously available, due to procurement restrictions. This report presents the panel's findings and recommendations based on this additional information.

Source record↗
NASA NTRS1983

The Information Adaptive System - A demonstration of real-time onboard image processing

The Information Adaptive System (IAS) program has the objective to develop and demonstrate, at the brassboard level, an architecture which can be used to perform advanced signal procesing functions on board the spacecraft. Particular attention is given to the processing of high-speed multispectral imaging data in real-time, and the development of advanced technology which could be employed for future space applications. An IAS functional description is provided, and questions of radiometric correction are examined. Problems of data packetization are considered along with data selection, a distortion coefficient processor, an adaptive system controller, an image processing demonstration system, a sensor simulator and output data buffer, a test support and demonstration controller, and IAS demonstration operating modes.

Thomas, G. L.↗
NASA NTRS1986

Requirements Analysis for Information-Intensive Systems

Report discusses role of requirements analysis in development of information-intensive systems. System examined from variety of human viewpoints during design, development, and implementation. Such examination, called requirements analysis, ensures system simultaneously meets number of distinct but interacting needs. Viewpoints defined and integrated to help attain objectives.

Callender, E. D.↗
NASA NTRS2014

An Analysis of Earth Science Data Analytics Use Cases

The increase in the number and volume, and sources, of globally available Earth science data measurements and datasets have afforded Earth scientists and applications researchers unprecedented opportunities to study our Earth in ever more sophisticated ways. In fact, the NASA Earth Observing System Data Information System (EOSDIS) archives have doubled from 2007 to 2014, to 9.1 PB (Ramapriyan, 2009; and https:earthdata.nasa.govaboutsystem-- performance). In addition, other US agency, international programs, field experiments, ground stations, and citizen scientists provide a plethora of additional sources for studying Earth. Co--analyzing huge amounts of heterogeneous data to glean out unobvious information is a daunting task. Earth science data analytics (ESDA) is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. It can include Data Preparation, Data Reduction, and Data Analysis. Through work associated with the Earth Science Information Partners (ESIP) Federation, a collection of Earth science data analytics use cases have been collected and analyzed for the purpose of extracting the types of Earth science data analytics employed, and requirements for data analytics tools and techniques yet to be implemented, based on use case needs. ESIP generated use case template, ESDA use cases, use case types, and preliminary use case analysis (this is a work in progress) will be presented.

data analytics↗
NASA NTRS2019

NASA EOSDIS Data Usage Metrics- Insight and Assessment

NASA's Earth Science Data and Information System (ESDIS) Project collects Earth science data usage metrics on a daily basis through the ESDIS Metrics System (EMS). This includes metrics on distribution of data products, users, data volumes, and number of files, which are key parameters in evaluating system-level performance of any of the Distributed Active Archive Centers (DAACs) encompassed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS). EOSDIS data usage metrics illustrate the benefits of making NASA data openly available to the public and show a rapid growth in data distribution to a worldwide user community. In fact, each year since 2014 the EOSDIS has distributed over one billion data files of products from EOS satellite, airborne, and in situ observations. An assessment of the long-term trends of data usage metrics and user characterization provides insights into data usability.This study will focus on describing the EMS as a metrics collection tool and will provide a comprehensive analysis of EOSDIS data usage metrics over the last 10 years. This study will also characterize the product distribution metrics by various tools and services, such as Giovanni, the Open-source Project for a Network Data Access Protocol (OPeNDAP), and subsets, to address how these tools/services have extended the usage of data in the EOSDIS collection. Data usage patterns based on discipline and study area will further assist in understanding how EOSDIS data user needs have evolved over time. Results from this study will provide useful information for the DAACs that can help them improve the functionality of their tools and services as well as more efficiently allocate the resources necessary for enhanced access and availability of their data products. Knowledge of these metrics may also benefit user discovery of data in the EOSDIS collection, promote research collaboration, and stimulate new ideas from work and research conducted using specific datasets and data collections.

Kafle, Durga N.↗
NASA NTRS1981

San Juan National Forest Land Management Planning Support System (LMPSS) requirements definition

The role of remote sensing data as it relates to a three-component land management planning system (geographic information, data base management, and planning model) can be understood only when user requirements are known. Personnel at the San Juan National Forest in southwestern Colorado were interviewed to determine data needs for managing and monitoring timber, rangelands, wildlife, fisheries, soils, water, geology and recreation facilities. While all the information required for land management planning cannot be obtained using remote sensing techniques, valuable information can be provided for the geographic information system. A wide range of sensors such as small and large format cameras, synthetic aperture radar, and LANDSAT data should be utilized. Because of the detail and accuracy required, high altitude color infrared photography should serve as the baseline data base and be supplemented and updated with data from the other sensors.

Werth, L. F.↗