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Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scalable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded with this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on concept called the DataHub. With the DataHub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (address, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗

The application of connectionism to query planning/scheduling in intelligent user interfaces

In the mid nineties, the Earth Observing System (EOS) will generate an estimated 10 terabytes of data per day. This enormous amount of data will require the use of sophisticated technologies from real time distributed Artificial Intelligence (AI) and data management. Without regard to the overall problems in distributed AI, efficient models were developed for doing query planning and/or scheduling in intelligent user interfaces that reside in a network environment. Before intelligent query/planning can be done, a model for real time AI planning and/or scheduling must be developed. As Connectionist Models (CM) have shown promise in increasing run times, a connectionist approach to AI planning and/or scheduling is proposed. The solution involves merging a CM rule based system to a general spreading activation model for the generation and selection of plans. The system was implemented in the Rochester Connectionist Simulator and runs on a Sun 3/260.

Short, Nicholas, Jr.↗

DataHub - Science data management in support of interactive exploratory analysis

DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactive nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc.) in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis is on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

Handley, Thomas H., Jr.↗

DataHub: Science data management in support of interactive exploratory analysis

The DataHub addresses four areas of significant needs: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactives nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc), in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

Handley, Thomas H., Jr.↗

Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center

The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.

Moroni, David F.↗

Performance issues in management of the Space Station Information System

The onboard segment of the Space Station Information System (SSIS), called the Data Management System (DMS), will consist of a Fiber Distributed Data Interface (FDDI) token-ring network. The performance of the DMS in scenarios involving two kinds of network management is analyzed. In the first scenario, how the transmission of routine management messages impacts performance of the DMS is examined. In the second scenario, techniques for ensuring low latency of real-time control messages in an emergency are examined.

Johnson, Marjory J.↗

Description of the PMAD systems test bed facility and data system

The power management and distribution (PMAD) systems test bed facility, including the power sources and loads available, is discussed, and the PMAD data system (PDS) is described. The PDS controls the test-bed facility hardware, and monitors and records the electric power system control data bus and external data. The PDS architecture is discussed, and each of the subsystems is described.

Trase, Larry↗

An overview of the EOSDIS V0 information management system: Lessons learned from the implementation of a distributed data system

The EOSDIS Version 0 system, released in July, 1994, is a working prototype of a distributed data system. One of the purposes of the V0 project is to take several existing data systems and coordinate them into one system while maintaining the independent nature of the original systems. The project is a learning experience and the lessons are being passed on to the architects of the system which will distribute the data received from the planned EOS satellites. In the V0 system, the data resides on heterogeneous systems across the globe but users are presented with a single, integrated interface. This interface allows users to query the participating data centers based on a wide set of criteria. Because this system is a prototype, we used many novel approaches in trying to connect a diverse group of users with the huge amount of available data. Some of these methods worked and others did not. Now that V0 has been released to the public, we can look back at the design and implementation of the system and also consider some possible future directions for the next generation of EOSDIS.

Ryan, Patrick M.↗

Space station - Technology development

The NASA manned space station program's systems technology effort involves the development of novel techniques that will reduce the scope of tasks neeeded for design, development, testing and evaluation of the hardware. Operations technology efforts encompass analyses that will define those techniques best able to improve the efficiency and reduce the costs of space station functions. The technology objective for data management calls for a fault-tolerant, distributed, expandable and adaptable, as well as repairable and user-friendly, flight data management system that employs state-of-the-art hardware and software. The space station's power system includes the largest element, a 'solar blanket', and the heaviest component, the batteries, of all the subsystems. A thermal management system for the power system is of paramount importance. Attention is also given to the exacting demands of attitude control and stabilization and a regenerative life support system of the requisite capacity and reliability.

Carlisle, R. F.↗

Countermeasure Evaluation and Validation Project (CEVP) Database Requirement Documentation

The initial focus of the project by the JSC laboratories will be to develop, test and implement a standardized complement of integrated physiological test (Integrated Testing Regimen, ITR) that will examine both system and intersystem function, and will be used to validate and certify candidate countermeasures. The ITR will consist of medical requirements (MRs) and non-MR core ITR tests, and countermeasure-specific testing. Non-MR and countermeasure-specific test data will be archived in a database specific to the CEVP. Development of a CEVP Database will be critical to documenting the progress of candidate countermeasures. The goal of this work is a fully functional software system that will integrate computer-based data collection and storage with secure, efficient, and practical distribution of that data over the Internet. This system will provide the foundation of a new level of interagency and international cooperation for scientific experimentation and research, providing intramural, international, and extramural collaboration through management and distribution of the CEVP data. The research performed this summer includes the first phase of the project. The first phase of the project is a requirements analysis. This analysis will identify the expected behavior of the system under normal conditions and abnormal conditions; that could affect the system's ability to produce this behavior; and the internal features in the system needed to reduce the risk of unexpected or unwanted behaviors. The second phase of this project have also performed in this summer. The second phase of project is the design of data entry screen and data retrieval screen for a working model of the Ground Data Database. The final report provided the requirements for the CEVP system in a variety of ways, so that both the development team and JSC technical management have a thorough understanding of how the system is expected to behave.

Shin, Sung Y.↗

EOS ground data systems: A description and interface overview

The Earth Observing System (EOS) is planned as a space-based measurement system, earth-science research program, and data and information system (EOSDIS). It will consist of several high data rate spacecraft with multiple earth sensing instruments which provide investigators with a thorough, longterm view of the earth's environment. Up to seven spacecraft may be supported at once, either in operational, checkout, or testing phases; and the average data rate from the EOS satellites in orbit at any one time is expected to be from 18 to 60 Mbps. Providing the data processing and flight operations support for EOS will be the EOSDIS Core System (ECS). The ECS will command and control the spacecraft; process and store the EOS data; provide access to the data for years; and support researchers. The data processing aspects of the ECS consist of a collection of Distributed Active Archive Centers (DAAC's) which perform the product generation, data archive and distribution, and information management services. Flight operations aspects will be provided by the EOS Operations Center, by instrument control centers, and by widely distributed instrument support terminals. The communications and system management aspects will be provided by the EOSDIS Science Network and the System Management Center. In addition to the EOS satellite data, other data sets from earlier earth science missions are also to be added to designated DAAC's. Other ground data systems which will provide support to EOS for acquiring, transporting, processing, and distributing the transformed spacecraft data are currently being defined or are being upgraded for the EOS era. These systems include the Space Network consisting of the Tracking and Data Relay Satellite System (TDRSS), the TDRSS Ground Terminals, and the Network Control Center as well as the night Dynamics Facility, the EOS Data and Operations System, and EOS Communications. This paper briefly describes data handling by the ECS, the support data systems, their interfaces, and their roles.

Smith, Gene↗

Achieving cost reductions in EOSDIS operations through technology evolution

The earth observing system (EOS) data information system (EOSDIS) mission includes the cost-effective management and distribution of large amounts of data to the earth science community. The effect of the introduction of new information system technologies on the evolution of EOSDIS is considered. One of the steps taken by NASA to enable the introduction of new information system technologies into the EOSDIS is the funding of technology development through prototyping. Recent and ongoing prototyping efforts and their potential impact on the performance and cost-effectiveness of the EOSDIS are discussed. The technology evolution process as it related to the effective operation of EOSDIS is described, and methods are identified for the support of the transfer of relevant technology to EOSDIS components.

Newsome, Penny↗

Application of ESE Data and Tools to Air Quality Management: Services for Helping the Air Quality Community use ESE Data (SHAirED)

The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. Its scope falls within the domain of air quality management and aims to develop a federated air quality information sharing network that includes data from NASA, EPA, US States and others. Project goals were achieved through a access of satellite and ground observation data, web services information technology, interoperability standards, and air quality community collaboration. In contributing to a network of NASA ESE data in support of particulate air quality management, the project will develop access to distributed data, build Web infrastructure, and create tools for data processing and analysis. The key technologies used in the project include emerging web services for developing self describing and modular data access and processing tools, and service oriented architecture for chaining web services together to assemble customized air quality management applications. The technology and tools required for this project were developed within DataFed.net, a shared infrastructure that supports collaborative atmospheric data sharing and processing web services. Much of the collaboration was facilitated through community interactions through the Federation of Earth Science Information Partners (ESIP) Air Quality Workgroup. The main activities during the project that successfully advanced DataFed, enabled air quality applications and established community-oriented infrastructures were: develop access to distributed data (surface and satellite), build Web infrastructure to support data access, processing and analysis create tools for data processing and analysis foster air quality community collaboration and interoperability.

Falke, Stefan↗

Description of the SSF PMAD dc testbed control system data acquisition function

A functional description of the various levels of the SSF power management and distribution dc test-bed control system architecture is presented, and the data acquisition function and the status of its implementation are described. The data requirements for the test-bed control system are dictated by the functionality being implemented at each level of the architecture. The test-bed control system hierarchy data acquisition function is distributed among its various levels. Fast-acting control functions that require time critical data are implemented at the lowest level. These functions require periodic data sampling to assure safe system operation and performance. Slower response control functions are implemented at the higher levels and require data to be reported at least every second. The present data acquisition function meets the requirements for a hierarchical and distributed power management and control system.

Baez, Anastacio N.↗

Computer Sciences and Data Systems, volume 1

Topics addressed include: software engineering; university grants; institutes; concurrent processing; sparse distributed memory; distributed operating systems; intelligent data management processes; expert system for image analysis; fault tolerant software; and architecture research.

Source record↗

Space Station Freedom Environmental Control and Life Support System design - A status report

Space Station Freedom (S.S. Freedom) has entered into the Preliminary Design Review (PDR) phase of the program. This paper outlines the Environmental Control and Life Support System (ECLSS) design with emphasis on the systems aspects of the ECLSS. Interactions with other distributed systems, such as data management and electrical power are described. The integration of the ECLSS into the S.S. Freedom pressurized elements and truss are addressed.

Humphries, W. R.↗

Space Station Freedom ECLSS design configuration - A post restructure update

The Space Station Freedom Program (SSFP) has undergone major design changes within the last year due to reduced budget appropriations imposed by Congress. This paper outlines the impacts of the design changes on the Environmental Control and Life Support System (ECLSS), with emphasis on the system aspects of the ECLSS. Brief descriptions of design impacts to all six ECLSS subsystems are provided in addition to interactions with other distributed systems such as Data Management, Electrical Power, and Man Systems. The assembly sequence for SSF is addressed with emphasis on key flights with respect to the ECLSS.

Bacskay, Allen S.↗

On-board B-ISDN fast packet switching architectures. Phase 2: Development. Proof-of-concept architecture definition report

For the next-generation packet switched communications satellite system with onboard processing and spot-beam operation, a reliable onboard fast packet switch is essential to route packets from different uplink beams to different downlink beams. The rapid emergence of point-to-point services such as video distribution, and the large demand for video conference, distributed data processing, and network management makes the multicast function essential to a fast packet switch (FPS). The satellite's inherent broadcast features gives the satellite network an advantage over the terrestrial network in providing multicast services. This report evaluates alternate multicast FPS architectures for onboard baseband switching applications and selects a candidate for subsequent breadboard development. Architecture evaluation and selection will be based on the study performed in phase 1, 'Onboard B-ISDN Fast Packet Switching Architectures', and other switch architectures which have become commercially available as large scale integration (LSI) devices.

Shyy, Dong-Jye↗