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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

NASA Information Technology Implementation Plan

NASA's Information Technology (IT) resources and IT support continue to be a growing and integral part of all NASA missions. Furthermore, the growing IT support requirements are becoming more complex and diverse. The following are a few examples of the growing complexity and diversity of NASA's IT environment. NASA is conducting basic IT research in the Intelligent Synthesis Environment (ISE) and Intelligent Systems (IS) Initiatives. IT security, infrastructure protection, and privacy of data are requiring more and more management attention and an increasing share of the NASA IT budget. Outsourcing of IT support is becoming a key element of NASA's IT strategy as exemplified by Outsourcing Desktop Initiative for NASA (ODIN) and the outsourcing of NASA Integrated Services Network (NISN) support. Finally, technology refresh is helping to provide improved support at lower cost. Recently the NASA Automated Data Processing (ADP) Consolidation Center (NACC) upgraded its bipolar technology computer systems with Complementary Metal Oxide Semiconductor (CMOS) technology systems. This NACC upgrade substantially reduced the hardware maintenance and software licensing costs, significantly increased system speed and capacity, and reduced customer processing costs by 11 percent.

Source record↗
DOE OSTI2023

Vectorization of CMSSW offline software

The CMS experiment has been utilizing vectorization, or SIMD, in parts of its data processing applications for over a decade. On x86 platforms the vectorization level is still SSE3. In the past attempts to use wider vector instruction sets such as AVX or AVX-512 have, in practice, not resulted in improvements in the overall event processing throughput, because the CPUs scale down their frequency when processing AVX instructions. In addition, a notable part of the global pool of CMS’ resources has been old systems either not supporting AVX, or where the CPU frequency downscaling impacts all cores of the CPU. CMS has nevertheless continued to vectorize more of its application code, and in this work we review profiling methods we have found effective to find out pieces of code that would benefit from vectorization, and techniques to transform those codes such that the GCC compiler is able to auto-vectorize those codes. The build system used for CMSSW, Scram, has also been enha nced to be able to build code for multiple CPU microarchitectures such that the shared libraries of desired microarchitecture level can be loaded based on the CPU of the system. This multi-microarchitecture setup is invisible to the workflow management system, which makes its deployment straightforward. We describe in detail how this multi-microarchitecture build is set up, and measure the impact of using wider vector units than SSE3 on the event processing throughput of CMS applications such as simulation and reconstruction on recent x86 CPUs.

Gartung, Patrick↗
DOE OSTI2019

ASCR Workshop on In Situ Data Management: Enabling Scientific Discovery from Diverse Data Sources

In January 2019, the U.S. Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions for in situ data management (ISDM). The workshop defined ISDM as the practices, capabilities, and procedures to control the organization of data and enable the coordination and communication among heterogeneous tasks, executing simultaneously in a high-performance computing system, cooperating toward a common objective. The workshop revealed two primary, interdependent motivations for processing and managing data in situ. The first motivation is that the in situ methodology enables scientific discovery from a broad range of data sources over a wide scale of computing platforms: leadership-class systems, clusters, clouds, workstations, and embedded devices at the edge. The successful development of ISDM capabilities will benefit real-time decision-making, design optimization, and data-driven scientific discovery. The second motivation is the need to decrease data volumes. ISDM can make critical contributions to managing large data volumes from computations and experiments to minimize data movement, save storage space, and boost resource efficiency, often while simultaneously increasing scientific precision. A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery across the Office of Science mission space. Applications wanting to use the in situ capabilities include those where data analysis feeds back to the simulation, decisions are made autonomously, big data or machine learning is among the tasks to be coordinated, and computations need to be completed in real time. The workshop identified six priority research directions that highlight the components and capabilities needed for ISDM to be successful for the wide variety of applications discussed: making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Putting ROSE to Work: A Proposed Application of a Request-Oriented Scheduling Engine for Space Station Operations

Scheduling engines are found at the core of software systems that plan and schedule activities and resources. A Request-Oriented Scheduling Engine (ROSE) is one that processes a single request (adding a task to a timeline) and then waits for another request. For the International Space Station, a robust ROSE-based system would support multiple, simultaneous users, each formulating requests (defining scheduling requirements), submitting these requests via the internet to a single scheduling engine operating on a single timeline, and immediately viewing the resulting timeline. ROSE is significantly different from the engine currently used to schedule Space Station operations. The current engine supports essentially one person at a time, with a pre-defined set of requirements from many payloads, working in either a "batch" scheduling mode or an interactive/manual scheduling mode. A planning and scheduling process that takes advantage of the features of ROSE could produce greater customer satisfaction at reduced cost and reduced flow time. This paper describes a possible ROSE-based scheduling process and identifies the additional software component required to support it. Resulting changes to the management and control of the process are also discussed.

Jaap, John↗
DOE OSTI2022

DER Cybersecurity Detection and Response Suite

SAND2024-08475O The Distributed Energy Resource (DER) Cybersecurity Detection and Response Suite is a solution for distributed energy resource (DER) systems. The DER Security Orchestration, Automation, and Response (SOAR) solution that uses alerts from signature- and behavior-based Intrusion Detection Systems are intended to be deployed as bump-in-the-wire (BITW) devices in front of DER equipment. The fielded application would use multiple intrusion detection systems that report data to SOAR to respond to cyberattacks. The suite consists of two software components: • The proactive intrusion detection and mitigation system (PIDMS) secures grid-edge photovoltaic smart inverters and other equipment in distributed energy resource systems. It is a distributed BITW solution; cyber and physical data are automatically processed using network inspection tools and custom machine learning algorithms to detect abnormal events and correlate cyber-physical events. • The Security Orchestration, Automation, and Response for Distributed Energy Resources (SOAR4DER) application ingests data from several intrusion detection systems to quickly block attacks and revert DER systems to good states. Using a collection of intrusion detection system technologies on a BITW device, it incorporates physical and cyber data to detect abnormal and potential malicious behaviors. Multiple SOAR playbooks then use the intrusion detection system data streams to automatically defend the system. SOAR4DER system testing showed detection and response times under 30 seconds for all adversary reconnaissance, denial-of-service attacks, malicious Modbus commands, brute-force logins, and machine-in-the-middle attacks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Johnson, Jay↗
DOE OSTI2022

Dynamic Decarbonization through Autonomous Physics-Centric Deep Learning and Optimization of Building Operations (Abstract only)

This project directly addresses the primary goal of Area of Interest 2 in the CRADA call: to advance optimization-based integrated energy management systems in commercial and residential buildings. Pacific Northwest National Laboratory (PNNL) and its industry partner PassiveLogic aim to accomplish this by reaching three key objectives. First, to ensure a broad impact in the building controls industry, PNNL will extend its open-source library for predictive control synthesis by augmenting its capabilities with data-driven self-learning of building models and auto-calibration of predictive controllers. The effort will focus on building use cases selected in collaboration with PassiveLogic. The team will specifically address the development of methods for data-driven adaptation of building models, investigation of model architectures that best address specific building types, and automated synthesis of differentiable predictive controllers that optimize diverse objectives. Second, PNNL will collaborate with PassiveLogic to integrate the aforementioned methods with PasiveLogic’s advanced controls platform. The collaborative integration effort will inform the developments under the first objective by providing specific data on the attainable performance of model learning on resource-constrained edge computing platforms. This software integration effort will increase the technical maturity of the developed libraries by exploring the use of software integration tools and methods. Third, PNNL and PassiveLogic will work to improve the technology readiness of the developed predictive controllers by testing their performance in relevant test environments, such as high-fidelity simulation, hardware in the loop, and actual test buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2012

Tools Ensure Reliability of Critical Software

In November 2006, after attempting to make a routine maneuver, NASA's Mars Global Surveyor (MGS) reported unexpected errors. The onboard software switched to backup resources, and a 2-day lapse in communication took place between the spacecraft and Earth. When a signal was finally received, it indicated that MGS had entered safe mode, a state of restricted activity in which the computer awaits instructions from Earth. After more than 9 years of successful operation gathering data and snapping pictures of Mars to characterize the planet's land and weather communication between MGS and Earth suddenly stopped. Months later, a report from NASA's internal review board found the spacecraft's battery failed due to an unfortunate sequence of events. Updates to the spacecraft's software, which had taken place months earlier, were written to the wrong memory address in the spacecraft's computer. In short, the mission ended because of a software defect. Over the last decade, spacecraft have become increasingly reliant on software to carry out mission operations. In fact, the next mission to Mars, the Mars Science Laboratory, will rely on more software than all earlier missions to Mars combined. According to Gerard Holzmann, manager at the Laboratory for Reliable Software (LaRS) at NASA's Jet Propulsion Laboratory (JPL), even the fault protection systems on a spacecraft are mostly software-based. For reasons like these, well-functioning software is critical for NASA. In the same year as the failure of MGS, Holzmann presented a new approach to critical software development to help reduce risk and provide consistency. He proposed The Power of 10: Rules for Developing Safety-Critical Code, which is a small set of rules that can easily be remembered, clearly relate to risk, and allow compliance to be verified. The reaction at JPL was positive, and developers in the private sector embraced Holzmann's ideas.

Source record↗
NASA NTRS2020

Enabling Assurance in the MBSE Environment

A number of specific benefits that fit within the hallmarks of effective development are realized with implementation of model-based approaches to systems and assurance. Model Based Systems Engineering (MBSE) enabled by standardized modeling languages (e.g., SysML®) is at the core. These benefits in the context of spaceflight system challenges can include [1]: • Improved management of complex development • Reduced risk in the development process • Improved cost management • Improved design decisions With appropriate modeling techniques the assurance community also can improve early oversight and insight into project development. NASA has shown the basic constructs of SysML in an MBSE environment offer several key advantages, within a Model Based Mission Assurance (MBMA) initiative [2, 3]. These include the following: • Model viewpoints that promote rapid and systematic assessment of requirements coverage, hazard tagging and risk management • Embedded safety assessments for launch vehicles • Deployment of model assisted development of reliability products - Failure Modes and Effects Analyses (FMEAs) and Fault Trees • Test Planning • Validation and Verification of complex functions • Support of Assurance Case development for complex systems In addition, while there are benefits to be harvested, there is a realization that these do not come without effort and cost. Enabling model-based approaches requires structure, not only in an organizational context, but in a modeling context as well. There can be a steep learning curve and costs associated to train skilled modelers. But, on the other hand, not all of the assurance community need to be modelers. Models themselves must conform to ontologies that enable assurance. This places constraints upon the models and modelers. Optimums have yet to be developed where resources and constraints on modeling must be traded off in the organization and modeling efforts for projects. A number of barriers need to be overcome, as well, which pose challenges to the developers of the software that supports MBSE/MBMA. Information and data must be made to flow seamlessly through the life cycle. Because there is a wide variety of tools used in the community, to avoid the problems of the past of silos, delays, and diverging interests, information should flow among these tools to support the “single source of truth” paradigm of MBSE. This will greatly facilitate MBMA and advancement of assurance functions.

Evans, John W.↗
NASA NTRSDate not supplied

Data Integrity Challenges in NASA Giovanni

The Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) is an online tool developed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers (DAACs) to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several well-known NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). There are twenty-two plots provided by Giovanni that can be used to analyze, compare, and explore Earth data across disciplines. Results can be shared with colleagues and downloaded for further analysis. Giovanni has helped publish over 3000 referral papers over the years. As open science policies roll in, data integrity has become a major challenge for Giovanni and other tools. For integrity, both data and workflows must be transparent. FAIR-compliant data, including input, intermediate, and result products, as well as their associated statistics, metadata, and information, are needed. The NASA Data Product Development Guide for Data Producers provides a key resource on how to develop FAIR-compliant data products. Data quality information is also needed from data producers and analysis services like Giovanni. The workflow part is quite challenging and requires workflow management improvements, such as recording workflows and making them available to users. In this presentation, we will discuss the data integrity challenges in Giovanni.

data analysis, visualization↗
DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗
DOE OSTI2021

Reusability First: Toward FAIR Workflows

The FAIR principles of open science (Findable, Accessible, Interoperable, and Reusable) have had transformative effects on modern large-scale computational science. In particular, they have encouraged more open access to and use of data, an important consideration as collaboration among teams of researchers accelerates and the use of workflows by those teams to solve problems increases. How best to apply the FAIR principles to workflows themselves, and software more generally, is not yet well understood. We argue that the software engineering concept of technical debt management provides a useful guide for application of those principles to workflows, and in particular that it implies reusability should be considered as ‘first among equals’. Moreover, our approach recognizes a continuum of reusability where we can make explicit and selectable the tradeoffs required in workflows for both their users and developers.To this end, we propose a new abstraction approach for reusable workflows, with demonstrations for both synthetic workloads and real-world computational biology workflows. Through application of novel systems and tools that are based on this abstraction, these experimental workflows are refactored to rightsize the granularity of workflow components to efficiently fill the gap between end-user simplicity and general customizability. Our work makes it easier to selectively reason about and automate the connections between trade-offs across user and developer concerns when exposing degrees of freedom for reuse. Additionally, by exposing fine-grained reusability abstractions we enable performance optimizations, as we demonstrate on both institutional-scale and leadership-class HPC resources.

Wolf, Matthew↗
DOE OSTI2015

Continuous Security and Configuration Monitoring of HPC Clusters

Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking can be managed from one central location.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1991

Monitoring and control technologies for bioregenerative life support systems/CELSS

The development of a controlled Ecological Life Support System (CELSS) will require NASA to develop innovative monitoring and control technologies to operate the different components of the system. Primary effort over the past three to four years has been directed toward the development of technologies to operate a biomass production module. Computer hardware and software required to operate, collect, and summarize environmental data for a large plant growth chamber facility were developed and refined. Sensors and controls required to collect information on such physical parameters as relative humidity, temperature, irradiance, pressure, and gases in the atmosphere; and PH, dissolved oxygen, fluid flow rates, and electrical conductivity in the nutrient solutions are being developed and tested. Technologies required to produce high artificial irradiance for plant growth and those required to collect and transport natural light into a plant growth chamber are also being evaluated. Significant effort was directed towards the development and testing of a membrane nutrient delivery system required to manipulate, seed, and harvest crops, and to determine plant health prior to stress impacting plant productivity are also being researched. Tissue culture technologies are being developed for use in management and propagation of crop plants. Though previous efforts have focussed on development of technologies required to operate a biomass production module for a CELSS, current efforts are expanding to include technologies required to operate modules such as food preparation, biomass processing, and resource (waste) recovery which are integral parts of the CELSS.

Knott, William M.↗
NASA NTRSDate not supplied

VISUALIZING INTERANNUAL TO DECADAL COASTAL VARIABILITY NEAR VULNERABLE NASA INFRASTRUCTURE UTILIZING VIDEOS PRODUCED FROM REMOTELY SENSED DATA AT CAPE CANAVERAL, FL AND WALLOPS ISLAND, VA

Coastlines represent an interesting convolution of intense anthropogenic development superimposed onto morphologies that are among the most dynamic on the planet. Two of NASA’s critical facilities are particularly vulnerable to coastal change, Kennedy Space Center, Cape Canaveral, FL and Wallops Flight Facility, Wallops Island, VA. With continuing global sea level rise and increasing storminess coastal vulnerabilities at these facilities will only be exacerbated. These launch centers a subject to multiple coastal hazards including, flooding, episodic coastal erosion, saltwater intrusion, and coastal morphological changes. Although rapid change is readily observed during large storms or hurricanes, long term annual to decadal coastal change is much harder to visualize and conceptualize. The authors use videos developed from remotely sensed data to enhance conceptualization of coastal processes for planning and management stakeholders at these NASA facilities. Near or better than decadal coastal imagery has been available through high altitude photogrammetry efforts since the 1930’s. A significant amount of additional imagery was acquired through other federal, state, and local government agencies such as the USGS, NOAA, State DOT, and local Assessors Offices providing annual and inter annual images at spatial resolutions of 10cm – 1m. With the advent of GIS systems these images could be rectified and then layered to better understand change through time using a multitude of visual base shoreline proxies. With the increased awareness and use of video editing software the rectified images can be used to create videos. These videos can then be used to conceptualize a multitude of coastal processes including: performance of coastal restoration efforts, rapid change in sedimentation rates due to storms or other geomorphic processes, loss of protective barrier islands as sea level rises and lower sedimentation rates occur. The videos are also useful as a tool for verification and comparison to coastal models and provide an easy to understand educational resource for stakeholder engagement at these NASA centers, and other vulnerable coastal populations.

Richard A. MacKenzie III↗
NASA NTRS1994

Software Process Assessment (SPA)

NASA's environment mirrors the changes taking place in the nation at large, i.e. workers are being asked to do more work with fewer resources. For software developers at NASA's Goddard Space Flight Center (GSFC), the effects of this change are that we must continue to produce quality code that is maintainable and reusable, but we must learn to produce it more efficiently and less expensively. To accomplish this goal, the Data Systems Technology Division (DSTD) at GSFC is trying a variety of both proven and state-of-the-art techniques for software development (e.g., object-oriented design, prototyping, designing for reuse, etc.). In order to evaluate the effectiveness of these techniques, the Software Process Assessment (SPA) program was initiated. SPA was begun under the assumption that the effects of different software development processes, techniques, and tools, on the resulting product must be evaluated in an objective manner in order to assess any benefits that may have accrued. SPA involves the collection and analysis of software product and process data. These data include metrics such as effort, code changes, size, complexity, and code readability. This paper describes the SPA data collection and analysis methodology and presents examples of benefits realized thus far by DSTD's software developers and managers.

Rosenberg, Linda H.↗
NASA NTRS2012

Bringing Together Users and Developers of Forest Biomass Maps

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the private sector because much forest acreage in the United States is privately held and needs data for forest management. Additional key outcomes identified by meeting participants include the following: (1) Priority should be given to building into the biomass product ease of use and low costs (including costs of hardware, software, and analysis requirements), (2) CMS products should also be relevant to other biomass measures for forest watershed management, habitat protection for biodiversity, and assessment of markets for ecosystem services, (3) CMS leadership should engage with the Subsidiary Body for Scientific and Technological Advice of the United Nations Framework Convention on Climate Change as they establish measuring, reporting, and verification standards, and (4) CMS leadership should continue to keep sister agencies and other organizations informed as CMS develops, particularly via the agencies active in the U.S. Global Change Research Program Carbon Cycle Interagency Working Group (U.S. Geological Survey, U.S. Department of Agriculture, and National Oceanic and Atmospheric Administration) and nongovernmental organizations.

Forest↗