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Electroencephalographic imaging of higher brain function

High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.

Non-NASA Center↗

Applying Space Technology to Enhance Control of an Artificial Arm

At the present time, myoelectric prostheses perform only one function of the hand: open and close with the thumb, index and middle finger coming together to grasp various shaped objects. To better understand the limitations of the current single-function prostheses and the needs of the individuals who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (August 1992 - November 1994), surveyed approximately 2500 individuals with upper limb loss. When asked to identify specific features of their current electric prosthesis that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement as well as poor control capability. Simply building a mechanism with individual finger and wrist motion is not enough. Individuals with upper limb loss tend to reject prostheses that require continuous visual monitoring and concentration to control. Robotics researchers at NASA's Johnson Space Center (JSC) and Rice University have made substantial progress in myoelectric teleoperation. A myoelectric teleoperation system translates signals generated by an able-bodied robot operator's muscles during hand motions into commands that drive a robot's hand through identical motions. Farry's early work in myoelectric teleoperation used variations over time in the myoelectric spectrum as inputs to neural networks to discriminate grasp types and thumb motions. The resulting schemes yielded up to 93% correct classification on thumb motions. More recently, Fernandez achieved 100% correct non-realtime classification of thumb abduction, extension, and flexion on the same myoelectric data. Fernandez used genetic programming to develop functions that discriminate between thumb motions using myoelectric signal parameters. Genetic programming (GP) is an evolutionary programming method where the computer can modify the discriminating functions' form to improve its performance, not just adjust numerical coefficients or weights. Although the function development may require much computational time and many training cases, the resulting discrimination functions can run in realtime on modest computers. These results suggest that myoelectric signals might be a feasible teleoperation medium, allowing an operator to use his or her own hand and arm as a master to intuitively control an anthropomorphic robot in a remote location such as outer space.

Atkins, Diane↗

Demonstrating High-Accuracy Orbital Access Using Open-Source Tools

Orbit propagation is fundamental to almost every space-based analysis. Currently, many system analysts use commercial software to predict the future positions of orbiting satellites. This is one of many capabilities that can replicated, with great accuracy, without using expensive, proprietary software. NASAs SCaN (Space Communication and Navigation) Center for Engineering, Networks, Integration, and Communications (SCENIC) project plans to provide its analysis capabilities using a combination of internal and open-source software, allowing for a much greater measure of customization and flexibility, while reducing recurring software license costs. MATLAB and the open-source Orbit Determination Toolbox created by Goddard Space Flight Center (GSFC) were utilized to develop tools with the capability to propagate orbits, perform line-of-sight (LOS) availability analyses, and visualize the results. The developed programs are modular and can be applied for mission planning and viability analysis in a variety of Solar System applications. The tools can perform 2 and N-body orbit propagation, find inter-satellite and satellite to ground station LOS access (accounting for intermediate oblate spheroid body blocking, geometric restrictions of the antenna field-of-view (FOV), and relativistic corrections), and create animations of planetary movement, satellite orbits, and LOS accesses. The code is the basis for SCENICs broad analysis capabilities including dynamic link analysis, dilution-of-precision navigation analysis, and orbital availability calculations.

propagation↗

Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data

Applications in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on spatial and temporal resolutions of satellite observations. However, there are typically trade-offs between spatial and temporal resolutions in dataset selection. For instance, geostationary weather tracking satellites are designed to take snapshots many times throughout the day but sensor hardware limits data collection. In this work we tackle this limitation, developing a method for temporal upsampling of multi-spectral satellite imagery using optical flow video interpolation deep convolutional neural networks. The presented model, extends Super SloMo (SSM) from single optical flow estimates to multichannel where flows are computed per band. We apply this technique on 8 multi-spectral bands of NOAA/NASA's GOES-16 mesoscale dataset to temporally enhance full disk hemispheric snapshots from 15 minutes to 1 minute. Through extensive experimentation, we show SSM vastly outperforms the linear interpolation baseline and that multichannel optical flows improves performance on GOES-16. A visual analysis of optical flow vectors clearly identifies hurricanes and large-scale atmospheric dynamics. Furthermore, we discuss challenges and open questions related to optical flow and temporal interpolation of multispectral geostationary satellite imagery.

Optical Flow↗

Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning

Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.

Yury Lebedev↗

Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning

Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.

Yury Lebedev↗

Corridor Design and Analysis for UAM Operations

The Urban Air Mobility (UAM) concept is a part of Advanced Air Mobility (AAM), a joint initiative between the Federal Aviation Administration (FAA), NASA, and industry to develop an air transportation system that uses new electric (i.e., green) air vehicles in geographical areas previously underserved by traditional aviation. Market forecast studies predict that there will be demand for alternate modes of air transportation using electric Vertical Take-off and Landing aircraft. UAM expands transportation networks by introducing short flights to move people and goods around metropolitan areas​. UAM is expected to improve mobility for the public, decongest road traffic, reduce trip time, and decrease strain on existing public transportation networks. Various challenges exist to make the introduction of UAM operations successful in the U.S. National Airspace System (NAS). These include but are not limited to integration with existing airports and airspace, provision of air traffic services (e.g., separation), vehicle design and certification, and community acceptance. The focus of this paper is on integration of UAM operations into the NAS via introduction of new airspace structures. UAM will operate within a regulatory, operational, and technical environment that is incorporated into the NAS​. As per the UAM Concept of Operations (ConOps), the FAA retains regulatory authority and is responsible for establishing operational parameters and maintaining oversight. The FAA’s UAM ConOps describes flights at low altitudes (below 5,000 ft) with minimal disruption to established conventional aircraft traffic and limited voice interactions with the Air Traffic Control (ATC). Early stages of UAM may use existing procedures to safely integrate UAM with conventional flights. This would involve flying under Part 91 Visual Flight Rules (VFR) and using voice for communications. The initial UAM ecosystem will utilize the current infrastructure such as routes, helipads, and ATC services, where practicable. ​A NASA study explored the use of existing helicopter routes in Dallas Fort Worth (DFW) airspace for initial UAM operations with a Letter of Agreement (LOA) that included procedures to request a Class B (controlled airspace) clearance. The research showed that the chosen approach was feasible for near-term, low-demand UAM traffic, but was not scalable. The growth of operations in today’s aviation system has resulted in airspace reorganization and procedures to ensure safety and efficiency as traffic rates increase. One proposed operating innovation that can help with the scalability of UAM is establishing routes and corridors. This may look similar to the Area Navigation (RNAV) procedures used today to streamline operations into busy airports. However, instead of FAA automation systems and ATC managing the flow of traffic, some UAM concepts envision a third-party service provider performing this role as part of the Provider of Services for UAM (PSU) network. The FAA’s UAM ConOps posits that new airspace structures such as UAM corridors include the following design criteria: 1) Minimal impact on existing NAS operations, 2) no or minimal additional ATC services, 3) public interest considerations such as noise, safety, and security, and 4) customer needs. The airspace available in urban environments is limited by the height of buildings, the effect of weather including wind gusts, privacy needs, and a clearance envelope. The new airspace structure would need to be designed around large airports and urban areas where the initial market demand is likely to exist. NASA has started evaluating airspace in the Dallas Fort Worth area to design new airspace structures, keeping the first two design criteria in mind. It is assumed that there will be an on-board pilot-in-command, and the flights will operate under VFR in Visual Meteorological Conditions. Corridors will be required in controlled airspace, whereas UAM operations can fly in uncontrolled Class G and E airspace using current day rules. Keeler et. al identified factors and heuristics for development of routes for UAM operations for integration with airspace close to large airports such as Dallas Fort Worth and Dallas Love Field. This paper describes the heuristics applied to define the corridors, analyzes them with respect to legacy traffic and presents key results.

Urban Air Mobility↗

Use of 3D vision for fine robot motion

An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.

Lokshin, Anatole↗

Atmospheric Infrared Sounder Version 7 Near-Real-Time Product and Imagery Released by NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of data processing, archive, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. The GES DISC provides service to both AIRS routine and Near Real-Time (NRT) products. The AIRS NRT products are an important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). In collaboration with AIRS Project, the GES DISC has just released products from the Version 7 algorithm. The new version algorithm provides significant improvements over the previous version. The most substantial advances are: improved consistency between day and night water vapor; improved total column ozone and temperature; improved infrared-only (IR-only) retrievals, especially in high latitude regions; an improved Stochastic Cloud Clearing Neural Network used as a first guess at the initial value in the iterative retrieval process; and removal of ambiguity in surface classification in the IR-only retrieval algorithm. In addition, the GES DISC produces AIRS NRT imagery. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The data products used to generate this imagery include atmospheric temperature, humidity, precipitation, cloud, Dust Score, CO, and SO2. In this presentation, we will demonstrate visualization of the AIRS NRT imagery from the new Version 7, and demonstrate some improvements over the previous version. Progress on improving the AIRS NRT imagery, a collaboration project with the AIRS Applications Development Team at NASA Jet Propulsion Laboratory (JPL), will also be presented.

Feng Ding↗

Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS) and Other Assimilated Hydrological Data at NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides science support for several data sets relevant to agriculture and food security, including the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS), or FLDAS data set. The GES DISC is one of twelve NASA Earth Observing System (EOS) data centers that process, archive, document, and distribute data from Earth science missions and related projects. The GES DISC hosts a wide range of remote sensing and model data, and provides reliable and robust data access and other services to users worldwide. Beyond data archive and access, the GES DISC offers many services to visualize and analyze the data. This presentation provides a summary of the hydrological data available at the GES DISC, along with an overview of related data services. Specifically, the FLDAS data set has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings. The FLDAS global monthly data have a 0.1 x 0.1 degree spatial resolution covering the period from January 1982 to present. Global FLDAS monthly anomaly and monthly climatology data are also available at the GES DISC to evaluate how current conditions compare to averages over the FLDAS 35-year period. Several case studies using the FLDAS soil moisture, evapotranspiration, rainfall, runoff, and surface temperature data will be presented.

Loeser, Carlee↗

Impact of Multimedia and Network Services on an Introductory Level Course

We will demonstrate and describe the impact of our use of multimedia and network connectivity on a sophomore-level introductory course in materials science. This class services all engineering students, resulting in large (more than 150) class sections with no hands-on laboratory. In 1990 we began to develop computer graphics that might substitute for some laboratory or real-world experiences, and demonstrate relationships hard to show with static textbook images or chalkboard drawings. We created a comprehensive series of modules that cover the entire course content. Called VIMS (Visualizations in Materials Science), these are available in the form of a CD-ROM and also via the internet.

Russ, John C.↗

High performance flight simulation at NASA Langley

The use of real-time simulation at the NASA facility is reviewed specifically with regard to hardware, software, and the use of a fiberoptic-based digital simulation network. The network hardware includes supercomputers that support 32- and 64-bit scalar, vector, and parallel processing technologies. The software include drivers, real-time supervisors, and routines for site-configuration management and scheduling. Performance specifications include: (1) benchmark solution at 165 sec for a single CPU; (2) a transfer rate of 24 million bits/s; and (3) time-critical system responsiveness of less than 35 msec. Simulation applications include the Differential Maneuvering Simulator, Transport Systems Research Vehicle simulations, and the Visual Motion Simulator. NASA is shown to be in the final stages of developing a high-performance computing system for the real-time simulation of complex high-performance aircraft.

Cleveland, Jeff I., II↗

Low level remote sensing: Orographic winds

The orographic flow data set was obtained from a flight program to measure the influence of orographic features on turbulence momentum, heat, and moisture fluxes. The NASA B-57 aircraft instrumented with probes for measuring the three fluctuating wind speed components, temperature, and humidity was the primary measuring vehicle. Ancillary measurements were made with several ground-based sensors. These include the NOAA radar wind profilers, the Boulder wind network, the PROFS mesoscale surface network, the Boulder Atmospheric Observatory 300 m tower, special rawinsonde observations, and the NOAA/WPL Doppler lidar. The major objective of the flight program was to provide planetary boundary layer parameter information for new and current general circulation computer models. A numerical code, WINDER, based on a discrete element technique was run to numerically model the water tunnel simulated flow. Comparison of the analytical model with the experimental results is very good. Physical fluid dynamic principles embedded in the computational model and visual and hot wire anemometer measurements from the simulation are being rationalized to develop a physical understanding of the vortex flow. The results will be interpreted as they pertain to full scale atmospheric flows.

Frost, Walter↗

Assessing Operational Total Lightning Visualization Products

In May 2003, NASA's Short-term Prediction Research and Transition (SPoRT) program successfully provided total lightning data from the North Alabama Lightning Mapping Array (NALMA) to the National Weather Service (NWS) office in Huntsville, Alabama. The major accomplishment was providing the observations in real-time to the NWS in the native Advanced Weather Interactive Processing System (AWIPS) decision support system. Within days, the NALMA data were used to issue a tornado warning initiating seven years of ongoing support to the NWS' severe weather and situational awareness operations. With this success, SPoRT now provides real-time NALMA data to five forecast offices as well as working to transition data from total lightning networks at Kennedy Space Center and the White Sands Missile Range to the surrounding NWS offices. The only NALMA product that has been transitioned to SPoRT's partner NWS offices is the source density product, available at a 2 km resolution in 2 min intervals. However, discussions with users of total lightning data from other networks have shown that other products are available, ranging from spatial and temporal variations of the source density product to the creation of a flash extent density. SPoRT and the Huntsville, Alabama NWS are evaluating the utility of these variations as this has not been addressed since the initial transition in 2003. This preliminary analysis will focus on what products will best support the operational warning decision process. Data from 19 April 2009 are analyzed. On this day, severe thunderstorms formed ahead of an approaching cold front. Widespread severe weather was observed, primarily south of the Tennessee River with multiple, weak tornadoes, numerous severe hail reports, and wind. This preliminary analysis is the first step in evaluation which product(s) are best suited for operations. The ultimate goal is selecting a single product for use with all total lightning networks to streamline training and science sharing.

Stano, Geoffrey T.↗

Customizing Countermeasure Prescriptions using Predictive Measures of Sensorimotor Adaptability

Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readapation phase following a return to a gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functional tasks during and after these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The ability to predict the manner and degree to which each individual astronaut will be affected would improve the effectiveness of a countermeasure comprised of a training program designed to enhance sensorimotor adaptability. Due to this inherent individual variability we need to develop predictive measures of sensorimotor adaptability that will allow us to predict, before actual space flight, which crewmember will experience challenges in adaptive capacity. Thus, obtaining this information will allow us to design and implement better sensorimotor adaptability training countermeasures that will be customized for each crewmember's unique adaptive capabilities. Therefore the goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to design sensorimotor adaptability training countermeasures that are customized for each crewmember's individual sensorimotor adaptive characteristics. To achieve these goals we are currently pursuing the following specific aims: Aim 1: Determine whether behavioral metrics of individual sensory bias predict sensorimotor adaptability. For this aim, subjects perform tests that delineate individual sensory biases in tests of visual, vestibular, and proprioceptive function. Aim 2: Determine if individual capability for strategic and plastic-adaptive responses predicts sensorimotor adaptability. For this aim, each subject's strategic and plastic-adaptive motor learning abilities are assessed using a test of locomotor function designed specifically to delineate both mechanisms. Aim 3: Develop predictors of sensorimotor adaptability using brain structural and functional metrics. We will measure individual differences in regional brain volumes (structural MRI), white matter integrity (diffusion tensor imaging, or DTI), functional network integrity (resting state functional connectivity MRI), and sensorimotor adaptation task-related functional brain activation (functional MRI). We decided to complete the data collection for Specific Aims 1, 2 and 3 simultaneously on the same subjects to increase data capture. By having the same subjects perform all three specific aims we can enhance our ability to detect how a wider range of factors can predict adaptability in a specific individual. This provides a much richer database and potentially a better understanding of the predictive power of the selected factors. In this presentation I will discuss preliminary data obtained to date.

Bloomberg, J. J.↗

Station report on the Goddard Space Flight Center (GSFC) 1.2 meter telescope facility

The 1.2 meter telescope system was built for the Goddard Space Flight Center (GSFC) in 1973-74 by the Kollmorgen Corporation as a highly accurate tracking telescope. The telescope is an azimuth-elevation mounted six mirror Coude system. The facility has been used for a wide range of experimentation including helioseismology, two color refractometry, lunar laser ranging, satellite laser ranging, visual tracking of rocket launches, and most recently satellite and aircraft streak camera work. The telescope is a multi-user facility housed in a two story dome with the telescope located on the second floor above the experimenter's area. Up to six experiments can be accommodated at a given time, with actual use of the telescope being determined by the location of the final Coude mirror. The telescope facility is currently one of the primary test sites for the Crustal Dynamics Network's new UNIX based telescope controller software, and is also the site of the joint Crustal Dynamics Project / Photonics Branch two color research into atmospheric refraction.

Mcgarry, Jan F.↗

Distributed Observer Network

The Distributed Observer network (DON) is a NASA-collaborative environment that leverages game technology to bring three-dimensional simulations to conventional desktop and laptop computers in order to allow teams of engineers working on design and operations, either individually or in groups, to view and collaborate on 3D representations of data generated by authoritative tools such as Delmia Envision, Pro/Engineer, or Maya. The DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3D visual environment. DON has been designed to enhance accessibility and user ability to observe and analyze visual simulations in real time. A variety of NASA mission segment simulations [Synergistic Engineering Environment (SEE) data, NASA Enterprise Visualization Analysis (NEVA) ground processing simulations, the DSS simulation for lunar operations, and the Johnson Space Center (JSC) TRICK tool for guidance, navigation, and control analysis] were experimented with. Desired functionalities, [i.e. Tivo-like functions, the capability to communicate textually or via Voice-over-Internet Protocol (VoIP) among team members, and the ability to write and save notes to be accessed later] were targeted. The resulting DON application was slated for early 2008 release to support simulation use for the Constellation Program and its teams. Those using the DON connect through a client that runs on their PC or Mac. This enables them to observe and analyze the simulation data as their schedule allows, and to review it as frequently as desired. DON team members can move freely within the virtual world. Preset camera points can be established, enabling team members to jump to specific views. This improves opportunities for shared analysis of options, design reviews, tests, operations, training, and evaluations, and improves prospects for verification of requirements, issues, and approaches among dispersed teams.

Conroy, Michael↗

Communications Dashboard (Control Rooms Take a Cue from Facebook), Chapter 1

Papers published via IEEE and AIAA conferences have presented an overview of how social media could benefit NASA working environments in general and proposed three specific social applications to benefit space flight control operations. One of them, Communications Dashboard, would help a real time flight controller keep up with both the "big picture" and significant details of operations via a cohesive interface similar to those of social networking services (SNS). Instead of recreational social features, "CommDash" would support functions like console logging, categorized and threaded text chat streams with enhanced accountability and graphics display features, high-level status displays driven by telemetry or other events, and an on-screen hailing function for requesting voice or text stream conversation. Moving certain voice conversations to text streams would reduce confusion and stress in two ways. Within text conversations, there would be far less repetition of content since text conversations have visual persistence and are reviewable instantly, e.g., there s no need to brief new participants to a discussion -- they just read what s already there. Remaining voice traffic would stand out more clearly, and quieter voice loops means fewer "say again" calls and less distraction from visual and mental tasks, thus less stress. (Most flight controllers monitor 4 or 5 voice loops at once.) Links could be created from console log entries to chat selections so that underlying details are readily available yet unobtrusive. This would reduce the confusion that rises from having multiple and sometimes divergent copies of the same information due to cut/copy and paste operations, attachments, and asynchronous editing. This concept could apply to a plethora of real time control environments and to other settings with lots of information juggling. This paper explores the dashboard concept in further detail and chronicles the first phase of a NASA IT Labs (Information Technology) project that could lead to a working system

Scott, David w.↗