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NASA Earth Science Data Systems: Open Data, Services and Software

Open, Public, Electronic and Necessary (OPEN) Government Data Act, which requires all non-sensitive government data to be made available in open and machine-readable formats by default is part of the overall Foundations for Evidence-Based Policymaking (FEBP) Act passed in late 2018. This town hall will bring together data officers and policy makers from NOAA, EPA, NASA and others to discuss the impact of the act on data management strategies going forward. In 1994 NASA's Earth Science Division committed to an open data policy for all civilian Earth satellite data. NASA's Earth Observing System Data and Information System (EOSDIS) became the first large scale data system to facilitate public access to global Earth system data and information. This presentation reviews key elements of EOSDIS data policy and data management activities that support the OPEN Government Data Act.

Moses, John F.↗

Re-Organizing Earth Observation Data Storage to Support Temporal Analysis of Big Data

The Earth Observing System Data and Information System archives many datasets that are critical to understanding long-term variations in Earth science properties. Thus, some of these are large, multi-decadal datasets. Yet the challenge in long time series analysis comes less from the sheer volume than the data organization, which is typically one (or a small number of) time steps per file. The overhead of opening and inventorying complex, API-driven data formats such as Hierarchical Data Format introduces a small latency at each time step, which nonetheless adds up for datasets with O(10^6) single-timestep files. Several approaches to reorganizing the data can mitigate this overhead by an order of magnitude: pre-aggregating data along the time axis (time-chunking); storing the data in a highly distributed file system; or storing data in distributed columnar databases. Storing a second copy of the data incurs extra costs, so some selection criteria must be employed, which would be driven by expected or actual usage by the end user community, balanced against the extra cost.

data storage↗

Availability of previously lost data and metadata from the Apollo Lunar Surface Experiments Package (ALSEP)

Fourteen types of geophysical instruments deployed at the Apollo 12, 14, 15, 16, and 17 sites by the astronauts for long-term observation were collectively called the Apollo Lunar Surface Experiments Package (ALSEP). These instruments were active from the times of their deployment (November 1969–December 1972) to September 1977. At the conclusion of the experiments, the raw instrument data received from the Moon prior to March 1976 were left unarchived. Portions of the data processed by the principal investigators (PIs) of these experiments had been archived at the NASA Space Science Data Coordinated Archive (NSSDCA) in various formats. The unarchived data, residing then on open-reel magnetic tapes, became lost in the decades since, along with much of the metadata (the supporting documents for these data). We have recently recovered 440 of the previously lost tapes, containing raw ALSEP instrument data from April through June of 1975. Here we describe the data extracted from these tapes and summarize the data products generated for archiving at the NASA Planetary Data System (PDS) and NSSDCA, along with their historical narrative. In addition, we have reformatted many of the datasets delivered to NSSDCA by the PIs in the 1970s for archiving at the PDS. Finally, we have compiled an online searchable repository of ALSEP-related documents by optically scanning tens of thousands of pages of them kept at the Lunar and Planetary Institute in Texas.

S. Nagihara↗

IMAGE Software Suite

The IMAGE Mission is generating a truely unique set of magnetospheric measurement through a first-of-its-kind complement of remote, global observations. These data are being distributed in the Universal Data Format (UDF), which consists of data, calibration, and documentation. This is an open dataset, available to all by request to the National Space Science Data Center (NSSDC) at NASA Goddard Space Flight Center. Browse data, which consists of summary observations, is also available through the NSSDC in the Common Data Format (CDF) and graphic representations of the browse data. Access to the browse data can be achieved through the NSSDC CDAWeb services or by use of NSSDC provided software tools. This presentation documents the software tools, being provided by the IMAGE team, for use in viewing and analyzing the UDF telemetry data. Like the IMAGE data, these tools are openly available. What these tools can do, how they can be obtained, and how they are expected to evolve will be discussed.

Gallagher, Dennis L.↗

Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.

GI↗

Low Latency DESDynI Data Products for Disaster Response, Resource Management and Other Applications

We are developing onboard processor technology targeted at the L-band SAR instrument onboard the planned DESDynI mission to enable formation of SAR images onboard opening possibilities for near-real-time data products to augment full data streams. Several image processing and/or interpretation techniques are being explored as possible direct-broadcast products for use by agencies in need of low-latency data, responsible for disaster mitigation and assessment, resource management, agricultural development, shipping, etc. Data collected through UAVSAR (L-band) serves as surrogate to the future DESDynI instrument. We have explored surface water extent as a tool for flooding response, and disturbance images on polarimetric backscatter of repeat pass imagery potentially useful for structural collapse (earthquake), mud/land/debris-slides etc. We have also explored building vegetation and snow/ice classifiers, via support vector machines utilizing quad-pol backscatter, cross-pol phase, and a number of derivatives (radar vegetation index, dielectric estimates, etc.). We share our qualitative and quantitative results thus far.

applications↗

Automation Hooks Architecture Trade Study for Flexible Test Orchestration

We describe the conclusions of a technology and communities survey supported by concurrent and follow-on proof-of-concept prototyping to evaluate feasibility of defining a durable, versatile, reliable, visible software interface to support strategic modularization of test software development. The objective is that test sets and support software with diverse origins, ages, and abilities can be reliably integrated into test configurations that assemble and tear down and reassemble with scalable complexity in order to conduct both parametric tests and monitored trial runs. The resulting approach is based on integration of three recognized technologies that are currently gaining acceptance within the test industry and when combined provide a simple, open and scalable test orchestration architecture that addresses the objectives of the Automation Hooks task. The technologies are automated discovery using multicast DNS Zero Configuration Networking (zeroconf), commanding and data retrieval using resource-oriented Restful Web Services, and XML data transfer formats based on Automatic Test Markup Language (ATML). This open-source standards-based approach provides direct integration with existing commercial off-the-shelf (COTS) analysis software tools.

Lansdowne, Chatwin A.↗

System and Method for Providing a Climate Data Persistence Service

A system, method and computer-readable storage devices for providing a climate data persistence service. A system configured to provide the service can include a climate data server that performs data and metadata storage and management functions for climate data objects, a compute-storage platform that provides the resources needed to support a climate data server, provisioning software that allows climate data server instances to be deployed as virtual climate data servers in a cloud computing environment, and a service interface, wherein persistence service capabilities are invoked by software applications running on a client device. The climate data objects can be in various formats, such as International Organization for Standards (ISO) Open Archival Information System (OAIS) Reference Model Submission Information Packages, Archive Information Packages, and Dissemination Information Packages. The climate data server can enable scalable, federated storage, management, discovery, and access, and can be tailored for particular use cases.

Schnase, John L.↗

NASA Open Science Data Repository: Maximizing Spaceflight Bioscience Data

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for data re-analysis and re-use via Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). To address the challenges posed by gaining new knowledge from a vast and diverse amount of biological, health and environmental data in space, the NASA Open Science Data Repository (OSDR - osdr.nasa.gov/bio) plays a crucial role in curating and openly publishing biological data from space-related experiments. Its design incorporates successes and lessons from NASA GeneLab, encompassing not only high-throughput sequencing data but also physiological, phenotypic, and telemetry data. The OSDR makes space biological data FAIR (findable, accessible, interoperable, reusable), and facilitates effective data ingestion, dissemination, and Open Science collaborations. The OSDR also has the capability to integrate human astronaut data with state-of-the-art security and accessibility procedures. We will discuss here several strategies that NASA’s Biological and Physical Science Division have put in place to maximize the return on investment for spaceflight bioscience data.

space biology↗

Functionality of the Python Packages for the HERMES Mission

The Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) is a set of four instruments that will fly on the Lunar Gateway, an orbital outpost which will support Artemis lunar operations. HERMES will focus on understanding the causes of space-weather variability as driven by the Sun and modulated by the magnetosphere. In this talk, we will discuss the open source approach of the HERMES Science Operation Center (SOC) team being implemented in a number of Python packages which all work together. We will describe the core package which contains Python interfaces for the loading, calibrating, plotting, validating, and saving of measurement data through Common Data Format (CDF) files making use of pycdf provided by spacepy. Each instrument also has a Python package developed using a package template and will provide specific calibration and processing functionality to each instrument. The packages make extensive use of the scientific Python ecosystem and maintain compatibility with PyHC standards. The abstraction of intricate, high heritage data formats, such as CDF files, in Python enables easier analysis and opens doors for greater participation in heliophysics science.

hermes↗

A FORTRAN program for the analysis of linear continuous and sample-data systems

A FORTRAN digital computer program which performs the general analysis of linearized control systems is described. State variable techniques are used to analyze continuous, discrete, and sampled data systems. Analysis options include the calculation of system eigenvalues, transfer functions, root loci, root contours, frequency responses, power spectra, and transient responses for open- and closed-loop systems. A flexible data input format allows the user to define systems in a variety of representations. Data may be entered by inputing explicit data matrices or matrices constructed in user written subroutines, by specifying transfer function block diagrams, or by using a combination of these methods.

Edwards, J. W.↗

Digital Twin Technology for Aviation

As technology progresses, so have the tools for data visualization. This project presents a digital twin model of the San Francisco airport displaying a 10-minute window of historical flight data, visualizing the trajectory data of airplanes and vehicles in three dimensions. Multiple different cameras where implemented to fully utilize the 3D visualization. This is a 100:1 feet scale model created in Autodesk Maya, using the airport center as the origin and recalculating all coordinates accordingly featuring the airport, some surrounding buildings, and the bay. For this project, six different models of airplanes were modeled at a 50:1 feet scale with texturing to mimic real-world aircraft models along with certain airlines. The animation is driven through archived data captured from NASA’s Sherlock Open-Data Portal, cleaned of noisy data points, processed into useable data formats, and implemented into a Maya ASCII file of animation paths with the corresponding previously-stated airplane models attached all using Java based conversion program.

Aleksander Schade↗

Common Web Mapping and Mobile Device Framework for Display of NASA Real-time Data

Scientists have strategic goals to deliver their unique datasets and research to both collaborative partners and more broadly to the public. These datasets can have a significant impact locally and globally as has been shown by the success of the NASA Short‐term Prediction Research and Transition (SPoRT) Center and SERVIR programs at Marshall Space Flight Center. Each of these respective organizations provides near real‐time data at the best resolution possible to address concerns of the operational weather forecasting community (SPoRT) and to support environmental monitoring and disaster assessment (SERVIR). However, one of the biggest struggles to delivering the data to these and other Earth science community partners is formatting the product to fit into an end user's Decision Support System (DSS). The problem of delivering the data to the end‐user's DSS can be a significant impediment to transitioning research to operational environments especially for disaster response where the deliver time is critical. The decision makers, in addition to the DSS, need seamless access to these same datasets from a web browser or a mobile phone for support when they are away from their DSS or for personnel out in the field. A framework has been developed for MSFC Earth Science program that can be used to easily enable seamless delivery of scientific data to end users in multiple formats. The first format is an open geospatial format, Web Mapping Service (WMS), which is easily integrated into most DSSs. The second format is a web browser display, which can be embedded within any MSFC Science web page with just a few lines of web page coding. The third format is accessible in the form of iOS and Android native mobile applications that could be downloaded from an "app store". The framework developed has reduced the level of effort needed to bring new and existing NASA datasets to each of these end user platforms and help extend the reach of science data.

Burks, Jason E.↗

Common Web Mapping and Mobile Device Framework for Display of NASA Real-time Data

Scientists have strategic goals to deliver their unique datasets and research to both collaborative partners and more broadly to the public. These datasets can have a significant impact locally and globally as has been shown by the success of the NASA Short‐term Prediction Research and Transition (SPoRT) Center and SERVIR programs at Marshall Space Flight Center. Each of these respective organizations provides near real‐time data at the best resolution possible to address concerns of the operational weather forecasting community (SPoRT) and to support environmental monitoring and disaster assessment (SERVIR). However, one of the biggest struggles to delivering the data to these and other Earth science community partners is formatting the product to fit into an end user's Decision Support System (DSS). The problem of delivering the data to the end‐user's DSS can be a significant impediment to transitioning research to operational environments especially for disaster response where the deliver time is critical. The decision makers, in addition to the DSS, need seamless access to these same datasets from a web browser or a mobile phone for support when they are away from their DSS or for personnel out in the field. A framework has been developed for MSFC Earth Science program that can be used to easily enable seamless delivery of scientific data to end users in multiple formats. The first format is an open geospatial format, Web Mapping Service (WMS), which is easily integrated into most DSSs. The second format is a web browser display, which can be embedded within any MSFC Science web page with just a few lines of web page coding. The third format is accessible in the form of iOS and Android native mobile applications that could be downloaded from an "app store". The framework developed has reduced the level of effort needed to bring new and existing NASA datasets to each of these end user platforms and help extend the reach of science data.

Burks, Jason↗

GES DISC Greenhouse Gas Data Sets and Associated Services

NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes rich collections of data on atmospheric greenhouse gases from multiple missions. Hosted data include those from the Atmospheric Infrared Sounder (AIRS) mission (which has observed CO2, CH4, ozone, and water vapor since 2002); legacy water vapor and ozone retrievals from TIROS Operational Vertical Sounder (TOVS); and Upper Atmosphere Research Satellite (UARS) going back to the early 1980s. GES DISC also archives and supports data from seven projects of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) program that have ozone and water vapor records. Greenhouse gases data from the A-Train satellite constellation is also available: (1) Aura-Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) ozone, nitrous oxide, and water vapor since 2004; (2) Greenhouse Gases Observing Satellite (GOSAT) CO2 observations since 2009 from the Atmospheric CO2 Observations from Space (ACOS) task; and (3) Orbiting Carbon Observatory-2 (OCO-2) CO2 data since 2014. The most recent related data set that the GES DISC archives is methane flux for North America, as part of NASAs Carbon Monitoring System (CMS) project. This dataset contains estimates of methane emission in North America based on an inversion of the GEOS-Chem chemical transport model constrained by GOSAT observations (Turner et al., 2015). Along with data stewardship, an important focus area of the GES DISC is to enhance the usability of its data and broaden its user base. Users have unrestricted access to a new user-friendly search interface, which includes many services such as variable subsetting, format conversion, quality screening, and quick browse. The majority of the GES DISC data sets are also accessible through Open-source Project for a Network Data Access Protocol (OPeNDAP) and Web Coverage Service (WCS). The latter two services provide more options for specialized subsetting, format conversion, and image viewing. Additional data exploration, data preview, and preliminary analysis capabilities are available via NASA Giovanni, which obviates the need forusers to download the data (Acker and Leptoukh, 2007). Giovanni provides a bridge between the data and science and has been very successful in extending GES DISC data to educational users and to users with limited resources.

data ordering↗

Provenance in Data Interoperability for Multi-Sensor Intercomparison

As our inventory of Earth science data sets grows, the ability to compare, merge and fuse multiple datasets grows in importance. This requires a deeper data interoperability than we have now. Efforts such as Open Geospatial Consortium and OPeNDAP (Open-source Project for a Network Data Access Protocol) have broken down format barriers to interoperability; the next challenge is the semantic aspects of the data. Consider the issues when satellite data are merged, cross-calibrated, validated, inter-compared and fused. We must match up data sets that are related, yet different in significant ways: the phenomenon being measured, measurement technique, location in space-time or quality of the measurements. If subtle distinctions between similar measurements are not clear to the user, results can be meaningless or lead to an incorrect interpretation of the data. Most of these distinctions trace to how the data came to be: sensors, processing and quality assessment. For example, monthly averages of satellite-based aerosol measurements often show significant discrepancies, which might be due to differences in spatio- temporal aggregation, sampling issues, sensor biases, algorithm differences or calibration issues. Provenance information must be captured in a semantic framework that allows data inter-use tools to incorporate it and aid in the intervention of comparison or merged products. Semantic web technology allows us to encode our knowledge of measurement characteristics, phenomena measured, space-time representation, and data quality attributes in a well-structured, machine-readable ontology and rulesets. An analysis tool can use this knowledge to show users the provenance-related distrintions between two variables, advising on options for further data processing and analysis. An additional problem for workflows distributed across heterogeneous systems is retrieval and transport of provenance. Provenance may be either embedded within the data payload, or transmitted from server to client in an out-of-band mechanism. The out of band mechanism is more flexible in the richness of provenance information that can be accomodated, but it relies on a persistent framework and can be difficult for legacy clients to use. We are prototyping the embedded model, incorporating provenance within metadata objects in the data payload. Thus, it always remains with the data. The downside is a limit to the size of provenance metadata that we can include, an issue that will eventually need resolution to encompass the richness of provenance information required for daata intercomparison and merging.

Lynnes, Chris↗

Common Data Format (CDF) and Coordinated Data Analysis Web (CDAWeb)

The Coordinated Data Analysis Web (CDAWeb) data browsing system provides plotting, listing and open access v ia FTP, HTTP, and web services (REST, SOAP, OPeNDAP) for data from mo st NASA Heliophysics missions and is heavily used by the community. C ombining data from many instruments and missions enables broad resear ch analysis and correlation and coordination with other experiments a nd missions. Crucial to its effectiveness is the use of a standard se lf-describing data format, in this case, the Common Data Format (CDF) , also developed at the Space Physics Data facility , and the use of metadata standa rds (easily edited with SKTeditor ). CDAweb is based on a set of IDL routines, CDAWlib . . The CDF project also maintains soft ware and services for translating between many standard formats (CDF. netCDF, HDF, FITS, XML) <! .

Candey, Robert M.↗

IECM calibration and data reduction requirements

The induced environment contamination monitor (IECM) tape recorder format, as it relates to the ouput of meaningful data from the IECM instrument, is explained. Eight-bit words (or bytes) generate numbers that represent voltage levels of electronic detection probes for each experiment. This information is amalgamated by the IECM Data Acquisition and Control System (DACS). In some cases bits represent certain status situations concerning an experiment, such as whether a valve is opened or closed. Voltages are transformed into meaningful physical phenomena through equations of calibration. Data formats and plots are generated as requested for each IECM experimenter.

Wills, F. D.↗