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NASA NTRS2015

Finding Atmospheric Composition (AC) Metadata

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

metadata search↗
NASA NTRSDate not supplied

Use of Spatial Metadata Simplification for TEMPO

The National Aeronautics and Space Administration's (NASA) Atmospheric Science Data Center (ASDC) at NASA Langley Research Center in Hampton, VA provides atmospheric science data products and services to the science community, including enhanced search and subsetting capabilities for numerous Earth Science datasets. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument. TEMPO is situated on a geostationary satellite positioned at a longitude near the center of the conterminous United States and focused on North America, making hourly swaths of its field of regard from east to west. Spatial metadata is an essential component for the discovery and distribution of Earth Science data. The simplified polygonal boundaries representing the archived data files ensure that any granule can be identified quickly and accurately by a geospatial query. Historically the Douglas-Peucker algorithm has been used for polygon simplification; however, due to the nature of the algorithm, a buffer must be added to the polygon before simplification to ensure pivotal points are not removed by the algorithm. This adds in additional error to the polygon simplification. ASDC’s goal is to test other methods of polyline simplification, such as Visvalingan-Whyatt and Opheim simplification alongside of Douglas-Peucker and different buffering methods, to produce less error during polygon simplification of TEMPO data swaths, and special spatial query geometries such as EPA non-attainment regions, and geopolitical boundaries.

Spatial Metadata↗
NASA NTRS2018

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Remote Sensing↗
NASA NTRS2020

Operability on the Europa Clipper Mission: Challenges and Opportunities

Flight and ground system operability has been a focus area on the Europa Clipper Project since early in its formulation phase. This has given the operations team the opportunity to influence the design, with a goal of increasing overall system operability. This paper presents example operability challenges, opportunities, and solutions arising from the pre-Critical Design Review (CDR) system design. The integrated wing assembly design directly couples a scientific instrument (the REASON sounding radar) to the spacecraft’s power source (solar array wing panels). Impacts to mission operations of this design include: increased slew durations; solar array pointing constraints during inner cruise, Europa flybys, and orbit trim maneuvers; and stray light intrusions into the stellar reference units’ keep out zones. The use of CCSDS File Delivery Protocol (CFDP) Class-2 for reliable downlink of the large volume of Europa Clipper science data is described, along with nominal and off-nominal use cases. The effort to improve post-launch spacecraft visibility by adding a third low-gain antenna to the spacecraft is detailed. The design of the bulk data store has necessitated the implementation of accountable data products (ADPs), accountability identifiers (AIDs), and metadata packets to provide end-to-end science data accountability. To streamline and automate the flight rules generation and checking process, a first order and temporal logic-based solution of expressing flight rules without ambiguity, and whose programmatic implementation can be automated, is proposed. The focus on operability has had a positive influence on Europa Clipper design decisions, although cost, schedule, budget, heritage, and other technical concerns have many times outweighed operability concerns. However, experience to date demonstrates that this approach to operability results in more thorough, balanced consideration of the effect of early design trades and decisions on the operations phase of a mission than seen in many previous missions, and provides operations development insight into prioritizing work to go.

Signorelli, Joel↗
NASA NTRS2021

Operability on the Europa Clipper Mission: Challenges and Opportunities

Flight and ground system operability has been a focus area on the Europa Clipper Project since early in its formulation phase. This has given the operations team the opportunity to influence the design, with a goal of increasing overall system operability. This paper presents example operability challenges, opportunities, and solutions arising from the Critical Design Review (CDR) system design. The integrated wing assembly design directly couples a scientific instrument (the REASON sounding radar) to the spacecraft’s power source (solar array wing panels). Impacts to mission operations of this design include: increased slew durations; solar array pointing constraints during inner cruise, Europa flybys, and orbit trim maneuvers; and stray light intrusions into the stellar reference units’ keep out zones. The use of CCSDS File Delivery Protocol (CFDP) Class-2 for reliable downlink of the large volume of Europa Clipper science data is described, along with nominal and off-nominal use cases. The effort to improve post-launch spacecraft visibility by adding a third low-gain antenna to the spacecraft is detailed. The design of the bulk data store has necessitated the implementation of accountable data products (ADPs), accountability identifiers (AIDs), and metadata packets to provide end-to-end science data accountability. To streamline and automate the flight rules generation and checking process, a first order and temporal logic-based solution of expressing flight rules without ambiguity, and whose programmatic implementation can be automated, is proposed. The focus on operability has had a positive influence on Europa Clipper design decisions, although cost, schedule, budget, heritage, and other technical concerns have many times outweighed operability concerns. However, experience to date demonstrates that this approach to operability results in more thorough, balanced consideration of the effect of early design trades and decisions on the operations phase of a mission than seen in many previous missions, and provides operations development insight into prioritizing work to go.

Kumar, Meghana↗
NASA NTRSDate not supplied

Complications of Metadata Curation for NASA Airborne and Field Campaigns, Platforms, and Instruments

The Airborne Data Management Group (ADMG) curates metadata that describe NASA's airborne and field campaigns, platforms and instruments. This activity is vital to building a useful inventory of sub-orbital Earth science data that improves data discovery and access. During the curation process, many metadata issues were identified that required improvement to campaign and data product metadata. In some cases, locating the needed metadata to add to the inventory was a simple process. For other cases, the information was hard to find. In addition, identifying accurate investigation instrument details to add to the inventory was especially complicated because of the variety of definitions used in the Earth science community for the same concepts. One example of this is the concept of instruments' spatial and temporal resolution. The spatial resolution is one of the more difficult elements to curate given the variations in meaning across various disciplines. Clarified definitions are needed to enable consistency of information across campaigns and instruments. In this presentation, we introduce results from a survey of scientists from various fields in which we asked for definitions of spatial and temporal resolution. Our survey results highlight the importance of creating more universally acceptable definitions for certain metadata elements. By curating sub-orbital field campaign and instrument metadata, ADMG is enabling more efficient discovery and access to NASA observations by allowing science data users to search for certain clearly defined criteria and metadata values.

Ashlyn Shirey↗
NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗
NASA NTRSDate not supplied

ICARTT File Format Enhancements: Supporting FAIRness and Data Discovery of Suborbital Campaign Data

Suborbital campaigns aim to accomplish a wide variety of goals and can include a variety of platforms, instruments, and parameters measured. In 2004, the ICARTT (International Consortium for Atmospheric Research on Transport and Transformation) standards were developed to fulfill data management needs for the ICARTT campaign. The ICARTT file format is text-based and composed of a header with important data description information and the data section. Built on the NASA Ames and GTE data formats, the ICARTT format was created to facilitate data exchange and promote collaborations among the science teams for achieving the ICARTT campaign goals. Due to its success and adaptation for use in many other field campaigns, the ICARTT file format became a NASA standard in 2010 and was amended in January 2017. These changes provided many enhancements, including the requirement for variable standard names. Primarily designed for airborne field studies, ICARTT has been further utilized for ground-based studies. NASA has made a commitment to build an inclusive open science community over the next decade. Open-source science strives to make publicly funded scientific research transparent, inclusive, accessible, and reproducible. The ICARTT format can host metadata that is critical for proper use of the data, particularly for in-situ measurements, and can enhance data discovery and accessibility. However, the required fields are often free text, meaning that the information is human readable, but not machine interpretable. Furthermore, the amount and type of information provided can vary significantly between principal investigators and campaigns. To support FAIR principles and interoperability, enhancements to the ICARTT standards are recommended. Possible recommendations include potential use of controlled and consistent vocabulary for variable standard name and certain common metadata elements; standardizing timestamps for easier data comparisons and analysis; and providing guidance on variable measurement units and how they are reported. Enhancing ICARTT metadata can further streamline the process to make suborbital data more readily available to the data user and improve variable-level metadata. Providing more variable-level metadata can enhance data searching and discovery, supporting NASA’s Open-Source Science Initiative (OSSI).

Megan Buzanowicz↗
NASA NTRS2015

NASA'S Earth Science Data Stewardship Activities

NASA has been collecting Earth observation data for over 50 years using instruments on board satellites, aircraft and ground-based systems. With the inception of the Earth Observing System (EOS) Program in 1990, NASA established the Earth Science Data and Information System (ESDIS) Project and initiated development of the Earth Observing System Data and Information System (EOSDIS). A set of Distributed Active Archive Centers (DAACs) was established at locations based on science discipline expertise. Today, EOSDIS consists of 12 DAACs and 12 Science Investigator-led Processing Systems (SIPS), processing data from the EOS missions, as well as the Suomi National Polar Orbiting Partnership mission, and other satellite and airborne missions. The DAACs archive and distribute the vast majority of data from NASA’s Earth science missions, with data holdings exceeding 12 petabytes The data held by EOSDIS are available to all users consistent with NASA’s free and open data policy, which has been in effect since 1990. The EOSDIS archives consist of raw instrument data counts (level 0 data), as well as higher level standard products (e.g., geophysical parameters, products mapped to standard spatio-temporal grids, results of Earth system models using multi-instrument observations, and long time series of Earth System Data Records resulting from multiple satellite observations of a given type of phenomenon). EOSDIS data stewardship responsibilities include ensuring that the data and information content are reliable, of high quality, easily accessible, and usable for as long as they are considered to be of value.

metadata↗
NASA NTRS2017

The Value of Data and Metadata Standardization for Interoperability in Giovanni Or: Why Your Product's Metadata Causes Us Headaches!

Giovanni is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization.

interoperability↗
NASA NTRS2016

Availability of Previously Unprocessed ALSEP Raw Instrument Data, Derivative Data, and Metadata Products

In year 2010, 440 original data archival tapes for the Apollo Lunar Science Experiment Package (ALSEP) experiments were found at the Washington National Records Center. These tapes hold raw instrument data received from the Moon for all the ALSEP instruments for the period of April through June 1975. We have recently completed extraction of binary files from these tapes, and we have delivered them to the NASA Space Science Data Cordinated Archive (NSSDCA). We are currently processing the raw data into higher order data products in file formats more readily usable by contemporary researchers. These data products will fill a number of gaps in the current ALSEP data collection at NSSDCA. In addition, we have estabilished a digital, searcheable archive of ALSEP document and metadata as part of the web portal of the Lunar and Planetary Institute. It currently holds approx. 700 documents totaling approx. 40,000 pages

ALSEP↗
NASA NTRSDate not supplied

New Ways of Facilitating Improved Data Discovery and Access for NASA's Suborbital Earth Science Observations

NASA conducts field research in various Earth Science disciplines utilizing airborne and other non-satellite platforms to acquire in situ and remotely sensed observations indicative of physical processes across a range of scales. Field efforts are key in the development and validation of instruments and satellite algorithm refinements. The heterogeneous data, with a range of file formats, scales, and acquisition methods, support research in several science areas. NASA’s archive process assigns data products to discipline-oriented Distributed Active Archive Centers (DAACs) for stewardship. Over time, individual DAACs have developed tools for data browsing and serving disparate user bases. As science becomes more interdisciplinary, researchers need to incorporate observations from multiple campaigns, and multiple DAACs, into their work. Motivated in part by this shifting paradigm of needs, the Catalog of Archived Suborbital Earth Science Investigations (CASEI) was created. CASEI provides a single starting point to browse, search, and discover airborne and field data. Contextual metadata are organized and inter-linked allowing intuitive, integrated exploration across all NASA DAACs. Campaign science objectives, platform and instrument configurations, geographical details, geophysical concepts, and more are tracked in CASEI’s database, facilitating multi-parameter search, browse, and discovery of relevant data products. Researchers are able to directly access associated data products, via DOI links, regardless of the DAAC where they reside. Significant events, key time periods of high science interest within the longer-duration campaign effort, are also indicated and allow for a more efficient identification of critical data subsets. This presentation describes CASEI’s development, intensive metadata curation process, and demonstrates the web interface experience. Initial content metrics and plans for continued maintenance will also be discussed.

metadata↗
NASA NTRSDate not supplied

Spaceflight Biospecimen Sharing in Support of Science Discovery and Exploration

For decades, NASA and international partners have flown non-human biological experiments in space to understand the effects of spaceflight and address potential biological hazards. Sending organisms into space is a costly endeavor which makes space-flown biological specimens a valuable resource. To enable maximum scientific return, samples not required by the Principal Investigators are harvested and collected mostly by NASA’s Space Biology Biospecimen Sharing Program. These specimens are collected according to well-established SOPs that maintain quality and integrity. The specimens are then preserved, archived, and made available to the international scientific community through NASA’s Institutional Scientific Collection (ISC) at Ames Research Center (ARC). The ISC-ARC biospecimens and descriptive metadata are findable and accessible for request through the Life Sciences Data Archive (LSDA). The NASA ISC-ARC currently stores over 32,000 specimens from Shuttle, International Space Station, and ground-based investigations (spaceflight analog experiments involving either hindlimb unloading, centrifugation, or partial weight-bearing study designs). Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. The specimens include tissues from many physiological systems including musculoskeletal, neurosensory, reproductive, respiratory, circulatory, and digestive. Tissues are stored at -80°C, -20°C, +4°C, or ambient and preserved in various fixatives. Descriptive metadata is available for all samples. Historically, these tissues have been used for a wide range of analyses, including histology, genomics, and transcriptomics. Plans are underway to expand the ISC-ARC beyond the mostly-rodent contents, to include a space-relevant microbial culture collection including bacteria, fungi, and yeast. This expansion of the ISC-ARC will now involve identifying and standardizing best practices for microbial curations. To ensure safe long-term storage of microbial isolates, a microbiology laboratory will be dedicated for identification, cell culture, and lyophilization. Awarding of tissue to public science investigators has resulted in 33 publications since 2011, with 48 requests being submitted since 2016. Of note, NASA GeneLab has been awarded ISC-ARC biospecimens in the past few years. GeneLab processes the biospecimens to generate various levels of ‘omics’ data, which are published on GeneLab’s open access online platform for bioinformatics analysis and visualization. This has helped a systems biology community grow around the processed-biospecimens’ datasets, resulting in many new publications and insights. Websites: https://www.nasa.gov/ames/research/space-biosciences/isc-bsp ; https://lsda.jsc.nasa.gov/Biospecimen

Ryan T. Scott↗
NASA NTRSDate not supplied

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗
NASA NTRS2008

Web Monitoring of EOS Front-End Ground Operations, Science Downlinks and Level 0 Processing

This paper addresses the efforts undertaken and the technology deployed to aggregate and distribute the metadata characterizing the real-time operations associated with NASA Earth Observing Systems (EOS) high-rate front-end systems and the science data collected at multiple ground stations and forwarded to the Goddard Space Flight Center for level 0 processing. Station operators, mission project management personnel, spacecraft flight operations personnel and data end-users for various EOS missions can retrieve the information at any time from any location having access to the internet. The users are distributed and the EOS systems are distributed but the centralized metadata accessed via an external web server provide an effective global and detailed view of the enterprise-wide events as they are happening. The data-driven architecture and the implementation of applied middleware technology, open source database, open source monitoring tools, and external web server converge nicely to fulfill the various needs of the enterprise. The timeliness and content of the information provided are key to making timely and correct decisions which reduce project risk and enhance overall customer satisfaction. The authors discuss security measures employed to limit access of data to authorized users only.

Cordier, Guy R.↗
NASA NTRSDate not supplied

ImageLabler: Labeling and Managing Image Data for Machine Learning in the Earth Sciences

While machine learning techniques for image classification have been around for a long time, storing and managing the vast number of images required as training data is still a problem for scientists. This is especially true for the field of Earth science, where only recently have experts begun using machine learning techniques for image-based phenomena classification. Image Labeler, a fast and scalable cloud-based tagging platform for Earth science images, seeks to improve upon existing methods of managing images and associated metadata, such as maintaining categorized folders of images on a local machine, a process that can be cumbersome and difficult to scale. The platform facilitates rapid development of image-based Earth science phenomena training datasets by allowing scientists to upload their existing imagery as well as extract new samples from open satellite imagery services made available through NASA’s Global Imagery Browse Service (GIBS). Image Labeler also supports GeoTIFF data, with capabilities such as displaying GeoTIFFs on an interactive map, drawing shapefiles over them, and tagging them with additional metadata. This allows scientists to perform spatiotemporal subsetting with geographic information and develop training data more quickly. Built using modern web technologies, Image Labeler includes additional capabilities such as team collaboration for large-scale image tagging projects. Users can download their data in a machine-learning-ready format, allowing scientists to spend time on experimentation rather than on the collection of training data. In this presentation, we demonstrate how Image Labeler seeks to become a one-stop image data management solution for machine learning applications in Earth science.

Ashish Acharya↗
NASA NTRS2006

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://qcrnd.nasa.qov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage. The directory also offers data holders a means to post and search their data through customized portals, i.e. online customized subset metadata directories. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1994. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as a coordinating node of the International Directory Network (IDN), has been active at the international, regional and national level for many years through its involvement with the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and partnerships (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP), sharing experience, knowledge related to metadata and/or data management and interoperability.

Meaux, Melanie↗
NASA NTRS2007

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://gcmd.nasa.gov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches, or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage, and data resolution for selected datasets. The directory also offers data holders a means to advertise and search their data through customized portals, which are subset views of the directory. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1988. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as the International Directory Network (IDN), has been providing its services and sharing its experience and knowledge of metadata at the international, national, regional, and local level for many years. Active partners include the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and organizations (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP).

Meaux, Melanie F.↗