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NASA is currently implementing capabilities to enable open science access. The Science Discovery Engine (SDE) is a major endeavor in this effort. The SDE supports discovery and access to complex, heterogeneous science data and information across science topical areas.
Effective management of energy resources is critical for the U.S. economy, the environment, and, more broadly, for sustainable development and alleviating poverty worldwide. The scope of energy management is broad, ranging from energy production and end use to emissions monitoring and mitigation and long-term planning. Given the extensive NASA Earth science research on energy and related weather and climate-related parameters, and rapidly advancing energy technologies and applications, there is great potential for increased application of NASA Earth science research to selected energy management issues and decision support tools. The NASA Energy Management Program Element is already involved in a number of projects applying NASA Earth science research to energy management issues, with a focus on solar and wind renewable energy and developing interests in energy modeling, short-term load forecasting, energy efficient building design, and biomass production.
Constellations have proven to be an effective and efficient way to acquire earth science data. By flying together, sensors on all satellites in a constellation take measurements of the same air, water, or land mass at essentially the same time. The sensors form a single "virtual satellite". The key to making a constellation effective and efficient is keeping the operations as independent as possible in order to minimize the operational burden and costs. The Earth Science Constellation (ESC) has been successful on all counts and continues to welcome new missions to continue its 18+ year record of coincidental earth science observations. The ESC also serves as a model for future constellation designs. This paper describes the ESC and its evolution from its initial launches in 1999 through the present and how new missions might benefit from joining the ESC.
The following working objectives were adopted: (1) define the current state of knowledge concerning the role of multispectral imaging science in hydrology; (2) identify critical areas where gaps in our knowledge limit opportunities for significant improvements in our understanding of the hydrologic processes; (3) evaluate the potential of multispectral imaging sciences as tools to close these gaps in knowledge; and (4) develop guidelines for a series of remote-sensing-based experiments that would help close these gaps in knowledge and, thereby, provide man with the improved scientific base necessary for better utilization of the world's water resource. The resulting documentation is intended to provide guidance for multispectral imaging programs in the hydrologic sciences with special emphasis on the visible and infrared (IR) wavelengths.
The Space Station, projected for construction in the early 1990s, will be an orbiting, low-gravity, permanently manned facility providing unprecedented opportunities for scientific research. Facilities for Life Sciences research will include a pressurized research laboratory, attached payloads, and platforms which will allow investigators to perform experiments in the crucial areas of Space Medicine, Space Biology, Exobiology, Biospherics and Controlled Ecological Life Support System (CELSS). These studies are designed to determine the consequences of long-term exposure to space conditions, with particular emphasis on assuring the permanent presence of humans in space. The applied and basic research to be performed, using humans, animals, and plants, will increase our understanding of the effects of the space environment on basic life processes. Facilities being planned for remote observations from platforms and attached payloads of biologically important elements and compounds in space and on other planets (Exobiology) will permit exploration of the relationship between the evolution of life and the universe. Space-based, global scale observations of terrestrial biology (Biospherics) will provide data critical for understanding and ultimately managing changes in the Earth's ecosystem. The life sciences community is encouraged to participate in the research potential the Space Station facilities will make possible. This document provides the range and scope of typical life sciences experiments which could be performed within a pressurized laboratory module on Space Station.
The primary goals of this project were to: 1. Promote and enhance K-12 earth science education; and enhance the access to and exchange of information through the use of digital networks in K-12 institutions. We have achieved these two goals. Through the efforts of many individuals at the University of Nebraska-Lincoln (UNL), Nebraska Earth Science Education Network (NESEN) has become a viable and beneficial interdisciplinary outreach program for K-12 educators in Nebraska. Over the last three years, the NASA grant has provided personnel and equipment to maintain, expand and develop NESEN into a program that is recognized by its membership as a valuable source of information and expertise in earth systems science. Because NASA funding provided a framework upon which to build, other external sources of funding have become available to support NESEN programs.
The Materials Science Research Rack I (MSRR-1) of the Materials Science Research Facility (MSRF) is a modular facility designed to accommodate two Experiment Modules (EM) simultaneously on board the International Space Station (ISS). One of these EMs will be the NASA/ESA EM being, developed collaboratively by NASA and the European Space Agency. The other EM position will be occupied by various multi-user EMs that will be exchanged in-orbit to accommodate a variety of materials science investigations. This paper discusses the resources, services, and allocations available to the EMs and briefly describes performance capabilities of the EMs currently planned for flight.
Infusion of automation technologies into NASA s future missions will be essential not only to achieve substantial reduction in mission operations staff and costs, but also in order to both effectively handle an exponentially increasing volume of scientific data and to successfully meet dynamic, opportunistic scientific goals and objectives. Current spacecraft operations cannot respond to science driven events, such as intrinsically variable or short-lived phenomena in a timely manner. For such investigations, we must teach our platforms to dynamically understand, recognize, and react to the scientists goals. While much effort has gone into automating routine spacecraft operations to reduce human workload and hence costs, applying intelligent automation to the science side, i.e., science data acquisition, data analysis and reactions to that data analysis in a timely and still scientifically valid manner, has been relatively under-emphasized.
The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) provides a framework for the future of NASA s distributed Earth science data systems. The NPP SDS performs research and data product assessment while using a fully distributed architecture. The components of this architecture are organized around key environmental data disciplines: land, ocean, ozone, atmospheric sounding, and atmospheric composition. The SDS thus establishes a set of concepts and a working prototypes. This paper describes the framework used by the NPP Project as it enabled Measurement-Based Earth Science Data Systems for the assessment of NPP products.
This document reports the findings of the Mars Science and Telecommunications Orbiter (MSTO) Science Advocacy Group (SAG), which was convened by the Mars Exploration Program Analysis Group (MEPAG) and the Mars Exploration Office at JPL to identify and prioritize areas of Mars atmospheric and surface science objectives for Mars that can be accomplished from orbit on a MSTO like mission.
.For the first time at JPL, the Cassini mission to Saturn is using distributed science operations for developing their experiments. Remote scientists needed the ability to: a) Identify observation opportunities; b) Create accurate, detailed designs for their observations; c) Verify that their designs meet their objectives; d) Check their observations against project flight rules and constraints; e) Communicate their observations to other scientists. Many existing tools provide one or more of these functions, but Science Opportunity Analyzer (SOA) has been built to unify these tasks into a single application. Accurate: Utilizes JPL Navigation and Ancillary Information Facility (NAIF) SPICE* software tool kit - Provides high fidelity modeling. - Facilitates rapid adaptation to other flight projects. Portable: Available in Unix, Windows and Linux. Adaptable: Designed to be a multi-mission tool so it can be readily adapted to other flight projects. Implemented in Java, Java 3D and other innovative technologies. Conclusion: SOA is easy to use. It only requires 6 simple steps. SOA's ability to show the same accurate information in multiple ways (multiple visualization formats, data plots, listings and file output) is essential to meet the needs of a diverse, distributed science operations environment.
MSLICE (Mars Science Laboratory InterfaCE) is the tool used by scientists and engineers on the Mars Science Laboratory rover mission to visualize the data returned by the rover and collaboratively plan its activities. It enables users to efficiently and effectively search all mission data to find applicable products (e.g., images, targets, activity plans, sequences, etc.), view and plan the traverse of the rover in HiRISE (High Resolution Imaging Science Experiment) images, visualize data acquired by the rover, and develop, model, and validate the activities the rover will perform. MSLICE enables users to securely contribute to the mission s activity planning process from their home institutions using off-the-shelf laptop computers. This software has made use of several plug-ins (software components) developed for previous missions [e.g., Mars Exploration Rover (MER), Phoenix Mars Lander (PHX)] and other technology tasks. It has a simple, intuitive, and powerful search capability. For any given mission, there is a huge amount of data and associated metadata that is generated. To help users sort through this information, MSLICE s search interface is provided in a similar fashion as major Internet search engines. With regard to the HiRISE visualization of the rover s traverse, this view is a map of the mission that allows scientists to easily gauge where the rover has been and where it is likely to go. The map also provides the ability to correct or adjust the known position of the rover through the overlaying of images acquired from the rover on top of the HiRISE image. A user can then correct the rover s position by collocating the visible features in the overlays with the same features in the underlying HiRISE image. MSLICE users can also rapidly search all mission data for images that contain a point specified by the user in another image or panoramic mosaic. MSLICE allows the creation of targets, which provides a way for scientists to collaboratively name features on the surface of Mars. These targets can also be used to convey instrument-pointing information to the activity plan. The software allows users to develop a plan of what they would like the rover to accomplish for a given time period. When developing the plan, the user can input constraints between activities or groups of activities. MSLICE will enforce said constraints and ensure that all mission flight rules are satisfied.
The Physical Science Informatics (PSI) system is the next step in this an effort to make NASA sponsored flight data available to the scientific and engineering community, along with the general public. The experimental data, from six overall disciplines, Combustion Science, Fluid Physics, Complex Fluids, Fundamental Physics, and Materials Science, will present some unique challenges. Besides data in textual or numerical format, large portions of both the raw and analyzed data for many of these experiments are digital images and video, requiring large data storage requirements. In addition, the accessible data will include experiment design and engineering data (including applicable drawings), any analytical or numerical models, publications, reports, and patents, and any commercial products developed as a result of the research. This objective of paper includes the following: Present the preliminary layout (Figure 2) of MABE data within the PSI database. Obtain feedback on the layout. Present the procedure to obtain access to this database.
Constellations have proven to be an effective and efficient way to acquire earth science data. By flying together, sensors on all satellites in a constellation take measurements of the same air, water, or land mass at essentially the same time. The sensors form a single "virtual satellite". The key to making a constellation effective and efficient is keeping the operations as independent as possible in order to minimize the operational burden and costs. The Earth Science Constellation (ESC) has been successful on all counts and continues to welcome new missions to continue its 18+ year record of coincidental earth science observations. The ESC also serves as a model for future constellation designs. This paper describes the ESC and its evolution from its initial launches in 1999 through the present and how new missions might benefit from joining the ESC.
The AEGIS (Autonomous Exploration for Gathering Increased Science) intelligent targeting software system has been in use on the Mars Science Laboratory (MSL) mission since 2016. The system allows on-board autonomous selection of targets for the ChemCam remote geochemistry instrument based on analysis of images taken by the rover. This paper describes the deployment of AEGIS to MSL and the operational use of the system since rollout to science operations in May of 2016.
The Committee on Earth Observation Satellites (CEOS) strives to enhance international coordination and data exchange and to optimize societal benefit. CEOS contributes to NASA’s core mission and is critical to NASA’s Earth Science program and to the future of Earth observations community as a whole because it advances mission planning, interagency coordination and technical implementation. Within NASA, the CEOS Working Group on Information System and Services (WGISS) is a forum for the Earth Sciences Data Systems (ESDS) Program to collaborate with other international and domestic agencies in the development of Earth observation data systems and services. NASA leads the development and demonstration of multiple prototypes supporting CEOS and Group on Earth Observations (GEO) requirements. NASA’s participation in WGISS influences NASA’s Earth Observing System Data and Information System’s (EOSDIS) ability to make high-quality data products available to the broad science community both nationally and internationally. Combined with NASA’s free and open data policy, EOSDIS’s involvement in WGISS is essential to widespread use of research satellite measurements. This presentation focuses on an overview and recent status of NASA’s EOSDIS.
The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission 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 AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS 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 AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.
The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission 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 AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS 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 AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.