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NASA NTRS2014

External Dependencies-Driven Architecture Discovery and Analysis of Implemented Systems

A method for architecture discovery and analysis of implemented systems (AIS) is disclosed. The premise of the method is that architecture decisions are inspired and influenced by the external entities that the software system makes use of. Examples of such external entities are COTS components, frameworks, and ultimately even the programming language itself and its libraries. Traces of these architecture decisions can thus be found in the implemented software and is manifested in the way software systems use such external entities. While this fact is often ignored in contemporary reverse engineering methods, the AIS method actively leverages and makes use of the dependencies to external entities as a starting point for the architecture discovery. The AIS method is demonstrated using the NASA's Space Network Access System (SNAS). The results show that, with abundant evidence, the method offers reusable and repeatable guidelines for discovering the architecture and locating potential risks (e.g. low testability, decreased performance) that are hidden deep in the implementation. The analysis is conducted by using external dependencies to identify, classify and review a minimal set of key source code files. Given the benefits of analyzing external dependencies as a way to discover architectures, it is argued that external dependencies deserve to be treated as first-class citizens during reverse engineering. The current structure of a knowledge base of external entities and analysis questions with strategies for getting answers is also discussed.

Ganesan, Dharmalingam↗

NASA NTRS2018

The Discovery of the Antarctic Ozone Hole

The author Nassim Taleb has coined the term ‘‘Black Swan’’ event to describe a very low probability event that come as a surprise and has a major effect in the field in which it occurs. He suggests that such events have occurred in history, finance, science, and technology more frequently than one can expect from stochastic theory. The discovery of the Antarctic Ozone Hole fits this description well. In this paper, we describe the events surrounding this discovery and the role of NASA satellite data before and soon after the seminal paper by Farman et al., in May 1985 that first brought this phenomenon to the attention of the broader science community.

Bhartia, Pawan Kumar↗

NASA NTRS2019

TESS Discoveries

TESS discoveries have already become fruitful targets for HST follow up, and this will undoubtedly continue through the JWST era. In addition to providing targets for atmospheric characterization, TESS' Level One Science Requirement is to measure masses for 50 transiting planets smaller than 4 Earth radii. A full suite of ground based facilities will be working together to optimize the TESS science yield. Somewhat surprisingly though, no study has quantified the accuracy of mass constraints required to yield robust atmospheric properties of small planets. Previous work showed that the mass of a transiting exoplanet could be inferred from its transmission spectrum alone. The method leverages the effect of the planet's surface gravity on the atmospheric scale height, which in turn influences the transmission spectrum. However, significant degeneracies exist between transmission spectra of planets with different masses and compositions, making difficult to unambiguously determine the planet's mass and composition in many cases. I will present the first quantitative answer to this pressing question. Our analysis places definitive limits on how accurate mass constraints need to be in order to unambiguously determine atmospheric composition for a diverse array of planets ranging from terrestrial-size (TRAPPIST-1-like) to mini-Neptunes and hot Jupiters. These results broadly impact the community of scientists working on exoplanets -- from the full breadth of ground based observers conducting TESS follow-up, to those studying planet populations, and finally to those planning atmospheric investigations. This is particularly timely as the STScI Director charged the HST-TESS Advisory committee to report to the Space Telescope Users Committee on how HST can best support follow-up observations of TESS exoplanet discoveries. The community needs to determine optimal strategies for maximizing the rapid scientific return from TESS targets.

Batalha, Natasha E.↗

NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗

NASA NTRS2018

How Do You Go From a Concept Idea to a NASA Selected Mission? Formulating the Psyche Discovery Mission with JPL's Concurrent Engineering Teams

JPL’s Office of Formulation provides continuity of support and access to domain subject matter experts, as Principal Investigators mature their mission concepts from “cocktail napkin” ideas to Preliminary Design Reviews [1]. Using NASA’s Psyche mission as a case study, we will describe JPL’s concurrent engineering ATeam and Team X support to the Psyche competed concept study team in the areas of 1) Science Feasibility, 2) Trade Space Exploration, 3) Spacecraft Point Design and Cost Estimate, 4) Science, Technical, Management, and Cost Review, and 5) Strategy and Communication Development. NASA’s Psyche Discovery class mission started as a grassroots idea in our A-Team facility, and in less than five years was selected as a mission under NASA’s Discovery Program. While Psyche had a dedicated concept development team [2], they utilized JPL’s concurrent engineering teams, methods, analysis tools, and experts throughout their mission concept lifecycle.

Ziemer, John↗

NASA NTRSDate not supplied

Designing the Design Process for Early Problem Discovery for a Complex Aeronautics Systems Challenge

The earliest stage in the innovation lifecycle, problem formulation, is crucial for setting direction in an innovation effort. When faced with an interesting problem, engineers commonly assume the approximate solution area and focus on ideating innovative solutions. However, in this project, NASA and their contracted partner, Accenture, collaboratively conducted problem discovery to ensure that solutioning efforts were focused on the right problems, for the right users, and addressing the most critical needs—in this case, exploring weather tolerant operations (WTO) to further urban air mobility (UAM) – known as UAM WTO. The project team leveraged generative, qualitative methods to understand the ecosystem, players, and where challenges in the industry are inhibiting development. The complexity of the problem area required that the team constantly observe and iterate on problem discovery, effectively “designing the design process.” This report discusses the approach, methodologies, and selected results, including insights on the application of early-stage design methodologies to a complex, system-level problem.

Problem formulation↗

NASA NTRS2020

Discovery of the Optical Afterglow and Host Galaxy of Short GRB 181123B at z = 1.754: Implications for Delay Time Distributions

We present the discovery of the optical afterglow and host galaxy of the Swift short-duration gamma-ray burst (SGRB) GRB 181123B. Observations with Gemini-North starting ≈9.1 hr after the burst reveal a faint optical afterglow with i ≈ 25.1 mag at an angular offset of 0 59 ± 0." 16 from its host galaxy. Using grizYJHK observations, we measure a photometric redshift of the host galaxy of z = 1.77+0.30-0.17. From a combination of Gemini and Keck spectroscopy of the host galaxy spanning 4500–18000 Å, we detect a single emission line at 13390 Å, inferred as Hβ at z = 1.754 ± 0.001 and corroborating the photometric redshift. The host galaxy properties of GRB 181123B are typical of those of other SGRB hosts, with an inferred stellar mass of ≈9.1 × 109Msun, a mass-weighted age of ≈0.9 Gyr, and an optical luminosity of ≈0.9L*. At z = 1.754, GRB 181123B is the most distant secure SGRB with an optical afterglow detection and one of only three at z > 1.5. Motivated by a growing number of high-z SGRBs, we explore the effects of a missing z > 1.5 SGRB population among the current Swift sample on delay time distribution (DTD) models. We find that lognormal models with mean delay times of ≈4–6 Gyr are consistent with the observed distribution but can be ruled out to 95% confidence, with an additional ≈one to five Swift SGRBs recovered at z > 1.5. In contrast, power-law models with ∝t−1 are consistent with the redshift distribution and can accommodate up to ≈30 SGRBs at these redshifts. Under this model, we predict that ≈1/3 of the current Swift population of SGRBs is at z > 1. The future discovery or recovery of existing high-z SGRBs will provide significant discriminating power on their DTDs and thus their formation channels.

K Paterson↗

NASA NTRS2021

An Information Theory Approach to Physical Domain Discovery

The project of physics discovery is often equivalent to finding the most concise description of a physical system. The description with optimum predictive capability for a dataset generated by a physical system is one that minimizes both predictive error on the dataset and the complexity of the description. The discovery of the governing physics of a system can therefore be viewed as a mathematical optimization problem. We outline here a method to optimize the description of arbitrarily complex physical systems by minimizing the entropy of the description of the system. The Recursive Domain Partitioning (RDP) procedure finds the optimum partitioning of each physical domain into subdomains, and the optimum predictive function within each subdomain. Penalty functions are introduced to limit the complexity of the predictive function within each domain. Examples are shown in 1D and 2D. In 1D, the technique effectively discovers the elastic and plastic regions within a stress-strain curve generated by simulations of amorphous carbon material, while in 2D the technique discovers the free-flow region and the inertially-obstructed flow region in the simulation of fluid flow across a plate.

Daniel Shea↗

NASA NTRS2021

Fast Discovery of an Extremely Radio-Faint Millisecond Pulsar from the Fermi-Lat Unassociated Source 3fgl J0318.1+0252

High sensitivity radio searches of unassociated γ-ray sources have proven to be an effective way of finding new pulsars. Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST) during its commissioning phase, we have carried out a number of targeted deep searches of Fermi Large Area Telescope (LAT) γ-ray sources. On February 27, 2018 we discovered an isolated millisecond pulsar (MSP), PSR J0318+0253, coincident with the unassociated γ-ray source 3FGL J0318.1+0252. PSR J0318+0253 has a spin period of 5.19 ms, a dispersion measure (DM) of 26 pc cm−3 corresponding to a DM distance of about 1.3 kpc, and a period-averaged flux density of (∼11±2) µJy at L-band (1.05–1.45 GHz). Among all high energy MSPs, PSR J0318+0253 is the faintest ever detected in radio bands, by a factor of at least ∼4 in terms of L-band fluxes. With the aid of the radio ephemeris, an analysis of 9.6 years of Fermi-LAT data revealed that PSR J0318+0253 also displays strong γ-ray pulsations. Follow-up observations carried out by both Arecibo and FAST suggest a likely spectral turn-over around 350 MHz. This is the first result from the collaboration between FAST and the Fermi-LAT teams as well as the first confirmed new MSP discovery by FAST, raising hopes for the detection of many more MSPs. Such discoveries will make a significant contribution to our understanding of the neutron star zoo while potentially contributing to the future detection of gravitational waves, via pulsar timing array (PTA) experiments.

Pei Wang↗

NASA NTRSDate not supplied

The Hubble Space Telescope: New Windows of Discovery

The Hubble Space Telescope has enabled incredible discoveries about our solar system, stars, galaxies, and the universe. It is also glimpsing the mysterious effects of dark matter, dark energy, and black holes. Thanks to a series of astronaut servicing missions and an incredible technical support team on the ground, Hubble is poised for many years of scientific discovery ahead. As we celebrate Hubble’s 32nd birthday, this presentation will showcase Hubble’s most recent incredible images and findings as well as innovative plans for future observations. Hubble is a key player in planned future scientific quests, to complement new solar system probes and major observatories on the ground and in space including the recently launched Webb Space Telescope.

Jennifer Wiseman↗

NASA NTRS2022

Discovery, Timing, and Multiwavelength Observations of the Black Widow Millisecond Pulsar PSR J1555–2908

We report the discovery of PSR J1555−2908, a 1.79 ms radio and gamma-ray pulsar in a 5.6 hr binary system with a minimum companion mass of 0.052 M⊙. This fast and energetic ((E =3 ×10(exp 35)) ̇ erg s(exp -1) millisecond pulsar was first detected as a gamma-ray point source in Fermi Large Area Telescope (LAT) sky survey observations. Guided by a steep-spectrum radio point source in the Fermi error region, we performed a search at 820 MHz with the Green Bank Telescope that first discovered the pulsations. The initial radio pulse timing observations provided enough information to seed a search for gamma-ray pulsations in the LAT data, from which we derive a timing solution valid for the full Fermi mission. In addition to the discovery and timing of radio and gamma-ray pulsations, we searched for X-ray pulsations using NICER but no significant pulsations were detected. We also obtained time-series r-band photometry that indicates strong heating of the companion star by the pulsar wind. Material blown off the heated companion eclipses the 820 MHz radio pulse during inferior conjunction of the companion for ≈10% of the orbit, which is twice the angle subtended by its Roche lobe in an edge-on system.

Millisecond pulsars↗

NASA NTRSDate not supplied

The Hubble Space Telescope: New Windows of Discovery (AAS 2022)

Jennifer Wiseman↗

NASA NTRSDate not supplied

The Science Discovery Engine: An Open Science Success Story

NASA is committed to building an inclusive open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI is made up of a number of activities including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to the wealth of NASA’s open science data and information. In this presentation, we will present our collaborative work to date to build the SDE and our vision for empowering open source science in the future.

Kaylin Bugbee↗

NASA NTRSDate not supplied

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Repositories of safety reports are often underutilized and only analyzed manually by trained experts, despite safety management systems requiring reports. These collections of documents contain a wealth of information from past projects and operations that could improve system safety and design. Advances in natural language processing techniques have improved information extraction and retrieval in consumer technology, biomedicine, and finance, for instance, but have not been applied to engineering documents on the same scale. To this end, the Manager for Intelligent Knowledge Access (MIKA) open-source toolkit has been developed for rapid knowledge discovery and information retrieval in safety engineering applications. The MIKA toolkit uses state-of-the-art natural language processing algorithms and allows a user to apply these methods to their own dataset. This paper describes the MIKA toolkit and its two primary capabilities, knowledge discovery and information retrieval, and demonstrates the toolkit via a case study on National Transportation Safety Board (NTSB) reports.

Machine Learning↗

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 NTRS2021

The Deep-Time Digital Earth program: data-driven discovery in geosciences

Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE’s mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth’s evolution.

Chengshan Wang↗

NASA NTRSDate not supplied

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Systems Engineering↗

NASA NTRS2022

The Psyche Planning Software Subsystem: Creating a Robust Toolset for a Discovery-class Mission

Psyche is a Discovery-class mission to the small metal-rich asteroid (16) Psyche, and is slated to launch in 2022. Psyche, like many missions, requires low-cost activity planning and sequence generation that serves as the backbone to overall uplink design. Such tools must be maintainable over long periods of operations, and powerful enough to solve complex issues that deep-space one-off missions encounter. In this paper we introduce cost-effective solutions that leverage inner- and open-source principles to meet a variety of common and novel use cases.The uplink process that was designed to meet these challenges is presented, as well as the data-flow through the high-level architecture of the planning software subsystem. The user-facing planning tools are described, particularly the Science Opportunity Analyzer, the Plan Editor, Psyche’s planning automation in the Blackbird framework, and Psyche Simulation Reports. All these applications are either new or have been substantially revamped to meet Psyche’s concept of operations. In particular, ensuring the entire toolchain can correctly process epoch-relative activities is discussed. Underlying the main applications are a common set of dependencies developed and maintained by a new cross-mission association of planning developers. In this way, Psyche can inherit well-tested functionality which saves effort and ensures its developers can focus on solving domain challenges. Quality control of the applications and libraries is ensured with a code-review and unit-test based novel ‘CM lite’ process. Collaboration with international industry and academia using the open-source modules is already occurring.The planning and scheduling software is designed to maximize operator awareness of the integrated plan at every step of the process and use common interfaces and file formats to easily transfer information. Design choices plus the team’s test-driven development process enables more expansive capabilities compared to the decentralized planning and sequence generation functions typical of Discovery-class orbiters without significant development cost increases. Benefits and drawbacks of Psyche’s approach are discussed, including comparison to other missions and tools where appropriate.

Ramanathan, Keshav↗