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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Maximizing Science in the Era of LSST: A Community-Based Study of Needed US Capabilities

The Large Synoptic Survey Telescope (LSST) will be a discovery machine for the astronomy and physics communities, revealing astrophysical phenomena from the Solar System to the outer reaches of the observable Universe. While many discoveries will be made using LSST data alone, taking full scientific advantage of LSST will require ground-based optical-infrared (OIR) supporting capabilities, e.g., observing time on telescopes, instrumentation, computing resources, and other infrastructure. This community-based study identifies, from a science-driven perspective, capabilities that are needed to maximize LSST science. Expanding on the initial steps taken in the 2015 OIR System Report, the study takes a detailed, quantitative look at the capabilities needed to accomplish six representative LSST-enabled science programs that connect closely with scientific priorities from the 2010 decadal surveys. The study prioritizes the resources needed to accomplish the science programs and highlights ways that existing, planned, and future resources could be positioned to accomplish the science goals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Engaging a Diverse Workforce in the Building Sciences Through the JUMP Into STEM Program: Impact Study; Preprint

Ensuring inclusivity in building science professions requires engaging people from underrepresented demographics; unfortunately, many races, ethnicities, and genders continue to be underrepresented. The JUMP into STEM program works to rectify this, encouraging creative ideation and highlighting the unique perspectives of a diverse array of students. The top students are awarded internships that provide opportunities to work in building science research with close supervision from mentors in the field. In the research presented here, we investigate the impact of participation in JUMP into STEM on students' careers, including the impact on students from diverse backgrounds. Furthermore, we research students' awareness of career opportunities in building science, students' perception of their ability to meaningfully contribute to this field, and the career building opportunities that JUMP into STEM provides for students. Through participant interviews and data analysis, we measure program diversity, inclusion, and effectiveness at achieving goals. We find that among the hundreds of students who have participated in this program, more than 25 different majors and/or educational degree programs are represented and more than 45% of students attend minority serving institutions or historically black colleges and universities. The JUMP into STEM experience had a significant effect on career choices or career development for more than 80% of participants. Our results also indicate that the JUMP into STEM program is effective at promoting diversity in the building sciences and is successfully contributing to the larger effort within the building science industry to promote and ensure equity in technological progress and innovation.

building energy science↗
DOE OSTI2023

Integrating Artificial Intelligence into Science Gateways

Science gateways are altering the manner in which people interact with high performance computing (HPC) by providing a web browser based interface to advanced computing platforms. In particular, science gateways lower the barrier to using HPC by simplifying the process of submitting workloads to such systems and by offloading the efforts required to use HPC to the maintainers of the system. While science gateways decrease the time-to-science that comes with using such advanced systems, progress can still be made in improving the user's experience. In this paper we explore two strategies for integrating artificial intelligence tools commonly found in non-HPC service workflows: voice activated assistants and chatbots. Since August 2021, the HPC group at Idaho National Laboratory answers an average of 581 support tickets per month of which a large percentage could be addressed via these two strategies. This work defines the key capabilities that an HPC voice activated assistant and chatbot would need to address for a userbase consisting of largely non-expert users as well as a design for integration into the Open OnDemand science gateway.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Science Breakthroughs 2030. Final report

Agriculture is a fundamental societal activity, characterized by many different landscapes, crops, markets, and participants. Food, agricultural, and biofuels products are central to the daily life of all citizens, though most do not recognize the fragility of the environment that brings forth this abundance. As is noted in the 2012 report from the President's Council of Advisors on Science and Technology, Agricultural Preparedness and the United States Agricultural Research Enterprise (PCAST, 2012) the food and agricultural system faces constant challenges in: Managing new pests, pathogens, and invasive plants. Increasing the efficiency of water use. Growing food in a changing climate. Reducing the environmental footprint of agriculture. Managing the production of bioenergy. Producing safe and nutritious food. Assisting with global food security and maintaining abundant yields. Science Breakthroughs 2030 was organized to identify the most compelling research directions in food and agriculture, in particular those empowered by the application of insights and tools from disciplines of science and engineering not typically associated with food and agricultural research. A committee appointed by the Chairman of the National Research Council explored ideas for research directions with input from the scientific community, with the objective of producing a report describing ambitious and achievable scientific pathways to address major problems and create new opportunities in food and agriculture. Following numerous meetings, a jamboree, and town hall, the appointed committee prepared a report that has subsequently become a reference for federal agencies supporting research in the food and agricultural space. It highlights five key areas for research investment with broad application across food and agriculture: integrated systems research; sensor development; data mining and information sciences, genomics; and the microbiome.

09 BIOMASS FUELS↗
DOE OSTI2015

The Globus Galaxies Platform. Delivering Science Gateways as a Service

We use public cloud computers to host sophisticated scientific data; software is then used to transform scientific practice by enabling broad access to capabilities previously available only to the few. The primary obstacle to more widespread use of public clouds to host scientific software (‘cloud-based science gateways’) has thus far been the considerable gap between the specialized needs of science applications and the capabilities provided by cloud infrastructures. We describe here a domain-independent, cloud-based science gateway platform, the Globus Galaxies platform, which overcomes this gap by providing a set of hosted services that directly address the needs of science gateway developers. The design and implementation of this platform leverages our several years of experience with Globus Genomics, a cloud-based science gateway that has served more than 200 genomics researchers across 30 institutions. Building on that foundation, we have also implemented a platform that leverages the popular Galaxy system for application hosting and workflow execution; Globus services for data transfer, user and group management, and authentication; and a cost-aware elastic provisioning model specialized for public cloud resources. We describe here the capabilities and architecture of this platform, present six scientific domains in which we have successfully applied it, report on user experiences, and analyze the economics of our deployments. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles

The sciences struggle with poor integration across disciplines, the absence of coordination within and across data generation and modeling activities, scarce or disconnected open data, and weaknesses of networks to engage diverse stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This article summarizes the ICON principles; discusses the crowdsourced approach to creating the collection; and explores insights from across the articles. There were multiple common themes among the commentary articles, including the broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together around ICON principles as a unified approach for improving how science is done across the geosciences and beyond.

58 GEOSCIENCES↗
DOE OSTI2022

Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles

Abstract The sciences struggle to integrate across disciplines, coordinate across data generation and modeling activities, produce connected open data, and build strong networks to engage stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross‐system transferability of science outcomes. This article (a) summarizes the ICON principles; (b) discusses the crowdsourced approach to creating the collection; (c) explores insights from across the articles; and (d) proposes steps forward. There were common themes among the commentary articles, including broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together to offer insights into ICON principles as a unified approach for improving how science is done across the geosciences and beyond.

Goldman, A. E.↗
DOE OSTI2022

The case for data science in experimental chemistry: examples and recommendations

The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities involves considerable challenges. In this Expert Recommendation, we focus on experimental co-design and its importance to experimental chemistry. We provide examples of how data science is changing the way we conduct experiments, and we outline opportunities for further integration of data science and experimental chemistry to advance these fields. Our recommendations include establishing stronger links between chemists and data scientists; developing chemistry-specific data science methods; integrating algorithms, software and hardware to ‘co-design’ chemistry experiments from inception; and combining diverse and disparate data sources into a data network for chemistry research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The NASA ISRO SAR (NISAR) Mission - Validation of Science Measurement Requirements

The NASA ISRO Synthetic Aperture Radar (NISAR) is scheduled for launch early in 2024 from the Satish Dhawan Space Centre (SDSC), at Sriharikota, near Chennai, India. This mission is the result of a collaboration between NASA and Indian Space Research Organization (ISRO), where NASA has contributed elements of the mission such as an L-band SAR, and ISRO has contributed other elements, such as an S-band SAR. After successful launch, the NISAR mission will collect left-looking L-band SAR data over most of the Earth’s land areas twice during every 12-day exact repeat orbit. (once while in an ascending orbit direction and once while in a descending orbit direction). NASA and ISRO have individual and joint requirements on the mission that include the performance of the imaging radars onboard the spacecraft. For example, NASA must demonstrate that this L-band SAR will achieve a set of identified science measurement accuracy requirements that span Ecosystem science, Solid Earth science, and Cryosphere science disciplines. Likewise, ISRO has several applications objectives on both the L-band and S-band data from NISAR that the ISRO science team and project will be developing and testing. Pre-launch and post-launch activities have been planned to validate that these requirements are met. Here, we will discuss how the NASA plans are being executed and will present any initial results at the conference.

Chapman, Bruce↗
DOE OSTI2022

Hands-On Computer Science: The Array of Things Experimental Urban Instrument

Chicago's Array of Things (AoT) project is aptly described as a technology experiment or a "smart city" prototype. The concept of such an extensible "instrument" arose within a larger translational research vision applying computer science and engineering research for the multidimensional benefit of people and communities in cities. The AoT project hypothesized that wireless intelligent sensor networks could enable both quantitative social science and urban monitoring while also stimulating youth interest in science and technology. Successful deployment of such sensor networks could provide open data from urban measurements not only in support of diverse research questions-in environmental dynamics, urban architecture, engineering, and social sciences-but also informing community groups and city planners. Further, the AoT project and its successor SAGE project are a computer science and engineering experiment, but its success is inextricably tied to community engagement and experiential education. Simply put, community acceptance is a prerequisite to installing and testing the instrument.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Taming the terminological tempest in invasion science

ABSTRACT Standardised terminology in science is important for clarity of interpretation and communication. In invasion science – a dynamic and rapidly evolving discipline – the proliferation of technical terminology has lacked a standardised framework for its development. The result is a convoluted and inconsistent usage of terminology, with various discrepancies in descriptions of damage and interventions. A standardised framework is therefore needed for a clear, universally applicable, and consistent terminology to promote more effective communication across researchers, stakeholders, and policymakers. Inconsistencies in terminology stem from the exponential increase in scientific publications on the patterns and processes of biological invasions authored by experts from various disciplines and countries since the 1990s, as well as publications by legislators and policymakers focusing on practical applications, regulations, and management of resources. Aligning and standardising terminology across stakeholders remains a challenge in invasion science. Here, we review and evaluate the multiple terms used in invasion science (e.g. ‘non‐native’, ‘alien’, ‘invasive’ or ‘invader’, ‘exotic’, ‘non‐indigenous’, ‘naturalised’, ‘pest’) to propose a more simplified and standardised terminology. The streamlined framework we propose and translate into 28 other languages is based on the terms ( i ) ‘non‐native’, denoting species transported beyond their natural biogeographic range, ( ii ) ‘established non‐native’, i.e. those non‐native species that have established self‐sustaining populations in their new location(s) in the wild, and ( iii ) ‘invasive non‐native’ – populations of established non‐native species that have recently spread or are spreading rapidly in their invaded range actively or passively with or without human mediation. We also highlight the importance of conceptualising ‘spread’ for classifying invasiveness and ‘impact’ for management. Finally, we propose a protocol for classifying populations based on ( i ) dispersal mechanism, ( ii ) species origin, ( iii ) population status, and ( iv ) impact. Collectively and without introducing new terminology, the framework that we present aims to facilitate effective communication and collaboration in invasion science and management of non‐native species.

Soto, Ismael↗
DOE OSTI2022

Preparing Precollege Students for the Second Quantum Revolution with Core Concepts in Quantum Information Science

After the passage of the U.S. National Quantum Initiative Act in December 2018, the National Science Foundation (NSF) and the Office of Science and Technology Policy (OSTP) recently assembled an interagency working group and conducted a workshop titled “Key Concepts for Future Quantum Information Science Learners” that focused on identifying core concepts for future curricular and educator activities to help precollege students engage with quantum information science (QIS). Helping precollege students learn these key concepts in QIS is an effective approach to introducing them to the second quantum revolution and inspiring them to become future contributors in the growing field of quantum information science and technology as leaders in areas related to quantum computing, communication, and sensing. This paper is a call to precollege educators to contemplate including QIS concepts into their existing courses at appropriate levels and get involved in the development of curricular materials suitable for their students. Also, research shows that compare-and-contrast activities can provide an effective approach to helping students learn. Therefore, we illustrate a pedagogical approach that contrasts the classical and quantum concepts so that educators can adapt them for their students in their lesson plans to help them learn the differences between key concepts in quantum and classical contexts.

Education & Educational Research↗
DOE OSTI2020

Mathematics: The Tao of Data Science

The two pieces, "Ten Research Challenge Areas in Data Science" by Jeannette M. Wing and “Challenges and Opportunities in Statistics and Data Science: Ten Research Areas” by Xuming He and Xihong Lin, provide an impressively complete list of data science challenges from luminaries in the field of data science. They have done an extraordinary job, so this response offers a complementary viewpoint from a mathematical perspective and evangelizes advanced mathematics as a key tool for meeting the challenges they have laid out. Notably, we pick up the themes of scientific understanding of machine learning and deep learning, computational considerations such as cloud computing and scalability, balancing computational and statistical considerations, and inference with limited data. We propose that mathematics is an important key to establishing rigor in the field of data science and as such has an essential role to play in its future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A prospective on machine learning challenges, progress, and potential in polymer science

Abstract Artificial intelligence and machine learning (ML) continue to see increasing interest in science and engineering every year. Polymer science is no different, though implementation of data-driven algorithms in this subfield has unique challenges barring widespread application of these techniques to the study of polymer systems. In this Prospective, we discuss several critical challenges to implementation of ML in polymer science, including polymer structure and representation, high-throughput techniques and limitations, and limited data availability. Promising studies targeting resolution of these issues are explored, and contemporary research demonstrating the potential of ML in polymer science despite existing obstacles are discussed. Finally, we present an outlook for ML in polymer science moving forward. Graphical Abstract

Struble, Daniel C. (ORCID:0009000093410612)↗
DOE OSTI2017

White Paper on Nuclear Data Needs and Capabilities for Basic Science

Reliable nuclear structure and reaction data represent the fundamental building blocks of nuclear physics and astrophysics research, and are also of importance in many applications. There is a continuous demand for high-quality updates of the main nuclear physics databases via the prompt compilation and evaluation of the latest experimental and theoretical results. The nuclear physics research community benefits greatly from comprehensive, systematic and up-to-date reviews of the experimentally determined nuclear properties and observables, as well as from the ability to rapidly access these data in user-friendly forms. Such credible databases also act as a bridge between science, technology, and society by making the results of basic nuclear physics research available to a broad audience of users, and hence expand the societal utilization of nuclear science. Compilation and evaluation of nuclear data has deep roots in the history of nuclear science research, as outlined in Appendix 1. They have an enormous impact on many areas of science and applications, as illustrated in Figure 2 for the Evaluated Nuclear Structure Data File (ENSDF) database. The present workshop concentrated on the needs of the basic nuclear science community for data and capabilities. The main role of this community is to generate and use data in order to understand the basic nuclear forces and interactions that are responsible for the existence and the properties of all nuclides and, as a consequence, to gain knowledge about the origins, evolution and structure of the universe. Thus, the experiments designed to measure a wealth of nuclear properties towards these fundamental scientific goals are typically performed from within this community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Deep Underground Science and Engineering Laboratory - Preliminary Design Report

The DUSEL Project has produced the Preliminary Design of the Deep Underground Science and Engineering Laboratory (DUSEL) at the rehabilitated former Homestake mine in South Dakota. The Facility design calls for, on the surface, two new buildings - one a visitor and education center, the other an experiment assembly hall - and multiple repurposed existing buildings. To support underground research activities, the design includes two laboratory modules and additional spaces at a level 4,850 feet underground for physics, biology, engineering, and Earth science experiments. On the same level, the design includes a Department of Energy-shepherded Large Cavity supporting the Long Baseline Neutrino Experiment. At the 7,400-feet level, the design incorporates one laboratory module and additional spaces for physics and Earth science efforts. With input from some 25 science and engineering collaborations, the Project has designed critical experimental space and infrastructure needs, including space for a suite of multidisciplinary experiments in a laboratory whose projected life span is at least 30 years. From these experiments, a critical suite of experiments is outlined, whose construction will be funded along with the facility. The Facility design permits expansion and evolution, as may be driven by future science requirements, and enables participation by other agencies. The design leverages South Dakota's substantial investment in facility infrastructure, risk retirement, and operation of its Sanford Laboratory at Homestake. The Project is planning education and outreach programs, and has initiated efforts to establish regional partnerships with underserved populations - regional American Indian and rural populations.

42 ENGINEERING↗
DOE OSTI2014

Computer Science Research Institute (CSRI) Summer Proceedings 2013

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on computer science, computational science, and mathematics problems that are critical to the mission of the laboratories, the Department of Energy, and the United States. The CSRI provides a mechanism by which university researchers learn about and impact national— and global—scale problems while simultaneously bringing new ideas from the academic research community to bear on these important problems. A key component of CSRI programs over the last decade has been an active and productive summer program where students from around the country conduct internships at CSRI. Each student is paired with a Sandia staff member who serves as technical advisor and mentor. The goals of the summer program are to expose the students to research in mathematical and computer sciences at Sandia and to conduct a meaningful and impactful summer research project with their Sandia mentor. Every effort is made to align summer projects with the student's research objectives and all work is coordinated with the ongoing research activities of the Sandia mentor in alignment with Sandia technical thrusts. For the 2013 CSRI Proceedings, research articles have been organized into the following broad technical focus areas — Computational Mathematics and Algorithms, Combinatorial Algorithms and Visualization, Advanced Architectures and Systems Software, Computational Applications — which are well aligned with Sandia's strategic thrusts in computer and information sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Conference Grant Report Submitted to the Office of Fusion Energy Science by the University of California, San Diego

The High Energy Density Science Association (HEDSA) in collaboration with the University of California San Diego (UCSD), hosted the High Energy-Density Science Summer School from July 30 – August 11, 2017 on the UC San Diego campus. The goal of the Summer School series is to introduce new talent to the breadth of the U.S. High Energy Density Science (HEDS) community through lectures, engaging workshops, and discussion sessions with leaders in academia and the national laboratories. The objectives are to inspire young scientists to pursue graduate and professional careers in the fields of high energy density science, teach them fundamental HED science and critical skills, and grant them the opportunity to network with leading academic and national laboratory researchers. Our focus was to attract promising early-career students from across the country.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗