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NASA invests in professional coaching as a way to accelerate the development of its staff. The speaker shares one foundational human development model in coaching - the Six Streams - and applies it to the challenges that new scientists face. The speaker also describes how a new scientist can develop greater capabilities in the Six Streams so that they can become a more effective scientist and feel more satisfaction with their work.
The traditional single institution User Facility model prevalent in the DOE complex funds Instrument Scientists (IS) full-time to collaborate with and guide users, disseminate results through publication, build a broad and competent user base, continuously improve instrumentation, enhance data collection methods, and improve data analysis methods. This model focuses the Instrument Scientist on ensuring that visiting researchers obtain the best and most comprehensive data. Instrument Scientists are also expected to establish personal research programs based on the use of the instrument(s) under their charge, which allows for further advances in instrumentation and science. This model ensures that the User Facility offers unique, world-leading instruments and data analysis to the user community, creates high demand among top researchers for the use of these capabilities, and as a result, positively impacts science and technology in the United States.
Abstract To co‐produce locally relevant climate knowledge, climate scientists are engaging in new collaborations—with stakeholders and with scholars in the humanities, arts, and social sciences. In our work as a Shakespeare scholar‐turned‐public‐humanist and a climate scientist, we have created a methodology that allows researchers and communities to co‐produce knowledge by co‐producing narratives. We combine principles from emerging climate “storylines” research with collaborative storytelling inspired by William Shakespeare's plays and theatrical practices. Shakespeare's plays spark collaborations and interpretations, in part, because of how Shakespeare leaves gaps in the narrative. These gaps allow others to enter as collaborators, creating a “cognitive ecology” that fosters knowledge and action among all engaged. Integrating these methods into climate storyline‐making offers a radical paradigm: it upends the scientist's role as the focal storyteller and expert, and fosters, instead, partnership, equity, and a co‐exploration of multiple uncertainties. It is time for researchers to cede control to a cognitive ecology of collaborative action. This article is categorized under: Trans‐Disciplinary Perspectives > Humanities and the Creative Arts
Early-career scientists, especially those just stepping into their first independent roles, represent the tenacity of our creed to continue exploring the microbial world through structured questioning, testing, and observation. While sometimes confused with the epithet “young scientist,” which may represent people with either considerable or limited experience, those in their early career are just starting to craft their professional reputation. This is a most exciting time; all of us can remember that first time we sat down at a desk or bench and realized that for all intents and purposes we were now responsible for our own fate. Let loose from the comparative shackles of graduate school and postdoctoral martyrdom, this period in our growth as professional scientists often presents so many opportunities that it can be bewildering.
This is a revised version of LA-UR-17-20752, Nuclear Targeting Terms for Engineers and Scientists, March 1, 2017. The discussion of compounding for damage and compounding for reliability was reworded for clarity. The Department of Defense has a methodology for targeting nuclear weapons, and a jargon that is used to communicate between the analysts, planners, aircrews, and missile crews. The typical engineer or scientist in the Department of Energy may not have been exposed to the nuclear weapons targeting terms and methods. This report provides an introduction to the terms and methodologies used for nuclear targeting. Its purpose is to prepare engineers and scientists to participate in wargames, exercises, and discussions with the Department of Defense. Terms such as Circular Error Probable, probability of hit and damage, damage expectancy, and the physical vulnerability system are discussed. Methods for compounding damage from multiple weapons applied to one target are presented.
Studies indicate that communications and information-related activities take up a substantial portion of an engineer's work week; therefore, effective communications and information-use skills are one of the key engineering competencies that early career-stage aerospace engineers and scientists must possess to be successful. Feedback from industry rates communications and information-use skills high in terms of their importance to engineering practice; however, this same feedback rates the communications and information-use skills of early career-stage engineers low. To gather adequate and generalizable data about the communications and information-related activities of entry-level aerospace engineers and scientists, we surveyed 264 members of the AIAA who have no more than 1-5 years of aerospace engineering work experience. To learn more about the concomitant communications norms, we compared the results of this study with data (1,673 responses) we collected from student members of the AIAA and with data (341 responses) we collected from a study of aerospace engineering professionals. In this paper, we report selected results from these studies that focused on the communications practices and information-related activities of early career-stage U.S. aerospace engineers and scientists in the workplace.
It is the Policy of NASA s Office of Space Science to emphasize and encourage the addition of Participating Scientist Programs (PSP s) to broaden the scientific impact of missions. A Participating Scientist Program for the STARDUST Mission: STARDUST is the fourth Discovery mission, and it is the first sample return mission selected within the Discovery Program. The STARDUST Spacecraft will fly through the coma of comet PIwildt-2 in early January 2004, and return the samples to the Earth in January 2006. The Principal Investigator of the STARDUST mission, Dr. Donald Brownlee, has generously requested the implementation of a PSP for STARDUST in order to provide more community participation in the initial characterization and analysis of the samples from PIwildt-2. In particular participating scientists will fill out the membership of the Preliminary Examination Team (PET) called for in the original 1994 STARDUST proposal accepted by NASA in 1995. The work of the PET will be organized around major subdiscipline areas such as mineralogy and petrology, isotopic abundances, and elemental composition. There will be leaders for each of these areas, and also a number of team members within each. Support will be commensurate with the level of participation.
Under this Indefinite Delivery Indefinite Quantity (IDIQ) contract, USRA was expected to provide short term (from I day up to I year) personnel as required to provide a Visiting Scientists Program to support the Earth Sciences Directorate (Code 900) at the Goddard Space Flight Center. The Contractor was to have a pool, or have access to a pool, of scientific talent, both domestic and international, at all levels (graduate student to senior scientist), that would support the technical requirements of the following laboratories and divisions within Code 900: 1) Global Change Data Center (902); 2) Laboratory for Atmospheres (Code 910); 3) Laboratory for Terrestrial Physics (Code 920); 4) Space Data and Computing Division (Code 930); 5) Laboratory for Hydrospheric Processes (Code 970). The research activities described below for each organization within Code 900 were intended to comprise the general scope of effort covered under the Visiting Scientist Program.
Planetary scientists represent an invaluable resource for information on and understanding of the solar system for all aspects of public communication.Yet most scientists have little time, funding, or connections to enable them to use that expertise. The OSS EPO Support Network, with its theme-based forums and regional brokers/facilitators, is already well equipped to assist scientists, non-intrusively, to establish partnerships with those who need their scientific expertise.
Due to the efforts by numerous ground-based surveys and NASA's Kepler and Transiting Exoplanet Survey Satellite (TESS), there will be hundreds, if not thousands, of transiting exoplanets ideal for atmospheric characterization via spectroscopy with large platforms such as James Webb Space Telescope and ARIEL. However their next predicted mid-transit time could become so increasingly uncertain over time that significant overhead would be required to ensure the detection of the entire transit. As a result, follow-up observations to characterize these exoplanetary atmospheres would require less-efficient use of an observatory's time—which is an issue for large platforms where minimizing observing overheads is a necessity. Here we demonstrate the power of citizen scientists operating smaller observatories (≤1 m) to keep ephemerides "fresh," defined here as when the 1σ uncertainty in the mid-transit time is less than half the transit duration. We advocate for the creation of a community-wide effort to perform ephemeris maintenance on transiting exoplanets by citizen scientists. Such observations can be conducted with even a 6 inch telescope, which has the potential to save up to ∼10,000 days for a 1000-planet survey. Based on a preliminary analysis of 14 transits from a single 6 inch MicroObservatory telescope, we empirically estimate the ability of small telescopes to benefit the community. Observations with a small-telescope network operated by citizen scientists are capable of resolving stellar blends to within 5''/pixel, can follow-up long period transits in short-baseline TESS fields, monitor epoch-to-epoch stellar variability at a precision 0.67% ± 0.12% for a 11.3 V-mag star, and search for new planets or constrain the masses of known planets with transit timing variations greater than two minutes.
Deep learning (DL), a new generation of artificial neural network research, has transformed industries, daily lives, and various scientific disciplines in recent years. DL represents significant progress in the ability of neural networks to automatically engineer problem-relevant features and capture highly complex data distributions. I argue that DL can help address several major new and old challenges facing research in water sciences such as interdisciplinarity, data discoverability, hydrologic scaling, equifinality, and needs for parameter regionalization. This review paper is intended to provide water resources scientists and hydrologists in particular with a simple technical overview, transdisciplinary progress update, and a source of inspiration about the relevance of DL to water. The review reveals that various physical and geoscientific disciplines have utilized DL to address data challenges, improve efficiency, and gain scientific insights. DL is especially suited for information extraction from image-like data and sequential data. Techniques and experiences presented in other disciplines are of high relevance to water research. Meanwhile, less noticed is that DL may also serve as a scientific exploratory tool. A new area termed AI neuroscience , where scientists interpret the decision process of deep networks and derive insights, has been born. This budding subdiscipline has demonstrated methods including correlation-based analysis, inversion of network-extracted features, reduced-order approximations by interpretable models, and attribution of network decisions to inputs. Moreover, DL can also use data to condition neurons that mimic problem-specific fundamental organizing units, thus revealing emergent behaviors of these units. Vast opportunities exist for DL to propel advances in water sciences.
Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.
Abstract Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists’ human sensory and cognitive systems during storms.
Emerging professionals are crucial in advancing ecological restoration by connecting newcomers with established leaders and blending new ideas with traditional practices. This paper highlights the vital role emerging scientists play in restoration ecology and the Society for Ecological Restoration (SER). A survey conducted during the SER2023 conference workshop, organized by the Students and Emerging Professionals committee, showed that emerging professionals contribute significantly to every stage of scientific work, from planning to publication. However, participants emphasized the scarcity of funding opportunities for non‐senior scientists, which limits academic growth. The workshop underscored the importance of nurturing emerging professionals to develop future leaders for SER and ensure continuity. Fostering non‐hierarchical and inclusive networking is key to engaging and empowering these professionals, ultimately contributing to the long‐term success of ecological restoration efforts.
The Atmospheric Radiation Measurement (ARM) user facility (Turner and Ellingson 2016) collects valuable observations of atmospheric variables affecting the Earth’s radiation budget. These include properties of aerosol, cloud, precipitation, dynamic, and thermodynamic fields. The ARM user facility also supports routine high-resolution modeling efforts at its Southern Great Plains (SGP) site, and over the years it has had significant impacts on cloud-resolving and Earth system model development (Krueger et al. 2016; Randall et al. 2016). In an effort to promote use of the ARM data by the next generation of atmospheric scientists, the second ARM Summer Training and Science Applications Event on observations and modeling of clouds and precipitation took place from 14 to 21 July 2018. The event was sponsored by the ARM User Facility and was catered toward graduate students and early career scientists interested in observations and modeling of aerosol, cloud, and precipitation processes. Theoretical and practical instructions on the application of ground- and aircraft-based observations from a wide array of active and passive sensors, and finescale-resolution model simulations were provided during the training. This informed the participants about innovative methods for using the ARM data and numerical models to address complex scientific questions. The event was locally organized by the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) and was held at the National Weather Center in Norman, Oklahoma. The training was attended by 12 instructors and 24 participants.
The first Department of Energy (DOE) Environmental and Molecular Science Laboratory (EMSL)/Atmospheric Radiation Measurement (ARM) aerosol summer school was held July 15-19, 2019 at the EMSL user facility located at Pacific Northwest National Laboratory. The school set out to provide graduate students and early-career scientists an overview of atmospheric aerosol science and an introduction to the measurement techniques available through the EMSL and ARM user facilities to address current aerosol science issues. Instructors for the course were drawn from scientists from the EMSL (Laskin et al., 2016; China et al., 2018) and ARM facilities (McComiskey and Ferrare, 2016) as well as from the DOE Atmospheric System Research (ASR) program. Student support for the summer school was also jointly provided by EMSL, ARM, and ASR. The school spanned five days with each day covering a particular theme. 25 students from 21 institutions attended morning lectures on aerosol composition, properties, theory, measurements, and modeling. During afternoons, the students explored instruments that collect and analyze aerosol samples at EMSL and PNNL’s Atmospheric Measurements Laboratory. They also tested relevant computer modeling simulations and learned about NWChem, EMSL’s open-source computational chemistry software suite.
The Department of Defense has a methodology for targeting nuclear weapons, and a jargon that is used to communicate between the analysts, planners, aircrews, and missile crews. The typical engineer or scientist in the Department of Energy may not have been exposed to the nuclear weapons targeting terms and methods. This report provides an introduction to the terms and methodologies used for nuclear targeting. Its purpose is to prepare engineers and scientists to participate in wargames, exercises, and discussions with the Department of Defense. Terms such as Circular Error Probable, probability of hit and damage, damage expectancy, and the physical vulnerability system are discussed. Methods for compounding damage from multiple weapons applied to one target are presented.
This presentation is an introduction to computational ontologies and semantic technology. The talk is intended for data scientists, computational scientists, and others who may not be familiar with knowledge systems and their representations.