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NASA NTRS2010

Kepler Data Release 4 Notes

The Data Analysis Working Group have released long and short cadence materials, including FFIs and Dropped Targets for the Public. The Kepler Science Office considers Data Release 4 to provide "browse quality" data. These notes have been prepared to give Kepler users of the Multimission Archive at STScl (MAST) a summary of how the data were collected and prepared, and how well the data processing pipeline is functioning on flight data. They will be updated for each release of data to the public archive and placed on MAST along with other Kepler documentation, at http://archive.stsci.edu/kepler/documents.html. Data release 3 is meant to give users the opportunity to examine the data for possibly interesting science and to involve the users in improving the pipeline for future data releases. To perform the latter service, users are encouraged to notice and document artifacts, either in the raw or processed data, and report them to the Science Office.

Van Cleve, Jeffrey↗

NASA NTRSDate not supplied

An Automated Approach to Labelling Datasets in Earth Science Publications

NASA Data Active Archive Centers, orDAACs, ingest, store, and distribute dataacquired from satellites, ground systems as well asreanalysis models. Many authors use this datain their research. However, most of the datasets usedin Earth Science Publications are not citedcorrectly or not cited at all. Thus, there is no directlink between the datasets used and thescientific publications which reference them. Thisleads to issues with reproducibility of theresults, attribution of the research results, anddiscovery of new datasets. This project began byexploring various methods of automatically labellingGoddard Earth Sciences Data andInformation Services Center (GES DISC) datasets usingSupervised Machine Learning and EarthData Search Common Metadata Repository (CMR) queries.The ultimate goal was to create alibrary of citations that utilized automated citationlabeling to directly link the researchpublications to the data they use. Supervised MachineLearning approaches struggled due to thelimited amount of labelled training data to learnfrom. Increasing the volume of training data isdifficult as it requires subject matter experts todevote time to manually reviewing journalarticles and determining the datasets used. The CMRqueries were inconsistent because theunderlying metadata is continuously being updated.Thus, it is hard to generalize theeffectiveness of the CMR results as they are dependenton the internal state of CMR. Theseapproaches helped inform the decision to transitionthe project into using a Knowledge Graph.Another key aspect of this project focused on theautomated extraction of features (platform,instrument, variables, etc) and explicit citationsfrom within Earth Science Publications. Theseautomated extractions were used to classify researchpapers based on their platform/instrumentcouples. This information was input into the CitationManagement System for GES DISC. Theseplatform/instrument couples also provide an additionalfacet that can be searched on the GESDISC website.

Edward Jahoda↗

NASA NTRS2008

Software Archive Related Issues

With the archive opening of the major X-ray and Gamma ray missions, the school is intended to provide information on the resource available in the data archive and the public software. This talk reviews the archive content, the data format for the major active missions Chandra, XMM-Newton, Swift, RXTE, Integral and Suzaku and the available software for each of these missions. It will explain the FITS format in general and the specific layout for the most popular mission, explaining the role of keywords and how they fit in the multimission standard approach embrace by the High Energy Community. Specifically, it reviews : the difference data levels and the difference software applicable; the popular/standard method of analysis for high level products such as spectra, timing and images; the role of calibration in the multi mission approach; how to navigate the archive query databases. It will present also how the school is organized and how the information provided will be relevant to each of the afternoon science projects that will be proposed to the students and led by a project leader

Angelini, Lorella↗

NASA NTRS1993

The Extreme Ultraviolet Explorer archive

The objectives and data products of the EUVE public archive, created to handle the storage, maintenance, and distribution of EUVE data and ancillary documentation, information, and software, are briefly reviewed. Archive data products presently include calibration target spectra, a catalog of past and future calibration targets, the EUVE Bright Source List, extreme ultraviolet skymaps and images of extended sources, a list of approved guest observer targets, a bibliography of EUVE publications, and C routines to calculate interstellar medium transmission at EUV wavelengths.

Polomski, E.↗

NASA NTRSDate not supplied

Supervised Machine Learning Approach for Classifying Earth Science Publications

The data collections archived and distributed by the GES DISC NASA data center are widely utilized for various Earth Science studies. As these collections are created, many research works are published regarding these collections' algorithms, their validation, and their applications. As NASA data centers collect these publications for public use, it is helpful to categorize them based on how they relate to their associated datasets. Specifically, whether the publication linked to the GES DISC dataset is using it for applicational research, describing the algorithm used for the dataset creation, validating the dataset, or providing a general overview of the data collection. Currently, this process requires simple manual labeling, and as such, it may be possible to solve via automation. To approach this problem, machine learning classifiers were developed to predict a publication's category. Manually labeled publications were used as the training data for the supervised machine learning algorithms, specifically Random Forest and Multinomial Naïve Bayes. After balancing the dataset and implementing the Multinomial Naïve Bayes algorithm, the classification accuracy achieved was substantially higher than the baseline accuracy, thus significantly improving the efficiency of publication labeling.

Rohan Dayal↗

DOE OSTI2022

Why don't we share data and code? Perceived barriers and benefits to public archiving practices

The biological sciences community is increasingly recognizing the value of open, reproducible and transparent research practices for science and society at large. Despite this recognition, many researchers fail to share their data and code publicly. This pattern may arise from knowledge barriers about how to archive data and code, concerns about its reuse, and misaligned career incentives. Here, we define, categorize and discuss barriers to data and code sharing that are relevant to many research fields. We explore how real and perceived barriers might be overcome or reframed in the light of the benefits relative to costs. By elucidating these barriers and the contexts in which they arise, we can take steps to mitigate them and align our actions with the goals of open science, both as individual scientists and as a scientific community.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRSDate not supplied

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗

DOE OSTI2021

ESS-DIVE guidelines for archiving terrestrial model data

This dataset contains supporting documents and images for ESS-DIVE terrestrial model data archiving guidelines.Terrestrial models are broadly defined as numerical models that couple both land dynamics and energy, water, carbon, or nutrient fluxes. We created these guidelines based on input from the U.S. Department of Energy’s Biological and Environmental Research land modeling community. The guidelines are intended to help modelers determine which components of their terrestrial model data associated with publication should be archived. Based on input from the land modeling community, the guidelines recommend archiving both model input and testing data, as well as code, script, and metadata. The guidelines also recommend archiving model data output, depending on the limitations set by data repositories. Lastly, we provide recommendations for bundling data files for publication as well as a discussion about tools that can facilitate model data archiving and reuse.This dataset is an archive of the associated GitHub repository for our model archiving guidelines (https://github.com/ess-dive-community/essdive-model-data-archiving-guidelines). The ‘README.pdf’ file gives a general introduction to the guidelines, and the ‘instructions.pdf’ file provides more detailed steps for following the guidelines. We also provide 2 figures in this data package: 1) a decision tree (model_data_guidelines_decision_tree.png) that can help users determine which components of their model data to archive. and 2) the ‘model_data_guidelines_flmd.png’ file depicts the different files that can be archived in addition to the model data itself. Lastly, we include 3 digitized tables from our associated manuscript and 3 CSV files with anonymized input from DOE scientists about the importance of different aspects of model data archiving from which we developed the guidelines.Dataset updates for v1.1.0: We updated this data package on 2021-11-22 in response to review comments on our related manuscript. In this update we removed one figure so that the model archiving guidelines are conveyed in text rather than an image. We updated the file-level metadata (FLMD) figure to be in accord with the most recent FLMD recommendations. We made minor edits to the README file to update the recommended citation and added two co-authors. We also added 6 new data files (3 are anonymized input from DOE scientists that helped to inform guidelines, and 3 are digitized tables from our manuscript.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2003

Discoveries about Tropical Tropospheric Ozone from Satellite and SHADOZ (Southern Hemisphere Additional Ozonesondes) and a Future Perspective on NASA's Ozone Sensors

We have been producing near-real tropical tropospheric ozone ('TTO') data from TOMS since 1997 with Prof. Hudson and students at the University of Maryland. Maps for 1996-2000 for the operational Earth-Probe instrument reside at: . We also have archived 'TTO' data from the Nimbus 7/TOMS satellite (1979-1992). The tropics is a region strongly influenced by natural variability and anthropogenic activity and the satellite data have been used to track biomass burning pollution and to detect interannual variability and climate signals in ozone. We look forward to future ozone sensors from NASA; four will be launched in 2004 as part of the EOS AURA Mission. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical variability. Thus, in 1998, NASA's Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches at selected sites and provides a public archive of ozonesonde data from twelve tropical and subtropical stations at http://croc.nsfc.nasa.gov/shadoz. The stations are: Ascension Island; Nairobi, Kenya; Irene, South Africa; R,union Island; Watukosek, Java; Fiji; Tahiti; American Samoa; San Cristobal, Galapagos; Natal, Brazil, Malindi, Kenya; Paramaribo, Surinam. From the first 3-4 years of data (presently greater than 1700 sondes), the following features emerge: (a) highly variable tropospheric ozone; (b) a zonal wave-one pattern in tropospheric column ozone; (c) tropospheric ozone variability over the Indian and Pacific Ocean displays strong convective signatures.

Thompson, Anne↗

NASA NTRS1989

Global data bases on distribution, characteristics and methane emission of natural wetlands: Documentation of archived data tape

Global digital data bases on the distribution and environmental characteristics of natural wetlands, compiled by Matthews and Fung (1987), were archived for public use. These data bases were developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. Five global 1 deg latitude by 1 deg longitude arrays are included on the archived tape. The arrays are: (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type. The first three data bases on wetland locations were published by Matthews and Fung (1987). The last two arrays contain ancillary information about these wetland locations: vegetation type is from the data of Matthews (1983) and soil type from the data of Zobler (1986). Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document the tape, and briefly explain the data sets and their initial application to estimating the annual emission of methane from natural wetlands. Included is information about array characteristics such as dimensions, read formats, record lengths, blocksizes and value ranges, and descriptions and translation tables for the individual data bases.

Matthews, Elaine↗

NASA NTRS2004

Discoveries about Tropical Ozone from Satellite and SHADOZ (Southern Hemisphere ADditional Ozonesondes)

We have been producing near-real tropical tropospheric ozone ("TTO") data from TOMS since 1997 with Prof. Hudson and students at the University of Maryland. Maps for 1996-2000 for the operational Earth-Probe instrument reside at: . The tropics is a region strongly influenced by natural variability and anthropogenic activity and the satellite data have been used to track biomass burning pollution and to detect interannual variability and climate signals in ozone. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical variability. Thus, in 1998, NASA's Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ provides a public archive of ozonesonde data from twelve tropical and subtropical stations at http://croc.gsfc.nasa.gov/shadoz. Highlights from the first 4-5 years of SHADOZ data (presently > 2000 sondes) will be shown.

Thompson, Anne M.↗

NASA NTRSDate not supplied

NASA Institutional Scientific Collection and Biospecimen Sharing Program at Ames Research Center

For decades, NASA and their international partners have flown and conducted non-human biological experiments in space to understand the effects of spaceflight and address potential biological hazards. It is imperative to understand the basic science and health risks associated with spaceflight, along with developing countermeasures, as humanity ventures back to the Moon, and then to Mars and beyond. 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, preserved and archived in NASA’s Institutional Scientific Collection (ISC) at Ames Research Center (ARC). These specimens are collected according to well-established SOPs that maintain their quality and integrity. To enable new discoveries, the samples are then made available to the international scientific community through NASA’s Biospecimen Sharing Program (BSP). The NASA ISC currently stores over 32,000 specimens from Shuttle, International Space Station and ground-based investigations. Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. The specimens include tissues from all biological systems including musculoskeletal, neurosensory, reproductive, respiratory, circulatory, and digestive and are stored at -80°C, -20°C, +4°C, or ambient. Descriptive metadata is available for all samples. Historically, these tissues have been used for a wide range of analyses, including histology, genomics, and transcriptomics. Also available through the ISC are tissue from NASA’s Space Radiation Laboratory. To study the effects of space radiation, researchers irradiate biological specimens and unused samples are made available through the LSDA. These biospecimens and data are made available through the public Life Sciences Data Archive (LSDA) website to promote basic discovery, pre-clinical and clinical science. Visit the NASA ISC-BSP website for more information. Websites: https://lsda.jsc.nasa.gov/ ; https://www.nasa.gov/ames/research/space-biosciences/isc-bsp

Space Flown Biospecimens↗

NASA NTRSDate not supplied

NASA Institutional Scientific Collection and Biospecimen Sharing Program at Ames Research Center

Space Flown Biospecimens↗

DOE OSTI2023

The cosmic DANCe of Perseus

Context. Star-forming regions are excellent benchmarks for testing and validating theories of star formation and stellar evolution. The Perseus star-forming region, being one of the youngest (< 10 Myr), closest (280-320 pc), and most studied in the literature, is a fundamental benchmark. Aims. We aim to study the membership, phase-space structure, mass, and energy (kinetic plus potential) distribution of the Perseus star-forming region using public catalogues (Gaia, APOGEE, 2MASS, and Pan-STARRS). Methods. We used Bayesian methodologies that account for extinction to identify the Perseus physical groups in the phase-space, retrieve their candidate members, derive their properties (age, mass, 3D positions, 3D velocities, and energy), and attempt to reconstruct their origin. Results. We identify 1052 candidate members in seven physical groups (one of them new) with ages between 3 and 10 Myr, dynamical super-virial states, and large fractions of energetically unbounded stars. Their mass distributions are broadly compatible with that of Chabrier for masses ≳0.1 M ⊙ and do not show hints of over-abundance of low-mass stars in NGC 1333 with respect to IC 348. These groups’ ages, spatial structure, and kinematics are compatible with at least three generations of stars. Future work is still needed to clarify if the formation of the youngest was triggered by the oldest. Conclusions. The exquisite Gaia data complemented with public archives and mined with comprehensive Bayesian methodologies allow us to identify 31% more members than previous studies, discover a new physical group (Gorgophone: 7 Myr, 191 members, and 145 M ⊙ ), and confirm that the spatial, kinematic, and energy distributions of these groups support the hierarchical star formation scenario.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2004

Discoveries about Tropospheric Ozone Pollution from Satellite and Sounding

We have been producing near-real time tropospheric ozone satellite maps from the TOMS (Total Ozone Mapping Spectrometer) sensor since 1997. This is most readily done for the tropics, where the stratospheric and tropospheric ozone column amounts can be discriminated readily. Maps for 1996-2000 for the operational Earth-Probe instrument reside at: chttp://www.atmos.umd.edu/-trope>. Pollution in the tropics is influenced by biomass burning and by transport patterns that favor recirculation and in other cases reflect climate variability like the El-Nino-Southern Oscillation [Thompson et al., 2001]. Time permitting, examples of mid-latitude, intercontinental transport of ozone pollution sensed by TOMS will be shown. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical variability. Thus, in 1998, NASA's Goddard Space Flight Center and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches and provides a public archive of ozonesonde data from twelve tropical stations at http://croc.gsfc.nasa.gov/shadoz. Further insights into the role of chemical and dynamical influences have emerged from the first 4-5 years of SHADOZ data (less than 2000 ozone profiles): (a) highly variable tropospheric ozone; (b) a zonal wave-one pattern in tropospheric column ozone; (c) convective variability affects tropospheric ozone over the Indian and Pacific Ocean; (d) a "tropical Atlantic Paradox" appears in December-January-February.

Thompson, Anne M.↗

NASA NTRS2004

Discoveries about Tropospheric Ozone Pollution from Satellite and Soundings

We have been producing near-red time tropospheric ozone satellite maps from the TOMS (Total Ozone Mapping Spectrometer) sensor since 1997. Maps for 1996-2000 for the operational Earth-Probe instrument are at: . Pollution in the tropics is influenced by biomass burning and by transport patterns that favor recirculation and in other cases reflect climate variability like the El-Nino-Southern Oscillation [Thompson et al., 2001]. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical gradients in pollution. Thus, in 1998, NASA's Goddard Space Flight Center and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches and provides a public archive of ozonesonde data from twelve tropical stations at http://croc.gsfc.nasa.gov/shadoz. Further insights into the role of chemical and dynamical influences have emerged from the first 4-5 years of SHADOZ data (more than 2000 ozone profiles). Highly variable tropospheric ozone and a zonal wave-one pattern in tropospheric ozone suggest that dynamics is as important as pollution in determining tropical ozone distributions.

Thompson, Anne M.↗

NASA NTRS2020

Accelerating Space Life Sciences: Successes and Challenges of Biospecimen and Data Sharing

NASA's current human space flight research is directed towards enabling human space exploration beyond Low Earth Orbit (LEO). To that end, NASA Space Flight Payload Projects; Rodent Research, Cell Science, and Microbial Labs, flown on the International Space Station (ISS), benefit the global life sciences and commercial space communities. Verified data sets, science results, peer-reviewed publications, and returned biospecimens, collected and analyzed for flight and ground investigations, are all part of the knowledge base collected by NASA's Human Exploration and Operations Mission Directorate's Space Life and Physical Sciences Research and Applications (SLPSRA) Division, specifically the Human Research and Space Biology Programs. These data and biospecimens are made available through the public Life Sciences Data Archive (LSDA) website to promote basic discovery, pre-clinical and clinical science.The NASA Institutional Scientific Collection (ISC), stores flight and ground biospecimens from Space Shuttle and ISS programs. These specimens are curated and managed by the Ames Life Sciences Data Archive (ALSDA), an internal node of NASA's LSDA. The ISC stores over 30,000 specimens from experiments dating from 1984 to present. Currently available specimens include tissues from the circulatory, digestive, endocrine, excretory, integumentary, muscular, neurosensory, reproductive, respiratory and skeletal systems.NASA's biospecimen collection represents a unique and limited resource of unique spaceflight payload and ground control research subjects. These specimens are harvested according to well established SOPs that maintain their quality and integrity. Once the primary scientific objectives have been met, the remaining specimens are made available to provide secondary opportunities for complementary studies or new investigations to broaden research without large expenditures of time or resources. Website: https://lsda.jsc.nasa.gov/

Scott, Ryan T.↗

NASA NTRS2021

Cluster after 20 Years of Operations: Science Highlights and Technical Challenges

The Cluster mission was the first constellation using four identical spacecraft to study Sun-Earth connection plasma processes. Using four spacecraft in a tetrahedron shape, it could measure, for the first time, 3D quantities such as electrical currents, plasma gradients or divergence of the electron pressure tensor and 3D structures such as boundaries, surface waves or vortices. Launched in pairs in July and August 2000, on two Soyuz rockets from Baikonur, the four spacecraft have been collecting data continuously for more than 20 years. The mission faced many challenges during the years of operations as some spacecraft subsystems had a lifetime of a few years beyond the initial two-year mission. The major one was to operate without functioning batteries and to successfully pass short and long eclipses, up to 3 h long, without damaging the on-board computers and transmitters and without freezing the fuel. More than 1,000 eclipses have been successfully passed since 2010 using a specially made procedure which switches off the complete spacecraft before entering into eclipse and switches it on when the Sun is again illuminating the solar panels. During 20 years, many discoveries and science results have been published in more than 2,700 scientific papers. A few highlights are presented here, focusing on how varying the spacecraft separation was essential to achieve the science goals of the mission. The Cluster Science Data System and the Cluster archive allows public access to all science data as well as spacecraft ancillary data.

C P Escoubet↗