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At least 613 records · Page 34

WormBase in 2022—data, processes, and tools for analyzing Caenorhabditis elegans

WormBase (www.wormbase.org) is the central repository for the genetics and genomics of the nematode Caenorhabditis elegans. We provide the research community with data and tools to facilitate the use of C. elegans and related nematodes as model organisms for studying human health, development, and many aspects of fundamental biology. Throughout our 22-year history, we have continued to evolve to reflect progress and innovation in the science and technologies involved in the study of C. elegans. We strive to incorporate new data types and richer data sets, and to provide integrated displays and services that avail the knowledge generated by the published nematode genetics literature. Here, we provide a broad overview of the current state of WormBase in terms of data type, curation workflows, analysis, and tools, including exciting new advances for analysis of single-cell data, text mining and visualization, and the new community collaboration forum. Concurrently, we continue the integration and harmonization of infrastructure, processes, and tools with the Alliance of Genome Resources, of which WormBase is a founding member.

59 BASIC BIOLOGICAL SCIENCES↗

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗

Enhancing the Impact of Science Data: Toward Data Discovery and Reuse

The amount of data produced in support of scientific research continues to grow rapidly. Despite the accumulation and demand for scientific data, relatively little data are actually made available for the broader scientific community. We surmise that one root of this problem is the perceived difficulty of electronically publishing scientific data and associated metadata in a way that makes it discoverable. We propose exploiting Semantic Web technologies and best practices to make metadata both discoverable and easy to publish. We share experiences in curating metadata to illustrate the cumbersome nature of data reuse in the current research environment. We also make recommendations with a real-world example of how data publishers can provide their metadata by adding limited additional markup to HTML pages on the Web. With little additional effort from data publishers, the difficulty of data discovery, access, and sharing can be greatly reduced and the impact of research data greatly enhanced.

Data Curation↗

A Section 106 Evaluation of the Mercury Bowling Alley, Area 23, Nevada National Security Site, Nye County, Nevada, with Photographic Documentation Addendums

The National Nuclear Security Administration Nevada Field Office (NNSA/NFO) anticipates demolition of the Mercury Bowling Alley (Building 23-517) on the Nevada National Security Site (NNSS) in Nye County, Nevada (Figure 1). This survey was prompted by plans to construct new facilities at the Bowling Alley location to support NNSS’s changing role in national security. The Bowling Alley has been largely vacant since the mid-1990s following the end of nuclear testing at what was then the Nevada Test Site (NTS). The building is suffering rapid decay. An Area of Potential Effects (APE) of 4.5 acres was surveyed, resulting in recording and evaluation of the Bowling Alley (SHPO Resource Number B14451) and one associated resource (AR1). The APE is located in Section 11 T15S R53E MDBM (projected) at the principal NNSS base of Mercury in Area 23. In 2010, the NTS name was changed to the NNSS, and will be referred to as such throughout this report. Fieldwork and report preparation were done by Desert Research Institute (DRI) cultural resources staff. Architectural descriptions and portions of this report specific to the architecture of the Bowling Alley were completed by Ron Reno, Ph.D., RPA who meets Secretary of the Interior’s Professional Qualifications Standards for Architectural Historian. Administration of the project was by Colleen M. Beck, Ph.D. Historical background regarding Mercury and the NNSS was developed by Maureen King. Beck photographed the building and its environs. Copies of the building form and report are on file in the Nevada Cultural Resources Inventory System at the Nevada State Office of Historic Preservation (SHPO); DRI, Las Vegas; and in the NNSA/NFO curation facility, Las Vegas.

54 ENVIRONMENTAL SCIENCES↗

CyanoCyc cyanobacterial web portal

CyanoCyc is a web portal that integrates an exceptionally rich database collection of information about cyanobacterial genomes with an extensive suite of bioinformatics tools. It was developed to address the needs of the cyanobacterial research and biotechnology communities. The 277 annotated cyanobacterial genomes currently in CyanoCyc are supplemented with computational inferences including predicted metabolic pathways, operons, protein complexes, and orthologs; and with data imported from external databases, such as protein features and Gene Ontology (GO) terms imported from UniProt. Five of the genome databases have undergone manual curation with input from more than a dozen cyanobacteria experts to correct errors and integrate information from more than 1,765 published articles. CyanoCyc has bioinformatics tools that encompass genome, metabolic pathway and regulatory informatics; omics data analysis; and comparative analyses, including visualizations of multiple genomes aligned at orthologous genes, and comparisons of metabolic networks for multiple organisms. CyanoCyc is a high-quality, reliable knowledgebase that accelerates scientists’ work by enabling users to quickly find accurate information using its powerful set of search tools, to understand gene function through expert mini-reviews with citations, to acquire information quickly using its interactive visualization tools, and to inform better decision-making for fundamental and applied research.

59 BASIC BIOLOGICAL SCIENCES↗

Using Gene Essentiality and Synthetic Lethality Information to Correct Yeast and CHO Cell Genome-Scale Models

Essentiality (ES) and Synthetic Lethality (SL) information identify combination of genes whose deletion inhibits cell growth. This information is important for both identifying drug targets for tumor and pathogenic bacteria suppression and for flagging and avoiding gene deletions that are non-viable in biotechnology. In this study, we performed a comprehensive ES and SL analysis of two important eukaryotic models (S. cerevisiae and CHO cells) using a bilevel optimization approach introduced earlier. Information gleaned from this study is used to propose specific model changes to remedy inconsistent with data model predictions. Even for the highly curated Yeast 7.11 model we identified 50 changes (metabolic and GPR) leading to the correct prediction of an additional 28% of essential genes and 36% of synthetic lethals along with a 53% reduction in the erroneous identification of essential genes. Due to the paucity of mutant growth phenotype data only 12 changes were made for the CHO 1.2 model leading to an additional correctly predicted 11 essential and eight non-essential genes. Overall, we find that CHO 1.2 was 76% less accurate than the Yeast 7.11 metabolic model in predicting essential genes. Based on this analysis, 14 (single and double deletion) maximally informative experiments are suggested to improve the CHO cell model by using information from a mouse metabolic model. This analysis demonstrates the importance of single and multiple knockout phenotypes in assessing and improving model reconstructions. The advent of techniques such as CRISPR opens the door for the global assessment of eukaryotic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Making Interoperability Easier with NASA's Metadata Management Tool (MMT)

While the ISO-19115 collection level metadata format meets many users' needs for interoperable metadata, it can be cumbersome to create it correctly. Through the MMT's simple UI experience, metadata curators can create and edit collections which are compliant with ISO-19115 without full knowledge of the NASA Best Practices implementation of ISO-19115 format. Users are guided through the metadata creation process through a forms-based editor, complete with field information, validation hints and picklists. Once a record is completed, users can download the metadata in any of the supported formats with just 2 clicks.

metadata quality↗

The Oxidation State of Sulfur in Apollo Samples 71035 and 71055

Lunar apatites contain 100s-1000s ppm sulfur [1-3]. This was initially puzzling because lunar basalts are thought to form, including at the time of apatite crystallization, in low oxygen fugacity (fO2) conditions where sulfur exists in its reduced form (S2-), a substitution not previously observed in natural apatite. It has been recently shown, using S-XANES measurements of the oxidation state of sulfur in apatites and proximal mesostasis in the lunar basalts 12039 and 10044, that sulfur is indeed present as S2- in both the mesostasis glass and apatite when measurements were performed far from cracks or pits in the thin section [4]. This observation is consistent with other mineralogical indications of the low fO2 during formation of these samples (~IW-1) such as the presence of Fe-metal, ulvöspinel, ilmenite, fayalite, and silica in the thin sections. In the same study, in addition to clear spectral evidence for the dominance of S2-, analyses of apatite grains in both samples that occurred near cracks or pits in the thin section sometimes revealed non-negligible spectral evidence (e.g., S6+/ΣS > 0.03; [4]) for the presence of S6+. Because S6+ was not observed in the mesostasis glass near the apatite grains measured, or in any phase far from cracks or pits in the studied thin sections, this S6+ was interpreted as either primary S2- in the sulfide altered to S6+ in the thin section, or S6+ of secondary origin, deposited in the fractures of the samples [4, 5]. Whether this is of lunar or terrestrial origin is unknown but has implications for lunar petrogenesis if lunar [e.g., 5], or sample handling and curation if terrestrial. To test between lunar and terrestrial origins for observed S6+ in Apollo-era thin sections, we will measure the oxidation state of sulfur in apatite and associated phases in a specially frozen sample from a boulder sampled at Station 1A during the Apollo 17 mission as part of the NASA Apollo Next Generation Sample Analysis (ANGSA) program. Here, we present “control” measurements of samples 71035 and 71055, using Apollo era thin sections of aliquots of these rocks that were processed upon return to Earth and since stored under N2 atmospheres at room temperature. These will be compared to measurements using newly made thin sections of aliquots of the same rocks (71035 and 71055). In addition, 71036, which has been in cold storage (-20℃) since the return of the Apollo 17 mission to Earth, has been recently made available through the ANGSA program. With 71036 we can test the effect of storage temperature on potential oxidation of S2- to S6+ in the relatively oxidizing and warm conditions of Earth’s surface.

apollo↗

Mars Sample Receiving Facility Research and Development to Enable Preservation, Safe Containment, and Scientific Research of Martian Samples on Earth

NASA and ESA are working together to plan a joint campaign to potentially bring back the first Martian samples to Earth in the early 2030s. On the surface of Mars, the Mars 2020Perseverance Rover is selecting and packaging samples that could be returned to Earth for careful examination by an international team of scientists. In preparation for this historic sample return, advance planning is underway to design and build a Mars Sample Receiving Facility (SRF) in the mid-2020s. In 2022, a Mars Sample Receiving Facility Assessment Study(MSAS) will be conducted to further define construction modality and capability options for a facility in the conterminous United States. Since Mars Sample Return (MSR) is currently categorized as a planetary protection restricted Earth return, this new facility would feature biosafety level 4 (BSL-4)-like high containment to protect Earth’s biosphere from any potential hazard. In addition, the facility also requires integration of cleanroom technologies to mitigate against terrestrial contamination and preserve sample integrity for science investigations. The integration of both clean handling and high containment requires significant technology research and development (R&D) by the mid-2020s to support the definition and planning of a SRF before commencing the site specific design phase. The SRF project will need to solidify the inorganic, organic, and biological contamination control (CC) requirements for the facility. This could entail a translation of Mars 2020 mission CC requirements for geologic material to engineering requirements for surfaces and airborne molecular contamination inside isolators and cleanrooms. In tandem, the project will need to determine precision cleaning and sterilization approaches for cleanrooms, isolators, equipment, and tools. Initial material selections for the facility construction materials, cleanrooms, isolators, and BSL-4 suits/garments are an important activity. The recent construction of the OSIRIS-REx and Hayabusa2 curation cleanroom laboratories greatly benefited from early materials testing, before the design phase, to reduced organic outgassing and particulate shedding inside the laboratory. While the early biohazard investigations in the SRF may deem the samples safe to release to laboratories throughout the world, sterilization methods need to be defined to safely release Martian samples. One key aspect of enabling simultaneous sample containment and cleanliness is the concept of a Double-Walled Isolator (DWI) that ESA has been pursuing. Further R&D is needed about DWIs, sample handling, and instrumentation interfaces before beginning the SRF site specific design phase. A working isolator/DWI engineering model should be developed and fabricated. Isolator sizes, connections, pass-through antechambers, and configurations and basic interfaces with instruments and tools as well as the use of robotic, mechanical, and/or human manipulation need to be considered. Inert high purity gas supply (one-pass or recirculation) and other isolator utilities must be determined. Special accommodations for large instruments (e.g., XCT,SEM, etc.) need to be developed. Techniques for opening the sample tubes packaged by M2020and extracting the headspace gas while keeping samples pristine will be challenging, requiring additional R&D, and engagement of the M2020 project. In addition, careful micromanipulation for subdivision and packaging of samples will also need to be included. These combined R&D activities are important before commencing the SRF design phase to ensure safe biohazard containment, sample preservation, and science integrity for the samples that would be studied in the SRF and in laboratories around the world.

mars sample return↗

Processing Frozen Apollo Samples in a Nitrogen Environment

A few weeks after their return to Earth, several Apollo 17 regolith sample splits and one Apollo 17 basalt were frozen at -20˚C (under dry gaseous N2 like all other pristine Apollo samples), and have remained essentially unstudied within the Apollo sample collection at NASA’s Johnson Space Center (JSC). As part of the Apollo Next Generation Sample Analysis (ANGSA) project, these frozen samples were selected for consortium study in 2019. Although the samples themselves were kept at -20˚C for nearly 50 years, the JSC Curation office has lacked a facility for processing frozen samples under pristine Apollo processing conditions. A temporary lab for this work was designed, built, and tested. Procedures were then developed for working in this unique environment, and the facility was sucessfully used to process the frozen Apollo samples for scientific allocation.

ANGSA↗

X-Ray Computed Tomography During Preliminary Examination of Apollo Drive Tube 73001

Introduction: Starting in 2019, the Apollo Next Generation Sample Analysis (ANGSA) Program has enabled consortium studies of specially curated Apollo samples that were previously unstudied (or under studied). This began with unsealed core tube 73002 [1,2] that is the upper part of a station 3 double drive tube. More recently the pro-gram extended to the study of a variety of frozen Apollo 17 samples [3], as well as the gas extraction [4] and dis-section [5] of 73001, the lower half of the station 3 double drive tube, that was sealed under vacuum on the Moon. In this abstract we will examine the role of X-ray Computed Tomography (XCT) during the preliminary examination process for sealed core 73001, including: (1) engineering scans to aid in understanding the gas extraction process, whole-core scanning prior to opening to inform extrusion and dissection work, and (3) individual particle scanning to characterize rock fragment lithologies for follow on studies. Methodology: Sample 73001 is a 33 cm long, 4 cm diameter regolith sample collected inside a drive tube (~1 mm aluminum walls). That drive tube was sealed inside a 0.5 mm thick stainless steel (SS) Core Sample Vacuum Container (CSVC). XCT scans for engineering purposes were done on the Nikon XTH 320 system at Johnson Space Center using the 225 kV multi-metal reflection source at 215 kV, 179 A, and a 38.49 m voxel size. Individual >4 mm particles separated from the core during processing (then triply sealed in Teflon bags) were also scanned at JSC using the 180 kV source at 90 kV, 33 A, and a 2.98 – 10.65 m voxel size. Whole-core scans were done at the University of Texas High-Resolution X-ray Computed Tomography Facility (UTCT) on the 225 kV reflection source on the North Star Imaging cabinet XCT system. These scans included: (1) a series of 9 overlapping super-resolution scans each covering a ~4 cm length of the tube at 190 kV, 180 µA, and a 12.9 µm voxel size and (2) a lower resolution continuous helical scan of the entire core at 190 kV, 180 µA, and a 51.8 µm voxel size. Progress and Results: Before piercing and extracting the gas from sample 73001, an XCT scan of the bottom portion of the CSVC was used to confirm the location of the Teflon cap on the inner drive tube, to ensure it was not accidentally pierced during gas extraction. Similarly, after piercing, the bottom and top portions of the CSVC were scanned in order to capture engineering knowledge about the results of the piercing process, as well as the metal knife edge vacuum seal (SS into In-Ag alloy). Both scans will provide constraints on future work of this type, particularly for samples collected during the Artemis mission. Another finding from these "engineering" scans was that the device in the drive tube that immobilizes the regolith (the keeper) was not seated in the tube properly. This meant that (1) the drive tube could not be removed from the CSVC for the trip to UTCT, and (2) the procedure for opening and extruding the drive tube had to be modified. Had either of these things not been known prior to opening the CSVC, it could have led to an inability to XCT scan the whole core at high resolution and/or potential disruption of the core stratigraphy during extrusion. At UTCT, the entire length of the core was scanned at high resolution (12.9 microns per voxel). This scan serves multiple purposes: (1) A lower resolution (and uncorrected) version of these scans stitched together was used to help inform the processors of potential pitfalls during extrusion and dissection; and (2) the full resolution corrected data will serve as the permanent in situ record of the stratigraphy of the sample and will enable future researchers to perform a variety of analyses. So far, 92 of the 121 >4 mm particles separated during dissection pass 1 of sample 73001 have been individually scanned. These scans clearly show the lithology of each particle while keeping the particles in pristine condition. Because of the dust adhering to particle exteriors it would otherwise be impossible to determine lithologies in a non-contaminating way. Thus far the types of lithologies seen in sample 73001 (e.g., regolith breccias, impact-melt breccias, agglutinates, and basalts) are similar to those previously identified in sample 73002 [2]. By the time of the meeting, all particles from all 3 dissection passes will have been scanned and statistics on the different lithologies in 73001 compiled. References: [1] Shearer et al. (2020) 51st LPSC, abstract 1181. [2] Zeigler et al. (2020) 51st LPSC, abstract 3023. [3] Kent et al. (2022) This Volume. [4] McDonald et al. (2022) European Lunar Symposium. [5] Gross et al (2022) This volume.

Moon↗

X-Ray Computed Tomography of Apollo Drive Tube 73001 as Part of the Apollo Next Generation Sample Analysis Program

Introduction: Starting in 2019, the Apollo Next Generation Sample Analysis (ANGSA) Program has enabled consortium studies of specially curated Apollo samples that were previously unstudied (or under studied). This program was intended as a participating scientist program for these Apollo samples, as well as a preparation for upcoming lunar sample return missions (e.g., Artemis). The work began with studies of unsealed core tube 73002 [1,2] that is the upper ~35 cm of an Apollo 17 double drive tube (~70 cm total depth) collected on the landslide deposit near Lara Crater at Station 3 in the Taurus Littrow Valley. More recently the program extended to the study of a variety of frozen Apollo 17 samples [3], as well as the gas extraction [4] and dissection [5] of 73001, the lower half of the station 3 double drive tube. Sample 73001 was sealed under vacuum on the Moon in a Core Sample Vacuum Container (CSVC). In this abstract we will examine the role of X-ray Computed Tomography (XCT) during the preliminary examination process for sealed core 73001, including: (1) engineering scans to aid in understanding the gas extraction process, (2) whole-core scanning prior to opening to inform extrusion and dissection work, and (3) individual particle scanning to characterize rock fragment lithologies for follow on studies. Methodology: Sample 73001 is a 33 cm long, 4 cm diameter regolith sample collected inside a lunar drive tube (~1 mm aluminum walls). That drive tube was sealed inside a 0.5 mm thick stainless steel (SS) CSVC. XCT scans for engineering purposes were done on the Nikon XTH 320 system at Johnson Space Center using the 225 kV multi-metal reflection source at 215 kV, 179 A, and a 38.49 m voxel size. Individual >4 mm particles separated from the core during processing (then triply sealed in Teflon bags) were also scanned at JSC using the 180 kV source at 90 kV, 33 A, and a 2.98 – 10.65 m voxel size. Whole-core scans were done at the University of Texas High-Resolution X-ray Computed Tomography Facility (UTCT) on the 225 kV reflection source on the North Star Imaging cabinet XCT system. These scans included: (1) a series of 9 overlapping super-resolution scans each covering a ~4 cm length of the tube at 190 kV, 180 µA, and a 12.9 µm voxel size and (2) a lower resolution continuous helical scan of the entire core at 190 kV, 180 µA, and a 51.8 µm voxel size. Progress and Results: Before piercing and extracting the gas from sample 73001, an XCT scan of the bottom portion of the CSVC was used to confirm the location of the Teflon cap on the inner drive tube and whether there was an “air” gap between the Teflon cap and the CSVC. This was to ensure the Teflon cap (which immobilized the soil inside the drive tube) was not accidentally pierced during gas extraction. Similarly, after piercing, the bottom and top portions of the CSVC were scanned in order to capture engineering knowledge about the results of the piercing process, as well as the metal knife edge vacuum seal (SS into an In-Ag alloy). Both scans will provide constraints on future work of this type, both for the design of tools used on the lunar surface during Artemis, as well as how we open future samples of this type. An unexpected finding from these engineering scans was that the device in the drive tube that immobilizes the regolith (the keeper) was not seated in the tube properly. This meant that (1) the drive tube could not be removed from the CSVC for the trip to UTCT, and (2) the procedure for opening and extruding the drive tube had to be modified. Had either of these things not been known prior to opening the CSVC, it could have led to an inability to XCT scan the whole core at high resolution and/or potential disruption of the core stratigraphy during extrusion. At UTCT, the entire length of the core was scanned at high resolution (12.9 microns per voxel). This scan serves multiple purposes: (1) A lower resolution (and uncorrected) version of these scans stitched together was used to help inform the processors of potential pitfalls during extrusion and dissection (voids, angular fragments at the edges of the sample, etc.); and (2) the full resolution corrected data will serve as the permanent in situ record of the stratigraphy of the sample and will enable future researchers to perform a variety of analyses. All 121 >4 mm particles separated during dissection pass 1 of sample 73001 have been individually scanned. These scans clearly show the lithology of each particle while keeping the particles in pristine condition (they are individually triply bagged in Teflon within our N2 purged processing cabinets). Because of the dust adhering to particle exteriors, it would otherwise be impossible to determine lithologies in a non-contaminating way. Thus far the types of lithologies seen in sample 73001 (e.g., regolith breccias, impact-melt breccias, agglutinates, and bas-alts) are similar to those previously identified in sample 73002 [2]. By the time of the meeting, all particles from all 3 dissection passes will have been scanned and statistics on the different lithologies in 73001 compiled. References: [1] Shearer et al. (2020) 51st LPSC, abstract 1181. [2] Zeigler et al. (2020) 51st LPSC, abstract 3023. [3] Kent et al. (2022) This Volume. [4] McDonald et al. (2022) European Lunar Symposium. [5] Gross et al (2022) This volume.

Moon↗

Generating Cryogenic Lunar Simulants Within the Planetary Exploration & Astromaterials Research Laboratory

The Planetary Exploration & Astromaterials Research Laboratory (PEARL) aims to provides capabilities for the creation of—and research on—cryogenic lunar regolith simulants (CRS) containing surface volatile analytes. CRS represent regolith samples that might be collected from lunar Permanently Shadowed Regions (PSRs) during future missions. Handling CRS requires procedural and engineering development due to extremely cold (i.e. ≤ - 196°C) working temperatures. However, there is an imperative to understand the physical and chemical alteration of samples during collection, transport, and curation processes throughout the Artemis missions. The chemistries that will be encountered within the PSRs need to be understood based upon prior mission data analysis. The ability to utilize these techniques provides future tests that could be relevant to planetary protection applications regarding future robotic sample return.

Lunar↗

Materials-Compliant Containers in Preparation for OSIRIS-REx Sample Return

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) is a spacecraft that collected samples from near-Earth asteroid Bennu in 2020. NASA is expecting OSIRIS-REx to return about 250 grams of Bennu dust particles and rocky material (regolith) in the Sample Return Capsule landing on September 24, 2023.This carbonaceous material is predicted to be rich in water and organic compounds that will provide key information on the solar system's genesis. The NASA Johnson Space Center (JSC) curation team is preparing to process the returned regolith and flight hardware to support critical scientific investigations worldwide.

Curation↗

Ultrapure Water System at JSC for High Purity Cleaning of Flight Hardware, Astromaterial Handling Tools and Solar Wind Samples

Use of Ultrapure Water (UPW) for cleaning of astromaterial sample handling tools and containers was driven by the discontinuation of Freon 113 as a cleaning solvent, due to environmental concerns. Freon 113, recycled using distillation, was very effective at removing organic residues from sample handling hardware. The initial switch to high purity water for astromaterial tool cleaning was modeled after efforts at White Sands Test Facility (WSTF) and current semiconductor UPW production practices in the early 1990s. JSC curation’s first system was comprised of ion exchange polishing cylinders, 55 gallon PVDF-lined storage tank, a few tens of feet of PVDF piping, UV and particle filtration, and this system supported cleaning for lunar, meteorite and Cosmic Dust collectors lab operations. By 2000 a major expansion and upgrade was providing UPW of quality E-1 (ASTM D5127-90) or better at 10 gpm for cleaning of the Genesis solar wind payload for flight, in addition to sample handling tools for other astromaterials. This expansion included a 1000 gallon storage tank and several hundred feet of PVDF piping located in B. 31 and 31N. An extra reverse osmosis process unit was added to incoming water in 2005. Subsequently several major components were replaced, and in anticipation of adding new labs, an enlarged UPW system was designed in 2018 and completed in 2019. This system produces grade E1.1 UPW at 15 gpm in a continuous 1100 ft. loop with 5000 gal. storage tank, supplying 8 laboratories.

Ultrapure water↗

Improving the Quality of Geothermal Data Through Data Standards and Pipelines Within the Geothermal Data Repository: Preprint

For machine learning outputs to be applicable to real world problems, high quality data are needed to ensure high quality results. With the more recent emphasis on machine learning in geothermal, there is an increasing need for greater focus on the quality of the data available for use in these projects. For example, Geothermal Operational Optimization Using Machine Learning (GOOML) utilized large quantities of geothermal power plant operational data to inform power plant operational configurations to maximize power generation. High quality datasets result from dependable sensors or devices collecting data, high frequency of measurements, sufficient data points, adequate metadata, reliable storage of data, and sufficient data curation. Another component that contributes to high quality data is reusability, which can be enhanced through data standardization. Data Standardization creates consistency in formatting and contents of like datasets, lessening preprocessing requirements and ensuring adequate information provided by a given dataset. The Geothermal Data Repository (GDR) aims to help improve data quality through automated data standardization for high-value datasets through the implementation of data pipelines alongside reliable and accessible long-term storage for datasets. As such, the GDR has decided to shift away from recommending the use of Excel-based content models and towards the implementation of automated data pipelines. This takes the burden of data standardization off the user and project team and will increase the availability of standardized geothermal data available through the GDR. A set of recommendations, or a data standard for each data type will exist with each data pipeline in order to advise data collection for maximum usability for future research. This paper serves to describe the GDR's proposed transition towards data standardization through automated data pipelines, to discuss the need for and value of such a shift, and to call for suggestions from the community regarding the most useful data standards and pipelines.

data↗

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented data standards and automated data pipelines for the following data types: 1) drilling data, 2) geospatial datasets, and 3) DAS data. An additional data pipeline is proposed for stimulation data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how we can improve this process.

cloud-optimized↗

Data-Centric AI and the Open Energy Data Initiative (OEDI)

This presentation emphasizes the critical importance of data-centric AI. The limitations of model-centric AI when dealing with poor or insufficient data are highlighted, and it is illustrated how training models on inaccurate or noisy data leads to suboptimal results. This talk advocates for a hybrid approach that combines a focus on data quality and model parameters to achieve optimal results. The Open Energy Data Initiative (OEDI) is introduced as a valuable resource for obtaining high-quality energy-related datasets, hosting nearly 2,000 publicly accessible datasets, including 99 solar-related datasets, totaling over 2.7 petabytes of data. OEDI's data lakes enable users to query and work with data without extensive transfers. In conclusion, the significance of data-centric AI and adherence to data curation best practices is emphasized, positioning OEDI as a prime source of high-quality data for AI and machine learning in the renewable energy sector.

AI↗