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User requirements, guidelines, and standards for interconnecting an Applications Data Service (ADS) program for data sharing are discussed. Methods for effective sharing of information (catalogues, directories, and dictionaries) among member installations are addressed. An ADS Directory/Catalog architectural model is also given.
Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each piece owned by one of the processors in the machine, and with all communication explicitly specified by low-level message-passing primitives. A new programming environment is presented for distributed memory architectures, providing a global name space and allowing direct access to remote parts of data values. The analysis and program transformations required to implement this environment are described, and the efficiency of the resulting code on the NCUBE/7 and IPSC/2 hypercubes are described.
This report is the final technical report on Alabama Carbon Storage: Data Sharing Engagement (ACS:DSE) project activities. The goals of the ACS:DSE project are to compile geologic, geophysical, infrastructure, and other relevant CCUS datasets for the study area and develop a geologic model of the study area; develop an online platform to serve data to stakeholders; engage with the public, students, and industry to educate them about CCUS and the data platform; and ensure energy and environmental justice is central to all aspects of the project. Datasets compiled and expanded include formation depths and elevations, digital geophysical well logs, reservoir properties, geologic structures, and geologic models. The geologic data were used to create a three-dimensional geologic model, structure grids, structure contour maps, and fault trace maps. In addition to downloadable datasets, links to CCUS relevant regulatory agencies (e.g., OGB, U.S. Environmental Protection Agency) and sources for infrastructure and educational information were included on the website Educational materials on CCUS for use by K-12 teachers were produced as part of the ACS:DSE project.
Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.
For decades, NASA and international partners have conducted biological experiments in space to understand effects of spaceflight and address potential hazards. To enable spaceflight back to the Moon, and then to Mars and beyond, it is imperative to further understand basic science and health risks associated with spaceflight, along with developing countermeasures. The sending of experiments and organisms into space is a costly endeavor. To maximize scientific return, sharing with the scientific community both space-flown biospecimens and data from completed experiments is essential. New fundamental, applied, and bioinformatic science insights can be gained from specimen and data sharing efforts. Data reuse enables spaceflight health risk modeling, analyzing adverse outcomes across spaceflight hazards, and deep space autonomous support for the flight medical officer.
Ocean metaproteomics is an emerging field enabling discoveries about marine microbial communities and their impact on global biogeochemical processes. Recent ocean metaproteomic studies have provided insight into microbial nutrient transport, colimitation of carbon fixation, the metabolism of microbial biofilms, and dynamics of carbon flux in marine ecosystems. Future methodological developments could provide new capabilities such as characterizing long-term ecosystem changes, biogeochemical reaction rates, and in situ stoichiometries. Yet challenges remain for ocean metaproteomics due to the great biological diversity that produces highly complex mass spectra, as well as the difficulty in obtaining and working with environmental samples. This review summarizes the progress and challenges facing ocean metaproteomic scientists and proposes best practices for data sharing of ocean metaproteomic data sets, including the data types and metadata needed to enable intercomparisons of protein distributions and annotations that could foster global ocean metaproteomic capabilities.
Conventional wisdom makes the suggestion that there are benefits to the creation of shared repositories of scientific data. Funding agencies require that the data from sponsored projects be shared publicly, but individual researchers often see little personal benefit to offset the work of creating easily sharable data. These conflicting forces have led to the emergence of a new role to support researchers: data managers. This paper identifies key differences between the socio-technical context of data managers and other "human infrastructure" roles articulated previously in Computer Supported Cooperative Work (CSCW) literature and summarizes the challenges that data managers face when accepting data for archival and reuse. Finally, while data managers' work is critical for advancing science and science policy, their work is often invisible and under-appreciated since it takes place behind the scenes.
As part of upgrading the Contact Dynamics Simulation Laboratory (CDSL) at the NASA Marshall Space Flight Center (MSFC), a simple, cost effective method was needed to communicate data among the networked simulation machines and I/O controllers used to run the facility. To fill this need and similar applicable situations, a generic protocol was developed, called ShareSync. ShareSync is a lightweight, real-time, publish-subscribe Ethernet protocol for simple and deterministic data sharing across diverse machines and operating systems. ShareSync provides a simple Application Programming Interface (API) for simulation programmers to incorporate into their code. The protocol is compatible with virtually all Ethernet-capable machines, is flexible enough to support a variety of applications, is fast enough to provide soft real-time determinism, and is a low-cost resource for distributed simulation development, deployment, and maintenance. The first design cycle iteration of ShareSync has been completed, and the protocol has undergone several testing procedures including endurance and benchmarking tests and approaches the 2001ts data synchronization design goal for the CDSL.
Increased biomedical risks associated with deep space crewed missions (cis-Lunar, Mars transit/surface) require development of health countermeasures, novel ecosystem support, risk modeling, and fundamental space biological knowledge discovery. Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from space biological and health studies are needed for reuse by scientists to address these tasks. The data as well as space-relevant biospecimens are being made more findable, accessible, interoperable, and reusable through NASA’s Open Science Data Repository (OSDR). This new OSDR umbrella grouping includes NASA GeneLab, the NASA Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection. The OSDR system design appropriately handles metadata and processed-tabular results from ALSDA studies collected from space experiments. But raw and processed ALSDA bioimage and video datasets require an expansion of OSDR’s data architecture to handle ingestion, curation, and egress. The academic-industry bioimaging field saw a scientific renaissance in the past several years through leveraging open-source software, international collaborations, machine learning, and other open science/programming approaches. As crewed missions and more biological experiments are on the deep space horizon, OSDR is embracing data stewardship through listening to feedback from subject matter experts and designing an expanded architecture which is appropriate for NASA’s goals to enable analysis and reuse of bioimaging and video data for the public science community.Discovery Through Image and Video Data Sharing
The NNSA Seismic Cooperation Program (SCP) sponsored Stephen Myers (LLNL), Michael Begnaud (LANL), Brian Young (SNL) and Istvan Bondar (Research Center for Astronomy and Earth Sciences, Hungary) to serve as a presenters/trainers at the “NDC Capacity Building Workshop and Regional Seismic Travel Time (RSTT) in combination with Data Sharing and Integration Training” September 4-8 2022 in Muscat, Oman (See Appendix A for the agenda). The workshop and training (workshop from here forward) was organized by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) Provisional Technical Secretariat (PTS). The first half of the week was devoted to NDC workshop activities, and the second half was devoted to RSTT training. Fifty-five participants from 27 countries and the CTBTO-PTS attended the 5-day workshop (See Appendix B for list of participants and countries of origin). Presentations from the PTS described the International Monitoring System (IMS), International Data Centre (IDC) products, and metrics of regional data utilization. Contributed presentations from each country’s scientists included descriptions of regional and national networks, methods of data analysis, and needs for material and technical assistance. Training included an overview of the RSTT method and instruction on how to locate seismic events with the iLoc program, which utilizes RSTT travel times to reduce bias in event location estimates. Methods of seismic tomography and the need for a high-quality tomographic set, including seismological “ground truth”, were emphasized. Seismological “ground truth” or “GT” is a term that has come to mean both events with known location and events with well-characterized locations that are estimated using seismological data, typically with epicenter accuracy of 5 km or better. Notably, the instructional platform has migrated from UNIX shell scripts to Jupyter Notebooks. Jupyter Notebooks have the advantage being more visually intuitive, including display of graphics within the notebook. Each notebook includes every processing step that participants need to reproduce the entire exercise.
Astrobiology is a multidisciplinary area of scientific research focused on studying the origins of life on Earth and the conditions under which life might have emerged elsewhere in the universe. NASA uses the results of Astrobiology research to help define targets for future missions that are searching for life elsewhere in the universe. The understanding of complex questions in Astrobiology requires integration and analysis of data spanning a range of disciplines including biology, chemistry, geology, astronomy and planetary science. However, the lack of a centralized repository makes it difficult for Astrobiology teams to share data and benefit from resultant synergies. Moreover, in recent years, federal agencies are requiring that results of any federally funded scientific research must be available and useful for the public and the science community. The Astrobiology Habitable Environments Database (AHED), developed with a consolidated group of astrobiologists from different active research teams at NASA Ames Research Center, is designed to help to address these issues. AHED is a central, high-quality, long-term data repository for mineralogical, textural, morphological, inorganic and organic chemical, isotopic and other information pertinent to the advancement of the field of Astrobiology.
Astrobiology is a multidisciplinary area of scientific research focused on studying the origins of life on Earth and the conditions under which life might have emerged elsewhere in the universe. NASA uses the results of Astrobiology research to help define targets for future missions that are searching for life elsewhere in the universe. The understanding of complex questions in Astrobiology requires integration and analysis of data spanning a range of disciplines including biology, chemistry, geology, astronomy and planetary science. However, the lack of a centralized repository makes it difficult for Astrobiology teams to share data and benefit from resultant synergies. Moreover, in recent years, federal agencies are requiring that results of any federally funded scientific research must be available and useful for the public and the science community. The Astrobiology Habitable Environments Database (AHED), developed with a consolidated group of astrobiologists from different active research teams at NASA Ames Research Center, is designed to help to address these issues. AHED is a central, high-quality, long-term data repository for mineralogical, textural, morphological, inorganic and organic chemical, isotopic and other information pertinent to the advancement of the field of Astrobiology.
Astrobiology is a multidisciplinary area of scientific research focused on studying the origins of life on Earth and the conditions under which life might have emerged elsewhere in the universe. NASA uses the results of Astrobiology research to help define targets for future missions that are searching for life elsewhere in the universe. The understanding of complex questions in Astrobiology requires integration and analysis of data spanning a range of disciplines including biology, chemistry, geology, astronomy and planetary science. However, the lack of a centralized repository makes it difficult for Astrobiology teams to share data and benefit from resultant synergies. Moreover, in recent years, federal agencies are requiring that results of any federally funded scientific research must be available and useful for the public and the science community. The Astrobiology Habitable Environments Database (AHED), developed with a consolidated group of astrobiologists from different active research teams at NASA Ames Research Center, is designed to help to address these issues. AHED is a central, high-quality, long-term data repository for mineralogical, textural, morphological, inorganic and organic chemical, isotopic and other information pertinent to the advancement of the field of Astrobiology.
Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.
The U.S. Department of Energy (DOE) Oak Ridge Office of Environmental Management (EM-OR) requested that Oak Ridge Associated Universities (ORAU), working under the Oak Ridge Institute for Science and Education (ORISE) contract, provide technical and independent waste management planning support under the American Recovery and Reinvestment Act (ARRA). Specifically, DOE EM-OR requested that ORAU plan and implement a sampling and analysis campaign targeting certain URS|CH2M Oak Ridge, LLC (UCOR) surveillance and maintenance (S&M) process inventory waste. Eight populations of historical and reoccurring S&M waste at the Oak Ridge National Laboratory (ORNL) have been identified in the Waste Handling Plan for Surveillance and Maintenance Activities at the Oak Ridge National Laboratory, DOE/OR/01-2565&D2 (WHP) (DOE 2012) for evaluation and processing to determine a final pathway for disposal. Population 7 (POP 7) consists of 56 containers of aged, low-level and potentially mixed S&M waste that has been staged in various locations around ORNL. Several of these POP 7 containers primarily contain personal protective equipment (PPE) and dry active waste (DAW), but may contain other miscellaneous debris. This data sharing report addresses the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) specified waste in a 13-container subpopulation (including eight steel boxes, three 55-gal drums, one sealand, and one intermodal) that lacked sufficient characterization data for possible disposal at the Environmental Management Waste Management Facility (EMWMF) using the approved Waste Lot (WL) 108.1 profile.
The Oak Ridge Leadership Computing Facility (OLCF) runs the No. 4 supercomputer in the world, supported by a petascale file system, to facilitate scientific discovery. In this paper, using the daily file system metadata snapshots collected over 500 days, we have studied the behavioral trends of 1, 362 active users and 380 projects across 35 science domains. In particular, we have analyzed both individual and collective behavior of users and projects, highlighting needs from individual communities and the overall requirements to operate the file system. We have analyzed the metadata across three dimensions, namely (i) the projects' file generation and usage trends, using quantitative file system-centric metrics, (ii) scientific user behavior on the file system, and (iii) the data sharing trends of users and projects. To the best of our knowledge, our work is the first of its kind to provide comprehensive insights on user behavior from multiple science domains through metadata analysis of a large-scale shared file system. We envision that this OLCF case study will provide valuable insights for the design, operation, and management of storage systems at scale, and also encourage other HPC centers to undertake similar such efforts.
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.
This paper makes three contributions to the area of modern science data processing systems. First, the paper describes the science data processing pipeline, developed at the Multi-mission Image Processing Lab of JPL, for transforming raw space data into high quality image data and automating the distribution of data using a high-performance file transaction service. File Exchange Interface is the file transaction service developed MIPL. Second, it presents the FEI component architecture in the are of file transaction management, security,a nd file integrity verfication. Finally, the paper presents the federated model for the FEI service to demonstrate how to create a pool of file trasaction services to support load balancing and service fallover, and simplify service management.