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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

High-performance web services for querying gene and variant annotation

Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info. Both are offered free of charge to the research community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Lynx web services for annotations and systems analysis of multi-gene disorders

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized both local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

A comparison of Amazon Web Services and Microsoft Azure cloud platforms for high performance computing

Advances in commercial cloud computing necessitate continual evaluation of the cloud's performance on a variety of applications. This work looks at compute oriented instances from Amazon Web Services and Microsoft Azure cloud platforms and evaluates them with several high-performance computing benchmarks, including HPCC and HPCG. These benchmarks illustrate that the most cost competitive solution depends on the application to be run.

Kotas, Charlotte↗
DOE OSTI2021

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

The use of haptic interfaces and web services in crystallography: an application for a `screen to beam' interface

Haptic interfaces have become common in consumer electronics. They enable easy interaction and information entry without the use of a mouse or keyboard. Our work illustrates the application of a haptic interface to crystallization screening in order to provide a natural means for visualizing and selecting results. By linking this to a cloud-based database and web-based application program interface, the same application shifts the approach from `point and click' to `touch and share', where results can be selected, annotated and discussed collaboratively. Furthermore, in the crystallographic application, given a suitable crystallization plate, beamline and robotic end effector, the resulting information can be used to close the loop between screening and X-ray analysis, allowing a direct and efficient `screen to beam' approach. The application is not limited to the area of crystallization screening; `touch and share' can be used by any information-rich scientific analysis and geographically distributed collaboration.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

Data Intensive Computing on Amazon Web Services

The Geophysical Monitoring Program (GMP) has spent the past few years building up the capability to perform data intensive computing using what have been referred to as “big data” tools. These big data tools would be used against massive archives of seismic signals (>300 TB) to conduct research not previously possible. Examples of such tools include Hadoop (HDFS, MapReduce), HBase, Hive, Storm, Spark, Solr, and many more by the day. These tools are useful for performing data analytics on datasets that exceed the resources of traditional analytic approaches. To this end, a research big data cluster (“Cluster A”) was set up as a collaboration between GMP and Livermore Computing (LC).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

EnergyIQ

EnergyIQ-the first "action-oriented" benchmarking tool for non-residential buildings-provides a standardized opportunity assessment based on benchmarking results. along with decision-support information to help refine action plans. EnergyIQ offers a wide array of benchmark metrics, with visuall as well as tabular display. These include energy, costs, greenhouse-gas emissions, and a large array of characteristics (e.g. building components or operational strategies). The tool supports cross-sectional benchmarking for comparing the user's building to it's peers at one point in time, as well as longitudinal benchmarking for tracking the performance of an individual building or enterprise portfolio over time. Based on user inputs, the tool generates a list of opportunities and recommended actions. Users can then explore the "Decision Support" module for helpful information on how to refine action plans, create design-intent documentation, and implement improvements. This includes information on best practices, links to other energy analysis tools and more. The variety of databases are available within EnergyIQ from which users can specify peer groups for comparison. Using the tool, this data can be visually browsed and used as a backdrop against which to view a variety of energy benchmarking metrics for the user's own building. User can save their project information and return at a later date to continue their exploration. The initial database is the CA Commercial End-Use Survey (CEUS), which provides details on energy use and characteristics for about 2800 buildings (and 62 building types). CEUS is likely the most thorough survey of its kind every conducted. The tool is built as a web service. The EnergyIQ web application is written in JSP with pervasive us of JavaScript and CSS2. EnergyIQ also supports a SOAP based web service to allow the flow of queries and data to occur with non-browser implementations. Data are stored in an Oracle 10g database. References: Mills, Mathew, Brook and Piette. 2008. "Action Oriented Benchmarking: Concepts and Tools." Energy Engineering, Vol.105, No. 4, pp 21-40. LBNL-358E; Mathew, Mills, Bourassa, Brook. 2008. "Action-Oriented Benchmarking: Using the CEUS Database to Benchmark Commercial Buildings in California." Energy Engineering, Vol 105, No. 5, pp 6-18. LBNL-502E.

MILLS, EVAN↗
DOE OSTI2023

Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters

Long-term, high-resolution, regional wave hindcast datasets were generated using unstructured-grid Simulating WAves Nearshore (SWAN) models for the U.S. coastal waters to support nearshore wave energy development in the U.S. including those bordering U.S. territorial islands. The model domains resolved the entire U.S. exclusive economic zones, with a spatial resolution of approximately 200 m nearshore. The regional SWAN models were driven by the global WAVEWATCH III® model outputs and run for a 42-year period from 1979 to 2020. Extensive model validations were performed using buoy observations and altimeter data. Regional resource characterization was performed based on hindcast data points at 2 km from shore and along the 100 m isobath. Aggregations of wave resource parameters were produced, and spatial and seasonal variations were analyzed for all the regions. Wave resource metrics recommended by international standards, including a 3-hour time series of six resource parameters, hourly frequency- and directionally resolved wave spectra at selected “virtual buoy” locations, and average-annual values of omni-directional wave power, significant wave height, and energy period are publicly disseminated through an Amazon Web Service and a Marine Energy Atlas web application tool to facilitate wave energy research and a wide range of coastal ocean applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Developer Network

NREL's Developer Network, developer.nrel.gov, provides data that users can access to provide data to their own analyses, mobile and web applications. Developers can retrieve the data through a Web services API (application programming interface). The Developer Network handles overhead of serving up web services such as key management, authentication, analytics, reporting, documentation standards, and throttling in a common architecture, while allowing web services and APIs to be maintained and managed independently.

Source record↗
DOE OSTI2016

A Science Data Gateway for Environmental Management

Science data gateways are effective in providing complex science data collections to the world-wide user Q1 communities. In this paper we describe a gateway for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Built on top of established web service technologies, the ASCEM data gateway is specifically designed for environmental modeling applications. Its key distinguishing feature sinclude (1) handling of complex spatiotemporal data, (2) offering a variety of selective data access mechanisms, (3) providing state-of-the-art plotting and visualization of spatiotemporal data records, and (4) integrating seamlessly with a distributed workflow system using a RESTful interface. ASCEM projectscientists have been using this data gateway since 2011.

ASCEM, Akuna, Database Management↗
DOE OSTI2014

InterMine Webservices for Phytozome (Rev2)

A datawarehousing framework for information provides a useful infrastructure for providers and users of genomic data. For providers, the infrastructure give them a consistent mechanism for extracting raw data. While for the users, the web services supported by the software allows them to make complex, and often unique, queries of the data. Previously, phytozome.net used BioMart to provide the infrastructure. As the complexity, scale and diversity of the dataset as grown, we decided to implement an InterMine web service on our servers. This change was largely motivated by the ability to have a more complex table structure and richer web reporting mechanism than BioMart. For InterMine to achieve its more complex database schema it requires an XML description of the data and an appropriate loader. Unlimited one-to-many and many-to-many relationship between the tables can be enabled in the schema. We have implemented support for:1.) Genomes and annotations for the data in Phytozome. This set is the 48 organisms currently stored in a back end CHADO datastore. The data loaders are modified versions of the CHADO data adapters from FlyMine. 2.) Interproscan results from all proteins in the Phytozome database. 3.) Clusters of proteins into a grouped heirarchically by similarity. 4.) Cufflinks results from tissue-specific RNA-Seq data of Phytozome organisms. 5.) Diversity data (GATK and SnpEFF results) from a set of individual organism. The last two datatypes are new in this implementation of our web services. We anticipate that the scale of these data will increase considerably in the near future.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

SU-E-T-241: Design and Implement of An Information Management System for Radiation Workers in a Hospital

Purpose: To meet the special needs of Medical Administration Division, an information management system for radiation workers in a hospital(IMSRWH) has been developed. Methods: There are about 200 radiation workers in 20 departments, such as department of radiology, department of radiation oncology, department of nuclear medicine, and so on. An IMSRWH server was used to run a database and web service of Apache+PHP+MySQL. The IMSRWH web service could be accessed with Internet Explorer(IE) to input, search, count, and print the radiation workers’ data. Every worker’s data information includes the following tables: registration, personal dose monitoring records, personnel certificate, training certificate, personnel license, medical examination, etc, and each table includes more optional detail information. Results: In the past year, the IMSRWH has been successfully developed and implemented in the hospital. According to the needs, the user rights are divided into: the system administrator, office manager, department manager and radiation worker. The different users have the different interfaces, and the appropriate authority permissions mean corresponding operations. The administrator and office manager could manage all personnel information, department manager could manage the staff information of his department, and the workers could view or modify their own information. Because information updates, involving hundreds of each entry and modification are complicated, each table information of all workers can be batch import from or export to a Microsoft Excel CSV format file, to update all together. However, it has only Chinese version now. Conclusion: It was demonstrated to be user-friendly and was proven to significantly improve the efficiency of the hospital management. Since it is an in-house developed system, more functions can be added or modified to further enhance its potentials in research and clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Development of an end state vision to implement digital monitoring in nuclear plants

Transitioning from an onsite Maintenance & Diagnostics Center to cloud-based services offers many new opportunities with computing power and storage, but also new challenges in terms of networking and security. This report will cover everything required for that transition including data processing and uploading to cloud services, feature selection, model creation, and result visualization for decision making. Although there are several other cloud-based services (e.g. Amazon Web Services and Google Cloud), this report explores Microsoft Azure to simplify nomenclature and maintain a consistent focus. Many of the services offered by Microsoft Azure are also available in the other cloud-based services, and their differences have been recorded in other literature. The Azure services most important to a nuclear power plant including networking & security, storage & databases, and Artificial Intelligence (AI) are reviewed here. Networking covers all aspects related to communication to Azure resources including security, privacy, and redundancy. Storage & databases includes data storage, upgrading, patching, backups, and monitoring. The AI services allows the user access to the machine learning (ML) techniques developed with Azure including automated ML, anomaly detection, computer vision, and natural language processing. This report summaries the features, capabilities, and challenges when using cloud-based services in a user-friendly manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗