Eric G. Stephan

A collaborative informatics infrastructure for multi-scale science

The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information in support of systems-based research and is applying it within combustion science. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.

Intensity-Value Corrections for Integrating Sphere Measurements of Solid Samples Measured Behind Glass

Accurate and calibrated directional-hemispherical reflectance spectra of solids are important for both in situ and remote sensing. Many solids are in the form of powders or granules and to measure their diffuse reflectance spectra in the laboratory, it is often necessary to place the samples behind a transparent medium such as glass for the ultraviolet (UV), visible, or near-infrared spectral regions. Using both experimental methods and a simple optical model, we demonstrate that glass (fused quartz in our case) leads to artifacts in the reflectance values. We report our observations that the measured reflectance values, for both hemispherical and diffuse reflectance, are distorted by the additional reflections arising at the air–quartz and sample–quartz interfaces. The values are dependent on the sample reflectance and are offset in intensity in the hemispherical case, leading to measured values up to ∼6% too high for a 2% reflectance surface, ∼3.8% too high for 10% reflecting surfaces, approximately correct for 40–60% diffuse-reflecting surfaces, and ∼1.5% too low for 99% reflecting Spectralon® surfaces. For the case of diffuse-only reflectance, the measured values are uniformly too low due to the polished glass, with differences of nearly 6% for a 99% reflecting matte surface. The deviations arise from the added reflections from the quartz surfaces, as verified by both theory and experiment, and depend on sphere design. Empirical correction factors were implemented into post-processing software to redress the artifact for hemispherical and diffuse reflectance data across the 300–2300 nm range.

Open data management solutions for problem solving environments: application of distributed authoring and versioning to the Extensible Computational Chemistry Environment

Next-generation problem solving environments (PSEs) promise significant advances over those now available. They will span scientific disciplines and incorporate collaboration capabilities. They will host feature-detection and other agents, allow data mining and pedigree tracking, and provide access from a wide range of devices. Fundamental changes in PSE architecture are required to realize these and other PSE goals. This paper focuses specifically on issues related to data management and recommends an approach based on open, metadata-driven repositories with loosely defined, dynamic schemas. Benefits of this approach are discussed and the redesign of the Extensible Computational Chemistry Environments (Ecce) data storage architecture to use such a repository is described, based on the distributed authoring and versioning (DAV) standard. The suitability of DAV for scientific data, the mapping of the Ecce schema to DAV, and promising initial results are presented.

Demonstrated Wavelength Portability of Raman Reference Data for Explosives and Chemical Detection

As Raman spectroscopy continues to evolve, questions arise as to the portability of Raman data: dispersive versus Fourier transform, wavelength calibration, intensity calibration, and in particular the frequency of the excitation laser. While concerns about fluorescence arise in the visible or ultraviolet, most modern (portable) systems use near-infrared excitation lasers, and many of these are relatively close in wavelength. We have investigated the possibility of porting reference data sets from one NIR wavelength system to another: We have constructed a reference library consisting of 145 spectra, including 20 explosives, as well as sundry other compounds and materials using a 1064 nm spectrometer. These data were used as a reference library to evaluate the same 145 compounds whose experimental spectra were recorded using a second 785 nm spectrometer. In 128 cases of 145 (or 88.3% including 20/20 for the explosives), the compounds were correctly identified with a mean “hit score” of 954 of 1000. Adding in criteria for when to declare a correct match versus when to declare uncertainty, the approach was able to correctly categorize 134 out of 145 spectra, giving a 92.4% accuracy. For the few that were incorrectly identified, either the matched spectra were spectroscopically similar to the target or the 785 nm signal was degraded due to fluorescence. The results indicate that imported data recorded at a different NIR wavelength can be successfully used as reference libraries, but key issues must be addressed: the reference data must be of equal or higher resolution than the resolution of the current sensor, the systems require rigorous wavelength calibration, and wavelength-dependent intensity response should be accounted for in the different systems.

A Web-Based Data Architecture for Problem-Solving Environments: Application of Distributed Authoring and Versioning to the Extensible Computational Chemistry Environment

Next-generation problem-solving environments (PSEs) promise significant advances over those now available. They will span scientific disciplines and incorporate collaboration capabilities. They will host feature-detection and other agents, allow data mining and pedigree tracking, and provide access from a wide range of devices. Fundamental changes in PSE architecture are required to realize these and other PSE goals. This paper focuses specifically on issues related to data management and recommends an approach based on open, metadata-driven repositories with loosely defined, dynamic schemas. Benefits of this approach are discussed, and the redesign of the Extensible Computational Chemistry Environments (Ecce) data storage architecture to use such a repository is described, based on the distributed authoring and versioning (DAV) standard. The suitability of DAV for scientific data, the mapping of the Ecce schema to DAV, and promising initial results are presented.

Leveraging the Open Provenance Model as a Multi-tier Model for Global Climate Research

Global climate researchers rely upon many forms of sensor data and analytical methods to help profile subtle changes in climate conditions. The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) program provides researchers with a collection of curated Value Added Products (VAPs) resulting from continuous sensor data streams, data fusion, and modeling. We are leveraging the Open Provenance Model as a foundational construct that serves the needs of both the VAP producers and consumers. We are organizing the provenance in different tiers of granularity to model VAP lineage, causality at the component level within a VAP, and the causality for each time step as samples are being assembled within the VAP. This paper shares our implementation strategy and how the ARM operations staff and the climate research community can greatly benefit from this approach to more effectively assess and quantify VAP provenance.

Data provenance hybridization supporting extreme-scale scientific workflow applications

As high performance computing (HPC) infrastructures continue to grow in capability and complexity, so do the applications that they serve. HPC and distributed-area computing (DAC) (e.g. grid and cloud) users are looking increasingly toward workflow solutions to orchestrate their complex application coupling, pre- and post-processing needs. To that end, the US Department of Energy Integrated end-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) project is currently investigating an integrated approach to prediction and diagnosis of these extreme-scale scientific workflows. To gain insight and a more quantitative understanding of a workflows performance our method includes not only the capture of traditional provenance information, but also the capture and integration of system environment metrics helping to give context and explanation for a workflows execution. In this paper, we describe IPPDs provenance management solution (ProvEn) and its hybrid data store combining both of these data provenance perspectives. We discuss design and implementation details that include provenance disclosure, scalability, data integration, and a discussion on query and analysis capabilities. We also present use case examples for climate modeling and thermal modeling application domains.

Effective Tooling for Linked Data Publishing in Scientific Research

Challenges that make it difficult to find, share, and combine published data, such as data heterogeneity and resource discovery, have led to increased adoption of semantic data standards and data publishing technologies. To make data more accessible, interconnected and discoverable, some domains are being encouraged to publish their data as Linked Data. Consequently, this trend greatly increases the amount of data that semantic web tools are required to process, store, and interconnect. In attempting to process and manipulate large data sets, tools -- ranging from simple text editors to modern triplestores -- eventually breakdown upon reaching undefined thresholds. This paper shares our experiences in curating metadata, primarily to illustrate the challenges, and resulting limitations that data publishers and consumers have in the current technological environment. This paper also provides a Linked Data based solution to the research problem of resource discovery, and offers a systematic approach that the data publishers can take to select suitable tools to meet their data publishing needs. We present a real-world use case, the Resource Discovery for Extreme Scale Collaboration (RDESC), which features a scientific dataset(maximum size of 1.4 billion triples) used to evaluate a toolbox for data publishing in climate research. This paper also introduces a semantic data publishing software suite developed for the RDESC project.

Using Domain Requirements to Achieve Science-Oriented Provenance

The US Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) is adopting the use of formalized provenance to support observational data products produced by ARM operations and relied upon by researchers. Because of the diversity of needs in the climate community provenance will need to be conveyed in a domain-oriented context. This paper explores a use case where semantic abstract workflows (SAW) are employed as a means to filter, aggregate, and contextually describe the historical events responsible for the ARM data product the scientist is relying upon.

Semantic catalog of things, services, and data to support a wind data management facility

Transparency and data integrity are crucial to any scientific study wanting to garner impact and credibility in the scientific community. The purpose of this paper is to discuss how this can be achieved using what we define as the Semantic Catalog. The catalog exploits community vocabularies as well as linked open data best practices to seamlessly describe and link things, data, and off-the-shelf (OTS) services to support scientific offshore wind energy research for the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) Wind and Water Power Program. This is largely made possible by leveraging collaborative advances in the Internet of Things (IoT), Semantic Web, Linked Services, Linked Open Data (LOD), and Resource Description Framework (RDF) vocabulary communities, which provides the foundation for our design. By adapting these linked community best practices, we designed a wind characterization Data Management Facility (DMF) capable of continuous data collection, processing, and preservation of in situ and remote sensing instrument measurements. The design incorporates the aforementioned Semantic Catalog which provides a transparent and ubiquitous interface for its user community to the things, data, and services for which the DMF is composed.