Search NASA⌕ Search

Engineering topics

Corrigan, Abigail L.

Publications and source records attributed to Corrigan, Abigail L..

Velo and REXAN - Integrated Data Management and High Speed Analysis for Experimental Facilities

The Chemical Imaging Initiative at the Pacific Northwest National Laboratory (PNNL) is creating a ‘Rapid Experimental Analysis’ (REXAN) Framework, based on the concept of reusable component libraries. REXAN allows developers to quickly compose and customize high throughput analysis pipelines for a range of experiments, as well as supporting the creation of multi-modal analysis pipelines. In addition, PNNL has coupled REXAN with its collaborative data management and analysis environment Velo to create an easy to use data management and analysis environments for experimental facilities. This paper will discuss the benefits of Velo and REXAN in the context of three examples: PNNL High Resolution Mass Spectrometry - reducing analysis times from hours to seconds, and enabling the analysis of much larger data samples (100KB to 40GB) at the same time · ALS X-Ray tomography - reducing analysis times of combined STXM and EM data collected at the ALS from weeks to minutes, decreasing manual work and increasing data volumes that can be analysed in a single step ·Multi-modal nano-scale analysis of STXM and TEM data - providing a semi automated process for particle detection The creation of REXAN has significantly shortened the development time for these analysis pipelines. The integration of Velo and REXAN has significantly increased the scientific productivity of the instruments and their users by creating easy to use data management and analysis environments with greatly reduced analysis times and improved analysis capabilities.

Kleese van Dam, Kerstin↗

Designing the Cloud-based DOE Systems Biology Knowledgebase

Systems Biology research, even more than many other scientific domains, is becoming increasingly data-intensive. Not only have advances in experimental and computational technologies lead to an exponential increase in scientific data volumes and their complexity, but increasingly such databases themselves are providing the basis for new scientific discoveries. To engage effectively with these community resources, integrated analyses, synthesis and simulation software is needed, regularly supported by scientific workflows. In order to provide a more collaborative, community driven research environment for this heterogeneous setting, the Department of Energy (DOE) has decided to develop a federated, cloud based cyber infrastructure - the Systems Biology Knowledgebase (Kbase). Pacific Northwest National Laboratory (PNNL) with its long tradition in data intensive science lead two of the five initial pilot projects, these two focusing on defining and testing the basic federated cloud-based system architecture and develop a prototype implementation. Hereby the community wide accessibility of biological data and the capability to integrate and analyze this data within its changing research context were seen as key technical functionalities the Kbase needed to enable. In this paper we describe the results of our investigations into the design of a cloud based federated infrastructure for: (1) Semantics driven data discovery, access and integration; (2) Data annotation, publication and sharing; (3) Workflow enabled data analysis; and (4) Project based collaborative working. We describe our approach, exemplary use cases and our prototype implementation that demonstrates the feasibility of this approach.

99 GENERAL AND MISCELLANEOUS↗