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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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NASA NTRS2020

Systems Development, Datamining and Knowledge Discovery Abstract

This summer, 2020, during my NASA internship I worked with my mentor, Ali Shaykhian, as well as a group of four other interns: Javel Gramling, Janelisse Morales, Tristian Running Crane, and Zulmarie Jiménez. Our research and projects all differ but work together to solve datamining unstructured data into an easy to read format. Turning unstructured data into something easier to follow is important for helping quickly pull data out of larger documents, so that one doesn’t have to go through multiple pages to find certain data points. By being able to structure data pulled from a document, it can be usedto collect data from mass amounts of forms and arrange it in an easy to glance at table instead of multiple forms. I chose to focus mainly on creating form templates with both Microsoft Word and Excel and getting used to the types of data that can be collected; as well as learning where both programs differed. After I was familiar with what could be gathered, I worked towards taking data collected by a Word form and importing it into an Excel spreadsheet. By being able to transfer data from a Word document to an Excel document, there is an added layer of functionality to the datamining. Moving data around between Excel sheets isn’t that complex of a process, but when you try to import from a Word document a lot of formatting and readability can be lost. The purpose of my research is to reduce that loss by using Visual Basic scripts to clean and arrange imported data.

Makayla Amber Renfro↗
NASA NTRS2000

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Dhaeseleer, Patrik↗
NASA NTRS2011

Report on the Global Data Assembly Center (GDAC) to the 12th GHRSST Science Team Meeting

In 2010/2011 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational Group for High Resolution Sea Surface Temperature (GHRSST) datastreams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Here we report on our data management activities and infrastructure improvements since the last science team meeting in June 2010.These include the implementation of all GHRSST datastreams in the new PO.DAAC Data Management and Archive System (DMAS) for more reliable and timely data access. GHRSST dataset metadata are now stored in a new database that has made the maintenance and quality improvement of metadata fields more straightforward. A content management system for a revised suite of PO.DAAC web pages allows dynamic access to a subset of these metadata fields for enhanced dataset description as well as discovery through a faceted search mechanism from the perspective of the user. From the discovery and metadata standpoint the GDAC has also implemented the NASA version of the OpenSearch protocol for searching for GHRSST granules and developed a web service to generate ISO 19115-2 compliant metadata records. Furthermore, the GDAC has continued to implement a new suite of tools and services for GHRSST datastreams including a Level 2 subsetter known as Dataminer, a revised POET Level 3/4 subsetter and visualization tool, a Google Earth interface to selected daily global Level 2 and Level 4 data, and experimented with a THREDDS catalog of GHRSST data collections. Finally we will summarize the expanding user and data statistics, and other metrics that we have collected over the last year demonstrating the broad user community and applications that the GHRSST project continues to serve via the GDAC distribution mechanisms. This report also serves by extension to summarize the activities of the GHRSST Data Assembly and Systems Technical Advisory Group (DAS-TAG).

sea surface temperature (SST)↗