Description: The ability to utilize the vast amounts of remote sensing data such as Earth observations currently requires significant efforts by experts in multiple domains. Further hindering the utilization of related information is the computational resources required to effectively store, access, and process the data. However, by utilizing the ever-increasing power of cloud computing, recent advances in computational fusion mechanisms, and emerging programming paradigms government agencies and the public at large can efficiently generate tools which utilize this data resulting in an increased return on investment. Geocent proposes the development of the Cloud-Based Open Data Environment and Flow-based Aggregation Science Tool (CODEFAST) a data processing framework and user-friendly platform, which will allow the efficient creation, customization, and processing of Decision Support Tools (DST) by different users in varied fields. The proposed architecture of CODEFAST is comprised of two main components: a Computational Fusion Platform (CFP) and a Flow-Based Programming Interface (FPI). By combining the capabilities of CODEFAST with the flexible and cost effective nature of commercial cloud-computing services the system can provide an easy to use mechanism for processing Earth science data in a high-performance computing environment.

Benefits: CODEFAST is the logical evolution of data access for both discovery and analysis. The advent of cost effective sensors and multiband remote sensing is delivering data at an unprecedented pace. A second order effect of this advance is the multiple incompatible formats, storage methods, and access barriers that result when interoperability is an afterthought of the development as well as programs built for solving specific programs within a domain. The use of CODEFAST opens new opportunities for analysis and research to add additional data sets that were once through to be isolated due to their formatting or the inability for the user side platform being able to access this information efficiently as well as the computing power that may not reside with the agency attempting the research. The proposed solution has an immediate application to NASA Earth Sciences but this extends to other organizations and agencies that share a similar dilemma.

Similar situations exist beyond the geosciences that would find use with CODEFAST. Several government agencies such as National Oceanographic and Atmospheric Agency (NOAA), the Department of Defense (DoD) and the Department of Homeland Security (DHS) have needs for data modeling and analysis that combines several disparate data sets. The true value of data is in its ability to integrate into analysis and study. CODEFAST would provide this capability and support the extension of current practices and methods for storage, access, and computing. More reliable forecast models that incorporate once inaccessible variables, intelligence correlations from multiple sources and the support to drive these computational intensive operations are possible utilizing this construct.