CREW Services LLC — Department of Energy SBIR Phase I: High-resolution and accurate terrestrial moisture, temperature and carbon conditions are i

Description

High-resolution and accurate terrestrial moisture, temperature and carbon conditions are increasingly demanded for precision energy, agriculture, water, and disaster management. However, the required information must be integrated and inferred from huge volumes of satellite, in-situ, and morel information that is produced by many different agencies and organizations. To address these issues, the Land Information System (LIS) was developed to use advanced flexible land surface modeling and data assimilation frameworks to integrate extremely large satellite- and ground-based observations with advanced land surface models to produce continuous high-resolution fields of land surface states and fluxes. The resulting fields are extremely useful for drought and flood assessment, agricultural planning, disaster management, weather and climate forecasting, water resources assessment, and the like. LIS currently only runs on specialized high-end computing platforms, which severely limits its use by the private sector or general users. There are essentially four barriers for wider utility and commercialization of LIS: (1) High-performance computing LIS currently exclusively runs on traditional high-performance computing platforms with specialized compilers and libraries that are not available to common users; (2) Big Data: LIS uses extremely large high-resolution spatiotemporal data compiled from in-situ, satellite and weather forecasts that are too extensive for casual users to compile; (3) User-interface: LIS lacks a seamless user- friendly control panel or graphical user interface (GUI) to control and visualize simulations; and (4) the LIS software has some very complex code heritage uncertainties that currently limit its wider licensing and use. CREW Services LLC (CREW a small female- and veteran-owned business) proposes to transform the LIS modeling system into a scientific cloud computing-aware web and data service. It is envisioned that this service will optimize the elasticity and performance of the LIS model-data interface including user-data access services, and will establish a user-friendly control and visualization interface. This innovation will essentially package LIS with a user-focused interface that seamlessly access cloud computing and data resources. The CREW proposed solution will be a 100% web-based cloud solution so that small research firms and individual practitioners will not have to have an IT department and extensive hardware to install and maintain it. It will be easy to setup and configure to keep upfront cost down and allow clients to get started quickly. The solution will cover the entire lifecycle of a LIS project so that small clients do not have to use multiple products and try to get them to interoperate. The focus of this Phase 1 proposal will be to determine the scientific, technical, commercial merit and feasibility of the proposed LIS-cloud innovations that are currently barriers to broad LIS applicability. Specifically, we will (a) quantify the four previously outlined barriers to broad LIS utility and commercialization (high performance computing, big data, user interface, and licensing issues); (b) design the proposed LIS-cloud web service, model-data interface, database services, and user interfaces; (c) construct a prototype LIS user interface including abstractions for simulation control, visualization, and data interaction, (d) use the prototype to conduct a market analysis and survey to determine potential market size and competition, (e) identify LIS software licensing and copyright limitations and develop solutions in partnership with HSL, and (f) develop a business plan for development and marketing of the LIS-cloud innovation. Provided the sound basis for the continued LIS-cloud development, demonstration and delivery of the full innovation will be pursued in Phase II efforts. Evolving LIS into a cloud-aware service and database with user-friendly interfaces will broaden its utility in the natural hazard, weather/climate projection, water resources, mobility and operations, health and welfare, and agricultural sectors by facilitating client access, scalability, timeliness and functionality. This proposed work will stimulate private sector technological innovation that is directly relevant to Federal research and development needs, and has a good potential to enable the commercial application of the LIS research results. This proposed project is directly relevant to the 2014 DOE/SBIR subtopic 1c: Big-Data-Aware Middleware and Networking. Specifically, high-resolution modeling and data assimilation exactly the intent of the LIS system design continues to challenge even the largest data systems. As new land observations come on line, and resolutions increase these data volumes will increase as well. In direct relevance to subtopic 1c, this project proposes to develop big-data scalable data analysis and visualization tools to not only aid in knowledge and discovery, but also in synthesis and integration. Further, transforming LIS into a cloud service will accelerate the use of commodity parallel processing, high performance file systems, large scientific data management and visualization, and large scale data movement and virtualization in model-data interaction. Finally, the proposed innovation fully embraces the subtopic goals to develop close partnerships with scientists and programs, such as the enhancement of existing DOE software, on-line data/computing services, and web services that promote interoperability and use standard protocols, file formats and Application Programming Interfaces. Commercial Applications and Other Benefits: If fully successful through Phase II, this project will mitigate the major barriers (high performance computing, big data, user interface, and licensing issues) for wider utility and commercialization of the Land Information System, essentially packaging LIS with a user-focused interface that seamlessly accesses cloud computing and data resources. The resulting scientific cloud computing-aware LIS web and data service will optimize the elasticity and performance of the LIS model-data interface including user-data access services, and will establish a user-friendly LIS control and visualization interface. Transforming LIS into a cloud-aware service and database with user-friendly interfaces will broaden its utility in the natural hazard, weather/climate projection, water resources, mobility and operations, health and welfare, and agricultural sectors by facilitating client access, scalability, timeliness and functionality. This proposed work will stimulate private sector technological innovation that is directly relevant to Federal research and development needs, and has a good potential to enable the commercial application of the LIS research results. The LIS development and user community is very interested in these proposed LIS extensions, and believes that the enhanced system can provide a broad public sector benefit. Delivering the software and data as a cloud service will also make LIS significantly more useful and accessible to LIS researchers and partners.