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Open-Source Pipeline for Large-Scale Data Processing, Analysis and Collaboration

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC18C0061
Agency Tracking Number: 174313
Amount: $749,870.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: S5
Solicitation Number: SBIR_17_P2
Timeline
Solicitation Year: 2017
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-04-24
Award End Date (Contract End Date): 2020-04-23
Small Business Information
16 Great Hollow Road, Hanover, NH, 03755-3116
DUNS: 072021041
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jerry Bieszczad
 (603) 640-2445
 jyb@creare.com
Business Contact
 Sheryl Belanger
Phone: (603) 643-3800
Email: contractsmgr@creare.com
Research Institution
N/A
Abstract

NASA's observational products generate petabytes of scientific data, which are highly underutilized due to computational requirements; disjoint data access protocols; and task-specific, non‑reusable code development. Our overall objective is to accelerate NASA science through development of an open-source, Python-based Pipeline for Observational Data Processing, Analysis, and Collaboration (PODPAC).  The PODPAC software framework will enable widespread exploitation of earth science data by enabling multi-scale and multi-windowed access, exploration, and integration of available earth science datasets to support both analysis and analytics; automatically accounting for geospatial data formats, projections, and resolutions; simplifying implementation and parallelization of geospatial data processing routines; unifying sharing of data and algorithms; and enabling seamless transition from local development to cloud processing. To achieve these objectives, we will work with NASA Science Team members involved with the SMAP (Soil Moisture Active Passive) and EOSDIS (Earth Observing System Data and Information System) programs and the wider scientific community to define technical specifications for the software, and plan a list of prioritized enhancements for each quarterly release cycle; further develop the core Python library based on user feedback and using agile development practices; develop integrations with cloud computing resources, specifically targeting Amazon Web Services; develop and demonstrate best-available remotely sensed soil moisture, high-resolution downscaled soil moisture, and flood/drought monitoring applications to promote infusion into NASA programs; and engage with scientific community through conferences, meetings, webcasts, and by providing support in order to promote adoption of the software.

* Information listed above is at the time of submission. *

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