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ARS Home » Pacific West Area » Logan, Utah » Pollinating Insect-Biology, Management, Systematics Research » Research » Publications at this Location » Publication #293612

Title: Big data computing: Building a vision for ARS information management

Author
item James, Rosalind
item Lawrence, Carolyn
item Schneider, Sharon
item Van Tassell, Curtis - Curt
item Ahuja, Lajpat
item Baxter, Ivan
item Cannon, Steven
item Lunney, Joan
item Rexroad, Caird
item Sadler, Edward
item Stanton, Thaddeus
item Stephensen, Charles

Submitted to: Agricultural Research Service Publication
Publication Type: Government Publication
Publication Acceptance Date: 3/8/2013
Publication Date: 3/8/2013
Citation: James, R.R., Lawrence, C.J., Papiernik, S.K., Van Tassell, C.P., Ahuja, L.R., Baxter, I.R., Cannon, S.B., Lunney, J.K., Rexroad Iii, C.E., Sadler, J., Stanton, T.B., Stephensen, C.B. 2013. Big data computing: Building a vision for ARS information management. USDA. Agricultural Research Service Publication (White Paper).

Interpretive Summary: On February 5-7, 2013, scientific leaders from the Agricultural Research Service (ARS) held a workshop to identify scientific information management needs within the agency, and to find solutions to address those needs. Workshop participants represented scientists from all National Programs and each geographic area. Speakers from industry, academia, and federal agencies provided information about their experiences with Big Data. Participants were challenged to articulate a vision for ARS information management unconstrained by current ARS capabilities and to formulate a strategy to achieve that vision. This document outlines the recommendations arising from that workshop: 1) Establish an Advisory Committee for Scientific Computing, led by a Chief Scientific Information Officer (CSIO), to coordinate efforts to advance the scientific mission of the agency by developing strategic plans and policies for scientific computing; 2) Conduct an assessment of agency resources associated with scientific computing including human resources, computation hardware, data storage, and network capacity; 3) Develop computing and data policies in support of the scientific mission; 4) Invest in high-priority enhancements in scientific IT capabilities; 5) Develop human resource policies that keep ARS on the scientific forefront; and 6) Promote documentation and sharing of scientific data. The big data workshop and this document provide a snapshot “view from the field” and are the first steps in defining how ARS should improve its use of big data to address agricultural problems, allowing scientists to gain new knowledge and address critical, recalcitrant questions.

Technical Abstract: Improvements are needed within the ARS to increase scientific capacity and keep pace with new developments in computer technologies that support data acquisition and analysis. Enhancements in computing power and IT infrastructure are needed to provide scientists better access to high performance computing, networking, and greater data storage capacity. However, improving scientific capacity as it relates to Big Data involves more than just hardware and software, it also involves communication and personnel issues. Information management within the ARS should give high priority to developing computing, data security, and human resource policies that advance the scientific mission. New methods that enable the use of Big Data are needed, both to facilitate sharing datasets and to make ARS data and software products more easily accessible to customers. The Big Data workshop and this document provide a snapshot “view from the field” and are the first steps in defining how the ARS should improve its use of Big Data to address agricultural problems, allowing scientists to gain new knowledge and address critical, recalcitrant questions. Enabling broad access to data through such systems could eliminate the bottleneck that is beginning to constrain agricultural advancement, opening a world where research is limited only by human creativity, which is boundless.