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Session: BIG DATA: Balancing Impacts, Investments and Education

BIG DATA: Balancing Impacts, Investments and Education

Today, 3:30 PM –  5:00 PM
Grand Ballroom at Hyatt at the Bellevue
200 S Broad Street
Philadelphia, Pennsylvania 19102

Part of the 2017 ESS/SAES/ARD Fall Meeting: A Question of Balance (

Jane Greenberg participated in BIG DATA: Balancing Impacts, Investments and Education, presenting, “Metadata Solutions for Sharing Restricted Data.”

Big data is the next revolution in agriculture and natural resources. Emerging technologies for accelerating plant breeding, monitoring crop growth, fertilization, soil conditions, water availability, pests and other management aspects are creating enormous amounts of heterogeneous data at increasingly granular scales. Data analytics are optimizing supply chains, reducing waste within the system, correlating consumer food choices with health outcomes, and allowing researchers to integrate the broad array of geospatial and –omics data in creative ways. Jane Greenberg to contributs to the session, presenting, Metadata Solutions for Sharing Restricted Data

ABSTRACT: Data sharing between different stakeholders in industry, research, and academia is normally encumbered by excessive use restrictions due to legal concerns and policies. Well-intentioned data sharing plans frequently fail due to prohibitive investment requirements and protracted negotiations. This presentation recognizes these challenges, and will highlight initial metadata-driven work helping to address current obstacles, as part of the NSF Spoke Initiative-A Licensing Model and Ecosystem for Data Sharing, connect with the NSF/Northeast Big Data Innovation Hub. We are creating a licensing model for sharing closed and not necessarily free data, and developing a prototype software platform that enforces data sharing conditions and restrictions.  The presentation will address the larger context of this research, introduce the NSF spoke project, and present initial results of a semantic analysis and attribute clustering study that is informing prototype system development.



Metadata Research Center, College of Computing and Informatics, Drexel University:

A Licensing Model and Ecosystem for Data Sharing:

Northeast Big Data Innovation Hub: