1. a. The New Jersey Big Data Alliance is designated as the State‘s advanced cyberinfrastructure consortium. The purpose of the consortium shall be to encourage State government, academia, and industry to address, in a strategic and coordinated manner, the significant and immediate challenges posed by the proliferation of big data sources and the resultant deluge of digital data. Major initiatives may include, but not be limited to: (1) encouraging the creation of joint education programs, including the establishment of a common curriculum for data sciences and the creation of coordinated certificates, workforce training, and outreach programs; (2) promoting inter-university research collaborations; (3) catalyzing interaction with national and international data consortiums, such as the National Consortium for Data Science; (4) organizing events that promote big data education and collaborating across State government, academia, and industry; (5) collaborating with the Rutgers Discovery Informatics Institute and the Office of Information Technology to develop an advanced cyberinfrastructure plan for the State; and (6) developing a shared data cloud that integrates data infrastructure, hosted data, and data analytics.

b. The New Jersey Big Data Alliance shall consist of the following members: Rutgers, the State University; Princeton University; New Jersey Institute of Technology; Rowan University; the Richard Stockton College of New Jersey; Kean University; Montclair State University; and the Stevens Institute of Technology. The New Jersey Big Data Alliance shall determine the appropriate size of its membership and admit future members as the alliance deems appropriate.

c. As used in this section:

“Big data” means high volume information assets, high velocity information assets, high variety information assets, or all three, that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization.

The term “cyberinfrastructure” includes, but is not limited to, data networks, computational facilities, computing resources, large data sets, specialized software applications, information technology usage improvements, and the human expertise necessary to develop and manage these resources.

L.2014, c.33, s.1.