NSF Org:	IIS Div Of Information & Intelligent Systems
Recipient:	AMERICAN STATISTICAL ASSOCIATION
Initial Amendment Date:	September 1, 2021
Latest Amendment Date:	September 6, 2023
Award Number:	2123321
Award Instrument:	Continuing Grant
Program Manager:	Christopher Stark cstark@nsf.gov  (703)292-4869 IIS  Div Of Information & Intelligent Systems CSE  Direct For Computer & Info Scie & Enginr
Start Date:	September 1, 2021
End Date:	August 31, 2024 (Estimated)
Total Intended Award Amount:	$1,500,000.00
Total Awarded Amount to Date:	$1,500,000.00
Funds Obligated to Date:	FY 2021 = $600,000.00 FY 2022 = $400,000.00 FY 2023 = $500,000.00
History of Investigator:	Mark Ward (Principal Investigator) mdw@purdue.edu Monica Jackson (Co-Principal Investigator) Talitha Washington (Co-Principal Investigator) Katherine Ensor (Co-Principal Investigator) Donna LaLonde (Co-Principal Investigator)
Recipient Sponsored Research Office:	American Statistical Association 732 N WASHINGTON ST ALEXANDRIA VA  US  22314-1925 (703)684-1221
Sponsor Congressional District:	08
Primary Place of Performance:	American Statistical Association 732 North Washington Street Alexandria VA  US  22314-1943
Primary Place of Performance Congressional District:	08
Unique Entity Identifier (UEI):	D3JBDRXT82B5
Parent UEI:
NSF Program(s):	HDR-Harnessing the Data Revolu, INFRASTRUCTURE PROGRAM
Primary Program Source:	01002122DB NSF RESEARCH & RELATED ACTIVIT 01002324DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	062Z
Program Element Code(s):	099Y00, 126000
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.070

ABSTRACT

The data science community has a timely opportunity to reimagine the impact of the data sciences on the economy, and to improve outcomes for communities, by ensuring that students at Minority Serving Institutions have access to cutting edge courses, research opportunities, and industry partnerships. In 2018, Purdue University established The Data Mine, a university-wide undergraduate learning community that teaches data science to participating undergraduates from all majors, regardless of their previous experience. It will scale naturally to a nationwide model because it is accessible, supportive, but also offers genuine data science challenges that motivate students to learn the required competencies. The National Data Mine Network (NDMN) will directly fund 300 undergraduate students at Minority Serving Institutions with research stipends (100 stipends per year), administered directly to students by the American Statistical Association. The leadership team leverages collaborative strengths of the American Statistical Association, the Math Alliance, Purdue University, American University, and the Atlanta University Center Data Science Initiative. The students will use high-performance computing to solve data-driven challenges that arise in every sector of industry, including biomedical engineering, healthcare engineering, image processing, manufacturing, supply chain management, and transportation.

This project will enable undergraduate students to learn data science with hands-on work, in research or data science projects informed by industry partners. Each participating institution will have a node led by faculty members and 3-4 undergraduate students. All faculty members will share their best practices about mentoring research, how to establish mutually beneficial relationships with industry partners in their community, and how to develop institutional mechanics to support the work and to build data science programs. Some of the key deliverables of this HDR DSC project will be: well-documented projects for courses and for student research, a robust online training resource of data science projects, an instructor handbook that accompanies the data science projects, a development curriculum for the faculty to grow their own skills, and promising best practices on how faculty can develop relationships with mentors from industry for real-world data-driven projects. A key benefit of the NDMN to faculty is the ability to inject data science skills into their careers, to gain knowledge and expertise about how to carry out hands-on, data-intensive research projects, as well as the potential to develop new industry partnerships, while also building their own data science courses and programs. Another key impact will be a tightly knit community supporting a new generation of 300 diverse undergraduate trainees in the data sciences. A third key impact will be a nationwide network of faculty who work together to build these data science courses, programs, and industry partnerships at Minority Serving Institutions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Please report errors in award information by writing to: awardsearch@nsf.gov.