How Can Small Businesses Tackle Big Data Challenges?

SMITH BRAIN TRUST – For small to midsized businesses, like their larger counterparts, success correlates with being adept in locating useful knowledge in an interlinked web of financial entities and networks, supply chains and ecosystems. Likewise, analysts and regulators are challenged in terms of monitoring, integrating and analyzing data at scale.

Challenges in this realm include identifying and classifying entities, as well as understanding the relationships among entities, and "ideally, Open Knowledge Networks (OKN) will be created to capture such knowledge," says professor Louiqa Raschid at the University of Maryland's Robert H. Smith School of Business. She is helping to organize and direct teams of academics and industry experts in a research challenge dedicated to this subject. It’s called the Financial Entity Identification and Information Integration (FEII) Challenge.  

The 2019 edition of the FEII Challenge involves tasks based on activity data of small-to-medium-size food and beverage sellers and distributors based in California and U.S. Customs and Border Protection Agency "Bill of Lading" data for all incoming shipments into U.S. ports of entry in 2018. 

The results will be showcased as part of Workshop on Data Science for Macromodeling on June 30, 2019, in Amsterdam.

"Creating such OKN resources potentially will lead to improved resources and tools for regulators, analysts and entrepreneurs," Raschid says. The results also may include “new ways to reach consumers and to exploit the wisdom of the crowds.”

Sponsored by the University of University of Maryland, the FEII Challenge has been supported by grants from the Office of Financial Research, the National Institute of Standards and Technology and the National Science Foundation.

Louiqa Raschid is a professor of information systems for the University of Maryland’s Robert H. Smith School of Business and holds appointments with UMD’s Institute for Advanced Computing Studies (UMIACS) and the Department of Computer Science. 

Research interests: Data management and data science, with a strong link to diverse applications, including the life sciences and health sciences, humanitarian disaster relief applications, human behavior modeling within social streams, and the modeling and management of financial ecosystems.

Selected accomplishments: About 150 papers in leading journals/conferences and covering databases, scientific computing, Web data management, bioinformatics and artificial intelligence; research awards including more than 25 grants from the National Science Foundation and DARPA; founding director of the Sahana FOSS project for disaster information management; evangelist for financial data science; Fellow of the ACM.

About this series: Maryland Smith celebrates Women Leading Research during Women’s History Month. The initiative is organized in partnership with ADVANCE, an initiative to transform the University of Maryland by investing in a culture of inclusive excellence. Other Women's History Month activities include the eighth annual Women Leading Women forum on March 5, 2019.

Other fearless ideas from:  Rajshree Agarwal  |  Ritu Agarwal  |  T. Leigh Anenson  |  Kathryn M. Bartol  |  Christine Beckman  |  Margrét Bjarnadóttir  |  M. Cecilia Bustamante  |  Jessica M. Clark  |  Rellie Derfler-Rozin  |  Waverly Ding  |  Wedad J. Elmaghraby  |  Rosellina Ferraro  |  Rebecca Hann  | Amna Kirmani  |  Hanna Lee  |  Hui Liao  |  Jennifer Carson Marr  |  Wendy W. Moe  |  Courtney Paulson  |  Louiqa Raschid  |  Rebecca Ratner  |  Rachelle Sampson  |  Debra L. Shapiro  |  M. Susan Taylor  |  Niratcha (Grace) Tungtisanont  |  Vijaya Venkataramani  |  Janet Wagner  |  Yajin Wang  | Liu Yang  |  Jie Zhang  |  Lingling Zhang