Big Data Paper Wins Best Paper at ASE/IEEE International Conference on Big Data

September 23, 2013

Dr. Arcot RajasekarDr. Arcot Rajasekar, professor at the School of Information and Library Science at University of North Carolina at Chapel Hill, and his colleagues were pleasantly surprised when their paper won best paper award at the Academy of Science and Engineering/Institute of Electrical and Electronics Engineers (ASE/IEEE) International Conference on Big Data held in Washington, D.C. Sept. 8 – 14, 2013. The paper was titled “The Data Bridge: Sociometric Methods for Long-Tail Scientific Data.”

The “2013 ASE/IEEE International Conference on Big Data aim is to bring together academic scientists, researchers and scholars to exchange and share their experiences and research results in Advancing Big Data Science & Engineering” according to the conference Web site.  

The paper, which was chosen through a blind selection process, was a collaboration between Rajasekar, and his UNC at Chapel Hill colleagues who included: Jonathan Crabtree, SILS Ph.D. student and assistant director of Computing and Archiving in the H.W. Odum Institute for Social Science Research; Howard Lander, RENCI Senior Research Software Developer; RENCI Executive Director, Sharlini Sankaran; UNC Political Science Distinguished Professor and Director of the H.W. Odum Institute for Social Science Research, Thomas M. Carsey; Hye-Chung Kum, research associate professor, School of Social Work and Department of Computer Science; and colleagues from Harvard University, North Carolina State University, North Carolina A&T and Texas A&M University.

“This paper is based on our project called ‘Data Bridge’ which is funded by the National Science Foundation (NSF) under the Big Data program,” said Rajasekar. “The project tries to use social media-type algorithms to link and aggregate scientific data - in a sense form data communities - based on their characteristic signatures. It is an ambitious project and this paper describes some of the main aspects of this project.”

After months of work on this paper and the project proposal to the NSF, Rajasekar’s hard work has already paid off.

“It feels great [to have won this award],” Rajasekar said. “I was not expecting anything like this, and it caught me by surprise—a pleasant surprise.”

Excerpt from Abstract:
 “As the push towards electronic storage, publication, curation and discoverability of research data collected in multiple research domains has grown, so too have the massive numbers of small to medium datasets that are highly distributed and not easily discoverable—a region of data that is sometimes referred to as the long tail of science. The rapidly increasing, sheer volume of these long tail data present one aspect of the Big Data problem: how does one  more easily access, discover, use, and reuse long tail data to lead to new multidisciplinary collaborative research and scientific advancement? In this paper, we describe DataBridge, a new e-science collaboration environment that will realize the potential of long tail data by implementing algorithms and tools to more easily enable data discoverability and reuse.”

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