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A Collaborative, Multinational Cyberinfrastructure for Big Data Analytics

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2014 ASEE Annual Conference & Exposition


Indianapolis, Indiana

Publication Date

June 15, 2014

Start Date

June 15, 2014

End Date

June 18, 2014



Conference Session

Emerging Computing and Information Technologies

Tagged Division

Computing & Information Technology

Page Count


Page Numbers

24.30.1 - 24.30.13



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Paper Authors

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Raymond A. Hansen Purdue University


Tomasz Wiktor Wlodarczyk University of Stavanger

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Dr. Tomasz Wiktor Wlodarczyk is an associate professor in the department of electrical and computer engineering at University of Stavanger in Norway. His work focuses on analysis, storage, and communication in data-intensive computing. His particular interest is time-series storage and analysis. He currently is working on these areas in several research projects including: SEEDS (EU FP7), Safer@Home (RCN), A4Cloud (EU FP7), BigDataCom-PU-UiS (SIU), SCC-Computing (EU FP7). He also has been the program committee chair of IEEE CloudCom – International Conference on Cloud Computing Technology and Science for 2011 and 2012.

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Thomas J. Hacker Purdue University, West Lafayette

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Thomas J. Hacker is an associate professor of computer and information technology at Purdue University in West Lafayette, Ind. His research interests include cyberinfrastructure systems, high performance computing, and the reliability of large-scale supercomputing systems. He holds a Ph.D. in computer science and engineering from the University of Michigan, Ann Arbor. He is a member of IEEE, the ACM, and ASEE.

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A collaborative, multinational curriculum and cyberinfrastructure for big data analyticsThe emergence of Big Data and Data Intensive Systems as specialized fields in computing isdriving the need for the development of new courses and curricula. Additionally, the skills andknowledge from these specializations are needed to support analytics for many other disciplines,such as life sciences or the financial industry. This paper details the curriculum and supportingcyberinfrastructure for the graduate-level course developed and delivered between X Universityand Y University. This course was delivered in a synchronous manner between the twouniversities, with faculty from both universities delivering portions of the curriculum.We detail the pedagogy of each major curriculum topics and the mapping of those topics tocourse outcomes which potentially support the specialized computing areas. We frame thesecurricular topics with respect to the “four V’s of big data: volume, variety, velocity, andveracity.” By highlighting the complexities and challenges in each of these “V’s”, we are able topresent theory and praxis of the impact(s) different computing/network architectures andsolutions have for analytics. Additionally, we provide details and discussions on the hands-onassignments and laboratory projects that directly support the lecture topics.In order to detail the assignments and projects, we will also discuss the physical cyber-infrastructure environment used to provide students with direct hands-on learning of big dataanalytics. This environment is also used to provide demonstrations of the topics presented duringlectures. The platform includes Fedora 19, Hadoop, Java, Perl, and VMWare. In addition, thearchitecture of network access is discussed as students from both universities require secureaccess to the computing resources, as well as the need for securing the computing resources fromunauthorized access.Finally, we discuss our next steps and potential improvements, modifications, and directions forfuture course offerings.

Hansen, R. A., & Wlodarczyk, T. W., & Hacker, T. J. (2014, June), A Collaborative, Multinational Cyberinfrastructure for Big Data Analytics Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--19922

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