A Virtual Infrastructure for Data intensive Analysis (VIDIA)


A Virtual Infrastructure for Data intensive Analysis (VIDIA)

Jim Greenberg is currently the Director of the Teaching, Learning, and Technology Center at SUNY Oneonta. I have worked at SUNY Oneonta 33 years helping to deploy technology in ways that improves teaching and learning (I hope). Along the way I have taught courses in Geographic Information Systems, Advanced Networking, various programming languages, and finally New Media. I’ve guest lectured and given workshops on numerous topics relating to technology over the years.

I have served on committees at all levels most recently EDUCAUSE’s EQ Editorial Committee and SUNY’s IITG Reviewer Committee. Personally I am interested in how technology and culture interact, particularly in education. Some of the things I’ve been involved with over the years that I am most proud of are the establishment of the Teaching, Learning, and Technology Center on my campus and being in the room when COA and CIT were conceived.

Abstract: The presentation will overview a the establishment of a collaborative virtual community, focusing initially on data-intensive computing education in the social sciences.

Website: http://vidia.ccr.buffalo.edu
Members: 12
Latest Activity: Feb 5, 2016

View a recording of this Fellow Chat: http://ow.ly/xFAOn

Discussion Forum

Data Science at the Undergraduate Level

Started by Jim Greenberg. Last reply by Jim Greenberg Jul 24, 2014. 4 Replies

I'd be interested in hearing from folks about any initiatives or emerging needs on their campuses to do social media analysis in the social sciences.  I am familiar with efforts at SUNY Stony Brook,…Continue

Tags: Visualization, Qualitative, Undergraduate, Social Media, Big Data

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Comment by Alexandra M. Pickett on July 11, 2014 at 1:28pm

The large datasets culled from social media such as Facebook and Twitter can easily grow to a size that is beyond the capability of commonly used software tools to store and analyze within an acceptable amount of time. Twitter, for example, easily generates 7 Terabytes (TB) of data per day, resulting in a raw dataset of over 210 TB per month (not including intermediate data generated during analysis).
Primarily Undergraduate Institutions (PUIs) typically do not have the computing and networking infrastructure or support personnel needed to allow creation, manipulation, and analysis of these large multi-terabyte datasets by faculty and students. SUNY Oneonta’s existing IT infrastructure is typical of the SUNY comprehensive colleges: total storage shared by its ~6,000 student and 900 faculty/staff users for personal/research data is currently 4 TB. Available software is limited to the standard set of Windows and Macintosh applications, including SPSS, R, Minitab, Atlas.ti, and SAS. As SUNY Oneonta has no highperformance
computing (HPC) capability, the visualization tools typically found at large research facilities are not available, strictly limiting the types of analysis that can be carried out.

The SUNY Research Centers, therefore, have an active role to play in supporting data-intensive computing education and analysis at SUNY’s PUIs. Accordingly, in order to provide the tools necessary to expose students to state-of-the-art data-intensive computing and analysis techniques, the Center for Computational Research (CCR) at the University at Buffalo (UB) and SUNY Oneonta will partner to pilot the establishment of a collaborative virtual community, focusing initially on data-intensive computing education in the social sciences. With necessary infrastructure lacking at PUIs, the formation of a virtual community is vitally important to this goal. The size of datasets culled from social media is expected to grow exponentially over time, making the co-location of data with analysis software and HPC resources increasingly more important. The virtual community to be created will provide a collaborative environment where open-source analysis tools, storage space, and costs c an be shared amongst multiple campuses.

From the perspective of a virtual portal user, data and analysis will be stored and carried out locally. This is the great utility and power of a virtual environment – it removes the constraints of distance from and access to computing resources.


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Created by Alexandra M. Pickett Aug 19, 2010 at 11:52am. Last updated by Alexandra M. Pickett May 20, 2020.


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