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DanaC: Workshop on Data analytics in the Cloud

Data nowadays comes from various sources including log files, transactional applications, the Web, social media and many others. A large part of this data is generated and transmitted in real time and in a large scale. To create value out of these data sets, business analysts and scientists employ advanced data analytics techniques combining, among others, traditional BI, text analytics, machine learning, data mining, and natural language processing. Tackling the complexity of both the data itself and its analysis remains an open challenge.

Cloud computing has emerged as a cost-effective and elastic computing paradigm that facilitates large scale data storage and analysis. Cloud infrastructures can provide adaptive resource provisioning with very little initial investment while scaling to massive amounts of commodity computing nodes. Data analytics, being very resource intensive, has the potential to be a significant cloud application, and to constitute a large fraction of the workload of modern data centers. Designing the infrastructures, systems and data analytics techniques in the new cloud computing environments remains an open challenge.


DanaC 2014 at a Glance

The workshop will take place in Snowbird, Utah, USA on Sunday 22nd June 2014 and is colocated with SIGMOD/PODS 2014.

The workshop is going to feature:

Check the workshop's program for details.


Keynote Talk

"Large-Scale Visual Data Analysis"

Dr. Christopher R. Johnson
Chris Johnson Director of the Scientific Computing and Imaging Institute (SCI) at the University of Utah.

Modern high performance computers have speeds measured in petaflops and handle data set sizes measured in terabytes and petabytes. Although these machines offer enormous potential for solving very large-scale realistic computational problems, their effectiveness will hinge upon the ability of human experts to interact with their simulation results and extract useful information. One of the greatest scientific challenges of the 21st century is to effectively understand and make use of the vast amount of information being produced. Visual data analysis will be among our most most important tools in helping to understand such large-scale information.

Our research at the Scientific Computing and Imaging (SCI) Institute at the University of Utah has focused on innovative, scalable techniques for large-scale visual data analysis. In this talk, I will present state- of-the-art visualization techniques, including scalable visualization algorithms and software, data management, cluster/cloud-based visualization methods and innovate visualization techniques applied to problems in computational science, engineering, and medicine.

Short Biography:
Chris Johnson is the founding director of the Scientific Computing and Imaging (SCI) Institute at the University of Utah where he is a Distinguished Professor of Computer Science and holds faculty appointments in the Departments of Physics and Bioengineering. His research interests are in the areas of scientific computing and scientific visualization. Dr. Johnson founded the SCI research group in 1992, which has since grown to become the SCI Institute employing over 200 faculty, staff and students. Professor Johnson serves on several international journal editorial boards, as well as on advisory boards to several national and international research centers. Professor Johnson was awarded a Young Investigator's (FIRST) Award from the NIH in 1992, the NSF National Young Investigator (NYI) Award in 1994, and the NSF Presidential Faculty Fellow (PFF) award from President Clinton in 1995. In 1996 he received a DOE Computational Science Award and in 1997 recevied the Par Excellence Award from the University of Utah Alumni Association and the Presidential Teaching Scholar Award. In 1999, Professor Johnson was Awardedthe Governor's Medal for Science and Technology from Governor Michael Leavitt. In 2003 he received the Distinguished Professor Award from the University of Utah. In 2004 he was elected a Fellow of the American Institute for Medical and Biological Engineering, 2005 he was elected a Fellow of the American Association for the Advancement of Science, in 2009 he was elected a Fellow of the Society for Industrial and Applied Mathematics (SIAM) and received the Utah Cyber Pioneer Award. In 2010 Professor Johnson received the Rosenblatt Award from the University of Utah and the IEEE Visualization Career Award. In 2012 Professor Johnson received the IEEE IPDPS Charles Babbage Award and in 2013 Professor Johnson received the IEEE Sidney Fernbach Award . In 2014, Professor Johnson was elected an IEEE Fellow.

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Accepted Papers

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Data Analysis Systems Demonstrations

In addition, the workshop will feature presentations and demos of six leading systems for large-scale data analysis developed by members of the database community:

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Detailed Program

08:30 - 10:00 Session 1: Keynote Speech & "Gong show"

10:00 - 10:30 Coffee break

10:30 - 12:00 Session 2: Research Paper presentations

12:00 - 13:30 Lunch Break

13:30 - 15:00 Session 3: Research Paper & Systems Presentations

15:00 - 15:30 Coffee Break

15:30 - 17:00 Session 4: Systems Presentations


Topics of Interest

Areas of particular interest for the workshop include (but are not limited to):

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Paper Submission

All papers should be submitted in pdf and formatted using the double-column ACM format (templates are available here).

The workshop solicits:

All papers should clearly mark their type (research/vision/industrial, etc.) in the paper title and should not exceed 4 pages.

Papers should be submitted using the conference management system:

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Important Dates

Submission deadline: April 7 April 11, 2014, 19:00 (PST)
Notification of acceptance:     May 5, 2014
Final papers due: May 27, 2014
Workshop: June 22, 2014

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PC chairs:

Program Committee:

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The proceedings of DanaC 2014 can be found in the ACM Digital Library.

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Previous workshops

DanaC 2013: , DanaC 2012:

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