Clemson University researchers are studying ways to simplify collaboration and improve efficiency in big data analytics.
The researchers note big data can lead to new and innovative ways to computationally analyze patterns, trends, and associations, but significant delays in big data transfer can cause scientists to give up on projects before they even start. The researchers found careful planning and engineering are required to move and manage big data at the speeds needed for high-throughput science.
If properly executed, sophisticated data networks and the inclusion of advanced applications and software can improve transfer efficiency by orders of magnitude, according to the researchers. Clemson professor Alex Feltus says, "there's a gulf between the 'technology people' and the 'research people.' We're trying to bring these two groups of experts together and learn to speak a common dialect."
Meanwhile, the U.S. National Science Foundation (NSF) and other high-profile organizations have made big data a priority and are encouraging scientists to explore the issues surrounding it in depth. For example, in August 2014, the Clemson researchers received a $1.4-million NSF grant with Louisiana State and Indiana universities to study collaborative research for computational science.
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