Communications of the ACM
NIST Seeks to Bring Rigor to Data Science
Credit: UC Berkeley
The U.S. National Institute of Standards and Technology (NIST) wants to develop a framework that can be used by all industries to understand how to use and measure the results from data science and big data projects. To start the project, NIST is planning a symposium with big data specialists and data scientists to better understand the challenges around the new disciplines.
"Data science is pretty convoluted because it involves multiple data types, structured and unstructured," says NIST's Ashit Talukder. "So metrics to measure the performance of data science solutions is going to be pretty complex."
NIST plans to seek feedback from industry about the challenges and success of data science and big data projects with the goal of developing a common taxonomy with the community that can be used across different domains of expertise. Technical University of Berlin professor Volker Markl says the field of data science is challenging in its requirement to both understand the technologies to handle the data, such as Hadoop and R, and the statistics and other forms of math needed to extract meaningful information from the data.
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