Title :
The NIST data science initiative
Author :
Bonnie J. Dorr;Craig S. Greenberg;Peter Fontana;Mark Przybocki;Marion Le Bras;Cathryn Ploehn;Oleg Aulov;Martial Michel;E. Jim Golden;Wo Chang
Author_Institution :
National Institute of Standards and Technology
Abstract :
We examine foundational issues in data science including current challenges, basic research questions, and expected advances, as the basis for a new Data Science Initiative and evaluation series, introduced by the National Institute of Standards and Technology (NIST) in the fall of 2015. The evaluations will facilitate research efforts, collaboration, leverage shared infrastructure, and effectively address cross-cutting challenges faced by diverse data science communities. The evaluations will have multiple research tracks championed by members of the data science community, and will enable rigorous comparison of approaches through common tasks, datasets, metrics, and shared research challenges. The tracks will measure several different data science technologies in a wide range of fields, starting with a pre-pilot. In addition to developing data science evaluation methods and metrics, it will address computing infrastructure, standards for an interoperability framework, and domain-specific examples.
Keywords :
"NIST","Computer architecture","Measurement","Big data","Cloud computing","Hardware"
Conference_Titel :
Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on
Print_ISBN :
978-1-4673-8272-4
DOI :
10.1109/DSAA.2015.7344805