This chapter will discuss the critical data intensive analysis and visualiza-tion challenges faced by the experimental science community at large scale and laboratory based facilities. The chapter will further highlight initial solutions under development through community efforts and lay out perspectives for the future, such as the potential of more closely linked experimental and computational science approaches, methods to achieve real time analysis capabilities and the challenges and opportunities of data integration across experimental scales, levels of theory and varying techniques.
Revised: May 21, 2012 |
Published: December 31, 2011
Citation
Kleese van Dam K., D. Li, S.D. Miller, J.W. Cobb, M.L. Green, and C.L. Ruby. 2011.CHALLENGES IN DATA INTENSIVE ANALYSIS AT SCIENTIFIC EXPERIMENTAL USER FACILITIES. In Handbook of Data Intensive Computing, edited by B Furht and A Escalante. 249-284. New York, New York:Springer.PNNL-SA-81459.