SABID 2015 - Workshop on Workshop on Management, Search and Mining of Massive Repositories of Solar Astronomy Data

Workshop on Management, Search and Mining of Massive Repositories of Solar Astronomy Data
With the launch of NASA’s Solar Dynamics Observatory (SDO) mission on 02/11/2010, researchers in solar physics have entered the era of Big Data. The Atmospheric Imaging Assembly (AIA) instrument on SDO provides imaging data and the Helioseismic and Magnetic Imager (HMI) instrument on SDO provides magnetic field data. Both instruments record data at a high spatial resolution and a time cadence, amounting to about 1 Petabyte of scientific data each year. The Big Data challenges in Solar Astronomy are expected to grow even further with the inauguration of the NSF funded Daniel K. Inouye Solar Telescope (DKIST), currently under construction in Hawaii. This telescope is expected to generate: 3-5 Petabytes of data per year.
Call for Papers in PDF http://www.cs.gsu.edu/rangryk/workshops/SABID15/im...
Important Dates
July 13, 2015: Due date for full workshop papers submission
August 24, 2015: Notification of paper acceptance to authors
September 8, 2015: Camera-ready of accepted papers
November 13, 2015: Workshop during IEEE International Conference on Data Mining 2015
Workshop Objectives
Providing exposure to the current interdisciplinary research of computer scientists, electrical and computer engineers, statisticians, and solar physicists conducted on solar astronomy data.
Engagement of solar pysicists, big data researchers and data miners to develop new collaborations by presenting massive solar datasets, and current challenges with data-driven knowledge discovery from solar astronomy big data.
Gathering of feedback on the current approaches to the management of solar data, retrieval, and analysis from a broader data mining community, in the expectation of establishing new collaborations, research avenues, and future working relationships.
Bringing people together from other disciplines and domains to share experiences, with hopes of determining if any transfer of big data and data mining expertises could benefit solar astronomy research projects and vice-versa.