Session Abstract

Session Chair: Harold Teunissen (SURFnet)

Big data is all about comprehending the data sets. It is a term applied to data sets whose size or complexity is beyond the ability of commonly used software tools to capture, manage, and process the data within a reasonable elapsed time. Thus a big data set is just too big to be handled and analyzed by traditional methods and protocols of an organization; a data set of 250 megabyte can already push the limits of the data capabilities because people are unable to retrieve and analyze the data using tools like spreadsheet applications or even a tablet computer. In any case, there is a limit to how much data leads to more knowledge.

With leading CIOs we will discuss the the different perspectives on dealing with the big data revolution that goes beyond the obvious constituency of high-energy particle physics and astronomy. Where small and medium science is suffering from big data problems since most of the attention is focused on the on top 1% producers / consumers of scientific data: the long tail of Big Data. How can campuses share their experience and start collaborations on dealing with the sheer amount of data.