As in daily life, data volume in science is increasing rapidly. Experiments and simulations produce enormous amounts of data. From this capital, researchers extract new findings using sophisticated analysis tools. On September 24, 2013, leading experts worldwide will meet at the second international symposium “The Challenge of Big Data in Science” at Karlsruhe Institute of Technology (KIT).
“Data analysis has long been established as the fourth pillar in science next to theory, experiment, and simulation,” says Professor Achim Streit, Director of the KIT Steinbuch Centre for Computing (SCC). Cutting-edge research in particle physics, earthquake science, biotechnology, and in the humanities is impossible without big data processing. “The discovery of the Higgs particle, to which KIT’s GridKa contributed, is the spearhead of the development only.” About 25 petabytes, the data volume stored on 5 million DVDs, are stored and constantly analyzed at GridKa, the German tier-1 computing and data center for the LHC at CERN.
Experience in handling big data is pooled in the “Large Scale Data Management and Analysis” (LSDMA) project at KIT. “High-performance software tools are developed to prevent the search for relationships and scientific findings in big and complex data inventories from becoming a search for the needle in a haystack,” Dr. Christopher Jung, manager of the LSDMA project, explains. “The symposium with its lecturers from natural sciences and humanities as well as from companies like Google will reflect the different facets of the topic.”
Symposium “The Challenge of Big Data in Science”
Tuesday, September 24, 2013, 9.00 hrs,
Auditorium of FTU on KIT Campus North,
76344 Eggenstein-Leopoldshafen, Germany.
The following persons will be among the lecturers of the symposium:
Beth Plale, Indiana University, will speak about the future trends of big data and open access and their potential symbiosis.
Sayeed Choudhury, Johns Hopkins University, will sum up ten years of data management for scientific large-scale projects, such as the Sloan Digital Sky Survey.
Alexander Hall, Google, will explain algorithms to efficiently analyze trillions of datasets.
The complete program can be found at:
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