The rapid development of synchrotron facilities has massively increased the speed with which experiments can be performed, while new methods and techniques have increased the amount of raw data collected during each experiment.　While this has created enormous new opportunities, it has also created tremendous challenges for the national facilities and the users.　Traditionally, users collect data during their assigned and limited “beam-time” and then spend many months analysing them.　With the huge increase in data volume, this is no longer possible.　As a consequence, typically only a fraction of the collected data is fully analysed and therefore used.　This is unfortunate because synchrotron beam-time is an expensive resource with respect to money as well as time.　Secondly, a lack of appropriate data analysis approach limits the realisation of experiments that generate a large amount of data in a very short period of time, and thirdly, the current lack of automatized data analysis pipelines prevents the fine-tuning of an experimental run during a beam-time, thereby further reducing the efficiency of beam-time potential usage.　This effect, commonly known as the “data deluge”, affects the light sources in several different ways such as fast data collection and available local storage, curation of the data, including data movement and deposition in a database. In order to address these crucial Big Data challenges that affect synchrotrons world-wide, Prof. Sepe is leading the deployment of a novel Big Data Science Infrastructure at the Shanghai Synchrotron Radiation Facility (SSRF) where Artificial Intelligence, Automation, Real-time remote experiments, and High Performance Cloud Supercomputing converge to create the first-ever World-Class User-Friendly Superfacility, aimed at accelerating scientific discoveries and technological advancements, where also non-specialists can obtain scientifically meaningful results in real-time. This will effectively extend the use of synchrotron facilities to the largest plethora of scientific disciplines ever, thus dramatically increasing the scientific outcome of Large Facilities like SSRF.
Biography of the Speaker

Prof. Alessandro Sepe specialized in synchrotron and material sciences at the most prestigious universities in Europe, including University of Milano, Munich (TUM) and Cambridge. He then moved to the University of Fribourg in Switzerland where he has further extended his research interests to the fields of High Performance Computing (HPC) and Big Data Science applied at Large Facilities. After successfully leading the deployment of the Swiss National Synchrotron Big Data initiative, he is now Head of the novel Big Data Science Center (BDSC) that he is establishing at the SSRF.