11 October 2017: Scheduled talks for 'Modern data management' session


Title: Querying and Exploring Big Scientific Data


Today's scientific processes heavily depend on fast and accurate analysis of experimental data. Scientists are routinely overwhelmed by the effort needed to manage the volumes of data produced either by observing phenomena or by sophisticated simulations. As database systems have proven inefficient, inadequate, or insufficient to meet the needs of scientific applications, the scientific community typically uses special-purpose legacy software. With the exponential growth of dataset size and complexity, application-specific systems, however, no longer scale to efficiently analyze the relevant parts of their data, thereby slowing down the cycle of analyzing, understanding, and preparing new experiments.

In this talk I will illustrate the problem with a challenging application featuring brain simulation data and will show how the problems from neuroscience translate into interesting data management challenges. Finally, I will also use the example of neuroscience to show how novel data management and, in particular, spatial indexing and navigation have enabled today's neuroscientists to simulate a meaningful percentage of the human brain.


Thomas Heinis, PhD, is a Lecturer in Computing/Data Management at Imperial College London since September 2014 leading the SCALE lab. He is currently also a Visiting Professor at the Ecole Polytechnique Federale De Lausanne (EPFL) in Switzerland. Dr. Heinis is renowned for research and development of systems in large-scale data management systems such as MapReduce, noSQL, distributed main memory databases and parallel databases in general. His research particularly focuses on scaling out big data into the cloud for industrial and scientific (medical) applications. Dr. Heinis received a BSc, MSc and PhD from the Swiss Federal Institute of Technology in Zurich. During his studies he also received several fellowships, including a Fulbright fellowship (Purdue University).

Title: Benchmarking SQL-On-MapReduce systems


Mohand-Said Hacid, LIRIS

Title: Advanced Data Analytics


Eric Simon, SAP