000234764 001__ 234764
000234764 005__ 20201030173028.0
000234764 0247_ $$2I:(DE-H235)DIB-20120731$$aG:(DE-HGF)2019_IVF-HIDSS-0002$$dHIDSS-0002
000234764 035__ $$aG:(DE-HGF)2019_IVF-HIDSS-0002
000234764 150__ $$aDASHH: Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter$$y2019 - 2025
000234764 371__ $$0P:(DE-H253)PIP1010949$$aRohringer, Nina
000234764 371__ $$0P:(DE-H253)PIP1087358$$aRarey, Matthias
000234764 371__ $$0P:(DE-H253)PIP1087349$$aLe Borne, Sabine
000234764 450__ $$aHIDSS-0002$$wd$$y2019 - 2025
000234764 5101_ $$0I:(DE-588b)5165524-X$$aHelmholtz Gemeinschaft Deutscher Forschungszentren$$bHGF
000234764 550__ $$0G:(DE-HGF)IVF-20140101$$aImpuls- und Vernetzungsfonds$$wt
000234764 680__ $$a‘Data Science’ is the science of extracting knowledge from typically large amounts of data. The increasing level of automatization and the increasing number and resolution of sensors in scientific experiments result in large, heterogeneous and highly complex data collections. Therefore, Data Science is seen as a key technology in modern and future natural sciences. Data intensive research in experimental and theoretical science at the Forschungscampus Hamburg-Bahrenfeld requires beyond off-the-shelf software solutions for data management, processing and analysis. Tailored or even completely new computational data science methods are indispensable. At the same time, the challenges ahead will foster new innovative ideas in computer science and applied mathematics. To develop these methods, scientists have to be highly skilled in the corresponding physics domain and computer science alike. The Data Science in Hamburg – Helmholtz Graduate School for the Structure of Matter (DASHH) will be established to address this highly interdisciplinary need. DASHH bundles competences of scientists with high international reputation in basic research for the structure of matter, computer science and applied mathematics in Hamburg in a new and unique fashion. The graduate school covers data challenges from application fields such as structural biology, particle physics, material science and ultrafast X-ray science. These data challenges have in common that they cannot be addressed with standard computational methods, but require modern data science techniques instead. Several areas from computer science and mathematics play important roles, especially data management and engineering, machine learning and data analytics, signal and image processing, algorithm design, optimization and simulation, software engineering and automation and control systems.
000234764 8564_ $$uhttps://hgf.desy.de/ivf/projekte/e289393/index_ger.html$$yDescription
000234764 909CO $$ooai:juser.fz-juelich.de:885933$$pauthority$$pauthority:GRANT
000234764 909CO $$ooai:juser.fz-juelich.de:885933
000234764 980__ $$aG
000234764 980__ $$aAUTHORITY