Introduction
Provide ground-breaking advances iin view of coping with “extreme data”, i.e. data that exhibits one or more of the following characteristics, to an extent that makes current technologies fail – increasing volume, speed, variety; complexity/diversity/multilinguality of data; the dispersed data sources; sparse/missing/insufficient data/extreme variations in values
Scope
The actions should address the integration of relevant technologies (e.g. big data, AI, IoT, HPC, edge/fog/cloud computing, language technologies, cybersecurity, telecommunications, autonomous systems etc.) as a means towards achieving the goals, and foster links to the respective research, industrial and user/innovator communities
Objectives
provide better technologies, tools and solutions for data mining of large, constantly growing amounts and varieties of data, and/or extremely sparse/dispersed/heterogeneous/multilingual data, in particular IoT, industrial, business, administrative, environmental, scientific or societal data
