Big Data from Space 2021

18-20 May 2021 | Virtual Event



 

Objectives

The 2021 edition of the Big Data from Space conference will emphasise not only on the insights that can be retrieved from Big Data from Space but also on the exploitation of these insights for foresight, that is our capacity of foreseeing. This capacity is becoming increasingly important given the pace at which our World is changing. This is exemplified and reflected by the EU Destination Earth (DestinE) initiative and the related ESA Digital Twin Earth, moving towards a predictive decision support capability for European environmental policies. Indeed, there is still a large gap to bridge between monitoring and understanding so that reliable scenarios of future evolution under different boundary conditions can be put forward. As for all past editions, the 2021 edition is open to any research and innovation development in the field of Big Data from Space including technical aspects and applications.

The main objectives of the BiDS 2021 Conference are:

  • Bring into scene new user needs and requirements related to the use of large amounts and varieties of data in different space domains such as Earth Observation (e.g. EU Copernicus programme),Space Science, Navigation and Telecommunications (e.g. EU Space programmes as Galileo and EU GovSatCom), mission operations and system engineering;
  • Bring together major European actors in the fields of Space and data technologies, including research, industry, institutions, and users, to strengthen the communication and transfer of requirements, methods and technologies, and to reinforce an interdisciplinary approach;
  • Explore and expand on the ever increasing relevance of Big Data in European and global environmental policy initiatives and programmes, and the corresponding increasing complexity of applications and use cases;
  • Discover and foster breakthrough data science processing and analysis techniques to extract insights and generate foresight, showing use cases wherever possible to facilitate future user uptake;
  • Focus on new paradigms of data science addressing the entire value chain, i.e., building of reference training sets, data processing to extract information, information analysis to gather knowledge, and knowledge transformation in foresight;
  • Maximise the uptake and impact of solutions exploiting multi-source spatio-temporal data linked with other data sources;
  • Advance the upscale of new solutions from R&I to operational use (e.g. for the security domain and informed policy making);
  • Foster inter-operability of platforms and services by promoting open standards, analysis ready data, and APIs;
  • Promote inter-disciplinarity to respond to multi-sectorial challenges such a those put forward by the European Green Deal and the wide-ranging consequences of the Covid-19 pandemic;
  • Promote cross-fertilisation with similar activities in other data intensive domains (e.g. high-energy physics, genomics, social media, internet of things, etc.).