Follow #BiDS23
Join us for an in-person conference at the Austria Center (Vienna) from 6 to 9 November, featuring new formats such as tutorials, lightning talks and birds of a feather sessions
Have a look at the Digital Flyer of the event!
Participation to the conference is free of charge
The official language of the conference is English
We thank our partners:
OBJECTIVES AND THEMES
Big Data from Space 2023 (BiDS) brings together key actors from industry, academia, EU entities and government to reveal user needs, exchange ideas and showcase latest technical solutions and applications touching all aspects of space and big data technologies. BiDS provides a premier opportunity for practitioners, researchers, and educators to present and discuss the most recent innovations, as well as practical challenges encountered in the context of big data from space.
The 2023 edition of BiDS will focus not only on the technologies enabling insight and foresight inferable from big data, but will emphasize how these technologies impact society. Today, access to global, free, and open Earth Observation (EO) data is complemented with new initiatives such as the Copernicus Data Space Ecosystem, the EU Destination Earth (DestinE) and ESA’s related Digital Twin Earth program, which will foster generating additional value and impact. Promoting trust in big data for policy interactions, insight and foresight enabled by the evolving geospatial data ecosystem should be transparent, sound, and reproducible with associated quality assurance, building on open data and methodologies.
Together, we want to explore and learn how space data driven insight and foresight, exploiting data from the different space domains (i.e. EO, science, navigation or telecommunications), can provide a sound basis for evidence-based decision-making and regulations addressing global societal challenges such as climate change, sustainability, and civil security.
- Showcase and investigate the impact of big data on society’s grand challenges, such as climate change, as well as key European and global policies such as the EU Green Deal and the UN 2030 Sustainable Development Goals.
- Discover and foster breakthrough data science technologies accelerating Big Data insight and foresight, from research and innovation to operational use.
- Define and promote open innovation, inter-operability of solutions, and interdisciplinarity of data sources and communities to respond to multi-sectoral challenges, building on open and FAIR data principles, digital trust, cloud-based technologies.
1. Big data-driven transformation in policy and society: solutions, analytics and technologies capable of impacting society or decision-making processes;
2. Cross-domain applications exploiting big data from Space to tackle global issues and societal threats such as climate change, sustainability, security, smart cities, or public health;
3. Ethics, equity and trust in Big Data driven policies: responsible technology design and assessment, open innovation, algorithmic governance and development of solutions that are explainable, trustworthy, auditable, interpretable and able to cope with intrinsic bias;
4. Cloud-native and digital innovation for big data management, access, processing, and visualization, including related scalability and interoperability challenges, as well as federated learning, multi-provenance data, security, privacy and green and sustainable computing.
5. New processing paradigms exploiting multi-source data applicable to real-world scenarios, including multimodal Artificial Intelligence (AI), AI foundation models, data fusion, data assimilation, knowledge extraction and data valorization, incorporating multiple-criteria decision analysis;
6. New methods and technologies for enabling foresight such as digital twins, forecasting, simulation, physics-informed AI, explainable AI, advanced interactivity such as natural language processing AI models or virtual reality;
7. Disruptive technologies addressing critical aspects such as real-time analysis of big-data streams, fusion of unstructured and structured data, hybrid high-performance computing, neuromorphic sensing or processing, and quantum computing.