Despite the large investments to mine data and explore analytics in the aviation industry, though, there is currently little data diffusion and sharing between the different stakeholders of the aviation-related sectors.
ICARUS realises a novel data value chain in the aviation-related sectors towards data-driven innovation and collaboration across diversified and fragmented industry players, acting as multiplier of the “combined” data value that can be accrued, shared and traded. ICARUS addresses critical barriers for the adoption of Big Data in the aviation industry (e.g. data fragmentation, data provenance, data licensing and ownership, data veracity), and enables aviation-related big data scenarios for companies, organisations and scientists, through a platform that will allow exploration, curation, integration and deep analysis of original, synthesised and derivative data characterised by different velocity, variety and volume in a trusted and fair manner.
ICARUS pursues its realisation through 7 objectives:
• Business Obj. I: To deliver a pan-European multi-sided big data platform for the aviation data value chain, validated through a set of demonstrators;
• Business Obj. II: To bring forward novel collaborative business models driven by big data sharing and analytics services; and
• Business Obj. III: To nurture a sustainable and ever-growing open ecosystem of collaborating organisations from diverse domains, taking advantage of the business offerings of the ICARUS platform.
• Technical Obj. I: To deliver a novel Big Data platform as a Service powered by aviation relevant data, allowing central and federated experimentation with big data analytics, service composition, data sharing, assets reuse and business value generation; and
• Technical Obj. II: To integrate existing approaches, tools and libraries that accelerate the data management and analysis cycle for powering the ICARUS platform.
• Scientific Obj. I: To successfully tackle the semantic enrichment, data improvement and value addition on existing hybrid big and open data sources, resulting in widely-adopted value chain models; and
• Scientific Obj. II: To deliver an innovative, secure, privacy preserving and IPR respecting data exchange methodology, propelling the creation of a joint venture of data owners and analytics providers.