FAIRICUBE

The challenge posed by the potential of such multi-thematic datacubes pertains to processing; while established processing paradigms align well with the constrained datasets traditionally available, these must be rethought when confronting both the structure and sheer volume of data available in cube formats. Fortuitously, the experience and compute resources to run artificial intelligence (AI) and specifically machine learning (ML) applications have significantly evolved, developing from what was long seen as a buzzword for untransparent data analysis towards viable tools enabling the extraction of real value and insights from large and complex data collections. Therefore, when providing data, processing functionality and data products to relevant stakeholders such as governmental authorities, civil society and NGOs, commercial players, or researchers, all these aspects must be considered. Following the FAIR principles, while data is becoming increasingly findable, accessible, and..