The core objective of the COMET project is to develop and validate novel data sharing and machine learning-based methods for achieving net-zero carbon energy supply and investigate business models to ensure that digitalization is optimally and fairly supporting the energy transition. This will be done by (i) developing novel capabilities for predictive and prescriptive analytics based on trusted data, and by (ii) designing novel mechanisms and a prototypical digital platform to enable and incentivise data sharing and collaborative ML model development. Emphasis will be placed on use-inspired research, by considering a set of real-world use cases as a basis for the research and validation of the new concepts developed during the project life. While these use cases are to be mainly related to energy (and transportation, through a focus on batteries and electric cars), the fundamental approaches we will introduce are to be generic enough that they may also be used in other areas, e.g., manufacturing (industry 4.0), smart cities, smart agriculture, etc. The backgrounds and competences of both PIs complement each other, while the research goals are key items on both of their research agendas. Furthermore, the planned digital platform will comprise a sustainable research result since it can be further developed and used after the project has ended.