HERITALISE mission is to research and develop advanced digitisation techniques and solutions for documenting and representing diverse CH assets, giving a full comprehension of the diverse CH features, visible and non-visible. In addition, AI-powered tools including Machine Learning (ML) will be developed for improved and optimised data post-processing and integration based on standard and expanded methodologies. All this will be connected through a knowledge graph environment that allows the individual aspects known about the CH object to be related and retrievable. As with Wikipedia, by following links it will be possible to learn more about a particular object, what research has been done, and what results have been derived from it. HERITALISE will provide the upcoming ECCCH with a interoperable web-based Ecosystem, advanced input data from improved digitalisation methodologies and preservation supporting tools, which will be achieved by meeting the following General Objectives (GO) and setting the conditions for a wide-scale replicability and scalability across European CH institutions/organisations across European CH institutions/organisations: GO1: State-of-the-art review of current digitisation standards and methodologies defining the data requirements for CH tangible and intangible objects GO2: Improve 3D/2D Data acquisition methods and technologies GO3: Data post-processing methods and technologies will be adopted, including new AI-powered digitisation methods and the development of data fusion techniques to mix various multimodal digitisation approaches (multisensory, multiscale, multispectral, external and internal) GO4: Development of methodologies and solutions as Hardware (HW) and/or Software (SW) services GO5: Development of ECCCH-compliant open interoperability components enabling connecting and sharing data and modular services in a distributed web-based architecture GO6: Increasing the Impact of current and developing digitisation technologies