[Call for Proposals] A European Collaborative Cloud for Cultural Heritage – Innovative tools for digitising Cultural Heritage Objects (HORIZON-CL2-2023-HERITAGE-ECCCH-01-02)

10 January - 21 September 2023

Expected Outcome:

Projects should contribute to all of the following expected outcomes:

  • Cultural heritage professionals in Europe, including curators, conservators and researchers of cultural heritage, use a common set of new innovative tools and methods for the digitisation and visualisation of cultural heritage objects (3D and enhanced 2D) with regard to their visible and non-visible properties and characteristics, which are accessible through and connected to the European Collaborative Cloud for Cultural Heritage (ECCCH).
  • The European Collaborative Cloud for Cultural Heritage (ECCCH) provides cultural heritage institutions and professionals with enhanced technological and methodological capabilities to study cultural heritage objects, to share related data of their visible and non-visible properties and characteristics, and to develop new forms of collaboration.


This topic aims at designing and implementing innovative tools and methods for digitisation of (a) visible characteristics and (b) non-visible characteristics of cultural heritage objects, to be incorporated into the European Collaborative Cloud for Cultural Heritage (ECCCH).

As regards digitisation of visible characteristics of cultural heritage objects, technologies are now satisfying the needs for a considerable part of uses and objects. For instance, in the field of digital documentation of cultural heritage, three-dimensional acquisition and reconstruction methods have been developed in the past twenty years, using photogrammetry and laser scanning techniques to capture the characteristics of physical cultural heritage objects. Such methods already provide robust solutions for the digital reconstruction of the geometry and visual appearance of object surfaces. In addition to these methods, in the field of cultural heritage conservation various non-destructive testing (NDT) techniques have become important technical and scientific means of examination. Such techniques allow understanding the phenomena of deterioration and defining the restoration, conservation and documentation needs of cultural heritage objects.

Nevertheless, there are still major needs in cultural heritage that require further research and innovation on more advanced digitisation tools and methods:

  • New AI-powered tools and methods that improve the digitisation process of tangible cultural heritage objects. The robustness and efficiency of the 3D digitisation process should be improved, especially in the case of massive digitisation (for example collections of objects). The accuracy and completeness of surface appearance acquisition should also be improved, as well as the mapping of complex reflectance data on digital surfaces. Furthermore, such solutions should yield new improved methods for post-processing and cleaning of the 3D models produced.
  • Improved methods for acquiring and processing enhanced 2D representations (e.g. reflectance transformation imaging, multispectral, panoramic), and for better integrating 2D representations with 3D representations.
  • Future 3D models need to encode other key attributes in addition to the usual geometric and reflectance data, such as local uncertainty information. New tools and methods are therefore needed to calculate and encode local accuracy limits with high precision in reconstructed 3D models. These tools should be capable of producing measurement-based limits of the similarity between the digital model and the physical object at any surface point, as well as algorithmically estimated accuracy boundaries.
  • To model a complex assembly is a costly effort, and today often requires dismounting the assembly – which is often not possible. Specific digitisation solutions should be developed that are capable of mixing various digitisation approaches (e.g. scanning and computer tomography scans) in order to capture dynamic or hidden characteristics of complex assemblies without dismounting them.[1]

As regards the study of non-visible characteristics of complex objects, nowadays different techniques are used, e.g. multispectral imaging, X-rays, infrared reflectance, terahertz imaging, etc. Proposals should focus on innovations at the data acquisition level, with a view to improve the quality and usability of the data generated. An important aspect is the robustness, reliability as well as the ease of use of any tool and method for analysing the visible characteristics and non-visible materials properties of cultural heritage objects under real world conditions. In addition, several recent experimental approaches have shown that multimodal analysis techniques should include a temporal dimension, observing the evolution of features and phenomena over time.

These challenges highlight the need for flexible, transferable, and simple solutions for documenting multimodal analyses. These solutions should include the integration of data acquisitions from different technologies into complex data structures that provide new analysis opportunities for conservation scientists, conservators and curators. This requires the introduction of new visualisation tools that act as virtual environments for scientific exploration, allowing scientists and curators to explore the full material complexity of cultural heritage objects beyond what is visible.

Large datasets are often generated (e.g., many dozens of images in the case of hyperspectral imaging). To address this, new AI solutions should be developed to generate categorised or pre-analysed data, enabling the selection and/or identification of specific elements, images or regions of interest that exhibit important differences for subsequent analysis and validation by the human expert.

The tools and methods introduced should focus on geometric and projective consistency of heterogeneous data from different technologies, with respect to different scales of observation and analysis, over a wide spectral range, to produce an integrated digital representation. Spatially localised characterisation of individual material layers is one of the goals, including coupling multi- or hyperspectral analyses with physicochemical characterisation of materials. New methods for access, exploration, and temporal monitoring of acquired data should be developed, including their interactive visualisation and classification.

The proposed software tools and methods to be developed should go beyond the lab prototype status, should be practical and possible to deploy easily in un-controlled environments (e.g. digitise in a museum room), and should ensure low cost and flexibility of use. The component for data integration into the ECCCH may extend the features of the basic tool developed by the project funded under topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01, with the goal of streamlining the upload of metadata/paradata and of raw sampled data.

The proposals should demonstrate the potential of the developed tools and methods through representative case studies, conducted in collaboration with relevant stakeholders. These case studies should cover a significant share of the range of cultural heritage objects, materials and conservation/restoration issues. The results of these case studies should produce emblematic data that can serve as models for promoting the re-use of the tool(s) and methods in other contexts and by other users within the ECCCH.

The proposed tool(s) to be developed should be implemented adopting the low-level libraries established by the project funded under topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01. The tool(s) developed should be compliant with the design of the ECCCH, and should be integrated with the ECCCH before the end of the project, together with proper documentation. All software and other related deliverables should be compliant with the data model and the software development guidelines elaborated by the project funded under topic ‘HORIZON-CL2-2023-HERITAGE-ECCCH-01-01’. If appropriate these tools should be developed with a view to a wider deployment, including in the Data Space.

The proposals should furthermore make provisions to actively participate in the common activities of ECCCH initiative. In particular, the proposals should coordinate technical work with other selected projects and contribute to the activities of the project funded under the topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01.

The proposals should set up its project website under the common ECCCH website, managed by the project funded under topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01. The proposal is further expected to include a budget for the attendance to regular joint coordination meetings and may consider covering the costs of any other joint activities without the prerequisite to detail concrete joint activities at this stage.

Please also refer to the Destination introduction text to consider some key characteristics of the vision for the ECCCH.

[1]Concerning digitisation tools and methods mentioned, see European Commission, Directorate-General for Research and Innovation, Brunet, P., De Luca, L., Hyvönen, E., et al., Report on a European collaborative cloud for cultural heritage : ex – ante impact assessment, 2022, pp. 38-42 and 61-62, https://data.europa.eu/doi/10.2777/64014

Type of action

HORIZON-RIA HORIZON Research and Innovation Actions

Type of MGA


Deadline model


Opening date

10 January 2023

Deadline date

21 September 2023 17:00:00 Brussels time

Geographical focus: