Structuring Spectral and Spatial Recording Strategies of Cultural Heritage Assets. Background, state of affairs, and future perspectives

Ashish Karmacharya and Stefanie Wefers


The activities of COSCH community and the disciplines it represents were as diverse as they can possibly be in research into cultural heritage. To achieve common goals it was of utmost importance to have a common understanding of these diverse activities and disciplines. Work on the COSCH Knowledge Representation, or COSCHKR, was undertaken to develop a common semantic base representing different disciplines and to facilitate communication within the Action. The COSCHKR is an ontology-based inference model, guided by inference rules that provide a semantic bridge between various interdisciplinary activities involved in non-invasive technical documentation of material cultural heritage. The inference model is intended to support the humanities experts by recommending optimal spatial and spectral techniques. The model may also be used by technology experts to compare their own solutions with the ones recommended through COSCHKR, and to understand why they may differ.

We present the methods adopted for designing the COSCHKR and the steps in the development of the inference model. The difficulties in maintaining a common level of understanding within the diverse disciplines during the knowledge acquisition process are discussed. We present different mechanisms and the methods of information collection, its structuring and aligning, to formulate different axioms and theorems within the model. The importance of experts’ involvement in designing and formulating theorems and axioms is noted. The designing and development of COSCHKR is based on the iterative mechanism where the gathered knowledge is first verified with the group of experts before it can be processed. This verification mechanism is important for the reliability of the model, ensuring technical consistency of the model. Experts are also involved after the formulation of theorems and axioms inside. This chapter highlights the importance of these iterative mechanisms in the validation of (1) knowledge gathered and then (2) knowledge populated inside the knowledge base.

The inference model is a rule-based model where the inference rules are used to bind different diverging components together. These inference rules need to be carefully formulated and evaluated against different applications. The inference model in question was tested against different case studies, to evaluate the correctness of the conclusions it permits to draw. We discuss how this works with respect to the study of the wall paintings in the Château de Germolles and spectral recording. The KUR project, which involved measurement of waterlogged wood samples on two different occasions, is presented as an example of spatial recording undertaken to determine geometric alteration.

Keywords: COSCH ontology, knowledge representation, cultural heritage recording, semantic web technologies, spatial data, spectral data, inference system



Figure 1. Visualisation of a section of the complex graph of the COSCHKR ontology with a focus on the classes and dependencies.


Figure 2. Five top-level classes and main dependencies of the COSCHKR ontology.


Figure 3. 3D models of one waterlogged wood object (V14-021). The shape before and after conservation treatment and the spatial differences as well as section planes are shown. 3D models and further waterlogged wood objects can be found at www.rgzm.de/kur/


Figure 4. The inference mechanism A) demands on data: deformation analysis demand high accuracy 3D data, B) generation on data at technical level through technologies first through the principle then instruments adapting to the technical process C) the restrictions provided by CH objects and other external influences on the technologies.


Figure 5. Simulation of a GUI for the case study in conservation of waterlogged wood. The red boxes represent the user input and the grey boxes represent the inferred information.