## 5 Discussion  
This section presents an overall discussion drawn from the case studies and involved components employed during the experiments. In terms of architecture, experiments in this paper (Section 4) and previous works adopting the framework, highlighted the adaptability and responsiveness of both client and server components. On the presentation side, ATON profiler and scalable rendering system (see Section 3.6.2) guarantee a responsive, universal and _liquid_ consumption of 3D content on the web, ranging from mobile devices, PC, museum kiosks and 3-DoF or 6-DoF HMDs for immersive VR (e.g., Oculus Quest) which all reported interactive framerates. For instance, the Aiano experiment (see Section 4.3), did show how a published 3D scene in ATON can be consumed and queried interactively on a wide range of devices. Furthermore, the adoption of a _physically-based rendering_ (PBR) model, the light-probing system offered by ATON and the gITF standard, as highlighted by the [PERSON] case study (Section 4.2), allow to better simulate the 3D object material properties in relation to the surrounding environment and with drastically different lighting conditions. The introduction of the digital replication concept among tools used by CH sciences responds to the need to go beyond the documentation of geometry and diffuse colour to include the material characteristics of artefacts (how surface features react to light). In other words, with digital replication, there was a need for a formalism that could describe the surface material in a compact and simple way so as to make available a visual substitute for the original object. The metaphor of the PBR, now an industry standard, responds perfectly to this need, allowing, in addition, to transform the digital assets of Cultural Heritage into reusable assets for the creative industry. The greatest challenge related to the PBR metaphor is the lack of a universal workflow in the literature for creating roughness and metalness maps for three-dimensional objects. In general, roughness maps are obtained by [86]:  
* Painting them directly using 2D applications (Photoshop, Krita, Gimp, Blender, Zbrush, Substance Painter,...);
* Generating them from photographs (Substance B2M, Quixel,...);
* Generating them from procedural materials (Substance Designer, Blender, 3 DMax, Maya,...). Acquiring the roughness value of a surface from real world data is possible: there are instruments such as box scanners for PBR materials, although they are currently designed to acquire flat surfaces. Creating roughness maps for 3D models requires semi-automatic approaches based on features extraction from images and specific skills in both CH and Computer Graphics in order to perform fine-tuning by comparison with real photos taken under different lighting conditions. Moreover, PBR models are also useful within _Augmented Reality_ WebXR sessions [87], where lighting information can be estimated from the real world [88] creating a more consistent AR presentation and visual appearance (see Figure 23A). The gITF standard including PBR materials moreover, is well supported on several software tools and game engines (like aforementioned Unreal Engine 4) allowing pipelines that directly export PBR assets to the web (see Figure 23B). Regarding Web3D rendering, Three.js (and other similar open-source libraries) allow more advanced effects targeting interactive presentation on the web, like _Screen-Space Reflections_ (SSR) already adopted in proprietary platforms like SketchFab, or _Ground Truth Ambient Occlusion_ (GTAO) [89], although introducing additional costs in terms of performance. Large open-source libraries like Three.js with active communities allow indeed to create a robust foundation for ATON, including custom visualization models (e.g., through the use of shaders) targeting the Cultural Heritage field, like real-time cross-sections or virtual lenses [67], slope gradients, outlines, etc.