The SEMIC approach has been compared to selected approaches to modelling 3D content, which are leading
in terms of functionality, available documentation and the community of users—approaches to declarative semantic
content creation (proposed by Latoschik et al., Troyer et al. and Kalogerakis et al.), imperative programming languages
and programming libraries (ActionScript with Away3D and Java with Java3D) as well as environments for
visual content creation (advanced environments—Blender and 3ds Max and user-friendly environments—SketchUp
and 3DVIA). The comparative analysis performed aims to indicate the major gaps in the available approaches, which
are to be covered by the proposed approach.
The analysis covers aspects related to conceptual and knowledge-based 3D content creation (Fig. 3). Conceptual
content creation has been considered in terms of representation of 3D content at different levels of abstraction
(detail) and the use of the well-established semantic web concepts (classes, individuals, properties and rules) in 3D
content creation process. Overall, the available semantic approaches enable the use of basic semantic expressions
(combinations of semantic concepts), such as classes and properties, at different levels of abstraction in modelling of
content. However, they do not permit a number of more sophisticated combinations of concepts, which are essential
to visualization of complex knowledge bases and which are covered by SEMIC. The imperative languages and visual
environments permit complex conceptual content representations at different levels of abstraction, however, expressed
imperatively, which is not convenient for knowledge extraction, reasoning and content management in web repositories.
The available approaches do not support separation of concerns between different users, who have different
modelling skills and experience, and are equipped with different modelling tools.
Knowledge-based 3D content creation has been considered in terms of building content representations with regards
to discovered properties and dependencies of content objects, which may be hidden (not explicitly specified),
but they are the logical implications of facts that have been explicitly specified in the knowledge base. On the one
hand, this aspect of content creation is not available in imperative languages, including the languages used in the
visual environments. On the other hand, although the available semantic approaches could be extended to enable
knowledge-based modelling, currently, they do not address content creation based on extracted data.