Modeling, extraction, and transformation of semantics in computer aided engineering systems

With the rapid advancement of information and internet technologies, engineering software systems are now commercially available to aid engineering tasks, such as design, analysis, integrated manufacturing, and requirements modeling. Recent trend in computer aided engineering (CAE) includes the integration and smooth communication between existing CAE systems [1], management of knowledge for different engineering tasks across disciplines [2], and development of natural human–computer interfaces [3]. In addressing these challenges, ontology and semantic web have been widely developed and used by researchers in various fields [4–8]. Particularly, research results have been focused on four aspects: (1) modeling and representation of engineering information that can effectively support the extraction of semantics [9– 12]; (2) conceptual structure of engineering information that embodies the semantics necessary for various engineering tasks [13–17]; (3) algorithms for transforming different representations of engineering information into semantic conceptual structures [18,19] and (4) innovative applications [20,21]. The focus of this special issue is on emerging technologies that can be used to extract useful knowledge or information for CAE applications from heterogeneous contents including documents, graph, geometry, and CAD drawings. In this special issue, seven research articles are included by addressing the aforementioned four research topics. To model and represent semantics, Raskin et al. present a meaningand ontology-based approach. In their paper titled ‘‘Meaningand Ontology-Based Technologies for High-Precision Language: an Information-Processing Computational Systems’’, the need for an ontologyand meaning-based approach is addressed for computational systems that can understand and process information in natural language. An example of an air crash is used to show that a disaster may happen when meaning is not accessed or accessed inadequately, for instance, without disambiguation. By discussing the very nature of meaning which tends to be taken for granted, misunderstood, and confused with formalism, the Ontological Semantic Technology proposed by the authors was introduced for possible applications to computer aided engineering applications. Particularly, the importance of and approaches to accessing implicit information by machines are discussed. This paper, which is contributed by authors outside of engineering fields, may stimulate the engineering community to look at the semantics from a different perspective. Zhang et al. highlights that design rationale (DR) information plays a very important role in the design reuse, design decision support and design analysis, in their paper titled ‘‘A Semantic Representation Model for Design Rationale of Products’’. From the point of view of semantic representation, their paper analyzes