Standards and ontologies for manufacturing understand resources differently. Because of this heterogeneity, misunderstandings arise concerning the basic features that characterize them. The purpose of the paper is to investigate how to ontologically model resources with the goal of facilitating the development of knowledge representation models for manufacturing. By reviewing the literature, we discuss and compare three approaches for the representation of resources depending on whether they are conceived in connection to either processes, plans or goals. By addressing the advantages and (...) shortcomings of each view, we present a unifying perspective to enable the modeling of resources in an integrated manner. In this way, the intended meanings of the used notions are harmonized and, as a result, one can facilitate multiple experts to interact e.g., via data sharing and/or data integration procedures. Differently, by keeping three separated views, there is no guarantee that data coming from different parties will share common meanings even if the same terms are used. By the end of the paper, we present a case study to show the application of our approach and to compare it with an existing ontology for manufacturing. (shrink)

Many types of part-whole relations have been proposed in the literature to aid the conceptual modeller to choose the most appropriate type, but many of those relations lack a formal specification to give clear and unambiguous semantics to them. To remedy this, a formal taxonomy of types of mereological and meronymic part-whole relations is presented that distinguishes between transitive and intransitive relations and the kind of entity types that are related. The demand to use it effectively brings afore new requirements (...) for automated reasoning over a hierarchy of relations. To ensure logically and ontologically correct inferencing over both the class and role hierarchy, the new reasoning service RBox compatibility for Description Logics reasoners is introduced. The proposed combination of formal semantics and the new reasoning service will improve the representation of the application domain when using part-whole relations in conceptual models and ontologies. (shrink)

Unlike identification with keys and reference schemes in ER and ORM, UML uses internal, system-generated, identifiers, with a little-known underspecified option for user-defined identifiers. To increase the ontological foundations of UML, we propose two language enhancements for UML, being formally defined simple and compound identifiers and the notion of defined class, which also have a corresponding extension of UML’s metamodel.

Multiple different understandings and uses exist of what granularity is and how to implement it, where the former influences success of the latter with regards to storing granular data and using granularity for reasoning over the data or information. We propose a taxonomy of types of granularity and discuss for each leaf type how the entities or instances relate within its granular level. Such unambiguous distinctions can guide a conceptual modeler to better distinguish between the types of granularity and the (...) software developer to improve on implementations of granularity. (shrink)

An essential aspect of conceptual data modeling methodologies is the language’s expressiveness so as to represent the subject domain as precise as possible to obtain good quality models and, consequently, software. To gain better insight in the characteristics of the main conceptual modeling languages, we conducted a comparison between ORM, ORM2, UML, ER, and EER with the aid of Description Logic languages of the DLR family and the new formally defined generic conceptual data modeling language CMcom that is based on (...) DLRifd. ORM, ER, EER, and UML class diagrams are proper fragments of ORM2 and CMcom has the most expressive common denominator with these languages. CMcom simplifies prospects for automated, online, interoperability among the considered languages so that modelers not only can continue using their preferred modeling language yet be compatible with the other ones, but also have a common ground that eases database and software integration based on commonly used conceptual data models. (shrink)

Representing parthood relations in ORM has received little attention, despite its added-value of the semantics at the conceptual level. We introduce a high-level taxonomy of types of meronymic and mereological relations, use it to construct a decision procedure to determine which type of part- whole role is applicable, and incrementally add mandatory and uniqueness constraints. This enables the conceptual modeller to develop models that are closer to the real-world subject domain semantics, hence improve quality of the software.

From the side of modelers and early-adopter industry, interest in reasoning over conceptual models and other online usage of conceptual models is growing. To obtain a more precise insight in the characteristics of the main conceptual modeling languages, we define the (semi-)standardized ORM, ORM2, UML, ER, and EER diagram languages in terms of the new generic conceptual data modeling language CMcom that is based on the DL language DLRifd. CMcom has the most expressive common denominator with these languages. CMcom advances (...) prospects for automated, online, interoperability among diverse conceptual data models and ensures compatibility with and between industrygrade conceptual data modeling languages. (shrink)