Multi-Level Ontology-based Conceptual Modeling

Since the late 1980s, there has been a growing interest in the use of foundational ontologies to provide a sound theoretical basis for the discipline of conceptual modeling. This has led to the development of ontology-based con- ceptual modeling techniques whose modeling primitives reflect the conceptual categories defined in a foundational ontology. The ontology-based conceptual modeling language OntoUML, for example, incorporates the distinctions under- lying the taxonomy of types in the Unified Foundational Ontology (UFO) (e.g., kinds, phases, roles, mixins etc.). This approach has focused so far on the sup- port to types whose instances are individuals in the subject domain, with no provision for types of types (or categories of categories). In this paper we ad- dress this limitation by extending the Unified Foundational Ontology with the MLT multi-level theory. The UFO-MLT combination serves as a foundation for conceptual models that can benefit from the ontological distinctions of UFO as well as MLT’s basic concepts and patterns for multi-level modeling. We dis- cuss the impact of the extended foundation to multi-level conceptual modeling.

Data & Knowledge Engineering, 2021

Types are fundamental for conceptual modeling and knowledge representation, being an essential construct in all major modeling languages in these fields. Despite that, from an ontological and cognitive point of view, there has been a lack of theoretical support for precisely defining a consensual view on types. As a consequence, there has been a lack of precise methodological support for users when choosing the best way to model general terms representing types that appear in a domain, and for building sound taxonomic structures involving them. For over a decade now, a community of researchers has contributed to the development of the Unified Foundational Ontology (UFO)-aimed at providing foundations for all major conceptual modeling constructs. At the core of this enterprise, there has been a theory of types specially designed to address these issues. This theory is ontologically well-founded, psychologically informed, and formally characterized. These results have led to the development of a Conceptual Modeling language dubbed OntoUML, reflecting the ontological micro-theories comprising UFO. Over the years, UFO and OntoUML have been successfully employed on conceptual model design in a variety of domains including academic, industrial, and governmental settings. These experiences exposed improvement opportunities for both the OntoUML language and its underlying theory, UFO. In this paper, we revise the theory of types in UFO in response to empirical evidence. The new version of this theory shows that many of OntoUML's meta-types (e.g. kind, role, phase, mixin) should be considered not as restricted to substantial types but instead should be applied to model endurant types in general, including relator types, quality types, and mode types. We also contribute with a formal characterization of this fragment of the theory, which is then used to advance a new metamodel for OntoUML (termed OntoUML 2). To demonstrate that the benefits of this approach are extended beyond OntoUML, the proposed formal theory is then employed to support the definition of UFO-based lightweight Semantic Web ontologies with ontological constraint checking in OWL. Additionally, we report on empirical evidence from the literature, mainly from cognitive psychology but also from linguistics, supporting some of the key claims made by this theory. Finally, we propose a computational support for this updated metamodel.

Conceptual models are often built with techniques which propose a strict stratification of entities into two classification levels: a level of types (or classes) and a level of instances. Despite that, there are several situations in which domains of inquiry transcend the conventional two-level stratification and domain experts use types of types (or categories of categories) to articulate their conceptualizations. In these settings, types are instances of other types and multiple levels of classification can be identified (individuals, classes, metaclasses, metametaclasses, and so on), characterizing what is now called " multi-level modeling ". Over the last years, we have worked out a foundational theory for multi-level modeling (dubbed MLT), whose aim is to clarify the basic elements of multi-level conceptual modeling. This paper describes the development of this theory, and reports on some of its applications, namely: the detection of (thousands of) occurrences of anti-patterns in the Wikidata knowledge base and the revision of the powertype pattern in UML.

For over a decade now, a community of researchers has contributed to the development of the Unified Foundational Ontology (UFO)-aimed at providing foundations for all major conceptual modeling constructs. This ontology has led to the development of an Ontology-Driven Conceptual Modeling language dubbed OntoUML, reflecting the ontological micro-theories comprising UFO. Over the years, UFO and OntoUML have been successfully employed in a number of academic, industrial and governmental settings to create conceptual models in a variety of different domains. These experiences have pointed out to opportunities of improvement not only to the language itself but also to its underlying theory. In this paper, we take the first step in that direction by revising the theory of types in UFO in response to empirical evidence. The new version of this theory shows that many of the meta-types present in OntoUML (differentiating Kinds, Roles, Phases, Mixins, etc.) should be considered not as restricted to Substantial types but instead should be applied to model Endurant Types in general, including Relator types, Quality types and Mode types. We also contribute a formal characterization of this fragment of the theory, which is then used to advance a metamodel for OntoUML 2.0. Finally, we propose a computational support tool implementing this updated metamodel.

2013

In recent years, there has been a growing interest in the use of Foundational Ontologies, i.e., ontological theories in the philosophical sense to provide real-world semantics and principled modeling guidelines for conceptual domain modeling languages. In this paper, we demonstrate how a philosophically sound and cognitively-oriented ontological theory of objects and moments (property-instances) has been used to: (i) (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML; (ii) derive supporting technology for mapping these conceptual domain models to less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) which addresses the issue of temporally changing information.

Subject domains are often conceptualized with entities stratified into a rigid two-level structure: a level of classes and a level of individuals which instantiate these classes. Multi-level modeling extends the conventional two-level classification scheme by admitting classes that are also instances of other classes, a feature which is key in a number of subject domains. Despite the advances in multi-level modeling in the last decade, a number of requirements arising from representation needs in subject domains have not yet been addressed in current modeling approaches. In this paper, we tackle this issue by proposing an expressive multi-level conceptual modeling language (dubbed ML2). We follow a prin-cipled approach in the design of ML2, constructing its abstract syntax as to reflect a formal theory for multi-level modeling (termed MLT*). We show that ML2 enables the expression of a number of multi-level modeling scenarios that cannot be currently expressed in the existing multi-level modeling languages. A textual syntax for ML2 is provided with an implementation in Xtext.

In recent years, there has been a growing interest in approaches that employ ontological models as theoretical tools for analyzing and improving conceptual modeling languages. In this paper we present a philosophically and cognitively well-founded formal ontology which has been developed with the special purpose of serving as a foundation for general conceptual modeling lan- guages. Furthermore, we demonstrate how this foundational ontology named the Unified Foundational Ontology (UFO) has been used to evaluate and redes- ign the metamodel of the Unified Modeling Language (UML) for the purpose of conceptual modeling.

2002

As pointed out in the pioneering work of [WSW99,EW01], an upper level ontology allows to evaluate the ontological correctness of a conceptual model and to develop guidelines how the constructs of a conceptual modeling language should be used. In this paper we adopt the General Ontological Language (GOL), proposed in [DHHS01], for this purpose. We discuss a number of issues that arise when applying the concepts of GOL to UML class diagrams as a conceptual modeling language. We also compare our ontological analysis of some parts of the UML with the one proposed in [EW01].

Traditionally, instances of attributes in conceptual modeling languages are associated to values like “1,86”, “small” or “John”. But what do such values mean? What is the real- world semantics behind these attributes and their values? An approach to improve the semantics of conceptual modeling languages is to ground them on ontological theories. Following this strategy, over the last decade, the foundational ontology UFO has been applied to create the OntoUML modeling language, an ontologically well founded version of UML. In the current work we present extensions to UFO in order to improve the ontological foundations concerning value spaces by employing the notion Semantic Reference Spaces. A concrete application of this theory is presented, applying the proposed UFO extensions to ground an ontologically founded version of (Onto)UML Datatype classes. A prototype editor of the proposed extension to OntoUML is also presented in order to illustrate the applicability of the ideas discussed here.

2020

Stability is a key quality of a conceptual model. A stable conceptual model is able to withstand changes in domain conceptualization and user requirements without major impact. This paper addresses stability of ontologydriven conceptual models by presenting a number of patterns in the OntoUML language which are derived from characteristics of the foundational ontology underlying the language. The discussed stability patterns include: orthogonal subtype partitions (more specifically phase and subkind partitions), multi-level modeling with high-order types, reification of intrinsic and relational aspects, and model taxonomy refactoring with non-sortal types.