Ontologically Correct Taxonomies by Construction (original) (raw)
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Building Correct Taxonomies with a Well-Founded Graph Grammar
Taxonomies play a central role in conceptual domain modeling having a direct impact in areas such as knowledge representation, ontology engineering, software engineering, as well as in knowledge organization in information sciences. Despite their key role, there is in the literature little guidance on how to build high-quality taxonomies, with notable exceptions such as the OntoClean methodology, and the ontology-driven conceptual modeling language OntoUML. These techniques take into account the ontological meta-properties of types to establish well-founded rules for forming taxonomic structures. In this paper, we show how to leverage on the formal rules underlying these techniques to build taxonomies which are correct by construction. We define a set of correctness-preserving operations to systematically introduce types and subtyping relations into taxonomic structures. To validate our proposal, we formalize these operations as a graph grammar. Moreover, to demonstrate our claim of correctness by construction , we use automatic verification techniques over the grammar language to show that: (i) all taxonomies produced by the grammar rules are correct; and (ii) the rules can generate all correct taxonomies.
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.
Acquisition And Structuring Of An Ontology Within Conceptual Graphs
1994
The elicitation of the ontology i.e. the objects of a domain is a key issue of conceptual modelling and therefore of knowledge acquisition. The Conceptual Graph Theory provides a knowledge representation formalism to be used in knowledgebased systems with an explicit type lattice" to account for the ontology. Since knowledge is in most AI applications non formal, it has to be normalized to ensure that the formal exploitation of its representation conforms to its meaning in the domain. Noting the intensional nature of types, which re ect the essences of the objects they denote, this normalization relies on a commitment o n t ype de nitions by necessary and su cient conditions at the knowledge level. Our claim is that the taxonomic structure that accounts for the intensional nature of the ontology can be nothing but a tree, precluding tangled taxonomies. From this starting point, we derive methodological principles to constrain the acquisition of the type tree", thus helping in the design of a domain ontology. These principles are currently applied to acquire the ontology and related knowledge in the context of the knowledgebased part of Menelas, a natural language understanding project in the medical domain, which uses Conceptual Graphs as its core formalism.
Formal Definition of a General Ontology Pattern Language using a Graph Grammar
—In recent years, there has been a growing interest in the use of ontological theories in the philosophical sense (Foundational Ontologies) to analyze and (re)design conceptual modeling languages. This paper is about an ontologically well-founded conceptual modeling language in this tradition, termed OntoUML. This language embeds a number of ontological patterns that reflect the micro-theories comprising a particular foundational ontology named UFO. We here (re)define OntoUML as a formal graph grammar and demonstrate how the models of this language can be constructed by the combined application of ontological patterns following a number of graph transformation rules. As a result, we obtain a version of this language fully defined as a formal Ontology Pattern Grammar. In other words, this paper presents a formal definition of OntoUML that is both explicit in terms of the ontological patterns that it incorporates and is completely independent of the UML meta-model.
Endurant Types in Ontology-Driven Conceptual Modeling: Towards OntoUML 2.0
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.
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 conceptual 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 underlying the taxonomy of types in the Unified Foundational Ontolo-gy (UFO) (e.g., kinds, phases, roles, mixins, etc.). This approach has focused so far on the support 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 address 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 discuss the impact of the extended foundation to multi-level conceptual modeling.
A Linguistic Approach to Conceptual Modeling with Semantic Types and OntoUML
2010 14th IEEE International Enterprise Distributed Object Computing Conference Workshops, 2010
The process of conceptual modeling involves the acquisition of concepts (and of the signs that represent them) used in the Universe of Discourse (UoD) being modeled, and the creation of the model (as a concrete artifact) according to a modeling language grammar. The knowledge about the UoD is obtained from a variety of sources, all of which are mostly expressed in a natural language. It is correct to say that conceptual modeling is much similar to language translation i.e., identifying concepts that are represented by signs of a language, and then representing those same concepts in a different language. Also, the semantic quality of the resulting model (translation) is directly affected by the modeler's (translator's) understanding of the source material. As so, conceptual modeling activities can benefit from an analysis carried out from a linguistic point of view, as well as from the use of a modeling language which constructs allow for a representation that is semantically equivalent to the natural language original descriptions. This work proposes a linguistic approach to conceptual modeling based on the notion of semantic types, and on the use of OntoUML as a modeling language. The proposed approach is illustrated in an example.
Abstracting Ontology-Driven Conceptual Models: Objects, Aspects, Events, and their Parts
International Conference on Research Challenges in Information Science (RCIS), 2022
Ontology-driven conceptual models are widely used to capture information about complex and critical domains. Therefore, it is essential for these models to be comprehensible and cognitively tractable. Over the years, different techniques for complexity management in conceptual models have been suggested. Among these, a prominent strategy is model abstraction. This work extends an existing strategy for model abstraction of OntoUML models that proposes a set of graph-rewriting rules leveraging on the ontological semantics of that language. That original work, however, only addresses a set of the ontological notions covered in that language. We review and extend that rule set to cover more generally types of objects, aspects, events, and their parts.
Stability Patterns in Ontology-Driven Conceptual Modeling
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.
Methodological Principles for Structuring an "Ontology
1995
The knowledge used in most AI applications does not rely on a formal model of the domain. Therefore, it has to be normalized to ensure that the formal exploitation of its representation conforms to its meaning in the domain. Considering the intensional non extensional nature of concepts, which re ects the essences of the objects they denote, this normalization relies on a commitment o n t ype denitions by necessary and su cient conditions at the knowledge level. Our claim is that the taxonomic structure that accounts for the intensional nature of the ontology can be nothing but a tree. From this starting point, we derive methodological principles to constrain and justify the structuring of ontological types. Based on this methodology, w e advocate understandability o f a n o n tology rather than a putative reusability.