16 research outputs found

    Ontology Validation for Managers

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    Ontology driven conceptual modeling focuses on accurately representing a domain of interest, instead of making information fit an arbitrary set of constructs. It may be used for different purposes, like to achieve semantic interoperability (Nardi, Falbo and Almeida, 2013), development of knowledge representation models (Guizzardi and Zamborlini, 2012) and language evaluation (Santos, Almeida and Guizzardi,2010). Regardless its final application, a model must be accurately defined in order for it to be a successful solution. This new branch of conceptual modeling improves traditional techniques by taking into consideration ontological properties, such as rigidity, identity and dependence, which are derived from a foundational ontology. This increasing interest in more expressive languages for conceptual modeling is shown by OMGs request for language proposals for the Semantic Information Model Federation (SIMF) (OMG,2011). OntoUML (Guizzardi, 2005) is an example of a language designed for that purpose.Its metamodel (Carraretto, 2010) is designed to comply to the Unified Foundational Ontology (UFO). It focus on structural aspects of individuals and universals.Grounded on human cognition and linguistics, it aims to provide the most basic categories in which humans understand and classify things around them.In (Guizzardi, 2010) Guizzardi quotes the famous Dijkstras lecture, in which he discusses the humble programmer and makes an analogy entitled the humble ontologist. He argues that the task of ontology-driven conceptual modeling is extremely complex and thus, modelers should surround themselves with as many tools as possible to aid in the development of the ontology. These complexities arise from different sources. A couple of them come from foundational ontology itself, both its modal nature, which imposes modelers to deal with possibilities, and the many different restrictions of each ontological category. But they also come from the need of accurately defining instance level constraints, which require additional rules, outside of the languages graphical notation. To help modelers to develop high quality OntoUML models, a number of tools have been proposed to aid in different phases of conceptual modeling. From the construction of the models themselves using design patterns questions (Guizzardi et al., 2011), to automatic syntax verification (Benevides, 2010) and model validation through simulation (Benevides et al., 2010). The importance of domain specification that accurately captures the intended conceptualization has been recognized by both the traditional conceptual modeling community (Moody et al., 2003) and the ontology community (Vrandečić, 2009). In this research we want to improve (Benevides et al., 2010) initiative, but focus exclusively on the validation of ontology driven conceptual models, and not on verification. With the complexity of the modeling activity in mind, we want to help modelers to systematically produce high quality ontologies, improving precision and coverage (Gangemi et al., 2005) of the models. We intend to make the simulationbased approach available for users that are not experts in the formal method, relieving them of the need to learn yet another language, solely for the purpose of validating their models

    Extending OntoUML Modelling Capabilities on the OpenPonk Platform

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    Tato práce se zaměřuje na rozšíření možností pro vytváření OntoUML modelů na platformě OpenPonk. Toto rozšíření je rozděleno do čtyř částí. Prvním rozšířením je grafické uživatelské rozhraní pro zobrazování výsledků verifikačního frameworku. Druhá část je prezenotvána novým frameworkem, sloužícím k automatické aktualizaci OunoUML verifikací. Třetím rozšířením je automatická detekce OntoUML anit-patternů. Poslední část se sestává z vybudování nové sekce portálu ontouml.org, obsahující dokumentaci k jednotlivým anti-patternům. V závěru práce je detekce anti-patternů demostrována na referenčním modelu.This work focuses on extending OntoUML modelling capabilities on the OpenPonk platform. This is done in four parts. First part of the expansion is graphical user interface for displaying results of the verification framework. Second part is represented by new framework, which is used for automatic updating of OntoUML verifications. Third part of the expansion is automatic detection of OntoUML anti-patterns. Last part consists of new section on portal ontouml.org, dedicated to anti-pattern documentation. End of this thesis focuses on demonstration of the anti-pattern detection using reference model

    Modeling and Analysis of Software Product Line Variability in Clafer

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    Both feature and class modeling are used in Software Product Line (SPL) engineering to model variability. Feature models are used primarily to represent user-visible characteristics (i.e., features) of products; whereas class models are often used to model types of components and connectors in a product-line architecture. Previous works have explored the approach of using a single language to express both configurations of features and components. Their goal was to simplify the definition and analysis of feature-to-component mappings and to allow modeling component options as features. A prominent example of this approach is cardinality-based feature modeling, which extends feature models with multiple instantiation and references to express component-like, replicated features. Another example is to support feature modeling in a class modeling language, such as UML or MOF, using their profiling mechanisms and a stylized use of composition. Both examples have notable drawbacks: cardinality-based feature modeling lacks a constraint language and a well-defined semantics; encoding feature models as class models and their evolution bring extra complexity. This dissertation presents Clafer (class, feature, reference), a class modeling language with first-class support for feature modeling. Clafer can express rich structural models augmented with complex constraints, i.e., domain, variability, component models, and meta-models. Clafer supports: (i) class-based meta-models, (ii) object models (with uncertainty, if needed), (iii) feature models with attributes and multiple instantiation, (iv) configurations of feature models, (v) mixtures of meta- and feature models and model templates, and (vi) first-order logic constraints. Clafer also makes it possible to arrange models into multiple specialization and extension layers via constraints and inheritance. On the other hand, in designing Clafer we wanted to create a language that builds upon as few concepts as possible, and is easy to learn. The language is supported by tools for SPL verification and optimization. We propose to unify basic modeling constructs into a single concept, called clafer. In other words, Clafer is not a hybrid language. We identify several key mechanisms allowing a class modeling language to express feature models concisely. We provide Clafer with a formal semantics built in a novel, structurally explicit way. As Clafer subsumes cardinality-based feature modeling with attributes, references, and constraints, we are the first to precisely define semantics of such models. We also explore the notion of partial instantiation that allows for modeling with uncertainty and variability. We show that Object-Oriented Modeling (OOM) languages with no direct support for partial instances can support them via class modeling, using subclassing and strengthening multiplicity constraints. We make the encoding of partial instances via subclassing precise and general. Clafer uses this encoding and pushes the idea even further: it provides a syntactic unification of types and (partial) instances via subclassing and redefinition. We evaluate Clafer analytically and experimentally. The analytical evaluation shows that Clafer can concisely express feature and meta-models via a uniform syntax and unified semantics. The experimental evaluation shows that: 1) Clafer can express a variety of realistic rich structural models with complex constraints, such as variability models, meta-models, model templates, and domain models; and 2) that useful analyses can be performed within seconds

    Uma linguagem para formalização de discursos com base em ontologias

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    Tese (doutorado)—Universidade de Brasília, Faculdade de Ciência da Informação, Programa de Pós-Graduação em Ciência da Informação, 2015.Esta pesquisa propõe a arquitetura da informação de uma linguagem formal textual para representar discursos sobre entidades ontológicas e obter deduções a respeito de ontologias de domínio. Por meio do paradigma de metamodelagem, a linguagem permite tratamento de ontologias heterogêneas que podem ser descritas como instâncias de uma ou mais ontologias de fundamentação. A linguagem suporta comportamentos clássicos e modais sustentados por noções de prova baseadas no paradigma de Programação em Lógica (Modal). O arcabouço modal desenvolvido possibilita que diferentes interpretações modais sejam introduzidas às especificações das ontologias, e contempla especialmente sistemas baseados em lógicas de múltiplos agentes. Uma sistematização do fragmento endurante da Unified Foundational Ontology (UFO) é realizada com objetivo de compor parte do marco teórico que fundamenta a proposta e de servir de exemplo de instanciação do arcabouço desenvolvido. Como resultados complementares, destacam-se: uma sistematização de um conjunto ampliado de regras para produção de modelos conceituais e um glossário detalhado de termos e conceitos da UFO-A; protótipos funcionais que implementam os sistemas elaborados; traduções das teorias descritas no arcabouço proposto para linguagens visuais, como extensões da representação gráfica da OntoUML; e discussões a respeito da integração de Arquitetura da Informação, Modelagem Conceitual e Programação em Lógica (Modal) no contexto social aplicado.This research proposes the information architecture of a textual formal language to represent and reason about ontological entities based on foundational ontologies. Through metamodeling, the language is able to deal with heterogeneous ontologies that can be described as instances of one or more foundational ontology. The language provides classic and modal inference mechanisms supported by proof notions based on the (Modal) Logic Programming paradigm. The modalities introduced by the modal framework allow a wide range of interpretations, including multi-agent systems. A systematization of the endurant fragment of the Unified Foundational Ontology (UFO) is produced in order to compose part of the theoretical framework underlying the proposal, and to serve as an example instantiating the developed framework. As complementary results we highlight: a systematization of an extended set of rules for conceptual modeling and a detailed glossary of terms and concepts of UFO-A; functional prototypes implementing the developed systems; translations of the theories described as instances of the framework to diagramatic representations, as extensions of the OntoUML visual language; and discussions regarding the integration of Information Architecture, Conceptual Modeling and Logic Programming within Applied Social Science

    UFO: Unified Foundational Ontology

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    The Unified Foundational Ontology (UFO) was developed over the last two decades by consistently putting together theories from areas such as formal ontology in philosophy, cognitive science, linguistics, and philosophical logics. It comprises a number of micro-theories addressing fundamental conceptual modeling notions, including entity types and relationship types. The aim of this paper is to summarize the current state of UFO, presenting a formalization of the ontology, along with the analysis of a number of cases to illustrate the application of UFO and facilitate its comparison with other foundational ontologies in this special issue. (The cases originate from the First FOUST Workshop – the Foundational Stance, an international forum dedicated to Foundational Ontology research.

    Spatial ontologies for architectural heritage

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    Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications

    Representing Dynamic Invariants in Ontologically Well-Founded Conceptual Models

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    Conceptual models often capture the invariant aspects of the phenomena we perceive. These invariants may be considered static when they refer to structures we perceive in phenomena at a particular point in time or dynamic/temporal when they refer to regularities across different points in time. While static invariants have received significant attention, dynamics enjoy marginal support in widely-employed techniques such as UML and OCL. This thesis aims at addressing this gap by proposing a technique for the representation of dynamic invariants of subject domains in UML-based conceptual models. For that purpose, a temporal extension of OCL is proposed. It enriches the ontologically well-founded OntoUML profile and enables the expression of a variety of (arbitrary) temporal constraints. The extension is fully implemented in the tool for specification, verification and simulation of enriched OntoUML models

    Spatial ontologies for architectural heritage

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    Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications
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