177 research outputs found

    Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

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    The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples.Sociedad Argentina de Informática e Investigación Operativa (SADIO

    Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

    Get PDF
    The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples

    Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

    Get PDF
    The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples.Sociedad Argentina de Informática e Investigación Operativa (SADIO

    Towards a meaningful manufacturing enterprise metamodel: a semantic driven framework

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    This paper presents a deep investigation and an interdisciplinary analysis of the collaborative networked enterprise engineering issues and modelling approaches related to the relevant aspects of the semantic web technology and knowledge strategies. The paper also suggests a novel framework based on ontology metamodelling, knowledge model discovery, and semantic web infrastructures, architectures, languages, and systems. The main aim of the research enclosed in this paper is to bridge the gaps between enterprise engineering, modelling, and especially networking by intensively applying semantic web technology based on ontology conceptual representations and knowledge discovery. The ontological modelling approaches together with knowledge strategies such as discovery (data mining) have become promising for future enterprise computing systems. The related reported research deals with the conceptual definition of a semantic-driven framework and a manufacturing enterprise metamodel (ME_M) using ontology, knowledge-driven object models, standards, and architectural approaches applied to collaborative networked enterprises. The conceptual semantic framework and related issues discussed in this paper may contribute towards new approaches of enterprise systems engineering and networking as well as applied standard and referenced ontological models

    Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

    Get PDF
    The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples.Sociedad Argentina de Informática e Investigación Operativa (SADIO

    Interoperability of Enterprise Software and Applications

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    How to connect design thinking and cyber-physical systems: the s*IoT conceptual modelling approach

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    The alignment of enterprise models and information systems is a factor that influences the efficiency of enterprise practices. Considering the changing landscape in the age of the fourth industrial revolution, it is imperative that alignment methodologies are evolved with the progression of enterprise models and the transformation from information systems to cyber-physical systems (CPSs). This issue was dissected in three layers - scenario layer, modelling layer, and run-time environment. In this structure, design thinking and CPSs were extended from the scenario layer and the run-time environment to the modelling layer. Focusing on the modelling layer, progress was made towards composing smart models that innovate enterprise models according to novel influences from design thinking while abstracting from run-time environments that CPS provide. The hypothesis was to consider the automated transformation of knowledge as an axle around which artifacts on the modelling layer revolve. Based on this hypothesis, the modelling layer was structured in a modelling hierarchy, in which a metamodel was defined using a metamodelling platform. The metamodel is the direct model of modelling methods which were used to build smart models that connect design thinking and CPSs

    Una arquitectura de referencia para ambientes web de ingeniería ontológica

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    Ontology authoring, maintenance and use are never easy tasks, mostly due to the complexity of real domains and how they dynamically change as well as different background possessed by modellers about methodologies and formal languages. However, although the needs for ontologies are well-understood, not less important is to provide editing tools to manipulate and understand them. In this context, this work proposes and documents a reference architecture for such tools running in web environments. Moreover, it provides the rationale for boosting the collaborative development of a novel tool based on this architecture, named crowd. Previous surveys reveal that few Webbased ontology engineering environments have been developed and in addition, almost all of them are mere visualisers, with limited graphical features and lacking inference services.La definición, mantenimiento y use de ontologías son tareas difíciles debido, en mayor medida, a la complejidad inherente al mundo real y a como éste cambia dinámicamente. Asimismo, también se debe a las diferencias en conocimiento sobre metodologías y lenguajes formales por parte de los modeladores. Sin embargo, aunque la necesidad de crear y obtener ontologías es clave, es también importante contar con herramientas para manipularlas y entenderlas. Este trabajo propone y documenta una arquitectura de referencia para ambientes Web y ofrece los fundamentos para impulsar el desarrollo colaborativo de la herramienta crowd, la cual esta basada sobre dicha architectura. Revisiones previas de la literatura indican la existencia de un numero reducido ambientes para la Ingeniería Ontológica basados en tecnologías Web, sin embargo, casi en su totalidad son solo visualizadores de modelos con soporte gráfico limitado y ausencia de razonamiento lógico integrado.Facultad de Informátic

    A foundation for multi-level modelling

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    Multi-level modelling allows types and instances to be mixed in the same model, however there are several proposals for how meta- models can support this. This paper proposes a meta-circular basis for meta-modelling and shows how it supports two leading approaches to multi-level modelling
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