991 resultados para Conceptual modelling


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Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behaviour of a dynamic system. The learner?s task then is to bridge the gap between their initial model, as their first attempt to represent the system, and the target models that provide solutions to that problem. We propose the use of semantic technologies and resources to help in bridging that gap by providing links to terminology and formal definitions, and matching techniques to allow learners to benefit from existing models.

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La innovación en Sistemas Intesivos en Software está alcanzando relevancia por múltiples razones: el software está presente en sectores como automóvil, teléfonos móviles o salud. Las empresas necesitan conocer aquellos factores que afectan a la innovación para incrementar las probabilidades de éxito en el desarrollo de sus productos y, la evaluación de productos sofware es un mecanismo potente para capturar este conocimiento. En consecuencia, las empresas necesitan evaluar sus productos desde la perpectiva de innovación para reducir la distancia entre los productos desarrollados y el mercado. Esto es incluso más relevante en el caso de los productos intensivos en software, donde el tiempo real, la oportunidad, complejidad, interoperabilidad, capacidad de respuesta y compartción de recursos son características críticas de los nuevos sistemas. La evaluación de la innovación de productos ya ha sido estudiada y se han definido algunos esquemas de evaluación pero no son específicos para Sistemas intensivos en Sofwtare; además, no se ha alcanzado consenso en los factores ni el procedimiento de evaluación. Por lo tanto, tiene sentido trabajar en la definición de un marco de evaluación de innovación enfocado a Sistemas intesivos en Software. Esta tesis identifica los elementos necesarios para construir in marco para la evaluación de de Sistemas intensivos en Software desde el punto de vista de la innovación. Se han identificado dos componentes como partes del marco de evaluación: un modelo de referencia y una herramienta adaptativa y personalizable para la realización de la evaluación y posicionamiento de la innovación. El modelo de referencia está compuesto por cuatro elementos principales que caracterizan la evaluación de innovación de productos: los conceptos, modelos de innovación, cuestionarios de evaluación y la evaluación de productos. El modelo de referencia aporta las bases para definir instancias de los modelos de evaluación de innovación de productos que pueden se evaluados y posicionados en la herramienta a través de cuestionarios y que de forma automatizada aporta los resultados de la evaluación y el posicionamiento respecto a la innovación de producto. El modelo de referencia ha sido rigurosamente construido aplicando modelado conceptual e integración de vistas junto con la aplicación de métodos cualitativos de investigación. La herramienta ha sido utilizada para evaluar productos como Skype a través de la instanciación del modelo de referencia. ABSTRACT Innovation in Software intensive Systems is becoming relevant for several reasons: software is present embedded in many sectors like automotive, robotics, mobile phones or heath care. Firms need to have knowledge about factors affecting the innovation to increase the probability of success in their product development and the assessment of innovation in software products is a powerful mechanism to capture this knowledge. Therefore, companies need to assess products from an innovation perspective to reduce the gap between their developed products and the market. This is even more relevant in the case of SiSs, where real time, timeliness, complexity, interoperability, reactivity, and resource sharing are critical features of a new system. Many authors have analysed product innovation assessment and some schemas have been developed but they are not specific to SiSs; in addition, there is no consensus about the factors or the procedures for performing an assessment. Therefore, it has sense to work in the definition of a customized software product innovation evaluation framework. This thesis identifies the elements needed to build a framework to assess software products from the innovation perspective. Two components have been identified as part of the framework to assess Software intensive Systems from the innovation perspective: a reference-model and an adaptive and customizable tool to perform the assessment and to position product innovation. The reference-model is composed by four main elements characterizing product innovation assessment: concepts, innovation models, assessment questionnaires and product assessment. The reference model provides the umbrella to define instances of product innovation assessment models that can be assessed and positioned through questionnaires in the proposed tool that also provides automation in the assessment and positioning of innovation. The reference-model has been rigorously built by applying conceptual modelling and view integration integrated with qualitative research methods. The tool has been used to assess products like Skype through models instantiated from the reference-model.

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Nowadays, data mining is based on low-level specications of the employed techniques typically bounded to a specic analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Here, we propose a model-driven approach based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (via data-warehousing technology) and the analysis models for data mining (tailored to a specic platform). Thus, analysts can concentrate on the analysis problem via conceptual data-mining models instead of low-level programming tasks related to the underlying-platform technical details. These tasks are now entrusted to the model-transformations scaffolding.

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Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.

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This paper reviews the key features of an environment to support domain users in spatial information system (SIS) development. It presents a full design and prototype implementation of a repository system for the storage and management of metadata, focusing on a subset of spatial data integrity constraint classes. The system is designed to support spatial system development and customization by users within the domain that the system will operate.

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Enterprise systems interoperability (ESI) is an important topic for business currently. This situation is evidenced, at least in part, by the number and extent of potential candidate protocols for such process interoperation, viz., ebXML, BPML, BPEL, and WSCI. Wide-ranging support for each of these candidate standards already exists. However, despite broad acceptance, a sound theoretical evaluation of these approaches has not yet been provided. We use the Bunge-Wand-Weber (BWW) models, in particular, the representation model, to provide the basis for such a theoretical evaluation. We, and other researchers, have shown the usefulness of the representation model for analyzing, evaluating, and engineering techniques in the areas of traditional and structured systems analysis, object-oriented modeling, and process modeling. In this work, we address the question, what are the potential semantic weaknesses of using ebXML alone for process interoperation between enterprise systems? We find that users will lack important implementation information because of representational deficiencies; due to ontological redundancy, the complexity of the specification is unnecessarily increased; and, users of the specification will have to bring in extra-model knowledge to understand constructs in the specification due to instances of ontological excess.

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The ontological analysis of conceptual modelling techniques is of increasing popularity. Related research did not only explore the ontological deficiencies of classical techniques such as ER or UML, but also business process modelling techniques such as ARIS or even Web services standards such as BPEL4WS. While the selected ontologies are reasonably mature, it is the actual process of an ontological analysis that still lacks rigor. The current procedure leaves significant room for individual interpretations and is one reason for criticism of the entire ontological analysis. This paper proposes a procedural model for the ontological analysis based on the use of meta models, the involvement of more than one coder and metrics. This model is explained with examples from various ontological analyses.

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Conceptual modeling forms an important part of systems analysis. If this is done incorrectly or incompletely, there can be serious implications for the resultant system, specifically in terms of rework and useability. One approach to improving the conceptual modelling process is to evaluate how well the model represents reality. Emergence of the Bunge-Wand-Weber (BWW) ontological model introduced a platform to classify and compare the grammar of conceptual modelling languages. This work applies the BWW theory to a real world example in the health arena. The general practice computing group data model was developed using the Barker Entity Relationship Modelling technique. We describe an experiment, grounded in ontological theory, which evaluates how well the GPCG data model is understood by domain experts. The results show that with the exception of the use of entities to represent events, the raw model is better understood by domain experts