22,819 research outputs found

    An Ontological Framework for Context-Aware Collaborative Business Process Formulation

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    In cross-enterprise collaborative environment, we have dealt with challenges in business process integration for common business goals. Research directions in this domain range from business to business integration (B2Bi) to service-oriented augmentation. Ontologies are used in Business Process Management (BPM) to reduce the gap between the business world and information technology (IT), especially in the context of cross enterprise collaboration. For a dynamic collaboration, virtual enterprises need to establish collaborative processes with appropriate matching levels of tasks. However, the problem of solving the semantics mismatching is still not tackled or even harder in case of querying space between different enterprise profiles as considered as ontologies. This article presents a framework based on the ontological and context awareness during the task integration and matching in order to form collaborative processes in the manner of cross enterprise collaboration

    The local economic development processes in low-income countries: the case of the metropolis of Chegutu in Zimbabwe

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    Local authorities are widely regarded as catalysts accelerating localised processes of economic development in industrialised countries but in low-income countries they are perceived as dysfunctional, inefficient and ineffective in meeting and addressing societal demands. This abstract view is however, not grounded in empirical research. As such, utilising the case of the metropolis of Chegutu a survey was designed to empirically explicate the economic processes militating its economic development. The findings are useful to policy-makers, local government authorities and management scholars. The study's unique contribution lies in its examination of the processes of local economic development in a low-income country

    Realizing Emancipatory Ideals in Phenomenological IS Research

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    Knowledge and perceptions in participatory policy processes: lessons from the delta-region in the Netherlands

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    Water resources management issues tend to affect a variety of uses and users. Therefore, they often exhibit complex and unstructured problems. The complex, unstructured nature of these problems originates from uncertain knowledge and from the existence of divergent perceptions among various actors. Consequently, dealing with these problems is not just a knowledge problem; it is a problem of ambiguity too. This paper focuses on a complex, unstructured water resources management issue, the sustainable development—for ecology, economy and society—of the Delta-region of the Netherlands. In several areas in this region the ecological quality decreased due to hydraulic constructions for storm water safety, the Delta Works. To improve the ecological quality, the Dutch government regards the re-establishment of estuarine dynamics in the area as the most important solution. However, re-establishment of estuarine dynamics will affect other uses and other users. Among the affected users are farmers in the surrounding areas, who use freshwater from a lake for agricultural purposes. This problem has been addressed in a participatory decision-making process, which is used as a case study in this paper. We investigate how the dynamics in actors’ perceptions and the knowledge base contribute to the development of agreed upon and valid knowledge about the problem–solution combination, using our conceptual framework for problem structuring. We found that different knowledge sources—expert and practical knowledge—should be integrated to create a context-specific knowledge base, which is scientifically valid and socially robust. Furthermore, we conclude that for the convergence of actors’ perceptions, it is essential that actors learn about the content of the process (cognitive learning) and about the network in which they are involved (strategic learning). Our findings form a plea for practitioners in water resources management to adopt a problem structuring approach in order to deal explicitly with uncertainty and ambiguity

    Social Learning Systems: The Design of Evolutionary, Highly Scalable, Socially Curated Knowledge Systems

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    In recent times, great strides have been made towards the advancement of automated reasoning and knowledge management applications, along with their associated methodologies. The introduction of the World Wide Web peaked academicians’ interest in harnessing the power of linked, online documents for the purpose of developing machine learning corpora, providing dynamical knowledge bases for question answering systems, fueling automated entity extraction applications, and performing graph analytic evaluations, such as uncovering the inherent structural semantics of linked pages. Even more recently, substantial attention in the wider computer science and information systems disciplines has been focused on the evolving study of social computing phenomena, primarily those associated with the use, development, and analysis of online social networks (OSN\u27s). This work followed an independent effort to develop an evolutionary knowledge management system, and outlines a model for integrating the wisdom of the crowd into the process of collecting, analyzing, and curating data for dynamical knowledge systems. Throughout, we examine how relational data modeling, automated reasoning, crowdsourcing, and social curation techniques have been exploited to extend the utility of web-based, transactional knowledge management systems, creating a new breed of knowledge-based system in the process: the Social Learning System (SLS). The key questions this work has explored by way of elucidating the SLS model include considerations for 1) how it is possible to unify Web and OSN mining techniques to conform to a versatile, structured, and computationally-efficient ontological framework, and 2) how large-scale knowledge projects may incorporate tiered collaborative editing systems in an effort to elicit knowledge contributions and curation activities from a diverse, participatory audience

    Evaluating the quality of a set of modelling languages used in combination: A method and a tool

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    [EN] Modelling languages have proved to be an effective tool to specify and analyse various perspectives of enterprises and information systems. In addition to modelling language designs, works on model quality and modelling language quality evaluation have contributed to the maturity of the model-driven engineering (MDE) field. Although consolidated knowledge on quality evaluation is still relevant to this scenario, in previous works, we have identified misalignments between the topics that academia is addressing and the needs of industry in applying MDE, thus identifying some remaining challenges. In this paper, we focus on the need for a method to evaluate the quality of a set of modelling languages used in combination within a MDE environment. This paper presents MMQEF (Multiple Modelling language Quality Evaluation Framework), describing its foundations, presenting its method components and discussing its trade-offs. (C) 2018 Elsevier Ltd. All rights reserved.This work was supported by COLCIENCIAS (Colombia) (grant 512, 2010); the European Commision FP7 Project CaaS (611351).Giraldo-Velásquez, FD.; España Cubillo, S.; Giraldo, WJ.; Pastor López, O. (2018). Evaluating the quality of a set of modelling languages used in combination: A method and a tool. Information Systems. 77:48-70. https://doi.org/10.1016/j.is.2018.06.002S48707

    A framework for evaluating the quality of modelling languages in MDE environments

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    This thesis presents the Multiple Modelling Quality Evaluation Framework method (hereinafter MMQEF), which is a conceptual, methodological, and technological framework for evaluating quality issues in modelling languages and modelling elements by the application of a taxonomic analysis. It derives some analytic procedures that support the detection of quality issues in model-driven projects, such as the suitability of modelling languages, traces between abstraction levels, specification for model transformations, and integration between modelling proposals. MMQEF also suggests metrics to perform analytic procedures based on the classification obtained for the modelling languages and artifacts under evaluation. MMQEF uses a taxonomy that is extracted from the Zachman framework for Information Systems (Zachman, 1987; Sowa and Zachman, 1992), which proposed a visual language to classify elements that are part of an Information System (IS). These elements can be from organizational to technical artifacts. The visual language contains a bi-dimensional matrix for classifying IS elements (generally expressed as models) and a set of seven rules to perform the classification. As an evaluation method, MMQEF defines activities in order to derive quality analytics based on the classification applied on modelling languages and elements. The Zachman framework was chosen because it was one of the first and most precise proposals for a reference architecture for IS, which is recognized by important standards such as the ISO 42010 (612, 2011). This thesis presents the conceptual foundation of the evaluation framework, which is based on the definition of quality for model-driven engineering (MDE). The methodological and technological support of MMQEF is also described. Finally, some validations for MMQEF are reported.Esta tesis presenta el método MMQEF (Multiple Modelling Quality Evaluation Framework), el cual es un marco de trabajo conceptual, metodológico y tecnológico para evaluar aspectos de calidad sobre lenguajes y elementos de modelado mediante la aplicación de análisis taxonómico. El método deriva procedimientos analíticos que soportan la detección de aspectos de calidad en proyectos model-driven tales como: idoneidad de lenguajes de modelado, trazabilidad entre niveles de abstracción, especificación de transformación de modelos, e integración de propuestas de modelado. MMQEF también sugiere métricas para ejecutar procedimientos analíticos basados en la clasificación obtenida para los lenguajes y artefactos de modelado bajo evaluación. MMQEF usa una taxonomía para Sistemas de Información basada en el framework Zachman (Zachman, 1987; Sowa and Zachman, 1992). Dicha taxonomía propone un lenguaje visual para clasificar elementos que hacen parte de un Sistema de Información. Los elementos pueden ser artefactos asociados a niveles desde organizacionales hasta técnicos. El lenguaje visual contiene una matriz bidimensional para clasificar elementos de Sistemas de Información, y un conjunto de siete reglas para ejecutar la clasificación. Como método de evaluación MMEQF define actividades para derivar analíticas de calidad basadas en la clasificación aplicada sobre lenguajes y elementos de modelado. El marco Zachman fue seleccionado debido a que éste fue una de las primeras y más precisas propuestas de arquitectura de referencia para Sistemas de Información, siendo ésto reconocido por destacados estándares como ISO 42010 (612, 2011). Esta tesis presenta los fundamentos conceptuales del método de evaluación basado en el análisis de la definición de calidad en la ingeniería dirigida por modelos (MDE). Posteriormente se describe el soporte metodológico y tecnológico de MMQEF, y finalmente se reportan validaciones.Aquesta tesi presenta el mètode MMQEF (Multiple Modelling Quality Evaluation Framework), el qual és un marc de treball conceptual, metodològic i tecnològic per avaluar aspectes de qualitat sobre llenguatges i elements de modelatge mitjançant l'aplicació d'anàlisi taxonòmic. El mètode deriva procediments analítics que suporten la detecció d'aspectes de qualitat en projectes model-driven com ara: idoneïtat de llenguatges de modelatge, traçabilitat entre nivells d'abstracció, especificació de transformació de models, i integració de propostes de modelatge. MMQEF també suggereix mètriques per executar procediments analítics basats en la classificació obtinguda pels llenguatges i artefactes de mode-lat avaluats. MMQEF fa servir una taxonomia per a Sistemes d'Informació basada en el framework Zachman (Zachman, 1987; Sowa and Zachman, 1992). Aquesta taxonomia proposa un llenguatge visual per classificar elements que fan part d'un Sistema d'Informació. Els elements poden ser artefactes associats a nivells des organitzacionals fins tècnics. El llenguatge visual conté una matriu bidimensional per classificar elements de Sistemes d'Informació, i un conjunt de set regles per executar la classificació. Com a mètode d'avaluació MMEQF defineix activitats per derivar analítiques de qualitat basades en la classificació aplicada sobre llenguatges i elements de modelatge. El marc Zachman va ser seleccionat a causa de que aquest va ser una de les primeres i més precises propostes d'arquitectura de referència per a Sistemes d'Informació, sent això reconegut per destacats estàndards com ISO 42010 (612, 2011). Aquesta tesi presenta els fonaments conceptuals del mètode d'avaluació basat en l'anàlisi de la definició de qualitat en l'enginyeria dirigida per models (MDE). Posteriorment es descriu el suport metodològic i tecnològic de MMQEF, i finalment es reporten validacions.Giraldo Velásquez, FD. (2017). A framework for evaluating the quality of modelling languages in MDE environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90628TESI
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