An enterprise modeling and integration framework based on knowledge discovery and data mining

This paper deals with the conceptual design and development of an enterprise modeling and integration framework using knowledge discovery and data mining. First, the paper briefly presents the background and current state-of-the-art of knowledge discovery in databases and data mining systems and projects. Next, enterprise knowledge engineering is dealt with. The paper suggests a novel approach of utilizing existing enterprise reference architectures, integration and modeling frameworks by the introduction of new enterprise views such as mining and knowledge views. An extension and a generic exploration of the information view that already exists within some enterprise models are also proposed. The Zachman Framework for Enterprise Architecture is also outlined versus the existing architectures and the proposed enterprise framework. The main contribution of this paper is the identification and definition of a common knowledge enterprise model which represents an original combination between the previous projects on enterprise architectures and the Object Management Group (OMG) models and standards. The identified common knowledge enterprise model has therefore been designed using the OMG's Model-Driven Architecture (MDA) and Common Warehouse MetaModel (CWM), and it also follows the RM-ODP (ISO/OSI). It has been partially implemented in Java(TM), Enterprise JavaBeans (EJB) and Corba/IDL. Finally, the advantages and limitations of the proposed enterprise model are outlined

A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach

A prominent and contemporary challenge for supply chain (SC) managers concerns the coordination of the efforts of the nodes of the SC in order to mitigate unpredictable market behaviour and satisfy variable customer demand. A productive response to this challenge is to share pertinent market-related information, on a timely basis, in order to effectively manage the decision-making associated with the SC production and transportation planning processes. This paper analyses the most well-known reference modelling languages and frameworks in the collaborative SC field and proposes a novel reference architecture, based upon the Zachman Framework (ZF), for supporting collaborative plan- ning (CP) in multi-level, SC networks. The architecture is applied to an automotive supply chain configuration, where, under a collaborative and decentralised approach, improvements in the service levels for each node were observed. The architecture was shown to provide the base discipline for the organisation of the processes required to manage the CP activity.The authors thanks the support from the project 'Operations Design and Management in Global Supply Chains (GLOBOP)' (Ref. DPI2012-38061-C02-01), funded by the Ministry of Science and Education of Spain, for the supply chain environment research contribution.Hernández Hormazábal, JE.; Lyons, AC.; Poler, R.; Mula, J.; Goncalves, R. (2014). A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach. Production Planning and Control. 25(13-14):1118-1134. https://doi.org/10.1080/09537287.2013.808842S111811342513-14Al-Mutawah, K., Lee, V., & Cheung, Y. (2008). A new multi-agent system framework for tacit knowledge management in manufacturing supply chains. Journal of Intelligent Manufacturing, 20(5), 593-610. doi:10.1007/s10845-008-0142-0Baïna, S., Panetto, H., & Morel, G. (2009). New paradigms for a product oriented modelling: Case study for traceability. Computers in Industry, 60(3), 172-183. doi:10.1016/j.compind.2008.12.004Berasategi, L., Arana, J., & Castellano, E. (2011). A comprehensive framework for collaborative networked innovation. Production Planning & Control, 22(5-6), 581-593. doi:10.1080/09537287.2010.536628Chan, H. K., & Chan, F. T. S. (2009). A review of coordination studies in the context of supply chain dynamics. International Journal of Production Research, 48(10), 2793-2819. doi:10.1080/00207540902791843Chen, D., Doumeingts, G., & Vernadat, F. (2008). Architectures for enterprise integration and interoperability: Past, present and future. Computers in Industry, 59(7), 647-659. doi:10.1016/j.compind.2007.12.016Choi, Y., Kang, D., Chae, H., & Kim, K. (2006). An enterprise architecture framework for collaboration of virtual enterprise chains. The International Journal of Advanced Manufacturing Technology, 35(11-12), 1065-1078. doi:10.1007/s00170-006-0789-7Choi, Y., Kim, K., & Kim, C. (2005). A design chain collaboration framework using reference models. The International Journal of Advanced Manufacturing Technology, 26(1-2), 183-190. doi:10.1007/s00170-004-2262-9COLQUHOUN, G. J., BAINES, R. W., & CROSSLEY, R. (1993). A state of the art review of IDEFO. International Journal of Computer Integrated Manufacturing, 6(4), 252-264. doi:10.1080/09511929308944576Danilovic, M., & Winroth, M. (2005). A tentative framework for analyzing integration in collaborative manufacturing network settings: a case study. Journal of Engineering and Technology Management, 22(1-2), 141-158. doi:10.1016/j.jengtecman.2004.11.008Derrouiche, R., Neubert, G., Bouras, A., & Savino, M. (2010). B2B relationship management: a framework to explore the impact of collaboration. Production Planning & Control, 21(6), 528-546. doi:10.1080/09537287.2010.488932Dudek, G., & Stadtler, H. (2005). Negotiation-based collaborative planning between supply chains partners. European Journal of Operational Research, 163(3), 668-687. doi:10.1016/j.ejor.2004.01.014Gruat La Forme, F.-A., Genoulaz, V. B., & Campagne, J.-P. (2007). A framework to analyse collaborative performance. Computers in Industry, 58(7), 687-697. doi:10.1016/j.compind.2007.05.007Gutiérrez Vela, F. L., Isla Montes, J. L., Paderewski Rodríguez, P., Sánchez Román, M., & Jiménez Valverde, B. (2007). An architecture for access control management in collaborative enterprise systems based on organization models. Science of Computer Programming, 66(1), 44-59. doi:10.1016/j.scico.2006.10.005Hernández, J. E., Poler, R., Mula, J., & Lario, F. C. (2010). The Reverse Logistic Process of an Automobile Supply Chain Network Supported by a Collaborative Decision-Making Model. Group Decision and Negotiation, 20(1), 79-114. doi:10.1007/s10726-010-9205-7Hernández, J. E., J. Mula, R. Poler, and A. C. Lyons. 2013. “Collaborative Planning in Multi-Tier Supply Chains Supported by a Negotiation-Based Mechanism and Multi-Agent System.”Group Decision and Negotiation Journal. doi:10.1007/s10726-013-9358-2.Jardim-Goncalves, R., Grilo, A., Agostinho, C., Lampathaki, F., & Charalabidis, Y. (2013). Systematisation of Interoperability Body of Knowledge: the foundation for Enterprise Interoperability as a science. Enterprise Information Systems, 7(1), 7-32. doi:10.1080/17517575.2012.684401Kampstra, R. P., Ashayeri, J., & Gattorna, J. L. (2006). Realities of supply chain collaboration. The International Journal of Logistics Management, 17(3), 312-330. doi:10.1108/09574090610717509Kim, W., Chung, M. J., Qureshi, K., & Choi, Y. K. (2006). WSCPC: An architecture using semantic web services for collaborative product commerce. Computers in Industry, 57(8-9), 787-796. doi:10.1016/j.compind.2006.04.007Ku, K.-C., Kao, H.-P., & Gurumurthy, C. K. (2007). Virtual inter-firm collaborative framework—An IC foundry merger/acquisition project. Technovation, 27(6-7), 388-401. doi:10.1016/j.technovation.2007.02.010LEE, J., GRUNINGER, M., JIN, Y., MALONE, T., TATE, A., YOST, G., & OTHER MEMBERS OF THE PIF WORKING GROUP. (1998). The Process Interchange Format and Framework. The Knowledge Engineering Review, 13(1), 91-120. doi:10.1017/s0269888998001015Lee, J., Chae, H., Kim, C.-H., & Kim, K. (2009). Design of product ontology architecture for collaborative enterprises. Expert Systems with Applications, 36(2), 2300-2309. doi:10.1016/j.eswa.2007.12.042Liu, J., Zhang, S., & Hu, J. (2005). A case study of an inter-enterprise workflow-supported supply chain management system. Information & Management, 42(3), 441-454. doi:10.1016/j.im.2004.01.010Marques, D. M. N., & Guerrini, F. M. (2011). Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment. Production Planning & Control, 23(8), 609-623. doi:10.1080/09537287.2011.572469Mula, J., Peidro, D., & Poler, R. (2010). The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. International Journal of Production Economics, 128(1), 136-143. doi:10.1016/j.ijpe.2010.06.007Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4), 541-580. doi:10.1109/5.24143Noran, O. (2003). An analysis of the Zachman framework for enterprise architecture from the GERAM perspective. Annual Reviews in Control, 27(2), 163-183. doi:10.1016/j.arcontrol.2003.09.002Olorunniwo, F. O., & Li, X. (2010). Information sharing and collaboration practices in reverse logistics. Supply Chain Management: An International Journal, 15(6), 454-462. doi:10.1108/13598541011080437Recker, J., Rosemann, M., Indulska, M., … Green, P. (2009). Business Process Modeling- A Comparative Analysis. Journal of the Association for Information Systems, 10(04), 333-363. doi:10.17705/1jais.00193Rodriguez, K., & Al-Ashaab, A. (2005). Knowledge web-based system architecture for collaborative product development. Computers in Industry, 56(1), 125-140. doi:10.1016/j.compind.2004.07.004Romero, F., Company, P., Agost, M.-J., & Vila, C. (2008). Activity modelling in a collaborative ceramic tile design chain: an enhanced IDEF0 approach. Research in Engineering Design, 19(1), 1-20. doi:10.1007/s00163-007-0040-zSandberg, E. (2007). Logistics collaboration in supply chains: practice vs. theory. The International Journal of Logistics Management, 18(2), 274-293. doi:10.1108/09574090710816977Spekman, R. E., & Carraway, R. (2006). Making the transition to collaborative buyer–seller relationships: An emerging framework. Industrial Marketing Management, 35(1), 10-19. doi:10.1016/j.indmarman.2005.07.002Stevens, W. P., Myers, G. J., & Constantine, L. L. (1974). Structured design. IBM Systems Journal, 13(2), 115-139. doi:10.1147/sj.132.0115Ulieru, M. (2000). A multi-resolution collaborative architecture for web-centric global manufacturing. Information Sciences, 127(1-2), 3-21. doi:10.1016/s0020-0255(00)00026-8Van der Aalst, W. M. P. (1999). Formalization and verification of event-driven process chains. Information and Software Technology, 41(10), 639-650. doi:10.1016/s0950-5849(99)00016-6Zachman, J. A. (1987). A framework for information systems architecture. IBM Systems Journal, 26(3), 276-292. doi:10.1147/sj.263.0276Zapp, M., Forster, C., Verl, A., & Bauernhansl, T. (2012). A Reference Model for Collaborative Capacity Planning Between Automotive and Semiconductor Industry. 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A framework for evaluating the quality of modelling languages in MDE environments

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

Enterprise modelling framework for dynamic and complex business environment: socio-technical systems perspective

The modern business environment is characterised by dynamism and ambiguity. The causes include global economic change, rapid change requirements, shortened development life cycles and the increasing complexity of information technology and information systems (IT/IS). However, enterprises have been seen as socio-technical systems. The dynamic complex business environment cannot be understood without intensive modelling and simulation. Nevertheless, there is no single description of reality, which has been seen as relative to its context and point of view. Human perception is considered an important determinant for the subjectivist view of reality. Many scholars working in the socio-technical systems and enterprise modelling domains have conceived the holistic sociotechnical systems analysis and design possible using a limited number of procedural and modelling approaches. For instance, the ETHICS and Human-centred design approaches of socio-technical analysis and design, goal-oriented and process-oriented modelling of enterprise modelling perspectives, and the Zachman and DoDAF enterprise architecture frameworks all have limitations that can be improved upon, which have been significantly explained in this thesis. [Continues.

Comprehensive measurement framework for enterprise architectures

Enterprise Architecture defines the overall form and function of systems across an enterprise involving the stakeholders and providing a framework, standards and guidelines for project-specific architectures. Project-specific Architecture defines the form and function of the systems in a project or program, within the context of the enterprise as a whole with broad scope and business alignments. Application-specific Architecture defines the form and function of the applications that will be developed to realize functionality of the system with narrow scope and technical alignments. Because of the magnitude and complexity of any enterprise integration project, a major engineering and operations planning effort must be accomplished prior to any actual integration work. As the needs and the requirements vary depending on their volume, the entire enterprise problem can be broken into chunks of manageable pieces. These pieces can be implemented and tested individually with high integration effort. Therefore it becomes essential to analyze the economic and technical feasibility of realizable enterprise solution. It is difficult to migrate from one technological and business aspect to other as the enterprise evolves. The existing process models in system engineering emphasize on life-cycle management and low-level activity coordination with milestone verification. Many organizations are developing enterprise architecture to provide a clear vision of how systems will support and enable their business. The paper proposes an approach for selection of suitable enterprise architecture depending on the measurement framework. The framework consists of unique combination of higher order goals, non-functional requirement support and inputs-outcomes pair evaluation. The earlier efforts in this regard were concerned about only custom scales indicating the availability of a parameter in a range.Comment: 22 Page

Using the Unified Modeling Language (UML) to represent artefacts in the Zachman Frameword

An interpretive research approach will be used to describe and decompose UML diagrams into their respective building blocks. A top down approach will be used to determine views that are important to enterprises during the system development lifecycle. The importance of providing graphical representations to describe conceptual ideas will be stressed. A short history will be provided of the origins of UML as well as a description of the diagrams used. Since UML is a language and not a methodology a brief discussion regarding a methodology, the Rational Unified Process, will be covered. The Zachman framework will be used to present a two-dimensional (Columns and Rows) view of an enterprise together with a summary of what could be represented in the framework. The UML building blocks will be mapped within the Zachman framework together with possible reasons for the mapping. The paper will conclude by combining several views by different authors to represent artefacts within the Zachman framework and to show the strengths and weaknesses of the current UML version 1.5 and what organisations should be aware of when considering implementing UML.Dissertation (M.IT)--University of Pretoria, 2007.Informaticsunrestricte

Conceptual modeling for the design of intelligent and emergent information systems

A key requirement to today's fast changing economic environment is the ability of organizations to adapt dynamically in an effective and efficient manner. Information and Communication Technologies play a crucially important role in addressing such adaptation requirements. The notion of `intelligent software' has emerged as a means by which enterprises can respond to changes in a reactive manner but also to explore, in a pro-active manner, possibilities for new business models. The development of such software systems demands analysis, design and implementation paradigms that recognize the need for ‘co-development’ of these systems with enterprise goals, processes and capabilities. The work presented in this paper is motivated by this need and to this end it proposes a paradigm that recognizes co-development as a knowledge-based activity. The proposed solution is based on a multi-perspective modeling approach that involves (i) modeling key aspects of the enterprise, (ii) reasoning about design choices and (iii) supporting strategic decision-making through simulations. The utility of the approach is demonstrated though a case study in the field of marketing for a start-up company

Primitives: Design Guidelines and Architecture for BPMN Models

The Business Process Modeling Notation has emerged as a popular choice for representing processes among Business Analysts and Information Systems professionals. While the BPMN specification provides a rich syntax for the capture and representation of process models, it does not provide any guidance for the organization of the resulting models. As a consequence, large process libraries may become disorganized and hard to manage due to variability in abstraction levels, process interfaces, and activity descriptions. Based on the analysis of a process library in a US government agency we present a proposal for design guidelines and use our design guideline to qualitatively assess existing work on model quality guidance. To better organize models at different abstraction levels we propose a process architecture that allows for the systematic organization of BPMN models for different stakeholder concerns

Enterprise architecture for small and medium-sized enterprises : CHOOSE

Enterprise architecture (EA) is a coherent whole of principles, methods, and models that are used in the design and realization of an enterprise’s organizational structure, business processes, information systems, and IT infrastructure. EA is used as a holistic approach to keep things aligned in a company. Some emphasize the use of EA to align IT with the business, others see it broader and use it to also keep the processes aligned with the strategy. Recent research indicates the need for EA in small and medium-sized enterprises (SMEs), important drivers of the economy, as they struggle with problems related to a lack of structure and overview of their business. However, existing EA frameworks are perceived as too complex and, to date, none of the EA approaches are sufficiently adapted to the SME context. Therefore, in this PhD, we present the CHOOSE approach for EA for SMEs. The approach consists of four artifacts: a metamodel, a method, software tool support, and a visualization. The approach is kept simple so that it may be applied in an SME context and is based on the essential dimensions of EA frameworks. Five steps were taken: first, the problem of EA in SMEs was extensively analyzed. Next, the CHOOSE metamodel was developed during action research in SMEs. Then, action research in six companies was used to develop an adequate method (consisting of guidelines, a roadmap, and stop criteria) and to further refine this CHOOSE metamodel, while different types of software tools (PC, iPad, Android, ...) were developed to enable the evaluation rounds. Finally, a proper visualization was established

Model driven validation approach for enterprise architecture and motivation extensions

As the endorsement of Enterprise Architecture (EA) modelling continues to grow in diversity and complexity, management of its schema, artefacts, semantics and relationships has become an important business concern. To maintain agility and flexibility within competitive markets, organizations have also been compelled to explore ways of adjusting proactively to innovations, changes and complex events also by use of EA concepts to model business processes and strategies. Thus the need to ensure appropriate validation of EA taxonomies has been considered severally as an essential requirement for these processes in order to exert business motivation; relate information systems to technological infrastructure. However, since many taxonomies deployed today use widespread and disparate modelling methodologies, the possibility to adopt a generic validation approach remains a challenge. The proliferation of EA methodologies and perspectives has also led to intricacies in the formalization and validation of EA constructs as models often times have variant schematic interpretations. Thus, disparate implementations and inconsistent simulation of alignment between business architectures and heterogeneous application systems is common within the EA domain (Jonkers et al., 2003). In this research, the Model Driven Validation Approach (MDVA) is introduced. MDVA allows modelling of EA with validation attributes, formalization of the validation concepts and transformation of model artefacts to ontologies. The transformation simplifies querying based on motivation and constraints. As the extended methodology is grounded on the semiotics of existing tools, validation is executed using ubiquitous query language. The major contributions of this work are the extension of a metamodel of Business Layer of an EAF with Validation Element and the development of EAF model to ontology transformation Approach. With this innovation, domain-driven design and object-oriented analysis concepts are applied to achieve EAF model’s validation using ontology querying methodology. Additionally, the MDVA facilitates the traceability of EA artefacts using ontology graph patterns