25,868 research outputs found

    Systemic classification of concern-based design methods in the context of enterprise architecture

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    Enterprise Architecture (EA) is a relatively new domain that is rapidly developing. "The primary reason for developing EA is to support business by providing the fundamental technology and process structure for an IT strategy” [TOGAF]. EA models have to model enterprises facets that span from marketing to IT. As a result, EA models tend to become large. Large EA models create a problem for model management. Concern-based design methods (CBDMs) aim to solve this problem by considering EA models as a composition of smaller, manageable parts—concerns. There are dozens of different CBDMs that can be used in the context of EA: from very generic methods to specific methods for business modeling or IT implementations. This variety of methods can cause two problems for those who develop and use innovative CBDMs in the field of Enterprise Architecture (EA). The first problem is to choose specific CBDMs that can be used in a given EA methodology: this is a problem for researchers who develop their own EA methodology. The second problem is to find similar methods (with the same problem domain or with similar frameworks) in order to make a comparative analysis with these methods: this is a problem of researchers who develop their own CBDMs related to a specific problem domain in EA (such as business process modeling or aspect oriented programming). We aim to address both of these problems by means of a definition of generic Requirements for CBDMs based on the system inquiry. We use these requirements to classify twenty CBDMs in the context of EA. We conclude with a short discussion about trends that we have observed in the field of concern-based design and modelin

    Systemic Classification of Concern-Based Design Methods in the Context of Enterprise Architecture

    Get PDF
    Enterprise Architecture (EA) is a relatively new domain that is rapidly developing. The primary reason for developing EA is to support business by providing the fundamental technology and process structure for an IT strategy [TOGAF]. EA models have to model enterprises facets that span from marketing to IT. As a result, EA models tend to become large. Large EA models create a problem for model management. Concern-based design methods (CBDMs) aim to solve this problem by considering EA models as a composition of smaller, manageable parts concerns. There are dozens of different CBDMs that can be used in the context of EA: from very generic methods to specific methods for business modeling or IT implementations. This variety of methods can cause two problems for those who develop and use innovative CBDMs in the field of Enterprise Architecture (EA). The first problem is to choose specific CBDMs that can be used in a given EA methodology: this is a problem for researchers who develop their own EA methodology. The second problem is to find similar methods (with the same problem domain or with similar frameworks) in order to make a comparative analysis with these methods: this is a problem of researchers who develop their own CBDMs related to a specific problem domain in EA (such as business process modeling or aspect oriented programming). We aim to address both of these problems by means of a definition of generic Requirements for CBDMs based on the system inquiry. We use these requirements to classify twenty CBDMs in the context of EA. We conclude with a short discussion about trends that we have observed in the field of concern-based design and modeling

    Industrial policy for the medium to long-term

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    This report reviews the market failure and systems failure rationales for industrial policy and assesses the evidence on part experience of industrial policy in the UK. In the light of this, it reviews options for reshaping the design and delivery of industrial policy towards UK manufacturing. These options are intended to encourage a medium- to long-term perspective across government departments and to integrate science, innovation and industrial policy

    Systems Theory Based Architecture Framework for Complex System Governance

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    The purpose of this research was to develop a systems theory based framework for complex system governance using grounded theory approach. Motivation for this research includes: 1) the lack of research that identifies modeling characteristics for complex system governance, 2) the lack of a framework rooted in systems theory to support performance of complex system governance functions for maintaining system viability. This research focused on answering: What systems theoretic framework can be developed to inform complex system governance and enable articulation of governance function performance? The grounded theory research approach utilized three phases. First, the literature in systems theory, management cybernetics, governance and enterprise architecture was synthesized and open-coded to generalize main themes using broad analysis in NVivo software, researcher note taking in EndNote, and cataloging in Excel spreadsheets. Second, the literature underwent axial-coding to identify interconnections and relevance to systems theory and complex system governance, primarily using Excel spreadsheets. Finally, selective coding and interrelationships were identified and the complex system governance architecture framework was shaped, reviewed, and validated by qualified experts. This research examined a grounded theory approach not traditionally used in systems theory research. It produced a useful systems theory based framework for practical application, bridging the gap between theory and practice in the emerging field of complex system governance. Theoretical implications of this research include identifying the state of knowledge in each literature domain and the production of a unique framework for performing metasystem governance functions that is analytically generalizable. Management cybernetics, governance, and systems theory are expanded through a testable tool for meta-level organizational and system governance theories. Enterprise architecture is advanced with a multi-disciplinary framework that coherently presents and facilitates new use for architecture at the metasystem level. Methodological implications of this research include using grounded theory approach for systems theory research, where it is atypical. Although a non-traditional method, it provides an example for conducting fruitful research that can contribute knowledge. Practical implications of this research include a useable framework for complex system governance which has never before existed and a living structure adaptable to evolutionary change coming from any related domain or future practical application feedback

    The business model: Theoretical roots, recent developments, and future research

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    The paper provides a broad and multifaceted review of the received literature on business models, in which we attempt to explore the origin of the construct and to examine the business model concept through multiple disciplinary and subject-matter lenses. The review reveals that scholars do not agree on what a business model is, and that the literature is developing largely in silos, according to the phenomena of interest to the respective researchers. However, we also found some emerging common ground among students of business models. Specifically, i) the business model is emerging as a new unit of analysis; ii) business models emphasize a system-level, holistic approach towards explaining how firms do business; iii) organizational activities play an important role in the various conceptualizations of business models that have been proposed, and iv) business models seek not only to explain the ways in which value is captured but also how it is created. These emerging themes could serve as important catalysts towards a more unified study of business models.Business model; strategy; technology management; innovation; literature review;

    Chemical enterprise model and decision-making framework for sustainable chemical product design

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    The chemical product substitution process is undertaken by chemical industries for complying with regulations, like REACH in Europe. Initially devoted to chemists, chemicals substitution is nowadays a complex process involving corporate, business and engineering stakeholders across the chemical enterprise for orienting the search toward a sustainable solution. We formalize a decision making process framework dedicated to the sustainable chemical product design activity in an industrial context. The framework aims at improving the sharing of information and knowledge and at enabling a collaborative work across the chemical enterprise stakeholders at the strategic, tactical and operational levels. It is supported by information and communication technologies (ICT) and integrates a computer aided molecular design tool. During the initial intelligence phase, a systemic analysis of the needs and usages enables to define the product requirements. In the design phase, they are compiled with the help of a facilitator to generate the input file of a computer aided product design tool. This multiobjective tool is designed to find mixtures with molecular fragments issued from renewable raw materials, and is able to handle environment-health and safety related properties along with process physicochemical properties. The final choice phase discusses the solution relevancy and provides feedback, before launching the product manufacturing. The framework is illustrated by the search of a bio-sourced water–solvent mixture formulation for lithographic blanket wash used in printing industry. The sustainability of the solution is assessed by using the sustainability shades metho

    Engineering Crowdsourced Stream Processing Systems

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    A crowdsourced stream processing system (CSP) is a system that incorporates crowdsourced tasks in the processing of a data stream. This can be seen as enabling crowdsourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ human intelligence. It also leads to a substantial expansion of the capabilities of data processing systems. Engineering a CSP system requires the combination of human and machine computation elements. From a general systems theory perspective, this means taking into account inherited as well as emerging properties from both these elements. In this paper, we position CSP systems within a broader taxonomy, outline a series of design principles and evaluation metrics, present an extensible framework for their design, and describe several design patterns. We showcase the capabilities of CSP systems by performing a case study that applies our proposed framework to the design and analysis of a real system (AIDR) that classifies social media messages during time-critical crisis events. Results show that compared to a pure stream processing system, AIDR can achieve a higher data classification accuracy, while compared to a pure crowdsourcing solution, the system makes better use of human workers by requiring much less manual work effort

    Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

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    Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)

    CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

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    After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges
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