Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Design of Variable Big Data Architectures for E-Government Domain
    Tekinerdogan, B. ; Uzun, Burak - \ 2019
    In: Software Engineering for Variable Intensive Systems / Mistrik, Ivan, Galster, Matthias, Maxim, Bruce R., New York : Taylor & Francis - ISBN 9780815348054 - p. 141 - 159.
    Like many application domains Big Data has become a very important driver for innovation and growth for e-government which aims to automate the public services to citizens. In general, e-government systems are often characterized as big data systems in which data storage and processing is one of the business-critical concerns. However, different features are required for different e-government systems, and likewise the corresponding big data architectures will need to be different as well. In this chapter, we present a systematic approach for the design of various big data architectures within the e-government domain. In this context, we adopt a big data reference architecture with a variability model for big data systems and e-government systems. We discuss the design decisions, the experiences and the lessons learned for deriving application architectures for different e-government systems.
    Variability Incorporated Simultaneous Decomposition of Models Under Structural and Procedural Views
    Cagri Kaya, Muhammed ; Suloglu, Selma ; Tokdemir, Gul ; Tekinerdogan, Bedir ; Dogru, Ali H. - \ 2019
    In: Software Engineering for Variability Intensive Systems / Mistrik, I., Galster, M., Maxim, B.R., New York : Taylor & Francis - ISBN 9780815348054 - 22 p.
    This chapter presents hierarchical variability as an important development notion especially when considered together with a systems specification through decomposition. A matured domain-specific environment is the precondition for variability-centric engineering for compositional approaches as targeted in this study: Most of the requirements have been already modeled, and most of the problem domain elements have corresponding reusable solutions. Also, a mature domain enjoys a wide community of developers who are familiar with those problems and solution-space elements and an effective set of specific tools. Decomposition is a fundamental mechanism in many approaches for the specification of various dimensions of modeling. Decomposition of especially structure modeling for software is not new. Here, variability guidance is incorporated into both structure and process decomposition. This chapter combines such notions in the demonstration of variability-centric development suggesting a structural and procedural decomposition of the system. The predecessors, component-oriented approaches rely on the structural decomposition whereas service-oriented development is being supported by process decomposition. A vending machine case study is presented in this chapter for demonstrating the propagation of variability specification along with the enhancements of the component-oriented model and the process model.
    Performance Isolation in Cloud-Based Big Data Architectures
    Tekinerdogan, B. ; Oral, Alp - \ 2017
    In: Software Architecture for Big Data and the Cloud / Mistrik, I., Bahsoon, R., Ali, N., Heisel, M., Maxim, B., Elsevier - ISBN 9780128054673 - p. 127 - 145.
    Cloud-based big data systems usually have many different tenants that require access to the server's functionality. In a nonisolated cloud system, the different tenants can freely use the resources of the server. Hereby, disruptive tenants who exceed their limits can easily cause degradation of performance of the provided services for other tenants. To ensure performance demands of the multiple tenants and meet fairness criteria, various performance isolation approaches have been introduced including artificial delay, round robin, blacklist, and thread pool. Each of these performance isolation approaches adopts different strategies to avoid the performance interference in case of multiple concurrent tenant needs. In this paper, we propose a framework and a systematic approach for performance isolation in cloud-based big data systems. To this end, we present an architecture design of cloud-based big data system and discuss the integration of feasible performance isolation approaches. We evaluate our approach using PublicFeed, a social media application that is based on a cloud-based big data platform.
    Domain-Driven Design of Big Data Systems based on a Reference Architecture
    Avci Salma, Cigdem ; Tekinerdogan, B. ; Athanasiadis, I.N. - \ 2017
    In: Software Architecture for Big Data and the Cloud / Mistrik, I., Bahsoon, R., Ali, N., Heisel, M., Maxim, B., Elsevier - ISBN 9780128054673 - p. 49 - 68.
    In general, different application domains may require different big data systems. To enhance the understanding of big data systems and support the architect in designing big data architectures, we propose a domain-driven design approach for deriving application architectures. To this end, we propose a domain engineering approach in which a family feature model, reference architecture, and corresponding design rules are identified. The family feature model is derived based on a domain analysis of big data systems and represents the common and variant features. The reference architecture represents a generic structure for various application architectures of big data systems. Finally, the design rules define reusable design heuristics for designing an application architecture based on the selection of features of the family feature model and the reference architecture. We illustrate our approach for deriving the big data architectures of different well-known big data systems.
    Preface
    Grundy, John ; Mistrik, Ivan ; Ali, Nour ; Soley, Richard M. ; Tekinerdogan, Bedir - \ 2016
    In: Software Quality Assurance / Mistrik, I., Ali, N., Tekinerdogan, B., Elsevier Inc. Academic Press - ISBN 9780128023013 - p. xxxiii - xlii.
    Architecture Viewpoint for Modeling Dynamically Configurable Software Systems
    Tekinerdogan, B. ; Sozer, H. - \ 2016
    In: Managing Trade-offs in Adaptable Software Architectures / Mistrik, I., Ali, N., Kazman, R., Grundy, J., Schmerl, B., Elsevier - ISBN 9780128028551 - p. 79 - 95.
    Architectural Perspective for Design and Analysis of Scalable Software as a Service Architectures
    Tekinerdogan, B. ; Ozcan, O. - \ 2016
    In: Managing Trade-offs in Adaptable Software Architectures / Mistrik, I., Ali, N., Kazman, R., Grundy, J., Schmerl, B., Elsevier - ISBN 9780128028551 - p. 223 - 243.
    The Time Is Right to Focus on Model Organism Metabolomes
    Edison, Arthur ; Hall, Robert ; Junot, Christophe ; Karp, Peter ; Kurland, Irwin ; Mistrik, Robert ; Reed, Laura ; Saito, Kazuki ; Salek, Reza ; Steinbeck, Christoph ; Sumner, Lloyd ; Viant, Mark - \ 2016
    Metabolites 6 (2016)1. - ISSN 2218-1989
    Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research.
    Architectural drift analysis using architecture reflexion viewpoint and design structure reflexion matrices
    Tekinerdogan, B. - \ 2015
    In: Sofware Quality Assurance in Large Scale and Complex Software-Intensive Systems / Mistrik, I., Soley, R.., Ali, N., Grundy, J., Tekinerdogan, B., Elsevier - ISBN 9780128023013 - p. 221 - 236.
    Quality Concerns in Large Scale and Complex Software-intensive Systems
    Tekinerdogan, B. ; Ali, N. ; Grundy, J. ; Mistrik, I. ; Soley, R. - \ 2015
    In: Sofware Quality Assurance in Large Scale and Complex Software-Intensive Systems / Mistrik, I., Soley, R., Ali, N., Grundy, J., Tekinerdogan, B., Elsevier - ISBN 9780128023013 - p. 1 - 17.
    Software quality assurance: in large scale and complex software-intensive systems
    Mistrik, I. ; Soley, R. ; Ali, N. ; Grundy, J. ; Tekinerdogan, B. - \ 2015
    Burlington, Massachusetts, USA : Morgan Kaufmann Publishers - ISBN 9780128023013 - 420
    Software Quality Assurance in Large Scale and Complex Software-intensive Systems presents novel and high-quality research related approaches that relate the quality of software architecture to system requirements, system architecture and enterprise-architecture, or software testing. Modern software has become complex and adaptable due to the emergence of globalization and new software technologies, devices and networks. These changes challenge both traditional software quality assurance techniques and software engineers to ensure software quality when building today (and tomorrow's) adaptive, context-sensitive, and highly diverse applications. This edited volume presents state of the art techniques, methodologies, tools, best practices and guidelines for software quality assurance and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited, to: quality attributes of system/software architectures; aligning enterprise, system, and software architecture from the point of view of total quality; design decisions and their influence on the quality of system/software architecture; methods and processes for evaluating architecture quality; quality assessment of legacy systems and third party applications; lessons learned and empirical validation of theories and frameworks on architectural quality; empirical validation and testing for assessing architecture quality.
    Metabolite identification: are you sure? And how do your peers gauge your confidence?
    Creek, D.J. ; Dunn, W.B. ; Fiehn, O. ; Griffin, J.L. ; Hall, R.D. ; Lei, Z. ; Mistrik, R. ; Neumann, S. ; Schymanski, E.L. ; Trengove, R. ; Wolfender, J. - \ 2014
    Metabolomics 10 (2014). - ISSN 1573-3882 - p. 350 - 353.
    spectrometry data
    Metabolomics is still faced with several significant challenges which currently limit its full scientific potential. The identification of metabolites is essential to convert analytical data into meaningful biological knowledge. However, identification confidence can vary widely because the process of identification is complex and dependent on the analytical platform and robustness of the methods applied, as well as the databases and resources used. Confident and unequivocal structure identification requires significant effort, which is multiplied dramatically in non-targeted metabolomics studies where 10–100s of metabolites can be deemed as biologically important and require identification. Mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR) or integrated MS–NMR strategies (Dunn et al. 2013; Kind and Fiehn 2010; van der Hooft et al. 2011) provide much information for the identification of metabolites (e.g. 1D/2D-NMR and MS/MS).
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