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  • 1. Aier, Stephan
    et al.
    Buckl, Sabine
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Gleichauf, Bettina
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Närman, Per
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Schweda, Christian M.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Survival Analysis of Application Life Spans based on Enterprise Architecture Models2009In: Proc. 3rd International Workshop on Enterprise Modelling and Information Systems Architectures, EMISA 2009, 2009, Vol. P-152, p. 141-154Conference paper (Refereed)
    Abstract [en]

    Modern enterprises face the challenge to survive in an ever changing environment. One commonly accepted means to address this challenge and further enhance survivability is enterprise architecture (EA) management, which provides a holistic model-based approach to business/IT alignment. Thereby, the decisions taken in the context of EA management are based on accurate documentation of IT systems and business processes. The maintenance of such documentation causes high investments for enter-prises, especially in the absence of information on the change rates of different systems and processes. In this paper we propose a method for gathering and analyzing such in-formation. The method is used to analyze the life spans of the application portfolio of three companies from different industry sectors. Based on the results of the three case studies implications and limitations of the method are discussed.

  • 2. Buckl, S.
    et al.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Holschke, O.
    Matthes, F.
    Schweda, C. M.
    Sommestad, Teodor
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A pattern-based approach to quantitative enterprise architecture analysis2009In: 15th Americas Conference on Information Systems 2009, AMCIS 2009, 2009, p. 2314-2324Conference paper (Refereed)
    Abstract [en]

    Enterprise Architecture (EA) management involves tasks that substantially contribute to the operations of an enterprise, and to its sustainable market presence. One important aspect of this is the availability of services to customers. However, the increasing interconnectedness of systems with other systems and with business processes makes it difficult to get a clear view on change impacts and dependency structures. While management level decision makers need this information to make sound decisions, EA models often do not include quality attributes (such as availability), and very rarely provide quantitative means to assess them. We address these shortcomings by augmenting an information model for EA modeling with concepts from Probabilistic Relational Models, thus enabling quantitative analysis. A sample business case is evaluated as an example of the technique, showing how decision makers can benefit from information on availability impacts on enterprise business services.

  • 3.
    Buschle, Markus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sommestad, Teodor
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A tool for enterprise architecture analysis using the PRM formalism2010In: CEUR Workshop Proceedings, 2010Conference paper (Refereed)
    Abstract [en]

    Enterprise architecture advocates model-based decision-making on enterprise-wide information system issues. In order to provide decisionmaking support, enterprise architecture models should not only be descriptive but also enable analysis. This paper presents a software tool, currently under development, for the evaluation of enterprise architecture models. In particular, the paper focuses on how to encode scientific theories so that they can be used for model-based analysis and reasoning under uncertainty. The tool architecture is described, and a case study shows how the tool supports the process of enterprise architecture analysis.

  • 4.
    Buschle, Markus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sommestad, Teodor
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Tool for Enterprise Architecture Analysis Using the PRM Formalism2011In: INFORMATION SYSTEMS EVOLUTION / [ed] Soffer P; Proper E, 2011, Vol. 72, p. 108-121Conference paper (Refereed)
    Abstract [en]

    Enterprise architecture advocates for model-based decision-making on enterprise-wide information system issues. In order to provide decision-making support, enterprise architecture models should not only be descriptive but also enable analysis. This paper presents a software tool, currently under development, for the evaluation of enterprise architecture models. In particular, the paper focuses on how to encode scientific theories so that they can be used for model-based analysis and reasoning under uncertainty. The tool architecture is described, and a case study shows how the tool supports the process of enterprise architecture analysis.

  • 5.
    Chenine, Moustafa
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Nordström, Lars
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Wu, Yiming
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ericsson, Göran
    Swedish National Grid (Svenska Kraftnät), Sundbyberg, Sweden.
    A Framework for Wide-Area Monitoring and Control Systems Interoperability and Cybersecurity Analysis2014In: IEEE Transactions on Power Delivery, ISSN 0885-8977, E-ISSN 1937-4208, Vol. 29, no 2, p. 633-641Article in journal (Refereed)
    Abstract [en]

    Wide-area monitoring and control (WAMC) systems are the next-generation operational-management systems for electric power systems. The main purpose of such systems is to provide high resolution real-time situational awareness in order to improve the operation of the power system by detecting and responding to fast evolving phenomenon in power systems. From an information and communication technology (ICT) perspective, the nonfunctional qualities of these systems are increasingly becoming important and there is a need to evaluate and analyze the factors that impact these nonfunctional qualities. Enterprise architecture methods, which capture properties of ICT systems in architecture models and use these models as a basis for analysis and decision making, are a promising approach to meet these challenges. This paper presents a quantitative architecture analysis method for the study of WAMC ICT architectures focusing primarily on the inter-operability and cybersecurity aspects.

  • 6.
    Ekstedt, Mathias
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerstrom, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sommestad, Teodor
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Tool for Enterprise Architecture Analysis of Maintainability: CSMR 2009, PROCEEDINGS2009In: EUR CON SFTWR MTNCE REENGR / [ed] Winter A, Knodel J, Los Almitos: IEEE COMPUTER SOC , 2009, p. 327-328Conference paper (Refereed)
    Abstract [en]

    A tool for Enterprise Architecture analysis using a probabilistic mathematical framework is demonstrated. The Model-View-Controller tool architecture is outlined, before the use of the tool is considered. A sample abstract maintainability model is created, showing the dependence of system maintainability on documentation quality. developer expertise, etc. Finally, a concrete model of an ERP system is discussed.

  • 7.
    Fazlollahi, Ariyan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Benefits of enterprise integration: Review, classification, and suggestions for future research2012In: Enterprise Interoperability: 4th International IFIP Working Conference, IWEI 2012, Harbin, China, September 6-7, 2012. Proceedings / [ed] Marten van Sinderen, Pontus Johnson, Xiaofei Xu, Guy Doumeingts, Springer, 2012, p. 34-45Conference paper (Refereed)
    Abstract [en]

    This article reports the findings of a literature review concerning the potential benefits of Enterprise Integration (EI) for organizations. The review reveals the current state of the scientific literature concerning the potential benefits of EI, classified using a conceptual model of the enterprise. We believe that the results provide a consolidated and comprehensive picture of such potential benefits, useful as a baseline for future research. Additionally, the review is expected to assist practitioners in establishing business cases for EI by means of scientifically grounded reasoning about how EI benefits can contribute to the achievement of certain business goals. Additionally, results could be employed to develop methods or models capable of measuring such benefits in financial terms.

  • 8.
    Franke, Ulrik
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Höök, David
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    König, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Närman, Per
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Gustafsson, Pia
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    EAF(2) - A Framework for Categorizing Enterprise Architecture Frameworks2009In: SNPD 2009: 10TH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCES, NETWORKING AND PARALLEL DISTRIBUTED COMPUTING, PROCEEDINGS, LOS ALAMITOS: IEEE COMPUTER SOC , 2009, p. 327-332Conference paper (Refereed)
    Abstract [en]

    What constitutes an enterprise architecture framework is a contested subject. The contents of present enterprise architecture frameworks thus differ substantially. This paper aims to alleviate the confusion regarding which framework contains what by proposing a meta framework for enterprise architecture frameworks. By using this meta framework, decision makers are able to express their requirements on what their enterprise architecture framework must contain and also to evaluate whether the existing frameworks meets these requirements. An example classification of common EA frameworks illustrates the approach.

  • 9.
    Franke, Ulrik
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Höök, David
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    König, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A formal method for cost and accuracy trade-off analysis in software assessment measures2009In: RCIS 2009: PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON RESEARCH CHALLENGES IN INFORMATION SCIENCE, NEW YORK: IEEE , 2009, p. 295-302Conference paper (Refereed)
    Abstract [en]

    Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, but the monetary aspects of the modeling of software systems are not equally well acknowledged. The present paper describes a method using Bayesian networks for optimizing modeling strategies, perceived as a trade-off between these two aspects. Using GeNIe, a graphical tool with the proper Bayesian algorithms implemented, decision support can thus be provided to the modeling process. Specifically, an informed trade-off can be made, based on the modeler's prior knowledge of the predictive power of certain models, combined with his projection of their costs. It is argued that this method might enhance modeling of large and complex software systems in two principal ways: Firstly, by enforcing rigor and making hidden assumptions explicit. Secondly, by enforcing cost awareness even in the early phases of modeling. The method should be used primarily when the choice of modeling can have great economic repercussions.

  • 10.
    Franke, Ulrik
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Höök, David
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    König, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Method for Choosing Software Assessment Measures using Bayesian Networks and Diagnosis: CSMR 2009, PROCEEDINGS2009In: 13TH EUROPEAN CONFERENCE ON SOFTWARE MAINTENANCE AND REENGINEERING: CSMR 2009, PROCEEDINGS / [ed] Winter A, Knodel J, LOS ALAMITOS, CA.: IEEE COMPUTER SOC. , 2009, p. 241-245Conference paper (Refereed)
    Abstract [en]

    Creating accurate models of information systems is an important but challenging task. While the scienti c aspects of such modeling are generally acknowledged, the monetary aspects of the modeling of software systems are not. The present paper describes a Bayesian method for optimizing modeling strategies, perceived as a trade-off between these two aspects. Speci cally, an informed trade-off can be made, based on the modeler's prior knowledge of the predictive power of certain models, combined with her projection of the costs. It is argued that this method enhances modeling of large and complex software systems in two principal ways: Firstly, by enforcing rigor and making hidden assumptions explicit. Secondly, by enforcing cost awareness even in the early phases of modeling. The method should be used primarily when the choice of modeling can have great economic repercussions.

  • 11.
    Franke, Ulrik
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sommestad, Teodor
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Decision Support oriented Enterprise Architecture Metamodel Management using Classification Trees2009In: 2009 13TH ENTERPRISE DISTRIBUTED OBJECT COMPUTING CONFERENCE WORKSHOPS (EDOCW 2009) / [ed] Tosic, V., NEW YORK: IEEE , 2009, p. 328-335Conference paper (Refereed)
    Abstract [en]

    Models are an integral part of the discipline of Enterprise Architecture (EA). To stay relevant to management decision-making needs, the models need to be based upon suitable metamodels. These metamodels, in turn, need to be properly and continuously maintained. While there exists several methods for metamodel development and maintenance, these typically focus on internal metamodel qualities and metamodel engineering processes, rather than on the actual decision-making needs and their impact on the metamodels used. The present paper employs techniques from information theory and learning classification trees to propose a method for metamodel management based upon the value added by entities and attributes to the decision-making process. This allows for the removal of those metamodel parts that give the least "bang for the bucks" in terms of decision support. The method proposed is illustrated using real data from an ongoing research project on systems modifiability

  • 12.
    Johnson, Pontus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Assessing Goal Fulfillment2007In: Enterprise Architecture: Models and Analyses for Information Systems Decision Making, Studentlitteratur, 2007, p. 253-269Chapter in book (Other academic)
  • 13.
    Johnson, Pontus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johansson, Erik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sommestad, Teodor
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A tool for enterprise architecture analysis2007In: 11TH IEEE INTERNATIONAL ENTERPRISE DISTRIBUTED OBJECT COMPUTING CONFERENCE, PROCEEDINGS, LOS ALAMITOS: IEEE COMPUTER SOC , 2007, p. 142-153Conference paper (Refereed)
    Abstract [en]

    The discipline of enterprise architecture advocates the use of models to support decision-making on enterprise-wide information system issues. In order to provide such support, enterprise architecture models should be amenable to analyses of various properties, as e.g. the availability, performance, interoperability, modifiability, and information security of the modeled enterprise information systems. This paper presents a software tool for such analyses. The tool guides the user in the generation of enterprise architecture models and subjects these models to analyses resulting in quantitative measures of the chosen quality attribute. The paper describes and exemplifies both the architecture and the usage of the tool.

  • 14.
    Johnson, Pontus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    FOI - Swedish Defence Research Agency, Sweden.
    Shahzad, Khurram
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    An architecture modeling framework for probabilistic prediction2014In: Information Systems and E-Business Management, ISSN 1617-9846, E-ISSN 1617-9854, Vol. 12, no 4, p. 595-622Article in journal (Refereed)
    Abstract [en]

    In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P(2)AMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P(2)AMF adds a probabilistic inference mechanism. The paper introduces P(2)AMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.

  • 15.
    Johnson, Pontus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Shahzad, Khurram
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    P2AMF: Predictive, probabilistic architecture modeling framework2013In: Lecture Notes in Business Information Processing, 2013, p. 104-117Conference paper (Refereed)
    Abstract [en]

    In the design phase of business and software system development, it is desirable to predict the properties of the system-to-be. Existing prediction systems do, however, not allow the modeler to express uncertainty with respect to the design of the considered system. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P 2AMF), capable of advanced and probabilistically sound reasoning about architecture models given in the form of UML class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P2AMF adds a probabilistic inference mechanism. The paper introduces P2AMF, describes its use for system property prediction and assessment, and proposes an algorithm for probabilistic inference.

  • 16.
    Källgren, Adrian
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Method for Constructing a Company Specific Enterprise Architecture Model Framework2009In: 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009: In conjunction with IWEA 2009 and WEACR 2009, LOS ALAMITOS: IEEE COMPUTER SOC , 2009, p. 346-351Conference paper (Refereed)
    Abstract [en]

    Good IT decision making is a highly desirable property that can be furthered by the use of enterprise architecture, an approach to IT management using diagrammatic models. In order to support decision making, the models must contain only relevant information since creation of enterprise architecture models often is a demanding task. This paper suggests a method for constructing an enterprise architecture model framework where enterprises in need of architecture and rational decision making are designated. The paper also describes the outcome of the method at a case for a Swedish utility company, Vattenfall AB.

  • 17.
    Lagerström, Robert
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A method for creating entreprise architecture metamodels: applied to systems modifiability2009In: International Journal of Computer Science and Applications, ISSN 0972-9038, E-ISSN 0972-9038, Vol. 6, no 5, p. 89-120Article in journal (Refereed)
    Abstract [en]

    Enterprise architecture models can be used in order to increase the general understanding of enterprise systems and specifically to perform various kinds of analysis. It is generally understood that such modeling encompasses general scientific issues, but the monetary aspects of the modeling of software systems and their environment are not equally well acknowledged. Even more so, creating a good metamodel for enterprise software systems analysis is an important but challenging task. The present paper describes a method for creating metamodels for such analysis. The enterprise architecture models are formalized using probabilistic relational models, which enables the combination of regular entityrelationship modeling aspects with means to perform enterprise architecture analysis. The proposed method for creating metamodels is general, however this paper presents the method by creating a metamodel for systems modifiability, i.e. the cost of making changes to enterprise-wide systems. The method and the method outcome, i.e. the metamodel, is validated based on survey and workshop data and the applicability of the metamodel is illustrated with an instantiated architectural model based on a software change project at a large Nordic software and hardware vendor.

  • 18. Lambert, Quentin
    et al.
    Bazatolle, Thibaut
    Ullberg, Johan
    van Sinderen, Marten
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Business models for an aggregator2012In: Information Management & Computer Security, ISSN 0968-5227, E-ISSN 1758-5805Article in journal (Refereed)
  • 19.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Application of a Language for Interoperability Modeling and Prediction2012Report (Other academic)
  • 20.
    Ullberg, Johan
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    OCL statements for interoperability prediction2012Report (Other academic)
  • 21.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Chen, David
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Barriers to Enterprise Interoperability2009In: ENTERPRISE INTEROPERABILITY, PROCEEDINGS / [ed] Poler R, VanSinderen M, Sanchis R, 2009, Vol. 38, p. 13-24Conference paper (Refereed)
    Abstract [en]

    Interoperability is a key feature for enterprises in today's competitive environment. Fundamental interoperability problems are however still not well understood. Within the scope of the Framework for Enterprise Interoperability (FEI) originally proposed by INTEROP NoE and now moved to ISO standardization process, this paper tentatively identifies and categorizes a set of interoperability barriers. Barriers to interoperability are defined as incompatibility between two enterprise systems. A list of interoperability barriers is presented and these barriers are then mapped to the FEI and illustrated with examples. The most significant dependencies between barriers are also tentatively defined and presented.

  • 22.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Tool for Interoperability Analysis of Enterprise Architecture Models using Pi-OCL2010In: Enterprise interoperability iv: making the internet of the future for the future of enterprise, 2010, p. 81-90Conference paper (Refereed)
    Abstract [en]

    Decision-making on enterprise-wide information system issues can be furthered by the use of models as advocated by the discipline of enterprise architecture. In order to provide decision-making support, enterprise architecture models should be amenable to analyses. This paper presents a software tool, currently under development, for interoperability analysis of enterprise architecture models. In particular, the ability to query models for structural information is the main focus of the paper. Both the tool architecture and its usage is described and exemplified.

  • 23.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Empirical assessment of the accuracy of an interoperability prediction language2016In: Information Systems Frontiers, ISSN 1387-3326, E-ISSN 1572-9419, p. 1-15Article in journal (Refereed)
    Abstract [en]

    Interoperability, defined as the satisfaction of a communication need between two or more actors, is an important aspect in many phases of an enterprise’s development. Mastering the field of interoperability is a daunting task so aid in predicting interoperability can be of great benefit. Formalisms capable of such predictions of future information system architectures are however sparse, and when employed, it is essential that the prediction is accurate. In this paper, a previously proposed interoperability modelling and prediction language is subjected to case testing and evaluated toward interoperability predictions made by practitioners and experts in the field. The results show that although there are some areas not currently covered by the framework, in general, it performs better than the intended users, and would thereby provide additional support in various development and design contexts.

  • 24.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Predicting Interoperability in an Environmental Assurance System2012In: Enterprise Interoperability V: Shaping Enterprise Interoperability in the Future Internet / [ed] Raúl Poler, Guy Doumeingts, Bernhard Katzy, Ricardo Chalmeta, Springer London, 2012, p. 25-35Conference paper (Refereed)
    Abstract [en]

    Decision-making on issues related to interoperability can be furthered by the use of models of the organization or information system where interoperability is of concern. In order to provide decision-making support, the models should be amenable to analyses. This paper presents the application of a modeling languge for interoperability prediction to an environmental assurance system. Using the modeling language it was possible to predict the probability of success for the communication needs of the assurance system, and also identify the main barriers for these comunication needs.

  • 25.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A language for interoperability modeling and prediction2012In: Computers in industry (Print), ISSN 0166-3615, E-ISSN 1872-6194, Vol. 63, no 8, p. 766-774Article in journal (Refereed)
    Abstract [en]

    Interoperability, defined as the satisfaction of a communication need between two or more actors, is a sought after quality for enterprises in today's competitive environment. For a decision maker, understanding the effects of a changing market place and understanding how to adapt to the new environment is essential. Sustainable interoperability is an approach where such dynamic environments are considered, including how to adapt to the new environments. This paper presents a modeling language for describing architectures from an interoperability perspective and a formalism for inferring the degree of interoperability from the architecture models, thus supporting sustainable interoperability. The interoperability language is expressed as a Unified Modeling Language, UML, class diagram specifying classes, attributes, and relationships relevant for interoperability modeling. The class diagram is also augmented with a set of statements in the Object Constraint Language, OCL, supporting automated interoperability prediction.

  • 26.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Modeling Language for Interoperability Assessments2011In: ENTERPRISE INTEROPERABILITY / [ed] VanSinderen, M; Johnson, P, BERLIN: SPRINGER-VERLAG BERLIN , 2011, Vol. 76, p. 61-74Conference paper (Refereed)
    Abstract [en]

    Decision-making on issues related to interoperability can be furthered by the use of models of the organization or information system where interoperability is of concern. In order to provide decision-making support, the models should be amenable to analyses. This paper presents a modeling language specifically for interoperability issues where interoperability is defined as the probability that two more actors will be able to exchange information and use that information. The language is coupled with a probabilistic mechanism for automated interoperability assessments of the models created. The paper also presents an example of how the language can be applied.

  • 27.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Education in Enterprise Architecture Analysis: Assessing interoperability of service oriented architectures2009Conference paper (Refereed)
  • 28.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Framework for interoperability analysis on the semantic web using architecture models2008In: Proceedings of the Workshop on Enterprise Interoperability (IWEI 2008), IEEE , 2008, p. 207-215Conference paper (Refereed)
    Abstract [en]

    IT decision making requires analysis of possible future scenarios. The quality of the decisions can be enhanced by the use of architecture models that increase the understanding of the components of the system scenario. It is desirable that the created models support the needed analysis effectively since creation of architecture models often is a demanding and time consuming task. This paper suggests a framework for assessing interoperability on the systems communicating over the semantic web as well as a metamodel suitable for this assessment. Extended influence diagrams are used in the framework to capture the relations between various interoperability factors and enable aggregation of these into a holistic interoperability measure. The paper is concluded with an example using the framework and metamodel to create models and perform interoperability analysis.

  • 29.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    A Framework for Service Interoperability Analysis using Enterprise Architecture Models2008In: 2008 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING, PROCEEDINGS, VOL 2, LOS ALAMITOS: IEEE COMPUTER SOC , 2008, p. 99-107Conference paper (Refereed)
    Abstract [en]

    Good IT decision making is a highly desirable property that can be furthered by the use of enterprise architecture, an approach to IT management using diagrammatic models. In order to support decision making, the models must be amenable to various kinds of analysis. It is desirable that the models support the sought after analysis effectively since creation of enterprise architecture models often is a demanding task. This paper suggests a framework for enterprise service interoperability analysis and a metamodel containing the information needed to perform the analysis. The paper also illustrates the use of the framework and metamodel in a fictional example.

  • 30.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Enterprise architecture - A service interoperability analysis framework2008In: ENTERPRISE INTEROPERABILITY III: NEW CHALLENGES AND INDUSTRIAL APPROACHES, NEW YORK: SPRINGER , 2008, p. 611-623Conference paper (Refereed)
    Abstract [en]

    Enterprise architecture is a model-based approach to IT management used for promotion of good IT decision making. Thus, an enterprise architecture framework needs to support various forms of analysis. Creation of enterprise architecture models is costly and without intrinsic value, therefore it is desirable to create models that effectively support the sought after analysis. This paper presents an extended influence diagram describing theory of enterprise service interoperability. The theory is augmented with a metamodel containing the information needed to perform analysis of interoperability. A fictional example is provided to illustrate the employment of the metamodel and the theory in the context of IT decision making.

  • 31.
    Ullberg, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sinderen, Marten van
    University of Twente.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Architecture Modeling for Interoperability Analysis on the Future Internet2013In: Enterprise Interoperability: I-ESA'12 Proceedings, 2013, p. 111-117Conference paper (Refereed)
    Abstract [en]

    One of the key aspects of the Future Internet is the Internet of Services, where companies are envisioned to sell and purchase services online in a dynamic fashion. A typical future scenario would be that companies form so-called ad-hoc business networks on the Future Internet to be able to collaborate together with a common goal of gaining value as a group. However, in order for these ad-hoc business networks to communicate and exchange services with each other they must be interoperable. This paper proposes architecture modeling and interoperability analysis as support functions in the ad-hoc business networks service life cycle.

1 - 31 of 31
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