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  • 1.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Internet of Things Approach to Cloud-Based Smart Car Parking2016In: The 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2016)/The 6th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2016)/Affiliated Workshops / [ed] Elhadi Shakshuki, Elsevier, 2016, Vol. 98, p. 193-198Conference paper (Refereed)
    Abstract [en]

    Concerns for parking are becoming imminent to best support the urban core. These persistent parking problems could be turned into new opportunities, brought by current trends in meeting the globally connected continuum. This paper reveals a work-in- progress to capitalize on private land properties for parking, in order to relieve stress on public agencies, create new sources of revenue, and enlist new entities in the intermediary market. These intermediaries, labelled as Parking Service Providers (or PSPs) play a broker role through advertising parking lots on a shared cloud platform. To streamline these business collaborations and related processes, physical parking lots are augmented with Internet connectivity allowing cloud-provided applications to congregate these lots into a larger inventory. The Internet of Things (IoT) paradigm expands the scope of cloud-based intelligent car parking services in smart cities, with novel applications that better regulate car-parking related traffic. This paper presents a work-in-progress agenda that contributes to new business solutions and state-of-the-art research impacts. We reveal a multi- layered system of PSP-business model through interdisciplinary research blocks where original results are expected to be made at each layer.

  • 2.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Yuning, Jiang
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    CombiTech AB, Skövde, Sweden.
    Gustavsson, Per M.
    CombiTech AB, Skövde, Sweden.
    Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection2017Conference paper (Refereed)
    Abstract [en]

    Critical infrastructures (CIs) are becoming increasingly sophisticated with embedded cyber-physical systems (CPSs) that provide managerial automation and autonomic controls. Yet these advances expose CI components to new cyber-threats, leading to a chain of dysfunctionalities with catastrophic socio-economical implications. We propose a comprehensive architectural model to support the development of incident management tools that provide situation-awareness and cyber-threats intelligence for CI protection, with a special focus on smart-grid CI. The goal is to unleash forensic data from CPS-based CIs to perform some predictive analytics. In doing so, we use some AI (Artificial Intelligence) paradigms for both data collection, threat detection, and cascade-effects prediction. 

  • 3.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jiang, Yuning
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Combitech.
    Haglund, Daniel
    Combitech.
    Lindström, Björn
    Combitech.
    Cyber-threat analysis for Cyber-Physical Systems: Technical report for Package 4, Activity 3 of ELVIRA project2018Report (Other academic)
    Abstract [en]

    Smart grid employs ICT infrastructure and network connectivity to optimize efficiency and deliver new functionalities. This evolu- tion is associated with an increased risk for cybersecurity threats that may hamper smart grid operations. Power utility providers need tools for assessing risk of prevailing cyberthreats over ICT infrastructures. The need for frameworks to guide the develop- ment of these tools is essential to define and reveal vulnerability analysis indicators. We propose a data-driven approach for design- ing testbeds to evaluate the vulnerability of cyberphysical systems against cyberthreats. The proposed framework uses data reported from multiple components of cyberphysical system architecture layers, including physical, control, and cyber layers. At the phys- ical layer, we consider component inventory and related physi- cal flows. At the control level, we consider control data, such as SCADA data flows in industrial and critical infrastructure control systems. Finally, at the cyber layer level, we consider existing secu- rity and monitoring data from cyber-incident event management tools, which are increasingly embedded into the control fabrics of cyberphysical systems.

  • 4.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jiang, Yuning
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Nero, Eva
    Combitech, Sweden.
    Brax, Christoffer
    Combitech, Sweden.
    Haglund, Daniel
    Combitech, Sweden.
    Multi-agent Systems for Power Grid Monitoring: Technical report for Package 4.1 of ELVIRA project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work- package 4.1 entitled “Multi-agent systems for power Grid monitoring”. ELVIRA project is a collaboration between researchers in School of IT at University of Skövde and Combitech Technical Consulting Company in Sweden, with the aim to design, develop and test a testbed simulator for critical infrastructures cybersecurity. This report outlines intelligent approaches that continuously analyze data flows generated by Supervisory Control And Data Acquisition (SCADA) systems, which monitor contemporary power grid infrastructures. However, cybersecurity threats and security mechanisms cannot be analyzed and tested on actual systems, and thus testbed simulators are necessary to assess vulnerabilities and evaluate the infrastructure resilience against cyberattacks. This report suggests an agent-based model to simulate SCADA- like cyber-components behaviour when facing cyber-infection in order to experiment and test intelligent mitigation mechanisms. 

  • 5.
    Ding, Jianguo
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    CPS-based Threat Modeling for Critical Infrastructure Protection2017In: Performance Evaluation Review, ISSN 0163-5999, E-ISSN 1557-9484, Vol. 45, no 2, p. 129-132Article in journal (Refereed)
    Abstract [en]

    Cyber-Physical Systems (CPSs) are augmenting traditionalCritical Infrastructures (CIs) with data-rich operations. Thisintegration creates complex interdependencies that exposeCIs and their components to new threats. A systematicapproach to threat modeling is necessary to assess CIs’ vulnerabilityto cyber, physical, or social attacks. We suggest anew threat modeling approach to systematically synthesizeknowledge about the safety management of complex CIs andsituational awareness that helps understanding the nature ofa threat and its potential cascading-effects implications.

  • 6.
    Horkoff, Jennifer
    et al.
    Chalmers University, Gothenburg.
    Jeusfeld, Manfred A.University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.Persson, AnneUniversity of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    The Practice of Enterprise Modeling: 9th IFIP WG 8.1. Working Conference, PoEM 2016, Skövde, Sweden, November 8-10, 2016, Proceedings2016Conference proceedings (editor) (Refereed)
    Abstract [en]

    This volume constitutes the proceedings of the 9th IFIP WG 8.1 Conference on the Practice of Enterprise Modeling held in November 2016 in Skövde, Sweden. The PoEM conference series started in 2008 and aims to provide a forum sharing knowledge and experiences between the academic community and practitioners from industry and the public sector. The 18 full papers and 9 short papers accepted were carefully reviewed and selected from 54 submissions and cover topics related to information systems development, enterprise modeling, requirements engineering, and process management. In addition, the keynote by Robert Winter on “Establishing 'Architectural Thinking' in Organizations” is also included in this volume.

  • 7.
    Horkoff, Jennifer
    et al.
    University of Gothenburg, Gothenburg, Sweden.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ralyté, Jolita
    University of Geneva, Geneva, Switzerland.
    Interview with Anne Persson on the Practice of Enterprise Modeling2018In: Business & Information Systems Engineering, ISSN 1867-0202, Vol. 60, no 1, p. 87-89Article in journal (Other (popular science, discussion, etc.))
    Abstract [en]

    We conducted the interview iteratively via email correspondence over the summer of 2017. Anne had been the general chair of PoEM 2017 in Skövde 2016 and, given her history with PoEM, we thus were very keen to learn about her views on enterprise modeling.

  • 8.
    Horkoff, Jennifer
    et al.
    University of Gothenburg, Gothenburg, Sweden.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ralyté, Jolita
    University of Geneva, Geneva, Switzerland.
    Karagiannis, Dimitris
    University of Vienna, Vienna, Austria.
    Enterprise Modeling for Business Agility2018In: Business & Information Systems Engineering, ISSN 1867-0202, Vol. 60, no 1, p. 1-2Article in journal (Refereed)
  • 9.
    Horkoff, Jennifer
    et al.
    University of Gothenburg.
    Jeusfeld, ManfredUniversity of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.Ralyté, JolitaUniversity of Geneva, Switzerland.Karagiannis, DimitrisUniversity of Vienna, Austria.
    Special Issue on Enterprise Modeling for Business Agility2018Collection (editor) (Refereed)
    Abstract [en]

    Enterprise Modeling (EM) addresses business-IT alignment in a holistic manner by providing the techniques, languages, tools and best practices for using models to represent organizational knowledge and information systems from different perspectives. Complex business and technology conditions means that EM plays an important role in reaching such alignment. Quality attributes such as agility, sensitivity, responsiveness, adaptability, autonomy and interoperability are emerging as the norms for advanced enterprise models. Achieving these qualities will allow all components of an enterprise to operate together in a cooperative manner for the purpose of maximizing overall benefit to the enterprise.

  • 10.
    Iriondo, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Oscarsson, Jan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Simulation Data Management in a Product Lifecycle Management Context2017In: Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK / [ed] James Gao, Mohammed El Souri, Simeon Keates, Amsterdam: IOS Press, 2017, p. 476-481Conference paper (Refereed)
    Abstract [en]

    Reuse of virtual engineering models and simulations improves engineering efficiency. Reuse requires preserving the information provenance. This paper suggests a framework based on the 7W data provenance model to be part of simulation data management implemented in product lifecycle management systems. The resulting provenance framework is based on a case study in which a product was re-engineered using finite element analysis.

  • 11.
    Jarke, Matthias
    et al.
    RWTH Aachen University, Informatik 5, Germany / Fraunhofer FIT, Sankt Augustin, Germany.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Quix, Christoph
    Fraunhofer FIT, Sankt Augustin, Germany.
    Data-centric intelligent information integration: from concepts to automation2014In: Journal of Intelligent Information Systems, ISSN 0925-9902, E-ISSN 1573-7675, Vol. 43, no 3, p. 437-462Article in journal (Refereed)
    Abstract [en]

    Intelligent integration of information continues to challenge database research for over 35 years. While data integration processes of all kinds are now reasonably well understood and widely used in practice, the growth and heterogeneity of data requires much higher degrees of automation to limit the need for human specialist work. This requires deeper insights in data-centric approaches of Enterprise Information Integration which focus on the semantics of information integration. Recent formalizations and algorithms enable both significant improvement in schema integration, and in its automated transformation to efficient data-level integration, in a wide variety of architectural settings such as data warehouses or peer-to-peer databases. In addition to giving a short overview of developments in this field for the past 20 years, this paper focuses particularly on the challenges posed by heterogeneity in data models.

  • 12.
    Jarke, Matthias
    et al.
    RWTH Aachen University & Fraunhofer FIT, Germany.
    Jeusfeld, Manfred
    Tilburg University, Netherlands.
    Quix, Christoph
    RWTH Aachen University & Fraunhofer FIT, Germany .
    Vassiliadis, Panos
    University of Ioannina, Greece .
    Vassiliou, Yanis
    National Technical University of Athens, Greece.
    Data Warehouse Architecture and Quality: Impact and Open Challenges2013In: Seminal Contributions to Information Systems Engineering / [ed] Janis Bubenko, John Krogstie, Oscar Pastor, Barbara Pernici, Colette Rolland, Arne Sølvberg, Berlin Heidelberg: Springer Berlin/Heidelberg, 2013, p. 183-189Chapter in book (Other (popular science, discussion, etc.))
    Abstract [en]

    The CAiSE 98 paper “Architecture and Quality in Data Warehouses” and its ex-panded journal version (Jarke et al. 1999) was the first to add a Zachman-like(Zachman 1987) explicit conceptual enterprise modeling perspective to the archi-tecture of data warehouses. Until then, data warehouses were just seen as collec-tions of – typically multidimensional and historized – materialized views on rela-tional tables, without consideration of modeling of the (business) conceptsunderlying their structure. The paper pointed out that this additional conceptualperspective was not just necessary for a truly semantic data integration but also aprerequisite for bringing the then very active data warehouse movement togetherwith another topic of quickly growing importance, that of data quality.

  • 13.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    DeepTelos Demonstration2019In: Proc. 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C 2019), Workshop MULTI 2019, IEEE Computer Society, 2019, p. 98-102Conference paper (Refereed)
    Abstract [en]

    DeepTelos is defined as a set of rules and constraints that enable multi-level modeling for the Telos metamodeling language. In its ConceptBase implementation, rules and constraints are realized by Datalog clauses. We start with demonstrating first the core functions of Telos, use of simple rules and constraints,then the meta-level rules and constraints defining DeepTelos. A couple of examples show how the DeepTelos rules and constraints are compiled to simple rules and constraints and then realize the desired multi-level modeling environment. The main example is taken from the Galileo satellite domain.

  • 14.
    Jeusfeld, Manfred
    Tillburg University, Netherlands.
    Metamodeling and method engineering with ConceptBase2009In: Metamodeling for Method Engineering / [ed] Manfred Jeusfeld, Matthias Jarke, John Mylopoulos, Cambridge, Massachusetts, USA: MIT Press, 2009Chapter in book (Other academic)
    Abstract [en]

    This chapter provides a practical guide on how to use the meta datarepository ConceptBase to design information modeling methods by using meta-modeling. After motivating the abstraction principles behind meta-modeling, thelanguage Telos as realized in ConceptBase is presented. First, a standard factualrepresentation of statements at any IRDS abstraction level is defined. Then, thefoundation of Telos as a logical theory is elaborated yielding simple fixpointsemantics. The principles for object naming, instantiation, attribution, andspecialization are reflected by roughly 30 logical axioms. After the languageaxiomatization, user-defined rules, constraints and queries are introduced. The firstpart is concluded by a description of active rules that allows the specification ofreactions of ConceptBase to external events. The second part applies the languagefeatures of the first part to a full-fledged information modeling method: The Yourdanmethod for Modern Structured Analysis. The notations of the Yourdan method aredesigned along the IRDS framework. Intra-notational and inter-notational constraintsare mapped to queries. The development life cycle is encoded as a software processmodel closely related to the modeling notations. Finally, aspects managing themodeling activities are addressed by metric definitions.

  • 15.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    DeepTelos for ConceptBase: A contribution to the MULTI process challenge2019In: Proc. 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C 2019), Workshop MULTI 2019, IEEE Computer Society, 2019, p. 66-77Conference paper (Refereed)
    Abstract [en]

    DeepTelos is a straightforward extension of the Telosmodeling language to allow some form of multi-level modeling. A variant of Telos has been implemented in the ConceptBase system on top of a Datalog engine. Telos defines the concepts of instantiation, specialization and attribution/relations by means of axioms. In addition, the user can define new constructs by deductive rules, integrity constraints, and so-called query classes. In this paper, we tackle the process challenge formulated for the MULTI 2019 workshop to see to which extent DeepTelos is ableto represent the requirements of this challenge.

  • 16.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    SemCheck - Script for the Case Studies2017Report (Other academic)
    Abstract [en]

    The Erasmus+ OMI initiative aims to facilitate academic education in enterprise modeling by create a shared and open modeling environment, in which various domain-specific modeling languages (DSML) are being integrated. The DSML form modeling perspectives, e.g. for data modeling, process modeling, goal modeling, and so forth.This document describes a tool that is designed to support the open modeling environmentt by providing semantic integrity checking services (SemCheck [1]), which can be used to analyze interrelated models formulated to find errors and to extract information from the models.

  • 17.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    SemCheck: Checking Constraints for Multi-perspective Modeling Languages2016In: Domain-Specific Conceptual Modeling: Concepts, Methods and Tools: Part I / [ed] Dimitris Karagiannis, Heinrich C. Mayr, John Mylopoulos, Switzerland: Springer, 2016, p. 31-53Chapter in book (Other academic)
    Abstract [en]

    Enterprises are complex and dynamic organizations that can hardly be understood from a single viewpoint. Enterprise modeling tackles this problem by providing multiple, specialized modeling languages, each designed for representing information about the enterprise from a given viewpoint. The OMiLAB initiative promotes the use of metamodeling to design such domain-specific languages and to provide them by an open repository to the community. In this chapter, we discuss how this metamodeling approach can be combined with the design of integrity constraints that span multiple modeling languages. We propose the services of the ConceptBase system as a constraint checker for modeling languages created by the ADOxx platform.

  • 18.
    Jeusfeld, Manfred A.
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jiang, Yuning
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Haglund, Daniel
    Combitech AB.
    Brax, Christoffer
    Combitech AB.
    Taxonomy of Events and Components in the Power Grid: Technical description for work packages 3.1 and 3.2 of the ELVIRA Project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work-package 3.1&3.2 entitled “Taxonomy of Critical Infrastructure (Taxonomy of events + Taxonomy of CI component and relationship)”. ELVIRA project is a collaboration between researchers in School of IT at University of Skövde and Combitech Technical Consulting Company in Sweden, with the aim to design, develop and test a testbed simulator for critical infrastructures cybersecurity.

  • 19.
    Jeusfeld, Manfred A.
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Karlapalem, KamalakarIndian Institute of Technology, Gandhinagar, India.
    Advances in Conceptual Modeling: ER 2015 Workshops, AHA, CMS, EMoV, MoBiD, MORE-BI, MReBA, QMMQ, and SCME Stockholm, Sweden, October 19–22, 2015, Proceedings2015Conference proceedings (editor) (Refereed)
    Abstract [en]

    PrefaceWelcome to the proceedings of the workshops held during the 34th InternationalConference on Conceptual Modeling (ER conference 2015) in Stockholm, Sweden.Workshops offer an incremental exploration of cutting-edge research issues thatbecome prominent in the future. The ER conference has a long tradition of thought-provoking and state-of-the-art workshops. This year we had a rich combination ofseven workshops and a special symposium on conceptual modeling education.We attracted 52 paper submissions for all the workshops, of which 26 wereaccepted. These workshops also have invited papers along with papers from thesymposium on conceptual modeling education.This volume comprises contributions from the following workshops:AHA 2015–Conceptual Modeling for Ambient Assistance and Healthy AgeingCMS 2015–Conceptual Modeling of ServicesEMoV 2015–Event Modeling and Processing in Business Process ManagementMoBiD 2015–Modeling and Management of Big DataMORE-BI 2015–Modeling and Reasoning for Business IntelligenceMReBA 2015–Conceptual Modeling in Requirements Engineering and Business AnalysisQMMQ 2015–Quality of Modeling and Modeling of QualitySCME 2015–Symposium on Conceptual Modeling Education

  • 20.
    Jeusfeld, Manfred A.
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Neumayr, Bernd
    Johannes Kepler University Linz, Linz, Austria.
    DeepTelos: Multi-level Modeling with Most General Instances2016In: Conceptual Modeling: 35th International Conference, ER 2016, Gifu, Japan, November 14-17, 2016, Proceedings / [ed] Isabelle Comyn-Wattiau, Katsumi Tanaka, Il-Yeol Song, Shuichiro Yamamoto, Motoshi Saeki, Springer Publishing Company, 2016, Vol. 9974, p. 198-211Conference paper (Refereed)
    Abstract [en]

    Multi-level modeling aims to reduce redundancy in data models by defining properties at the right abstraction level and inheriting them to more specific levels. We revisit one of the earliest such approaches, Telos, and investigate what needs to be added to its axioms to get a true multi-level modeling language. Unlike previous approaches, we define levels not with numeric potencies but with hierarchies of so-called most general instances.

  • 21.
    Jeusfeld, Manfred A.
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Thoun, Samsethy
    Pannasastra University, Phnom Penh, Cambodia.
    Key Performance Indicators in Data Warehouses2016In: Business Intelligence: 5th European Summer School, eBISS 2015, Barcelona, Spain, July 5-10, 2015, Tutorial Lectures / [ed] Esteban Zimányi, Alberto Abelló, Berlin, Germany: Springer Berlin/Heidelberg, 2016, p. 111-129Chapter in book (Refereed)
    Abstract [en]

    Key performance indicators are widely used to manage any type of processes including manufacturing, logistics, and business processes. We present an approach to map informal specifications of key performance indicators to prototypical data warehouse designs that support the calculation of the KPIs via aggregate queries. We argue that the derivation of the key performance indicators shall start from a process definition that includes scheduling and resource information.

  • 22.
    Jeusfeld, Manfred
    et al.
    University of Skövde, School of Humanities and Informatics.
    Delcambre, Lois
    Ling, Tok Wang
    Preface: Special Section featuring extended papers from the 30th International Conference on Conceptual Modeling (ER-2011)2013In: Data & Knowledge Engineering, ISSN 0169-023X, E-ISSN 1872-6933, Vol. 87, p. 259-Article in journal (Other (popular science, discussion, etc.))
    Abstract [en]

    The 30th International Conference on Conceptual Modeling (ER-2011) highlighted the strong and persistent interest in research on conceptual modeling for developing information systems. Topics included data modeling theory, goal modeling, socio-technical factors, requirements engineering, process modeling, and ontologies.

  • 23.
    Jeusfeld, Manfred
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lange, Christoph
    Fraunhofer FIT, Germany.
    CEUR-WS.org: Open-Access as a Community Effort2019Conference paper (Other academic)
    Abstract [en]

    Conventional wisdom says that open-access (OA) publishing is not sustainable without a proper financial basis. Commercial OA publishers charge authors, their employers, or their roof organizations considerable fees to cover the costs and to generate income for the OA publishers. This may lead to undesired effects such as giving preference to authors who can afford the fee over those who do not have the resources.CEUR-WS.org (CEUR Workshop Proceedings) selected a different path in 1995 when it was founded as a service operated under the umbrella of Sun SITE Central Europe at RWTH Aachen University. We deliberately focused on computer science workshop proceedings, which had difficulties to find publishers at that time. More importantly, we designed the service with a team of volunteer scientists who perform the publication service in their free time and without charging any fee from authors, editors, or readers.Now, after more than 20 years, the service is still operating and growing every year. In the last year, we published more than 250 proceedings volumes, making CEUR-WS.org one of the largest open-access publication channels for computer science proceedings.In this talk, we discuss the success factors of CEUR-WS.org and some of the challenges that we encountered over the past two decades. We also give some glimpses into future extensions of the service such as open data, semantification, and improved interoperability with neighbor services such as DBLP and the indexing by national libraries.We believe that scientists should take a greater role in the publication value chain. We know best our needs for future publication models, the ethical conditions for fairness, and the rules governing scientific publication.Many thanks go to the team of Sun SITE Central Europe for hosting the service and the members of the CEUR-WS.org Team who run the service for free, for you.

  • 24.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Combitech, Sweden.
    Haglund, Daniel
    Combitech, Sweden.
    Complex Dependencies Analysis: Technical Description of Complex Dependencies in Critical Infrastructures, i.e. Smart Grids. Work Package 2.1 of the ELVIRA Project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work-package 2.1 entitled “Complex Dependencies Analysis”. In this technical report, we review attempts in recent researches where connections are regarded as influencing factors to  IT systems monitoring critical infrastructure, based on which potential dependencies and resulting disturbances are identified and categorized. Each kind of dependence has been discussed based on our own entity based model. Among those dependencies, logical and functional connections have been analysed with more details on modelling and simulation techniques.

  • 25.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Combitech AB, Skövde, Sweden.
    Nero, Eva
    Combitech AB, Skövde, Sweden.
    A Language and Repository for Cyber Security of Smart Grids2018In: 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC 2018) / [ed] Selmin Nurcan, Pontus Johnson, Los Alamitos, CA: IEEE, 2018, p. 164-170Conference paper (Refereed)
    Abstract [en]

    Power grids form the central critical infrastructure in all developed economies. Disruptions of power supply can cause major effects on the economy and the livelihood of citizens. At the same time, power grids are being targeted by sophisticated cyber attacks. To counter these threats, we propose a domain-specific language and a repository to represent power grids and related IT components that control the power grid. We apply our tool to a standard example used in the literature to assess its expressiveness.

  • 26.
    Morshedzadeh, Iman
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Oscarsson, Jan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Sillanpaa, Janne
    InterSystems Sweden AB, Stockholm.
    Product lifecycle management with provenance management and virtual models: an industrial use-case study2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 1190-1195Article in journal (Refereed)
    Abstract [en]

    Saving and managing virtual models’ provenance information (models’ history) can increase the level of reusability of those models. This paper describes a provenance management system (PMS) that has been developed based on an industrial case study.

    The product lifecycle management (PLM) system, as a main data management system, is responsible for receiving virtual models and their related data from Computer-Aided technologies (CAx) and providing this information for the PMS. In this paper, the management of discrete event simulation data with the PLM system will be demonstrated as the first link of provenance data management chain (CAx-PLM-PMS).

  • 27.
    Morshedzadeh, Iman
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Oscarsson, Jan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H.C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jenefeldt, Anders
    Volvo Cars Corporation, Skövde, Sweden.
    Real World Data Identification and Classification for Support of Virtual Confidence2016Conference paper (Refereed)
    Abstract [en]

    Shortening of the product development process time is one of the main approaches for all enterprises to offer their products to the market. Virtual manufacturing tools can help companies to reduce their time to market, by reduction of the engineering lead time. Extensive use of virtual engineering models results in a need for verification of the model’s accuracy. This virtual engineering usability and assessment have been named virtual confidence. The two main factors of the achievement of this confidence are the accuracy of the virtual models and the virtual engineering results.

    For controlling of both above factors, a complete virtual model and related virtual model knowledge are needed. These knowledges can be tacit or explicit. For exploring explicit knowledge, a data and information collection from different disciplines in the organization is needed.

    In this paper, a data map with focus on the manufacturing engineering scope will be presented. This data map is generated from different data sources at a manufacturing plant, and gives an overview of different data that exist at different data sources, in the area of manufacturing. Combining real world data from different sources with virtual engineering model data supports, amongst others, establishment of virtual confidence.

  • 28.
    Neumayr, Bernd
    et al.
    Johannes Kepler University Linz, Austria.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Schrefl, Michael
    Johannes Kepler University Linz, Austria.
    Schütz, Christoph
    Johannes Kepler University Linz, Austria.
    Dual Deep Instantiation and Its ConceptBase Implementation2014In: Advanced Information Systems Engineering: 26th International Conference, CAiSE 2014, Thessaloniki, Greece, June 16-20, 2014, Proceedings / [ed] M. Jarke, J. Mylopoulos, C. Quix, C. Rolland, Y. Manolopoulos, H. Mouratidis, J. Horkoff, Springer Berlin/Heidelberg, 2014, p. 503-517Conference paper (Refereed)
    Abstract [en]

    Application integration requires the consideration of instance data and schema data. Instance data in one application may be schema data for another application, which gives rise to multiple instantiation levels. Using deep instantiation, an object may be deeply characterized by representing schema data about objects several instantiation levels below. Deep instantiation still demands a clear separation of instantiation levels: the source and target objects of a relationship must be at the same instantiation level. This separation is inadequate in the context of application integration. Dual deep instantiation (DDI), on the other hand, allows for relationships that connect objects at different instantiation levels. The depth of the characterization may be specified separately for each end of the relationship. In this paper, we present and implement set-theoretic predicates and axioms for the representation of conceptual models with DDI.

  • 29.
    Neumayr, Bernd
    et al.
    Johannes Kepler University Linz, Linz, Austria.
    Schuetz, Christoph G.
    Johannes Kepler University Linz, Linz, Austria.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Schrefl, Michael
    Johannes Kepler University Linz, Linz, Austria.
    Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic2018In: Journal of Software and Systems Modeling (online), ISSN 1619-1366, E-ISSN 1619-1374, Vol. 17, no 1, p. 233-268Article in journal (Refereed)
    Abstract [en]

    An enterprise database contains a global, integrated, and consistent representation of a company’s data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

  • 30.
    Oscarsson, Jan
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jenefeldt, Anders
    Volvo Cars Corporation, Skövde, Sweden.
    Towards Virtual Confidence - Extended Product Lifecycle Management2016In: Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers / [ed] Abdelaziz Bouras, Benoit Eynard, Sebti Foufou & Klaus-Dieter Thoben, Springer, 2016, Vol. 467, p. 708-717Chapter in book (Refereed)
    Abstract [en]

    Product lifecycle management (PLM) systems maintain amongst others the specifications and designs of product, process and resource artefacts and thus serve as the basis for realizing the concept of Virtual Manufacturing, and play a vital role in shortening the leadtimes for the engineering processes. Design of new products requires numerous experiments and test-runs of new facilities that delays the product release and causes high costs if performed in the real world. Virtualization promises to reduce these costs by simulating the reality. However, the results of the simulation must predict the real results to be useful. This is called virtual confidence. We propose a knowledge base approach to capture and maintain the virtual confidence in simulation results. To do so, the provenance of results of real, experimental and simulated processes are recorded and linked via confirmation objects.

1 - 30 of 30
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