437 research outputs found

    Measuring the Cognitive Complexity in the Comprehension of Modular Process Models

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    Modularization in process models is a method to cope with the inherent complexity in such models (e.g., model size reduction). Modularization is capable to increase the quality, the ease of reuse, and the scalability of process models. Prior conducted research studied the effects of modular process models to enhance their comprehension. However, the effects of modularization on cognitive factors during process model comprehension are less understood so far. Therefore, this paper presents the results of two exploratory studies (i.e., a survey research study with N = 95 participants; a follow-up eye tracking study with N = 19 participants), in which three types of modularization (i.e., horizontal, vertical, orthogonal) were applied to process models expressed in terms of the Business Process Model and Notation (BPMN) 2.0. Further, the effects of modularization on the cognitive load, the level of acceptability, and the performance in process model comprehension were investigated. In general, the results revealed that participants were confronted with challenges during the comprehension of modularized process models. Further, performance in the comprehension of modularized process models showed only a few significant differences, however, the results obtained regarding the cognitive load revealed that the complexity and concept of modularization in process models were misjudged initially. The insights unraveled that the attitude towards the application and the behavioral intention to apply modularization in process model is still not clear. In this context, horizontal modularization appeared to be the best comprehensible modularization approach leading to a more fine-grained comprehension of respective process models. The findings indicate that alterations in modular process models (e.g., change in the representation) are important to foster and enable their comprehension. Finally, based on our results, implications for research and practice as well as directions for future work are discussed in this paper

    Cognitive Effectiveness of Visual Instructional Design Languages

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    The introduction of learning technologies into education is making the design of courses and instructional materials an increasingly complex task. Instructional design languages are identified as conceptual tools for achieving more standardized and, at the same time, more creative design solutions, as well as enhancing communication and transparency in the design process. In this article we discuss differences in cognitive aspects of three visual instructional design languages (E²ML, PoEML, coUML), based on user evaluation. Cognitive aspects are of relevance for learning a design language, creating models with it, and understanding models created using it. The findings should enable language constructors to improve the usability of visual instructional design languages in the future. The paper concludes with directions with regard to how future research on visual instructional design languages could strengthen their value and enhance their actual use by educators and designers by synthesizing existing efforts into a unified modeling approach for VIDLs

    Design and Evaluation of Domain-Specific Platforms and the Special Case of Digital Healthcare

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    The implementation of digital innovations in the healthcare sector is faced with different barriers and challenges. The complex system of regulations, the lack of interoperability, and highly dynamic interorganisational networks lead to missing widespread adoption of eHealth solutions. Digital platforms can help to overcome these barriers by providing a holistic infrastructure. They create a modularised foundation that innovators can use to create own innovations and provide them to demanders of digital solutions. As intermediaries, they can be accessed both by healthcare professionals and eHealth solution providers. Providers can offer their eHealth services via the platform. Healthcare professionals can use these services to create own interorganisational information systems. In the field of information systems research, effects and strategies for two-sided platforms are well researched and the potentials of eHealth platforms are also discussed. However, the organisational and technological design and methods for the construction of platforms are fewer questioned. Nonetheless, platform owners can benefit from implementation strategies and architectural guidance to create sustainable platforms and surrounding ecosystems. This doctoral thesis questions how domain-specific platforms can be designed systematically. Conducting a design-science research process, it develops both a modelling system and the Dresden Ecosystem Management Method (DREEM) to support the development of platforms in different domains. Furthermore, it describes the design characteristics of two-sided platforms in the healthcare sector and provides an evaluation approach to analyse the platforms’ ability to create a viable innovation ecosystem in the healthcare sector. The doctoral thesis contributes by providing methodical guidance for platform owners and researchers to design and evaluate digital platforms in different domains and improves the understanding of platform theory in the healthcare sector.:A. Synopsis of the Doctoral Thesis 1. Introduction 2. Foundational Considerations 3. Requirements for Design Artefacts and Knowledge 4. Structure of the Doctoral Thesis 5. Conclusion B. Paper 1 - Governance Guidelines for Digital Healthcare Ecosystems C. Paper 2 - Revise your eHealth Platform! D. Paper 3 - Business Model Open ”E-Health-Platform” E. Paper 4 - Modelling Ecosystems in Information Systems F. Paper 5 - Designing Industrial Symbiosis Platforms G. Paper 6 - Management of Digital Ecosystems with DREEM H. Paper 7 - Guiding the Development of Digital Ecosystems I. Paper 8 - Towards Maintenance Analytics Ecosystems J. Paper 9- Sustainability of E-Health-Projects K. Paper 10 - ISO 11354-2 for the Evaluation of eHealth-Platform

    Robotics Software Engineering: A Perspective from the Service Robotics Domain

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    Robots that support humans by performing useful tasks (a.k.a., service robots) are booming worldwide. In contrast to industrial robots, the development of service robots comes with severe software engineering challenges, since they require high levels of robustness and autonomy to operate in highly heterogeneous environments. As a domain with critical safety implications, service robotics faces a need for sound software development practices. In this paper, we present the first large-scale empirical study to assess the state of the art and practice of robotics software engineering. We conducted 18 semi-structured interviews with industrial practitioners working in 15 companies from 9 different countries and a survey with 156 respondents (from 26 countries) from the robotics domain. Our results provide a comprehensive picture of (i) the practices applied by robotics industrial and academic practitioners, including processes, paradigms, languages, tools, frameworks, and reuse practices, (ii) the distinguishing characteristics of robotics software engineering, and (iii) recurrent challenges usually faced, together with adopted solutions. The paper concludes by discussing observations, derived hypotheses, and proposed actions for researchers and practitioners.Comment: 11 pages + 1 page for references, 3 figures, 3 tables, in proceedings of ESEC/FSE 202

    Tradespace and Affordability – Phase 2

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    MOTIVATION AND CONTEXT: One of the key elements of the SERC’s research strategy is transforming the practice of systems engineering – “SE Transformation.” The Grand Challenge goal for SE Transformation is to transform the DoD community’s current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first, outside-in, document-driven, point-solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise-oriented, hardware-software-human engineered, balanced outside-in and inside-out, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046)

    Contribution des services dirigés par l’ontologie pour l’interopérabilité de la gestion opérationnelle multi-acteurs des situations des crises

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    La gestion opérationnelle de situations de crise nécessite, selon l’importance et l’étendue de la crise, la mobilisation rapide et la coordination des différents services de secours. Malheureusement, cette coordination interservices est un exercice très délicat du fait de la diversité des acteurs intervenant sur le terrain et de l’hétérogénéité des différentes organisations. Aujourd’hui, il y a un manque de coordination, l’information n’est que très peu partagée entre les acteurs opérationnels et la communication n’est pas formalisée. Ces inconvénients conduisent au dysfonctionnement des réponses aux situations de crise. Afin de mieux répondre aux situations de crise, nous proposons POLARISC, une plateforme interopérable de coordination interservices pour la gestion opérationnelle de catastrophes visualisant en temps réel le théâtre des opérations. L’objectif de POLARISC est d’aider à la décision quel que soit le niveau de commandement. Pour atteindre ces objectifs, le premier enjeu de cette thèse est de garantir une interopérabilité sémantique entre les différents acteurs métiers pour assurer l’échange et le partage des informations. À cet égard, l’idée est de formaliser sémantiquement les connaissances des acteurs métiers de la gestion opérationnelle à l’aide des ontologies. En effet, nous proposons une approche fédérée qui représente les données, les services, les processus et les métiers de chaque acteur. Nous avons modélisé les connaissances des acteurs de secours en développant une ontologie modulaire (POLARISCO) comportant un module ontologique pour chaque acteur de secours et intégré ces derniers pour proposer un vocabulaire partagé. L’utilisation des ontologies de haut niveaux et des ontologies intermédiaires, respectivement « Basic Formel Ontology » et « Common Core Ontologies », facilitent l’intégration de ces modules et de leurs mappings. Le deuxième enjeu est d’exploiter ces ontologies afin de diminuer l’ambigüité et d’éviter la mal interprétation des informations échangées. Par conséquent, nous proposons un service de messagerie appelé PROMES transformant sémantiquement le message envoyé par un acteur émetteur selon le module ontologique de l’acteur destinataire. En effet, PROMES se base sur l’ontologie POLARISCO et sert à enrichir sémantiquement le message pour éviter tout type d’ambiguïté. Le fonctionnement de PROMES est basé principalement sur deux algorithmes ; un algorithme de transformation textuelle, et par la suite, un algorithme de transformation sémantique. Ainsi, nous avons instancié l’ontologie POLARISCO avec des données réelles de la réponse aux attaques terroristes de Paris en 2015 afin d’évaluer l’ontologie et le service de messagerie. Le troisième et dernier enjeu est de proposer un service d’aide à la décision multicritère qui permet de proposer des stratégies d’évacuation des victimes après le lancement du plan blanc. L’objectif est de trouver les structures hospitalières les plus adaptées à l’état de la victime. Le choix de l’hôpital le plus approprié dépend de la durée du transport, et surtout de la disponibilité des ressources matérielles et humaines, de façon à prendre en charge les victimes le plus rapide que possible. Notre étude comprend deux étapes : la première étape consiste à développer un module ontologique qui associe à chaque pathologie les ressources indispensables pour une meilleure prise en charge des victimes selon leurs états. La deuxième étape consiste à développer un algorithme qui permet de vérifier la disponibilité des ressources nécessaires, calculer le temps d’attente pour que la victime soit prise en charge dans chaque hôpital et par la suite choisir l’hôpital le plus appropri

    Service-Oriented Process Models in Telecommunication Business

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    The thesis concentrates on to evaluate challenges in the business process management and the need for Service-oriented process models in telecommunication business to alleviate the integration work efforts and to reduce total costs of ownership. The business aspect concentrates on operations and business support systems which are tailored for communication service providers. Business processes should be designed in conformance with TeleManagement Forum's integrated business architecture framework. The thesis rationalizes the need to transform organizations and their way of working from vertical silos to horizontal layers and to understand transformational efforts which are needed to adopt a new strategy. Furthermore, the thesis introduces service characterizations and goes deeper into technical requirements that a service compliant middleware system needs to support. At the end of the thesis Nokia Siemens Networks proprietary approach – Process Automation Enabling Suite is introduced, and finally the thesis performs two case studies. The first one is Nokia Siemens Networks proprietary survey which highlights the importance of customer experience management and the second one is an overall research study whose results have been derived from other public surveys covering application integration efforts

    Model Driven Development of Agents for Ambient Intelligence

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    En esta tesis se define un proceso dirigido por modelos para el desarrollo de sistemas de Inteligencia Ambiental (AmI) basados en agentes auto-gestionados que pueden ser ejecutados en los dispositivos más usuales de los entornos AmI, teléfonos inteligentes o sensores. Nuestra solución está centrada en una arquitectura de MAS totalmente distribuida y descentralizada, gracias a la integración de los agentes en los dispositivos heterogéneos que suelen formar parte de un sistema AmI
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