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  • Public defence: 2019-11-14 13:30 J1640, Karlskrona
    Guo, Yang
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Heterogeneous Knowledge Sharing in eHealth: Modeling, Validation and Application2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Knowledge sharing has become an important issue in the eHealth field for improving the quality of healthcare service. However, since eHealth subject is a multidisciplinary and cross-organizational area, knowledge sharing is a serious challenge when it comes to developing eHealth systems. Thus, this thesis studies the heterogeneous knowledge sharing in eHealth and proposes a knowledge sharing ontology. The study consists of three main parts: modeling, validation and application.

    In the modeling part, knowledge sharing in eHealth is studied from two main aspects: the first aspect is the heterogeneous knowledge of different healthcare actors, and the second aspect is the interactivities among various healthcare actors. In this part, the contribution is to propose an Activity Theory based Ontology (ATO) model to highlight and represent these two aspects of eHealth knowledge sharing, which is helpful for designing efficient eHealth systems.

    In the validation part, a questionnaire based survey is conducted to practically validate the feasibility of the proposed ATO model. The survey results are analyzed to explore the effectiveness of the proposed model for designing efficient knowledge sharing in eHealth. Further, a web based software prototype is constructed to validate the applicability of the ATO model for practical eHealth systems. In this part, the contribution is to explore and show how the proposed ATO model can be validated.

    In the application part, the importance and usefulness of applying the proposed ATO model to solve two real problems are addressed. These two problems are healthcare decision making and appointment scheduling. There is a similar basic challenge in both these problems: a healthcare provider (e.g., a doctor) needs to provide optimal healthcare service (e.g., suitable medicine or fast treatment) to a healthcare receiver (e.g., a patient). Here, the optimization of the healthcare service needs to be achieved in accordance with eHealth knowledge which is distributed in the system and needs to be shared, such as the doctor’s competence, the patient’s health status, and priority control on patients’ diseases. In this part, the contribution is to propose a smart system called eHealth Appointment Scheduling System (eHASS) based on ATO model.

    This research work has been presented in eight conference and journal papers, which, along with an introductory chapter, are included in this compilation thesis.

  • Public defence: 2019-12-16 09:00 J1516, Karlskrona
    Klotins, Eriks
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Software Engineering in Start-up Companies2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Start-up companies have emerged as suppliers of innovation and software-intensive products. Small teams, lack of legacy products, experimental nature, and absence of any organizational processes enable start-ups to develop and market new products and services quickly. However, most start-ups fail before delivering any value.

    Start-up failures can be attributed to market factors, shortcomings in business models, lack of motivation, or self-destruction among other reasons. However, inadequacies in product engineering precede any market or business-related challenges and could be a significant contributing factor to start-up failures. At the same time, state-of-the-art software engineering (SE) practices offer little support for start-ups and are often neglected by start-ups as inadequate.

    At the beginning of this work, SE in start-ups had attracted very little attention from researchers. Thus, there was no coherent view of SE state-of-practice in start-ups and no starting point for a focused investigation.

    This thesis seeks to understand how start-ups practice SE, what specific SE challenges should be addressed, and what new SE practices are needed to support the engineering of innovative software-intensive products and services.

     This thesis utilizes a multi-vocal literature review, a case survey, qualitative data analysis, two industrial case studies, and a design science research method.

    A substantial part of this work is exploratory and aimed to explore SE state-of-practice in start-ups. Our initial findings suggest that start-ups overlook the best SE practices. Teams of a few people working on relatively simple and experimental software see no upside of following the best practices. However, late start-ups face substantial challenges as their teams grow and products become more complex. The key difficulties concern installing adequate SE practices supporting collaboration, coordination of work, and management of accumulated technical debt. To support the evolution of engineering practices in start-ups, we propose the start-up progression model outlining engineering goals, common challenges, and useful practices with regards to the start-up life-cycle phases.

    Further findings suggest inadequate support for market-driven requirements engineering (MDRE). Specifically, on how to aggregate needs and wishes of a large and loosely defined set of stakeholders who may not be able to articulate their needs and expectations. To address this challenge, we propose a method for the identification and prioritization of data sources and stakeholders in MDRE.

    Analyzing SE context in start-ups and other organizations developing innovative and market-driven products we have found many similarities. Thus, the results of this thesis could be applicable in all types of organizations developing innovative market-driven products and services.

    We conclude that the key start-up specific engineering challenge is to manage evolution of SE practices to match complexities of the product and rising demands of the stakeholders.

    Our work highlights the opportunity for better MDRE practices to support innovation in both start-ups and other types of organizations.